Retrospective Theses and Dissertations Iowa State University Capstones, Theses andDissertations
1994
Water table management effects on photosynthesis,chlorophyll, crop yield, and water qualityMohammad Saffar MirjatIowa State University
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Water table management effects on photosynthesis, chlorophyll, crop yield, and water quality
Mirjat, Mohammad SafFar, Ph.D.
Iowa State University, 1994
U M I 300 N. ZeebRd. Ann Arbor, MI 48106
Water table management effects on photosynthesis,
chlorophyll, crop yield, and water quality
by
Mohammad Saffar Mirjat
A Dissertation Submitted to the
Graduate Faculty in Partial fulfillment of the
Requirements for the Degree of
DOCTOR OF PHILOSOPHY
Department: Agricultural and Biosystems Engineering Major: Agricultural Engineering
Approved:
In Charge of Major Work
For the Major Department
For the Graduate College
Iowa State University Ames,Iowa
1994
Signature was redacted for privacy.
Signature was redacted for privacy.
Signature was redacted for privacy.
ii
TABLE OF CONTENTS Page
GENERAL INTRODUCTION 1
Objectives 4
Explanation of dissertation format 5
REVIEW OF LITERATURE 6
Water table management 6
Water table depth and crop production 8
Photosynthesis response and crop yield 11
Stomatal conductance under different moisture conditions 13
Relationship between chlorophyll content and crop yield 15
Water table management for NO3-N improvement 18
Pesticides in the groundwater 24
Factors affecting fate and behavior of pesticides 26
Pesticide control through water table management 29
PAPER I. EFFECTS OF WATER TABLE DEPTHS ON DIFFERENT PLANT PHYSIOLOGICAL PARAMETERS 32
ABSTRACT 33
in
Page
INTRODUCTION 35
MATERIALS AND METHODS 40
Description of experimental sites 40
Experimental setup at Ames site 40
Experimental setup at Ankeny site 42
Water table management treatments 43
Measurements of plant physiological parameters 44
Chlorophyll Measurements 45
SPAD-502 chlorophyll meter (principle description) 46
Plant culture 47
RESULTS AND DISCUSSION 48
Photosynthesis response to water table depths 48
Effect of water table depth on stomatal conductance 52
Effects of WTD on transpiration rate 55
Effects of WTD on intercellular COj (Ci) 58
Effects of WTD on chlorophyll content 59
Crop canopy temperature and water table depth 62
Relationships between photosynthesis and chlorophyll readings 65
iv
Paqe Relations between stomatal conductance and transpiration rate 68
Crop yield 72
CONCLUSIONS 74
PAPER II. EFFECTS OF WATER TABLE DEPTHS ON THE TRANSPORT OF NO3-N INTO GROUNDWATER 95
ABSTRACT 96
INTRODUCTION 98
MATERIALS AND METHODS 105
Description of experimental sites 105
Experimental setup at Ames site 105
Experimental setup at Ankeny site 107
Water table management treatments 108
Groundwater sampling 109
Soil sampling and analysis methods 110
Soil nitrate extraction and analysis 111
Plant culture 112
RESULTS AND DISCUSSIONS 114
NO3-N concentrations in piezometer water samples at the Ankeny site 114
NO3-N concentrations in suction tube water samples at the Ankeny site 116
V
Page NO3-N concentrations in piezometer water samples at the Ames site 119
NO3-N concentrations in suction tube water samples at the Ames 121
Distribution of NO3-N in the soil profile 123
Crop yield 126
CONCLUSIONS 128
PAPER III. MOVEMENT OF PESTICIDES INTO SHALLOW GROUNDWATER AS AFFECTED BY WATER TABLE MANAGEMENT 146
ABSTRACT 147
INTRODUCTION 149
MATERIALS AND METHODS 156
Description of experimental sites 156
Water table management treatments 158
Groundwater sampling 159
Herbicide extraction procedures 160
Analysis of herbicide 160
Planting, harvesting, and chemical management system 161
RESULTS AND DISCUSSION 162
Atrazine concentrations in piezometer water samples at the Ames site 162
Atrazine concentrations in suction tube water samples at the Ames site 164
vi
Page Atrazine concentrations in piezometer water samples at the Ankeny site 166
Atrazine concentrations in suction tube water samples at the Ankeny site 168
Alachlor concentrations at the Ames site 170
Alachlor concentrations at the Ankeny site 171
Atrazine and alachlor distribution pattern in the soil profile 173
Crop yield 174
CONCLUSIONS 177
OVERALL CONCLUSIONS 197
Physiological parameters and WTDs 197
NO3-N concentrations in groundwater 199
Pesticide concentrations in groundwater 200
Corn yield 201
RECOMMENDATIONS FOR FUTURE WORK 202
REFERENCES 204
ACKNOWLEDGEMENTS 220
APPENDIX: SUMMARIZED DATA ON PLANT PHYSIOLOGICAL PARAMETERS NO3-N AND PESTICIDE 223
1
GENERAL INTRODUCTION
Agricultural production systems in the humid regions of the U.S.A.
historically have been influenced by high rainfall, occasional flooding, and
seasonal drought. These factors contribute to the degradation of
environmentally sensitive areas, such as wetlands and lowlands, and productive
estuarine areas and marshes. Although farmers in the U.S. have been using
subsurface drainage methods to allow cultivation of poorly drained soils for the
past 2 centuries (Fausey et al., 1990), more sophisticated agricultural water-
management techniques are now possible to accommodate crop water needs.
Excess water on the field surface and in the root zone restricts production
of about 25% of U.S. cropland. According to a USDA publication (1987), an
estimated 44 million hectares of agricultural land in the United States benefits
from artificial drainage. The capital value of all U.S. farm drainage is estimated
to be over 40 billion dollars. For example, about 40% of Iowa's corn and
soybean acreage are artificially drained (Kalita and Kanwar, 1992). Thus,
drainage is of vital importance to the sustainability of the current level of
agricultural production and is still needed on much of the corn and soybean land
in the U.S. For instance in Ohio, about 3 million hectares or over 60% of the
cropland needs drainage (Nolte, 1976).
Artificial drainage can provide a suitable environment for plant growth
during the growing season, but excessive drainage is undesirable because it
2
reduces the soil water available to growing plants and can leach fertilizers and
pesticides into receiving streams or deeper groundwater systems where these
chemicals might act as pollutants (Kanwar et al., 1991). Since herbicides are
used on approximately 98% of the corn and soybean acreage in Iowa, the
potential for groundwater contamination from artificially drained soils is high
(Kanwar et al., 1988). Groundwater contamination as a result of nitrate and
pesticide leaching has been reported in Iowa, Minnesota, Ohio and in several
other eastern states (Hallberg, 1986; Kanwar et al., 1988; Kanwar and Baker
1991; Baker and Johnson, 1977; Baker and Johnson, 1981; Bengtson et al.,
1984; Gilliam and Skaggs, 1986; Wright et al., 1989; Kalita and Kanwar,
1990). To control the rate of future contamination, water table management
(WTM) practices have been implemented in many areas of the U.S. such as the
eastern coastal plain, and the mid-western region.
Water table management for improved agricultural production has
progressed from the concept of drainage alone to that of surface and
subsurface drainage, controlled drainage, controlled drainage-subirrigation
(combined drainage and subirrigation). Controlled drainage-subirrigation
maintains shallow water table depths in the field during certain periods of the
growing season. Water table management with controlled drainage or
controlled drainage-subirrigation prevents indiscriminate drainage of wetlands
and also provides water quality benefits by promoting the growth of denitrifying
3
bacteria (Shirmohammadi et al., 1992).
Compared with conventional drainage systems, WTM can provide better
flood control, improved water conservation, optimized water conditions for crop
growth, and improved water quality (Thomas et al., 1992). WTM is especially
suited to areas where high water tables persist for long periods, and has the
potential to increase net farm returns by improving crop yield and reducing
chemical use (Kalita and Kanwar, 1990).
WTM maintains adequate soil-moisture and soil-air in the crop root-zone
and creates favorable plant growth conditions. The quantity of soil-moisture
and soil-air in the root-zone, however, depends on the depth at which the
water-table is maintained. Based on the availability of soil-moisture and soil-air
in the root zone, crop physiological growth differs significantly. Transpiration
rates, photosynthesis rates, stomatal conductance, chlorophyll content, and
canopy temperatures may vary. Numerous studies have been conducted to
establish relationships between the average seasonal water-table depths, crop
physiological parameters, and crop yield. In such a study, Wesseling (1974)
reported that the reduced oxygen supply to roots resulting from shallow water-
table depths led to decreased rates of transpiration, nutrient uptake,
photosynthesis, and crop growth. Similar results have been reported by Evans
and Skaggs (1985), Kanwar (1988), and Carter et al. (1988).
Recent studies conducted in Iowa by Kalita and Kanwar (1992) have
4
shown that photosynthesis rates were higher for shallow water-table depths
than for deeper water-table depths during the dry season. Photosynthesis rates
were not significantly different during the wet season. The influence of the
water table depth on photosynthèse water-use efficiency (PWUE), however,
was highly significant in both dry and wet seasons.
More information is needed on the performance of water table
management systems in sustainable agriculture. Information on the movement
of pesticides in water table management systems is particularly scarce but
critically needed. Therefore, better management techniques and improved
information for technology transfer are important to the successful use of water
table management across the U.S.
Objectives
To develop a better understanding of water-table management practices
on crop growth and groundwater quality, this study was conducted with the
following main objectives:
1. To investigate photosynthesis response to different water table management
practices and their effect on crop growth.
2. To investigate the effect of various water-table management practices on
5
chlorophyll content and corn yield.
3. To evaluate the transport of nitrate-nitrogen and pesticides into shallow
groundwater in response to various water-table depths.
Explanation of dissertation format
This dissertation reports the candidate's original work on water table
management effects on plant physiological parameters, groundwater quality,
and corn yield. The entire dissertation contains three separate papers. Each
paper was written by the author in a format suitable for submission for
publication to a referred technical journal.
The first paper has been proposed for presentation at the mid-central
meeting of the American Society of Agricultural Engineers.
Each paper contains an abstract, introduction, materials and methods,
results and discussion, and conclusions. All three papers are preceded by a
general introduction and review of literature and are followed by overall
conclusions. The references for the introduction, materials and methods, and
results and discussion of all three papers and sections of the general
introduction and review of literature are cited at the end of the dissertation.
6
REVIEW OF LITERATURE
Water table management
The management of soil water in agricultural cropland in humid and
semi-humid areas of the U.S. is complicated by the erratic spatial and temporal
occurrence of rainfall. In many humid areas, such as the mid-western regions of
the U.S., periods of surplus and deficit soil water conditions occur within the
same cropping season. This sometimes leads to production losses. Therefore,
proper soil and water management have become one of the most important
challenges in these and the other humid areas of the U.S. to reduce soil
productivity losses.
The primary purposes of water table control are to minimize the time of
surplus or deficit soil-water conditions in the root-zone and to maximize the use
of natural rainfall, thus minimizing the amount of subirrigation water required
from external sources. Water table management which includes both irrigation
and drainage, can improve productivity in humid and semi-humid climates,
where weather extremes can result in crop losses and in arid areas where
salinity control is necessary for sustained agricultural production.
The objective of water table management is to provide a root
environment that results in optimum crop yields. In the past, the direct aim of
water table management systems in humid regions was to lower the moisture
7
content of upper layers of the soil so that air could penetrate into the soil more
easily and become available to roots of the plants. At the same time, carbon
dioxide produced by roots, by microorganisms, or by chemical reactions in the
soil were able to diffuse through the air-filled pores to the surface.
The water table should not be lowered so deep that a severe water
deficiency will cause death or reduced plant production. Therefore, water table
management systems have been used to maintain the required water table
depths in the field during certain periods of the growing season. These systems
are known by various names such as drainage, controlled drainage, drainage-
subirrigation, controlled drainage-subirrigation, controlled and reversible drainage
(Shirmohammadi et al., 1992).
Research to improve water table management was given considerable
emphasis in the United States during the 1970s. Ideas developed by Schwab
(1951) and van Schilfgaarde (1965) led to improved system development by
others (Skaggs, 1974; Doty and Parsons, 1979). Water table management
research has primarily been conducted during the last decade in states such as
Iowa, Michigan, Ohio, Indiana, Louisiana, and North Carolina (Hallberg, 1986;
Kanwar et al., 1988; Kanwar and Baker 1991; Kalita and Kanwar, 1992);
Bengtson et al., 1993; Fausey, 1991; Sabbagh et al., 1991 ; Gilliam and
Skaggs, 1986; Cooper et al., 1991; Wright et al., 1989. Most of this research
has focussed on crop yields, economic benefits, and modeling the flow
8
systems. However, in the last decade a few researchers have initiated studies
on the effect of water table management practices on groundwater quality.
Much of this research is being conducted in the north-central (Gish et al., 1991;
Southwick et al., 1992; Southwick et al., 1993; Bengtson et al., 1993), and
mid-western states including Iowa (Kalita and Kanwar, 1993). Water table
management in the artificially drained areas of Iowa is very important to
sustainable agriculture because about 40 percent of the state's corn and
soybean acreage being currently drained.
Water table depth and crop production
Numerous field and laboratory experiments on the effects of water table
depth on crop yields have been conducted at various locations, but it is difficult
to transfer the results from one location to another because of different soil
types, climatic conditions, and irrigation methods. A water table depth 15 cm
below the soil surface has produced maximum yield for certain crops under
certain conditions while other crops have performed best with the water table at
90 cm or an intermediate depth.
Crop response to water table depth from earlier studies has been reported
in the literature. Williamson (1964) studied different plant species under
different water table depths of 15, 30, 46, 61, and 76 cm below the soil
surface. He found that the yields of grain sorghum, soybean, cabbage, sweet
9
corn, and dwarf field corn for the 15 cm water table depth were reduced by 25,
35, 40, 65, and 75%, respectively. Coins et al. (1966) found that tomato
yields increased as the water table was lowered from 15 to 80 cm. There was
no statistically significant difference among soil types. In a lysimeter study
conducted in North Carolina, Williamson (1968) found that the yield for
stringbeans and cabbage in fine sandy loam was maximum with the water table
at 30 and 45 cm, respectively, van Schilfgaarde and Williamson (1965) found
the maximum yield of soybeans in fine sandy loam when subsurface irrigation
occurred when the water table depth was at 30 cm below the soil surface.
Williamson and Khz (1970) found that optimum water-table depth under
different soil types was a major factor contributing crop production for many
crop species.
Gosnel (1971) studied the effect of water table elevations on the growth
of sugarcane and observed that sugarcane germination was significantly
reduced if the water table depth was at 25 cm from the soil surface. However,
he found good germination and higher yield when the water table depth was
lowered to about 50 cm from the soil surface. Wesseling (1974) reported that
shallow water-table depths reduced oxygen supply to the roots and decreased
nutrient uptake and crop growth.
Meek et al. (1980) determined the growth of cotton under three different
water table depths (30, 60, 90 cm). They found optimum yield with a water
10
table depth of 90 cm. At water table depths of 30 and 60 cm, cotton yield was
reduced by 43 and 25%, respectively.
Kanwar et al. (1983, 1984) found that inadequate drainage of heavy soil
reduced crop yield by about one-third of the potential yield. Cavazza and Pisa
(1988) found the maximum yield of wheat with a 1.25 m water table depth.
Any drop in the water depth beyond this level caused moisture shortages in the
root zone which significantly reduced crop yield.
Recently, water table management by controlled drainage or controlled
drainage-subirrigation practices have received renewed attention because
excessive soil water has become a major factor affecting crop growth and yield.
Numerous field and lysimeter experiments (Ahmed et al., 1992; Kalita and
Kanwar, 1992; Evans et al., 1990; Kanwar et al., 1988; Mukhtar et al., 1990)
have been conducted to determine crop responses under different water table
management practices.
Bhuiyan and Alagcan (1990) investigated the growth response of corn to
changes in the shallow water table in fields near irrigation canals or rice areas.
They found that lowering the water table a small amount produced a strong
negative response in both plant height and yield. The investigators indicated
that during the vegetative growth stage of corn, yields above 7.3 t/ha could be
achieved by controlling the average water-table depth at 15 cm.
In Iowa, Kalita and Kanwar (1992) studied response of corn to water
11
table depths of 20, 30, 60, 90, and 110 cm below the soil surface. They found
that corn yields increased with increasing water table depths. For water table
depths of 20 and 30 cm, corn yield decreased significantly compared with
yields from plots with deeper water table depths. Dry and wet seasons
significantly affected grain yield. Plant water use efficiency and grain yield
were significantly related. Ahmed et al. (1992) investigated effects of soil
surface submergence and a water table depth at 15 cm on corn vegetative
growth. They observed that plant growth was significantly affected by
excessive water stress due to soil submergence as compared to that under 15
cm depth.
Photosynthesis response and crop yield
Photosynthesis is the ultimate physiological factor limiting the plant
growth, which in turn affects crop production. Crop growth and yield depend
upon the production and partitioning of carbon assimilates. The rate of
photosynthesis as measured by COg uptake per unit area of leaf surface,
depends on the plant's photosynthetic capacity, and on environmental factors
such as CO2 level, solar radiation, air and leaf temperature, soil moisture
availability, nutrient availability etc. (Gimenez et al., 1992). Photosynthesis rate
also depends on variety of plant parameters such as genotype, plant stage, leaf
age, leaf orientation and position, plant density, and assimilate demand by sink
12
(Dwyer et al., 1989). Differences among genotypes may be due to morphology,
resulting in different mesophyll resistances, or they may be explained by the
timing and size of carbohydrate requirement of other parts of the plant,
particularly the grain (Hunt and van der Poorten, 1985; Hesketh, 1963).
Photosynthesis responses for a wide variety of crops including maize
have been documented in the literature (Bhagsari and Harmon, 1982; Bhagsari,
1988; Dwyer and Stewart, 1986; Dywer et al., 1991; Thiagarajah et al., 1981).
Constable and Rawson (1980), observed that the photosynthesis rates of 40
day old tall fescue leaves were only 20% of their maximum photosynthesis rate,
whereas, for 60 day old cotton leaves, it was 30% of the maximum
Photosynthesis rate (Jewiss and Woledge, 1967). Bhagsari (1988) reported
decreases in net photosynthesis and stomatal conductance with increasing leaf
age for sweet potato under field conditions in full sunlight (above 1500 u mole
m ̂ s'^). Dwyer et al. (1989) reported cultiver differences in photosynthèse
rates as a function of plant age, and pointed that late-maturing cultivars had
higher photosynthetic rates than early-maturing cultivars at comparable growth
stages.
Pearson et al. (1984) observed that the photosynthesis rate for the upper
canopy leaves of 85-day-old maize was three to six times higher than for the
lower canopy leaves. However, Thiagarajah et al. (1981) observed that the COg
exchange rate (CER) of newly matured leaves of hybrid corn was lower for
13
leaves produced in the early stages of ontogeny than for older ones.
Under non-stressed conditions, irradiance is the most important
environmental factor causing variations in photosynthetic rates (Reed et al.,
1976; Hari et al., 1981). Dwyer and Stewart (1986) observed that the
dependence of photosynthetic rate on irradiance was a nonlinear function best
described by a rectangular hyperbolic equation.
Photosynthesis also varies in response to other environmental factors.
Cristy and Porter (1982) found that the net photosynthesis rate of soybean was
significantly reduced by cloud cover, cold temperatures, and water limitations.
Water stress reduced photosynthesis by increasing the resistance of COg
diffusion into the leaf surfaces by closure and "Patchiness" of stomata
(Downton at al., 1988; Sharicey and Seemann, 1989). Kalita and Kanwar
(1992) compared photosynthesis rates under varying water table depths and
observed higher photosynthesis rates when the soil moisture was not limiting.
Stomatal conductance under different moisture conditions
Processes such as photosynthesis are slowed as leaves age. The
photosynthesis decline rate appears to be related to a decrease in stomatal
conductance (Atkinson et al., 1989). Finn and Burn (1980) observed that
stomatal conductance directly affects transpiration rate and photosynthesis and
indirectly influence Nj fixation. Several other studies have reported a linear
14
relationship between stomatal conductance and photosynthesis (Field, 1987;
Wong et al., 1979; Farquhar and Wong, 1984).
The two most important environmental factors most likely to have the
greatest effect on the stomatal behavior of many field crops are light and water.
Water deficits cause stomata to close which reduces transpiration and
photosynthesis activities {Selmani and Wassom, 1992). Stomatal conductance
may be more closely related to soil water availability, however, than to short-
term variation in leaf water potential (Osonubi, 1985; Turner et al., 1985;
Gollan et al., 1986; Kûppers et al., 1988). Tan and Layne (1991) reported
lower leaf stomatal conductance in mature peaches under low soil moisture
conditions compared with high soil moisture conditions.
Kalita and Kanwar (1992) evaluated the water table management effects
on corn growth using energy balance concept. They observed that crop
physiological parameters (stomatal conductance, transpiration rate, and net
radiation) were very sensitive to the water table depth during the vegetative and
flowering stages of corn. The highest values of stomatal conductance,
transpiration rate, and net radiation were observed for a water table depth of
0.3 m. On the contrary, a shallow water table depth of 0.2 caused
waterlogging in the root zone and resulted in the poorest plant growth and the
lowest values of stomatal conductance, transpiration rate, and net radiation.
Their results indicate that plant physiological parameters could be used to
15
evaluate and develop the best management practices.
Relationship between chlorophyll content and crop yield
The greenness of a plant is an indicator of its health. Since healthy
plants contain more chlorophyll, the amount of chlorophyll present in plant
leaves can serve as an indicator of the overall condition of the plant. If a
reliable measurement of chlorophyll content can be made in-season and
correlated with the nitrogen content of a plant, then supplemental nitrogen
fertilizer can be added without time-consuming sampling and laboratory
analysis.
The application of fertilizer N for optimum crop production is important,
but, contamination of surface and groundwater due to leaching of applied
nitrogen fertilizers has become a growing concern. Accurate predictions of N
status in the field are needed to efficiently use fertilizer N and minimize surface
and groundwater contamination. Soil tests for this purpose have successfully
been used in regions of low rainfall, such as the western U.S. where minimal
NO3-N leaching occurs (Wood et al., 1992a). Several methods have been used
to assess N status in the soil and plant that could help improve N management
(Binford et al., 1990; Blackmer et al., 1989; Fox et al., 1989; Hong et al.,
1990; Piekielek and Fox, 1992). AH these N testing methods involve collecting
soil or tissue samples, drying, grinding and screening the samples, and
16
analyzing the samples with laboratory or field instruments. From this
information, fertilization programs for the specific field and crop conditions can
be developed. Too little N early in the growing season may limit vegetative
growth and cause a yield reduction, while excess N may promote vegetative
growth and delay maturity.
Recently, hand held meters that rapidly determine leaf chlorophyll have
become available in the U.S. One commercial meter, the SPAD-502 chlorophyll
meter (Soil-Plant Analysis Development, Minolta Camera Co. Ltd. Japan) is
effective for determining the N status of major crops. There is generally a
positive correlation between leaf chlorophyll content (as determined by the
chlorophyll meter), crop N uptake, leaf N concentration, and grain yield.
In contrast, Schepers et al. (1992) concluded that using the SPAD-502
chlorophyll meters to determine crop N status may not be practical because of
the unique "greenness" characteristics of different hybrids. They recommended
calibrating the meter using direct measurements of leaf N to standardize the
meter test for different hybrids, locations, and growth stages. This
standardization process can be done by comparing chlorophyll meter readings
from well fertilized plants to readings from plants in the test area.
Wood et al. (1992a) found significant relationships between SPAD-502
readings and corn grain yield during two years of study. At maximum
agronomic yields of 6898 kg ha^ in 1990 and 9233 kg ha"^ in 1991, SPAD-502
17
readings were 56 and 56.8, respectively, at the VI0 stage of growth. Readings
at the midsilk stage were 60.2 and 62.3, respectively. Chlorophyll
measurements at V10 were especially promising because supplemental N could
easily be applied at that stage of growth. In another experiment. Wood et al.
(1992b) compared leaf blade N and chlorophyll meter readings at three growth
stages for cotton, first square, first bloom, and midbloom. The chlorophyll
meter readings were highly correlated to leaf blade N concentration at all three
stages. Chlorophyll readings were a good predictor of seed cotton yield. Leaf
chlorophyll readings at maximum economic yield were 39, 49, and 47 at first
square, first bloom, and midbloom stages, respectively. At midbloom, the
chlorophyll meter reading were lower for irrigated cotton than for non-irrigated
cotton.
Follett et al. (1992) in a study conducted in Colorado compared dry land
winter wheat yield, leaf N concentration, soil N tests, and SPAD-502 chlorophyll
meter readings. There was a positive association between grain yield and
chlorophyll meter readings, N leaf concentration, and soil combined NH^-N and
NO3-N. The authors stressed the need for additional studies to evaluate other
factors such as difference among locations, cultivars, soil moisture and profile N
status. Reeves et al. (1993) conducted a field study on wheat in east-central
Alabama. Leaf chlorophyll meter readings were significantly correlated to tissue
N concentration and grain yield. The best predictor of grain yield was N uptake
18
at growth stage 5, but chlorophyll meter reading and dry matter at growth stage
5 were also good predictors of yield.
Estill et al. (1991) evaluated alfalfa leaf chlorophyll response to different
moisture regimes for two color variants (pale and dark). The chlorophyll
concentration of pale variants remained the same for the moisture extremes,
While the chlorophyll in the dark variants was 20% lower in the low moisture
regime compared with the high moisture treatments.
Water table management for NO3-N improvement
Although, the use of fertilizers and pesticides is currently an integral part
of crop production in the U.S.A. and elsewhere. The contamination of surface
and groundwater due to the leaching of these chemicals is becoming a serious
threat to human health, wildlife and the environment (Prunty and Montgomery,
1991). Particularly, nitrate leaching into groundwater has become one of the
major pollution concerns facing agriculture today (Hallberg, 1984). Studies
during the past decade have documented the detrimental effects of agriculture
on water quality (Hallberg, 1989; Schaller and Baily, 1983; Hamlett et al.,
1990). These studies suggest that surface and groundwater resources are
vulnerable to non-point pollution from agricultural activities.
Nitrate-nitrogen (NO3-N) concentrations exceeding the 10 mg/L safe
drinking water limit, have been detected in both surface and groundwater
19
supplies all across the midwestern and in other states in the U.S. (Hubbard and
Sheridan, 1989). The public is especially concerned because the NO3-N
concentrations in excess of 10 mg/L in drinking waters cause serious health
problems (such as methemoglobinemia) to infants who drink this water. The
problems receiving the most attention from researchers are the contribution of
nutrients to eutrophication of surface water resources, and the increased levels
of NO3-N in the drinking water. In the past two decades, much work has been
done to characterize nutrient losses through drainage systems and the effect of
these losses on water quality and crop productivity. Several studies conducted
in Iowa (Baker and Johnson, 1981; Kanwar et al., 1985; Kanwar et al., 1988;
Kanwar, 1991; Kanwar and Baker, 1991) have shown that great quantities of
NO3-N were rapidly leaching to shallow groundwaters. In 1988 through 1989,
a survey of private rural wells in Iowa found that 18% of the water in all wells
had NO3-N concentrations above the 10 mg/L drinking water standard, while
35% of the samples from wells less than 50 ft deep had NO3-N concentrations
above the standard (Anonymous, 1990). These and other studies all across the
U.S., have reported that NO3-N concentrations in subsurface drainage from row-
crop land usually exceeded the 10 mg/L drinking water standard, and, as
fertilization increased, NO3-N concentrations in tile drainage water sometimes
approached 100 mg/L (Kanwar, 1991). Ritter and Manger (1985) and
Lowrance (1981) reported that NO3-N concentrations in subsurface drainage
20
from agriculturally influenced areas ranged from 20 to 47 mg/L on coastal plain
soils. Skaggs et al. (1982) found wide variability in NO3-N losses from drainage
systems on muck and clay soils in North Carolina.
Water-table management (WTIVI) practices, especially controlled drainage
and drainage-subirrigation, have shown potential for inducing denitrification and
reducing the concentration of agricultural chemicals reaching water supplies
(Skaggs and Gilliam, 1981; Gilliam and Skaggs, 1986; Evans and Skaggs,
1989; Wright et al., 1989; Wright, 1990; Kalita and Kanwar, 1989; Kanwar and
Kalita, 1990; Kalita and Kanwar, 1993).
During the last few years, several studies have addressed the effects of
WTIVI practices under different soils, crops, and climatic conditions, such as, in
Iowa (Kanwar, 1990; Kalita and Kanwar, 1992), Michigan (Belcher and Merva,
1991), Ohio (Fausey et al., 1991), North Carolina (Skaggs et al., 1991),
Louisiana (Bengtson et al., 1991), Georgia (Thomas et al., 1987a, 1992). The
main focus in these studies has been crop yields, economic benefits, and
groundwater modeling. Few other studies have been reported in the literature
which address the benefits of WTIVI practices in relation to reducing nutrient
transport in drainage outflow.
Bengtson et al. (1988) studied the influence of subsurface drainage
practices on nitrogen and phosphorus losses on a Commerce clay soil in the
lower Mississippi River Valley. Compared to undrained areas, they found that
21
subsurface drainage reduced surface runoff by 34%, erosion by 30%, and
nitrogen and phosphorus losses by 20 and 36%, respectively.
Thomas et al. {1987b, 1991) measured NO3-N concentrations in shallow
subsurface wells and outlets of a controlled drainage-subirrigation system in a
blueberry field in the Georgia flatwoods. Their results showed that NO3-N
concentrations were less than the 10 mg/L maximum contaminant level (MCL)
for public drinking supplies for all outflow samples, although 6% of the shallow
groundwater samples within the field exceeded this limit.
Evans et al. (1989a) presented a compilation of data from North Carolina
supporting the classification of controlled drainage as a best management
practice. Their data showed that controlled drainage reduced both surface and
subsurface nitrogen losses as opposed to uncontrolled drainage. They
concluded that denitrification accounted for the reduced nitrogen transport from
controlled drainage site in eastern North Carolina where conditions are
conducive to denitrification. In another study, Evans et al. (1989b) reported
that the controlled drainage reduced the annual transport of total nitrogen (NO3-
N and TKN) at the field edge by 46.5% and total phosphorus by 44%. In
previous studies, similar results have been reported using simulation methods
(Skaggs and Gilliam, 1981; Deal et al., 1986).
Gilliam et al. (1979) compared nitrate concentrations from uncontrolled
and controlled drained fields, and found nearly a 50% reduction in nitrate losses
22
under controlled drainage. While comparing nitrate transport from controlled
and conventional drainage systems, Gilliam and Skaggs (1986) observed a 32%
reduction in nitrate outflow with controlled drainage as compared to
conventional drainage.
Hubbard et al. (1991) determined transport of NO3-N by surface runoff,
and shallow subsurface flow on a sandy coastal plain soil having plinthic sub
soil material. They observed that most of the NO3-N leached from the upper 30
cm of the root zone within 1 % month after N application. NO3-N
concentrations in surface runoff were very small, with monthly loads not
exceeding 0.3 kg ha \ However, NO3-N concentrations in shallow groundwater
(at the 0.9 to 1.8 m sampling depth) were between 11 to 19 mg/L.
Weight et al. (1992) simulated a controlled drainage-subirrigation (CD-SI)
system to investigate the effects of different WTM practices on water quality.
The results from their CD-SI simulations indicate that raising the water table
during the fallow season can reduce nitrogen leaching by increasing
denitrification. It can also increase the amount of nitrogen lost in runoff and in
sediment. They pointed out that, water table management using a CD-SI
system increased predicted runoff nitrogen by 340% and increased predicted
sediment nitrogen loss by 118%, it decreased nitrogen leaching by 35.1 %.
They concluded that, the predicted total average nitrogen non-point source
pollution losses were 17.8% less for the CD-SI system than for the subsurface
23
drainage system.
Studying effects of WTM on NO3-N transport to shallow groundwater,
Kalita and Kanwar (1993) found that nitrate concentrations were reduced by
maintaining shallow water table depths in the range of 0.3 to 0.6 m. In the
unsaturated zone of the soil profile, NO3-N concentrations as high as 285 mg/L
were observed, but the average NO3-N concentrations in the groundwater never
exceeded the 10 mg/L drinking water standard. Drury et al. (1991); and Myrold
and Tiedje (1985), found that the average NO3-N concentrations in groundwater
were generally lower where shallow water table depths were maintained.
Bottcher et al. (1981) measured mean annual sediment, nitrogen, and
phosphorus losses of 94, 8.66, and 0.22 kg/ha, respectively, from a subsurface
drained area near Woodburn, Indiana. Their results showed that losses of
sediment and nutrient were reduced by subsurface drainage. They
recommended that on a suitable soil, subsurface drainage may well be preferred
as a best management practice for water quality control. Kladivko et al. (1991)
determined field scale NO3-N losses to subsurface drainage on a low organic
matter and poorly structured silt loam soil under typical agricultural management
practices in Indiana. They found that the annual NO3-N losses in subsurface
drain flow ranged from 18 to 70 kg/ha.
24
Pesticides in the groundwater
IVIodern agriculture is heavily dependent on the use of agrichemicals,
particularly fertilizers and pesticides. As of 1982, the pesticide usage in the
United States was nearly 300 million kilograms, and 85 percent of this usage
was in corn belt states such as Iowa, Illinois, Indiana, Ohio, and Michigan
(Hallberg, 1986). A major concern is that low concentrations of less soluble but
widely used pesticides have been detected in shallow aquifers under a wide
range of agricultural and climatic conditions. In 1986 the Environmental
Protection Agency (EPA) reported the presence of 17 pesticides in groundwater
in 23 states (Cohen et al., 1986). However, during recent years this figure has
gone up, and the reported cases increased to 77 pesticides in groundwater in
39 states (Williams et al 1988).
During the past decade numerous studies have been conducted to
characterize the fate and movement of applied pesticides and their impact on
surface and groundwater. This is of particular concern because groundwater is
the predominant source of domestic water in most rural areas in the United
States (National, 1985). It is estimated that 97% of the nation's rural
population relies on groundwater as its source of drinking water (Moody, 1990).
According to Fitter (1986), widely used herbicides such as atrazine,
alachlor, metalachlor, and cyanazine have been detected in groundwater
systems of several states. He further reported that atrazine and alachlor
25
together accounted for 25 percent of all pesticides sold in U.S. during 1982.
Isensee et al. (1988) reported that three corn production herbicides,
atrazine [2-chloro-4-(ethylamlno)-6-(isopropylamino)-S-triazine], alachlor [2-
chloro-2',6'-diethyl-N-(methoxymethyl) acetanilide], and cyanazine [2-chloro-4-
(cyano-1-methylamino)-6-ethylamino-S-triazine], have been detected in
groundwater in many states because of their wide application. They found that
atrazine concentration in shallow groundwater was between 0.2 to 1.8 ppb and
that of alachlor was 0.3 ppb. These concentrations were far below the health
advisory limits for atrazine (3 //g/L) and alachlor (2 //g/L).
Alachlor has been found to be less persistent than atrazine in soil profiles
(Buhler et al., 1993). In their tests of drain outflow, alachlor was found in only
2% of samples whereas atrazine was detected in 97% of the samples taken in a
6 year period. Alachlor has been reported in groundwater samples in Iowa,
Nebraska, Maryland, and Pennsylvania at residue levels of 0.1-10 //g/L (Cohen
et al., 1986). Alachlor concentration in groundwater as high as 16 /vg/L was
found in Iowa (Kelley et al., 1986). Libra et al. (1986); and Kelley et al. (1986)
reported that atrazine concentrations of 10 //g/L were detected in a karst aquifer
in Iowa.
In a study. Smith et al. (1990) found that atrazine concentration in the
soil water, at a depth of 0.61 m, reached 350//g/L 19 days after application.
They also reported atrazine concentration as high as 90 //g/L were observed
26
in the shallow groundwater 16 months after application, however, alachlor was
not detected in the soil below 0.36 m. They hypothized that apparently most of
the alachlor had degraded during their experimental period.
Factors affecting fate and behavior of pesticides
The four major mechanisms that determine the fate of a pesticide are
adsorption, degradation, volatilization, and leaching/runoff. The rate of these
mechanisms is influenced by management practices, environmental conditions,
and physical and chemical properties of the applied chemical. Jury (1986a)
described physical and chemical properties effecting the fate and transport of
pesticides in a porous media. Those properties are solubility, vapor pressure,
toxicity, adsorption rate, and soil reactivity. The environmental conditions
influencing the fate of atrazine include rainfall, temperature, soil properties, and
rate of erosion. Whereas, rate of pesticide application, method of application,
cropping method, irrigation and/or drainage practices, and chemical used and its
formulation also influence the fate and transport of pesticide. For example, in a
study on atrazine leaching, Schriber et al. (1993) observed significant reduction
in the loss of atrazine from a starch encapsulated formulation as compared to
those from liquid formulations. Wienhold and Gish (1992) reported the relation
between water potential, temperature, soil microbial activity and release of
starch encapsulated atrazine and alachlor. They concluded that escapusulated
27
formulation resulted in slow release of the herbicide and the rate of release
declined with declining water potential. A study conducted by Shirmohammadi
et al. (1992) also showed higher concentrations of atrazine at depths shallower
than 8 cm in the field treated with encapsulated atrazine. Below the 8 cm
depth the concentration of atrazine was higher in the fields supplied with
conventional application of the pesticide (liquid formulation).
Smith et al. (1988) mentioned some of the soil properties that influence
pesticide transport are water content, bulk density, permeability, clay content,
organic matter content, and water retention. Gish et al. (1991) pointed out that
soil texture may play an important role in preventing pesticide movement to
deeper depths in the soil profile. They reported from their study that only 1 %
of applied atrazine was detected below the 45 cm depth. However, there were
no textural, hydraulic and physical properties available to express this pattern of
movement. Wietersen et al. (1993) monitored transport mechanisms of
atrazine, alachlor, and metolachlor through soil columns of Sparta sand and
Plainfield sand in Wisconsin. They observed that all pesticides were more
mobile through the Sparta sand as compared to the Plainfield sand. Atrazine
concentration was 15 times greater in the leachate from Sparta sand than from
Plainfield. Similar results were found for alachlor and metolachlor. The relative
order of mobility for each soil was found to be atrazine > metolachlor >
alachlor. The factors found to contribute to increased mobility of pesticides
28
through the Sparta sand include higher hydraulic conductivity, smaller water
holding capacity, and less atrazine adsorption. The hydraulic conductivity of
the upper root-zone (0-20 cm) of the Sparta sand was 5 time greater than the
Plainfield sand.
Jury (1986b) reported that precipitation, evapo-transpiration, and
temperature were among some of the environmental factors influencing
pesticide transport. Plant processes affecting pesticide transport are very
complex. Donigian and Rao (1986) explained that the uptake, translocation,
accumulation, and transformation of pesticides by plants affect the availability
of pesticides for transport processes and the potential exposure to pesticide
residues by the consumers of the vegetation, fruits, etc. Plant processes can
serve both as a sink and a source of pesticide residues available for transport.
Plant cover has been observed to influence pesticide persistence as a
result of lower soil temperature during summer. Birk and Roadhouse (1964)
found atrazine to be more persistent in soil planted to corn than in fallow land.
This was attributed to transpiration of the crop maintaining relatively dry soil
and reducing the microbiological degradation of the herbicide. In contrast, Sikka
and Davis (1966) found that uptake and metabolism by the crop reduced
atrazine persistence in soil planted to corn. Lower atrazine concentration was
found in the top 0.15 m depth of cropped plots than in fallow plots at all
sampling dates up to 6 months after planting. Pesticide leaching may be
29
affected by the amount and type of vegetation on the soil surface. Sigua et al.
(1993) reported that covering soil cores with 2000 or 8000 kg ha'^ of crop
residue reduced atrazine leaching by 26% to 37%, respectively, compared with
soil cores without crop residue. Furthermore, they also observed that the soil
cores covered with recently harvested vegetation reduced atrazine leaching by
39% compared with cores covered with aged crop residue.
Hiltbold (1974) hypothized that soil flooding and temporary anaerobiosis
may permit reductive degradation of certain pesticides and markedly alter their
persistence. Results of field experiments by Guenzi et al. (1971) and laboratory
experiments by Castro and Yoshida (1971) showed that flooding influenced
biodégradation rather than chemical degradation of pesticides.
Pesticide control through water table management
There is scant literature on pesticide management with water table
management practices. However, recently these management practices have
received attention as potential measures to reduce pollution hazards to
groundwater systems. Few studies have shown that WTM practices that
include controlled drainage, and controlled drainage-subirrigation can reduce
pesticide concentrations in shallow groundwater and improve crop yield (Baker,
1980; Baker and Johnson, 1976; Bengtson et al., 1990; Evans et al., 1989;
Fausey et al., 1990; Kanwar, 1990; Kanwar et al., 1988; Kalita and Kanwar,
30
1989, 1990; and Kalita, 1992).
Baker (1980) and Baker and Johnson (1976) found that the concentration
of most herbicides and insecticides were higher in surface runoff than in
subsurface drainage, but chemicals that were not adsorbed, such as anionic
herbicides, usually had higher concentrations in the subsurface drainage.
Kladivko et al. (1991) determined field scale pesticide losses to
subsurface drainage on a low organic matter and poorly structured silt loam soil
under typical agricultural management practices. They observed small amounts
of carbofuran, atrazine, cyanazine, and alachlor in subsurface drain flow within
3 weeks of pesticide application. The annual carbofuran losses in subsurface
drain flow ranged from 0.8 to 14.1 g/ha, whereas, the losses of all other
pesticides were ^ 0.06% of the amount applied.
Bengtson et al. (1990) reported that atrazine and metolachlor losses were
reduced by 55 and 51 percent, respectively, in the areas where subsurface
drainage systems were used. They concluded that subsurface drainage
substantially reduced atrazine losses, and about 2/3 of the losses occurred
within 30 days after herbicide application. They also found that atrazine
concentrations were substantially greater than EPA's advisory level for drinking
water. In another study, Bengtson et al. (1993) reported that subsurface
drainage reduced alachlor and norflurazon losses by 34 and 31%, respectively.
In a recent study conducted in Iowa, Kalita (1992) observed that under
31
different water table depths, pesticide concentrations were lower at shallow
water table depths, however pesticide concentrations in the groundwater
increased with lowering water table depths. Higher concentrations of atrazine
and alachlor were observed when water table depths were maintained at 0.9 m
or deeper. Results of this and other studies have stressed the need for further
research on the use of WTM practices to reduce groundwater contamination
caused through the use of pesticides.
32
PAPER I. EFFECTS OF WATER TABLE DEPTHS ON DIFFERENT PLANT
PHYSIOLOGICAL PARAMETERS
33
ABSTRACT
A study was conducted to evaluate the effects of various water table
depth (WTD) practices on plant physiological parameters. Data for 1992 and
1993 were collected from field experiments conducted at two sites in Iowa
(Ankeny and Ames). At the Ankeny site, water table depths were maintained at
0.2, 0.3, 0.6, 0.9, and 1.1 m depths on a 0.5 ha subirrigation field, whereas
water table depths of 0.3, 0.6, and 0.9 m were maintained in lysimeter plots at
the Ames site. Measurements on different physiological parameters
(photosynthesis, stomatal conductance, transpiration, intercellular COg (Ci), and
canopy temperatures) were taken on a biweekly basis using leaf chamber
techniques, and those on chlorophyll were taken using a SPAD-502 chlorophyll
meter. The yield data were collected at harvest.
Analysis of the data revealed that photosynthesis rates, stomatal
conductances, transpiration rates. Ci, canopy temperatures, and chlorophyll
were correlated with various WTDs during the growing season. The values of
these parameters were significantly affected at WTDs of 0.2 and 1.1 m as
compared to those at WTDs of 0.3, 0.6, and 0.9 m. The 0.3 WTD resulted in
larger values of these physiological parameters, and these values decreased
with the lowered WTD. In 1993, an extremely wet year, the values of
physiological parameters were lower than those in 1992 under all WTDs.
34
The statistical analysis of the data showed that means for photosynthesis
between WTDs for the Ames site were significantly different at the 0.05
probability level during both years, whereas those were not significant for 1993
at Ankeny site. However, the means for chlorophyll readings between WTDs
were significantly different at the 0.05 probability level at both sites for both
years. The stomatal conductances were not significant at the 0.05 probability
level.
Relationships between different parameters were developed by fitting
lines of linear regression. The regression analysis showed strong positive
relations between photosynthesis and leaf chlorophyll readings for 1992 and
1993, at both experimental sites. Results of these analyses revealed that leaf
chlorophyll could be used as a good predictor of photosynthesis rates regardless
of water table treatment depth. Also, a strong positive relation between
stomatal conductance and transpiration rates was observed. The regression
analysis revealed that the transpiration rates were highly dependent on the
stomatal behavior.
35
INTRODUCTION
The management of soil water for agricultural cropland in humid and
semi-humid areas of the U.S. is complicated by the erratic spatial and temporal
occurrence of rainfall. In many humid areas, such as the mid-western region of
the U.S., periods of excess and deficit soil water conditions occur within the
same cropping season, which sometimes lead to production losses in those
areas. Therefore, proper soil and water management are one of the most
important challenges in those and other humid areas to reduce soil productivity
losses and excessive off-site impacts. One technique to counter these
challenges is the efficient management of water in agricultural soils.
The primary purposes of water table control are to minimize the time of
excess or deficit soil-water conditions in the root-zone, and to maximize the use
of natural rainfall, thus minimizing the amount of subirrigation water required
from external sources for irrigated systems. Water table management which
includes both irrigation and drainage, can improve productivity in humid and
semi-humid climates, where weather extremes can result in crop loss, and in
arid areas, where salinity control is necessary for sustainable agriculture.
Research to improve water table management was given considerable
emphasis in the United States during the 1970s. Ideas developed by Schwab
(1951) and van Schilfgaarde (1965) led to improved systems development by
36
others (Skaggs, 1974; Doty and Parsons, 1979). In the past, the direct aim of
water table management systems in humid regions was to lower the moisture
content of upper layers of the soil so that air can penetrate into the soil easily
and become available to plant roots. At the same time, it is necessary that
carbon dioxide produced by roots, by microorganisms, or by chemical reactions
in the soil can diffuse through the air-filled pores to the surface. On the other
hand, the water table should not be lowered so deep that a severe deficiency of
moisture may cause death or reduced plant production.
Water table management research has primarily been conducted during
the last decade in states such as Iowa, Michigan, Ohio, Indiana, Louisiana, and
North Carolina. Most of this research has focussed on crop yields, economic
benefits and modeling of the flow systems. Water table management such as
drainage, drainage-subirrigation, controlled drainage-subirrigation, controlled and
reversible drainage have received renewed attention because the excessive soil
water has become a major factor affecting crop growth and yield. Numerous
field and lysimeter experiments (Ahmed et al., 1992; Kalita and Kanwar, 1992;
Evans et al., 1990; Kanwar et al., 1988; Mukhtar et al., 1990) have been
conducted to determine crop yield response to water table management.
However, the data on the effects of water table management practices on crop
physiological parameters such as photosynthesis rates, stomatal conductance,
intercellular COg, transpiration rates, chlorophyll content, and canopy
37
temperatures are rather scanty.
It has been recognized that processes such as photosynthesis is an
ultimate physiological factor limiting the plant growth which in turn affects crop
production. Photosynthesis CO; assimilation per unit area of leaf surface
depends on the capacity of the plant's photosynthetic mechanism and on those
environmental factors such as CO; supply and radiation which are the
substrates for the process, and on those (e.g. moisture availability, and nutrient
deficiency etc.) that affect the mechanism (Gimenez et al., 1992). Besides
these factors, photosynthesis rate also depends on a variety of plant parameters
such as, genotype, plant stage, leaf age, leaf orientation and position, plant
density, and assimilate demand by sink (Dwyer et al., 1989). Photosynthesis
responses for a variety of crops from several previous studies in general, and
maize in particular have been documented in the literature (Bhagsari and
Harmon, 1982; Bhagsari, 1988; Dwyer and Stewart, 1986; Dywer et al., 1991;
Thiagarajah et al., 1981). Constable and Rawson (1980), observed that the
photosynthesis rates of 40 day old tall fescue leaves were only 20% of their
maximum photosynthesis rate, whereas, for 60 days old cotton leaves, were
30% of the maximum Photosynthesis rates (Jewiss and Woledge, 1967).
Bhagsari (1988) reported decrease in net photosynthesis and stomatal
conductance with increasing leaf age for sweet potato under field conditions in
full sunlight (above 1500 // mole m ̂ s'^). An important factor to this decline in
38
photosynthesis in nnany species appears to be decrease in stomatal
conductance (Atkinson et al. 1989). Owyer et al. (1989) reported cultiver
differences in photosynthetic rates as a function of plant age, and pointed that
late-maturing cultivars had higher photosynthesis rates than early-maturing
cultivars at comparable phenological stages. Finn and Burn (1980) observed
that stomatal conductance directly affects transpiration and photosynthesis
rates and indirectly influence Ng fixation. Several other studies have reported a
linear relationship between stomatal conductance and photosynthesis rates
(Field, 1987; Wong et al. 1979; Farquhar and Wong, 1984). These studies
have indicated that light and water are the two most important environmental
factors most likely to have the greatest effect on stomatal behavior of many
field crops. These studies have shown that water deficits cause stomata to
close which in turn reduces transpiration and photosynthesis activities (Selmani
and Wassom, 1992). However, recent studies on different species have shown
that stomatal conductance may be more closely related to soil water availability
than the short-term variation in leaf water potential (Osonubi, 1985; Turner et
al. 1985; Gollan et al. 1986; Kùppers et al. 1988). In a study, Tan and Layne
(1991) reported lower leaf stomatal conductance in mature peaches under low
soil moisture conditions as compared to one under high soil moisture conditions.
In a recent study, Kalita and Kanwar (1992) compared photosynthesis rates
under varying water table depths and observed higher photosynthesis rates
39
under shallow water table depths than deeper ones.
Chlorophyll Is also important plant physiological parameter which
indicates the nitrogen status of the plant. Therefore, accurate predictions of N
status by measuring chlorophyll in the field can led to efficient utilization of
fertilizer N and protection of surface and groundwaters against contamination.
Several studies have been conduced to assess N status in the soil and plant that
could help improve N management (Binford et al., 1990; Blackmer et al., 1989;
Fox et al., 1989; Hong et al., 1990, Piekielek and Fox, 1992). Few other
studies have related chlorophyll readings with crop yield (Wood et al., 1992;
Follett et al., 1992; Reeves et al., 1993). However, previous studies have not
reported the effects of excess soil-water, water-table management and/or
drainage practices on chlorophyll content.
With the aim of developing better understanding of water table
management practices on plant physiological parameters, this study was
initiated with the following main objectives:
1. To investigate photosynthesis and chlorophyll responses to different water
table depths.
2. To determine the effects of different water depths on stomatal conductance,
transpiration rate, intercellular COg, and canopy temperature.
3. To recommend the best plant parameter for future plant growth
measurements on the basis of this study.
40
MATERIALS AND METHODS
Description of experimental sites
The experimental sites for this study were located on land owned by
Iowa State University near Ames and Ankeny. The experiments at these sites
were conducted during 1992 and 1993. The soils at these sites are
predominantly Nicollet loam in the Clarion-Nicollet-Webster soil association.
Table 1 lists some of the physical properties of the soils at these two sites.
Experimental setup at Ames site
Nine experimental plots with surface slopes ranging from 1 to 3% were used
to construct field lysimeters. The lysimeters (each 3 m wide and 6 m long)
were installed during 1986. A 0.2 m wide and 1.2 m deep trench around the
perimeter of each lysimeter was made using a Ditch Witch^ trencher, and the
bottom of the trench was finished manually with a "tile trench crumber. " The
lysimeter soil remained undisturbed during trench the digging process.
Following the digging of the trench, the each lysimeter was completely enclosed
using a plastic barrier (0.25-mm-thick, polyethylene sheet) which extended from
the soil surface to the bottom of the trench. The purpose of this plastic barrier
^Name of commercial products given for the benefit of readers only. Iowa State University does not endorse any of these products for benefit.
41
was to "isolate" the lysimeter from its surroundings and to minimize any lateral
subsurface water movement between plots. A corrugated, perforated plastic
tube ( 100-mm diameter) was installed at the bottom of the trench inside the
plastic barrier. A 0.9 m wide ditch was dug to a depth of 1.35 m with a back
hoe mounted on the Ditch Witch trencher to install a 1.5 m tall corrugated
plastic pipe (0.46-m OD X 0.032-m wall) at the corner of each lysimeter. The
bottom of 1.5 m tall sump was located 1.35 below the soil surface, and the top
of the sump was 0.15 m above the soil surface. The two ends of the
perforated plastic tubes at right angles to each other were inserted into the
sump at a height of 0.15 m from the bottom of the sump. The trenches were
back-filled with the excavated soil. In 1989, all lysimeters were enclosed with
another 0.25 mm-thick PVC (poly-vinyl-chloride) flexible liner to a depth of 1.7
m. Each liner encased a square area (9 m X 9 m) with the 3 X 6 m original field
lysimeter located in the center of the enclosed area to ensure that subsurface
water did not move laterally between lysimeters to a depth of 1.7 m. A detailed
procedure for the lysimeter installation is described by Kalita and Kanwar
(1990), and is also shown in Figure 1. Figure 1 shows an isometric view of the
lysimeter with installed sump and float assembly. A float mechanism was
installed in each sump to maintain the desired water level in the lysimeter plot
area. Each lysimeter was connected to the main water-supply tank using a 75-
mm diameter PVC irrigation pipe. The niain water-supply tank {1.6-m high and
42
1.3-m inside diameter) was raised 2 m from the soil surface on a concrete floor
to maintain sufficient hydraulic head for gravity flow of water from the tank to
all lyslmeters for maintaining water tables in the plot area. The layout of the
experimental area is shown in Figure 2.
Experimental setup at Ankeny site
In 1988, a dual pipe subirrigation system was installed at this site on a
0.5-ha area with significant natural ground slope of 2.5 percent. The basic
concept of the dual-pipe subirrigation system is illustrated in Figure 3. Shallow
irrigation pipes (51-mm diameter) were installed at a depth of 0.5 to 0.6 m
parallel to and midway between drainage pipes, which were installed at a depth
of 1.2 m. Drainage lines discharged into a sump from which water is pumped
into a storage reservoir. The storage reservoir has a storage capacity of
approximately 900 cubic meters. During irrigation, water is pumped from the
reservoir into a head tank at the top of the plot area, where the water is
distributed to the laterals by a sub-main line equipped with valves to control
pressure in the supply line. Because of the natural ground slope along the
length of the field, water tables could be maintained at various depths below
the soil surface by controlling the subsurface drainage outflows and by
supplying irrigation water through the subirrigation pipes.
43
Water table management treatments
At the Ames site, water table depths were maintained at 0.3, 0.6, and
0.9 m in 1992 and 1993. Each water table depth treatment was replicated
three times. Water table depths were maintained to the desired depths from
day 49 to 110th day after planting (DAP) during the growing season of 1992,
and from 50 to 98 DAP during the growing season of 1993. The elapsed time
of about 50 days from planting to the start of water-table treatment allowed
corn roots to develop within 0.3 to 0.9 m soil profile, it took almost three days
to bring the water tables to the required depths during 1992, whereas, during
1993, the record wet year, there was no problem in bringing the water tables
near the surface but many times water tables had to be lowered using a sump
pump. Observation wells (25-mm diameter and 1.2-m long PVC pipes) were
installed in the center of each lysimeter to monitor water levels.
At the Ankeny site, the average water table depths at five major locations
marked as A, B, C, D, and E (where monitoring devices were installed in the
subirrigation) were maintained at 0.2, 0.3, 0.6, 0.9, and 1.1 m, respectively.
However, the water table depths ranged from 0.05 to 1.2 m during the growing
season. A maximum water-table depth of 1.2 m was observed at the highest
elevation site (north boundary) of the field at the beginning of the 1992 season.
The minimum water table depth of 0.05 m was observed at the lowest elevation
site of the field twice during the growing season of 1992, and most of the time
44
during growing season of 1993 due to heavy rainfall.
Each major location was divided into three subplots, where the
monitoring devices were installed. This combination provided three replications
per each depth treatment along the row. Water table depths, however, were
maintained from 49 to 110 DAP in 1992 and from 50 to 98 DAP In 1993. An
elapsed period of about 50 days between planting and start of subirrigation
allowed corn roots to develop uniformly in this field to a depth of 0.2 to 1.1 m.
Measurements of plant physiological parameters
Measurements on photosynthesis rate, stomatal conductance, leaf
transpiration, intercellular CO;, were taken with a LICOR-6200^ portable
photosynthesis system. Details of this measurement system are given in
LICOR-6200: Technical Reference (1987), therefore, only the details peculiar to
this work are given here. This system consists of a COg analyzer, a system
console, and a sensor housing with interchangeable leaf chambers. The CO;
analyzer is a differential, non-dispersive, infrared-type (NDIR) instrument
calibrated for measurements of 0-1100 ppm. A portable photosynthesis system
(Model 6200, LICOR, Inc. Lincoln, NE) calculated Rs to water vapor and net
photosynthèse rate (±) based on the change in water vapor, rate of change in
CO2, leaf area enclosed, air and leaf temperatures, and volume of leaf chamber.
PAR, ambient COg, leaf and air temperature, and relative humidity were also
45
recorded using this instrument at the time of photosynthèse measurement.
Measurements on plant physiological parameters were made on a
biweekly basis at both experimental sites (Ames and Ankeny) during the two
years of study. All measurements were made between 1000 and 1400 hours
of the day generally under clear sky. If clouds appeared during any
measurement, the observed data changed significantly and were therefore
discarded and new measurements were taken later on the same plant. Nine
plants in each treatment (3 plants per replication) were randomly
selected and marked, and measurements were taken on these plants during the
entire growing season.
The net exchange of CO; between leaf and the atmosphere was
measured by enclosing midsection of a latest fully developed leaf (generally
third or fourth leaf from the top) in the leaf-chamber and monitoring the
exchange rate in COg concentration of the air in the chamber during a short
interval of 15 to 20 s.
Chlorophyll measurements
Leaf chlorophyll measurements were made with a Minolta SPAD 502
chlorophyll meter. The SPAD-502^ chlorophyll meter, is a nondestructive, hand
held meter available for measurement of the green color intensity in crop leaves
which is directly related to leaf chlorophyll content (Tabkebe and Yoneyama,
46
1989). The meter is light weight (225 g), powered by two AA alkaline
batteries, has a 2-second interval between measurements, and can store up to
30 measurements.
SPAD-502 chlorophyll meter (principle description)
The principle of measurement is based on the difference in light
attenuation at wavelengths 430 and 750 nm. The 430 nm wavelength is a
spectral transmittance peak for chlorophyll, while the 750 nm wavelength is in
the near-infrared region, where no transmittance occurs. The ratio of the light
transmittance at these wavelengths, is processed by the instrument to produce
a reading shown on a digital display. This reading is in SPAD (Soil Plant
Analysis Development) units ranging from 0 to 80, which are values defined by
Minolta to indicate the relative amount of chlorophyll contained in plant leaves.
The chlorophyll measurements were made on 15 randomly selected
plants per treatment (five plants per replication). The latest fully developed leaf
(generally 3rd or 4th leaf from the top) was used for chlorophyll measurements.
The leaf chlorophyll measurements were made on a biweekly basis at both
experimental sites during the two years of study. Measurements on plant
heights were also made on the same plants used for the chlorophyll
measurements.
47
Plant culture
The corn variety Pioneer 3379 was planted at both sites (with no till
practices). In 1992, seeds were planted on May 8, while, they were planted on
May 21 in 1993 at both sites. The plant population was 67,000 per ha with a
row-to-row spacing of 0.75 m and seed-to-seed distance of 0.2 m at each site.
Plants were hand harvested on November 6 in 1992 in the lysimeter plots at
Ames site, and were harvested using a combine on the same day at Ankeny. In
1993, the plants were hand harvested on October 21 in the lysimeter plots at
Ames site, and were harvested on October 31 using a combine at Ankeny.
Grain yield was determined by harvesting and shelling all the ear heads in each
plot. The moisture content of the grain was determined and all yields were
adjusted to 15.5 percent moisture content basis (wet basis). Urea nitrogen
[N = (46-0-0) HgNCONHg], phosphorus [P = (0-43-0) PgOg], and potassium
[K = (0-0-54) KgO] fertilizers were surface applied at planting time at both sites
every year at the rate of 200 kg-N ha'\ 60 kg ha'\ and 40 kg ha \ respectively.
Herbicides atrazine and lasso were applied at the rate of 2.2 kg ha'\ in both
years at the Ankeny and Ames sites.
48
RESULTS AND DISCUSSION
Photosynthesis response to water table depths
The data on the effects of water table depth (WTD) on photosynthesis
rate as a function of time and days after planting (DAP) for the Ankeny and
Ames sites are plotted in Figures 4 and 5, respectively. As shown in Figure 4
the photosynthesis rates at the Ankeny site during 1992 were higher at the 0.3
m depth than for 0.2, 0.6, 0.9, and 1.1m depths. The photosynthesis rates
increased with time for all WTDs until mid August, 86 DAP, and thereafter
decreased with small variations between water table depths. In a previous
study Kalita and Kan war (1992) found maximum photosynthesis rates on 48
DAP during 1990 at this site (Table 3). During 1993, the WTDs fluctuated in
time from 0.05 to 1.2 m due to the combined effects of field slope, high rainfall,
and subirrigation practices. The photosynthesis rates were significantly
affected at the 0.2 m depth (Fig. 4). Due to heavy rainfall, the plots at WTD of
0.2 m remained flooded during most of the growing season. These results and
those from previous studies conducted at the same location by Kalita and
Kanwar (1992) reveal that a very high water table restricts oxygen supply to
the roots and soil microorganisms. Root growth requires metabolic energy that
is generated in aerobic conditions, but in the absence of oxygen, this energy is
significantly reduced (Cannel and Jackson, 1981). Therefore, less
49
photosynthesis rates due to excessive water stress at 0.2 m depth and due to
moisture deficit at 1.1 m depth could be anticipated.
Comparison of photosynthesis rates at the Ankeny site show that
photosynthesis rates were higher in 1992 than in 1993. In 1992, at the 0.3 m
depth photosynthesis rates varied from 30 to 52 // mol m^ s'\ and in the
extremely wet growing season of 1993, those varied from 30 to 40 // mol m ̂ s
\ The maximum photosynthesis rates at the water table depths of 1.1, 0.9,
0.6, and 0.2 m were 39.7, 42.9, 47.4, and 38 fj mol m^ s'\ respectively, and
those were 35.6, 38.6, 40.6, and 34// mol m"^ s"^ during 1993 for the same
plant phenological age.
The analysis of variance (ANOVA) was performed using SAS procedures
on the entire data set to determine the differences between photosynthesis
means under five WTD treatments for individual year. The ANOVA results are
presented in Table 2. The ANOVA results for 1992 show that the means for
0.2, 0.3, 0.6, 0.9, and 1.1 m depths were 30.1, 34.2, 32.3, 30.7, and 28.9//
mol m^ s \ respectively, with F-value = 12.8, and Pr > F = 0.0006, which
indicates that the means were significantly different at the 0.05 probability
level. In 1993, the means were 23.7, 29.5, 28.8, 26.8, and 24.0 // mol m'^ s'^
for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths, respectively, with F-value = 7.95,
and Pr > F = 0.0038, which indicates that these means were significantly
different at the 0.05 probability level.
50
Photosynthesis rates as a function of time and water table depth for the
Ames site are plotted in Figure 5. Figure 5 shows that during 1992, the
photosynthesis rates were higher for the 0.3 m water table depth than for the
0.6 and 0.9 m depths. The 0.3 m shallow water table supplied more water to
the plant-root system than did 0.6 and 0.9 m WTDs. In a study, Good and Bell
(1980) also reported that higher photosynthesis rates could be enhanced by
providing adequate water supply that prevents stress. This may explain why
higher photosynthesis rates were observed at the 0.3 m WTD. The
photosynthesis rates increased after water table treatments were started. The
increasing trend continued until mid August, 86 DAP, and then dropped slowly.
Almost similar trends were observed by Kalita and Kanwar (1992), they found
maximum photosynthesis rates on 70 DAP during the growing season of 1989
and those between 77 to 84 DAP during 1990 at the Ames site (Table 3). The
highest photosynthesis rates of 47.7, 39.8, and 35 on 86 DAP were observed
for 0.3, 0.6, and 0.9 m WTDs, respectively. As mentioned earlier, the 1993
season was a very wet season, therefore, the water table at this site was
maintained by continuous pumping from the sumps (during rain events).
Figure 5 shows the photosynthesis rates as a function of time and WTD
for 1993. This figure shows that similar trends were observed during 1993.
The photosynthesis rates were higher for the 0.3 m depth than for 0.6, and 0.9
m depths. Comparison of photosynthesis rates for 1992 and 1993 at the Ames
51
site on 40, 56, 71, 86, 98, and 110 DAP show that photosynthesis rates were
higher in 1992 than in 1993. In 1992, for 0.3, 0.6 and 0.9 m WTDs, the
photosynthesis rates varied from 25.2 to 47.7, 25.5 to 39.8, and 22.2 to 35 //
mol m^ s'\ respectively. Whereas, in an extremely wet growing season of
1993, they varied from 12.1 to 39, 11.9 to 34.6, and 10.1 to 30.2// mol m"^ s"
\ respectively, for the same phenological plant age. For 1992, the maximum
photosynthesis rates at 0.3, 0.6, and 0.9 m depths were 47.7, 39.8 and 35 //
mol m^ s'\ respectively, and those were 39, 34.6, and 30.2 // mol m^ s'^ in
1993. As compared to growing season of 1993, the 1992 season was
relatively dry. Therefore, during dry season of 1992 plants at the 0.3 depth
were neither restricted to water supply nor were subjected to excessive water
supply, hence, photosynthesis rates were higher than at 0.6 and 0.9 m WTDs.
In fact, the 1992 data show positive effect of subirrigation on photosynthesis.
In the very wet year of 1993, the soil moisture in the soil profile remained
above field capacity, due to continuous rainfall, during the growing season
between May through October. Therefore, water table elevation had little
influence on water supply, to the plants, and due to excessive soil moisture
conditions low photosynthesis rates were observed during the year. These
findings did not agree with previous results by Kalita and Kan war (1992) for the
same location. They reported high photosynthesis rates during a wet year as
compared to a dry year. Therefore, the effects of water table depth on
52
photosynthesis in a wet season still remain inconclusive and in question.
The analysis of variance (ANOVA) was performed using SAS procedures
on the entire data set to determine the differences between photosynthesis
means under three WTD treatments for individual year. The ANOVA results are
presented in Table 2. The ANOVA results for 1992 show that the means for
0.3, 0.6, and 0.9 m depths were 29.2, 26.1, and 25.1 // mol m^ s \
respectively, with F-value = 10.72, and Pr > F = 0.0104, which indicates that
these means were significantly different at the 0.05 probability level. For 1993,
the means were 27.3, 25.9, and 24.1 // mol m'^ s"^ for 0.3, 0.6, and 0.9 m
depths, respectively, with F-value = 2.67, and Pr > F = 0.1482, which
indicates that these means were not significantly different at the 0.05
probability level.
Effect of water table depth on stomatal conductance
The data on leaf stomatal conductance measured during the two year
study period at the Ankeny and Ames sites are illustrated in Figures 6 and 7.
Leaf stomatal conductivity was significantly affected by WTD. Plants with a
shallow water table depth of 0.3 always showed higher stomatal conductance
than with deep WTDs. Figure 6 shows the relationship between WTD and
stomatal conductance with respect to time, for the growing seasons of 1992
and 1993 for the subirrigation field at the Ankeny site. This figure shows that
53
stomatal conductance values increased by almost 2 times only 6 days after
water table treatment was lowered to 0.3 and 0.6 m depths. It increased by
approximately 1.5 times or more for 1.1, 0.9, and 0.2 m WTDs. These values
increased with time and peaked to 0.94, 0.76, 0.70, and 0.63 mol m^ s'^ on
86 DAP for 0.3, 0.6, 0.9, and 1.1 m depths, respectively, and then declined.
However, for the 0.2 m WTD the highest value of 0.62 mol m'^ s'^ was
observed on 98 DAP. The stomatal conductance values decreased towards the
end of the season and reached almost one value of 0.33 mol m ̂ s'\
The relationship between stomatal conductance and WTD as a function
of time for 1993 is also shown in Figure 6. Almost similar trends were also
observed during this year. The stomatal conductance values increased with
time until 86 DAP and then decreased. The maximum values of 0.72, 0.93,
0.72, 0.79, and 0.71 mol m'^ s'^ were observed for 0.2, 0.3, 0.6, 0.9, and 1.1
m WTDs, respectively, on 86 DAP. It could be seen in Figure 6 that values of
stomatal conductance were not significantly different between treatments
except that of the 0.3 m depth. This might be due to excessive wet conditions
during the year.
The analysis of variance (ANOVA) was performed using SAS procedures
on the entire data set to determine the differences between stomatal
conductance means under five WTD treatments for individual year. The
ANOVA results are presented in Table 2. The ANOVA results for 1992 show
54
that the means for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths were 0.49, 0.62, 0.58,
0.55, and 0.50 mol m"^ s"\ respectively, with F-value = 9.50, and Pr > F =
0.0019, which indicates that these means were significantly different at the
0.05 probability level. In 1993, the means were 0.56, 0.63, 0.56, 0.61 and
0.52 mol m'^ s'^ for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths, respectively, with F-
value = 1.59, and Pr > F = 0.2500, which indicates that these means were
not significantly different at the 0.05 probability level.
Figure 7 shows that the 0.3 m WTD gave higher stomatal conductance
values than did 0.6, and 0.9 m WTDs during 56 to 110 DAP in lysimeter plots
at Ames site in 1992. This figure shows that stomatal conductivity increased
by almost 1.5 times in all treatments only 6 days after water table treatments
began. It increased with time until mid August, 86 DAP, and peaked to 0.77,
0.72 mol m'^ s'^ for 0.3 and 0.6 m depths, respectively, and then dropped off.
For the 0.9 m depth it peaked to 0.67 mol m'^ s'^ on 98 DAP. However, during
1993, the highest stomatal conductance values of 0.94, 0.89, and 0.79 mol m'^
s'^ were observed on 86 DAP for 0.3, 0.6, and 0.9 m WTDs, respectively. A
comparison between years in Figure 7 shows that stomatal conductance values
on 40, 56, 71, 86, 98, and 110 DAP were significantly different for the two
study years (1992 and 1993) for the same plant phenological age.
The analysis of variance (ANOVA) was performed using SAS procedures
on the entire data set to determine the differences between stomatal
55
conductance means under three WTD treatments for individual year. The
ANOVA results are presented in Table 2. The ANOVA results for 1992 show
that the means for 0.3, 0.6, and 0.9 m depths were 0.52, 0.50, and 0.45 mol
m'^ s'\ respectively, with F-value = 3.39, and Pr > F = 0.1033, which
indicates that these means were not significantly different at the 0.05
probability level. For 1993, the means were 0.63, 0.59, and 0.53 mol m'^ s'^
for 0.3, 0.6, and 0.9 m depths, respectively, with F-value = 4.80, and Pr > F
= 0.0568, which indicates that these means were not significantly different at
the 0.05 probability level.
Effects of WTD on transpiration rate
The effects of WTD on day time leaf transpiration from 56 to 110 DAP
showed significant differences for subirrigation field at Ankeny site during 1992
as indicated in Figure 8. This figure shows that 0.2 and 1.1 m WTDs always
showed lower transpiration rates than did 0.3, 0.6, and 0.9 m depths. The
lower transpiration rates at the 0.2 m depth were due to excessive water supply
which in turn caused the stress, whereas, the reduction in transpiration rates at
1.1 m depth could be attributed to increased stress due to deficit water supply
to plant roots. These results are in agreement with the previous findings by
Kalita and Kan war (1992), they observed low transpiration rates under 0.2 and
1.1 m WTDs. Cannel and Jackson (1981) also reported that waterlogging
56
causes shoot wilting in a very short time, which in turn causes physiological
drought to the plant leaves by increasing resistance to water flow to the roots.
When stomata are open wide enough transpiration rates are higher, and in
contrast, when roots reduce water supply to the leaves, the plant leaves wilt
and as a result, transpiration rate slows down significantly.
However, the plants with the 0.3 m depth showed significantly higher
transpiration rates, throughout water table treatment period between 56 to 110
DAP, than did the plants with 0.2, 0.6, 0.9, and 1.1 m depths. The
transpiration rate increased, by about 1.5 times in almost all but the 1.1 m WTD
only 6 days after water table treatments were initiated. The plants with a 1.1
m WTD, however, showed no immediate response in transpiration rates. The
maximum transpiration rates at the peak hour during day time were 13.9, 22.8,
16.2, 16.3, and 12.7 mm/day for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths,
respectively, on 86 DAP. Transpiration rates decreased with plant age after 86
DAP under all WTD treatments. These rates were 5.1, 8.7, 7.2, 6.9, and 4.6
mm/day for 0.2, 0.3, 0.6, 0.9, and 1.1m depths, respectively, during the peak
day time hours on 110 DAP.
The transpiration rates as a function of time and WTD for the
subirrigation field at Ankeny for 1993 are also plotted in Figure 8. This figure
shows that no significant differences among treatments were found during this
year. This was because of extremely wet conditions caused by heavy rainfalls
57
during the entire growing season. However, the transpiration rates increased
between 56 and 86 DAP. The highest transpiration rates were 12.3, 12.7,
13.6, 11.7, 10.1 mm/day for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths on 86 DAP.
These rates decreased with plant age thereafter. Comparison between two
years in Figure 8 shows that transpiration rates were significantly higher in
1992 than in 1993 for the same plant growth stage. This could be anticipated
because of low temperatures and overcast conditions during 1993.
The data on transpiration rate for the lysimeter plots at the Ames site are
plotted in Figure 9. This figure shows that the transpiration rates were
significantly affected by WTDs. In 1992, the transpiration rates increased by
almost 2 times or more only 6 days after water table was raised to desired
depths of 0.3, 0.6, 0.9 m. Figure 9 shows that transpiration rates were
significantly higher during 56 to 98 DAP with the 0.3 WTD in comparison with
0.6 and 0.9 m WTDs. The maximum transpiration rates during the peak day
time hours on 86 DAP for 0.3, 0.6, and 0.9 m depths were 22, 14.7, and 12.3
mm/day, respectively. These rates then decreased with the plant age.
During 1993, similar trends were observed. The plants with the 0.3 m
WTD always showed higher transpiration rates then did the plants with 0.6 and
0.9 m WTD. The maximum transpiration rates during the peak day time hour on
86 DAP were 15.1, 13.6, and 11.2 for 0.3, 0.6, and 0.9 depths, respectively.
However, these rates were statistically significant at the 0.5 probability level.
58
As mentioned earlier, 1993 was an extremely wet year, the water table depths
at this site during excessive rainfall were maintained by pumping the water,
therefore, the treatment responses at this site were clear and measurable during
wet year.
Effects of WTD on intercellular 00% (Ci)
The relationships between Ci as function of time and WTD are shown in
Figure 10 . Leaf intercellular COj (Ci) was affected by WTDs. Plants with the
0.3 m water table depth most of the time showed higher Ci than did the
shallow or deep WTDs for the subirrigation field at Ankeny during the growing
season of 1992. Figure 10 shows that the 0.3 m WTD gave higher Ci than did
0.2, 0.6, 0.9, and 1.1 m depths. The highest Ci observed on 71 DAP under
0.3 m depth was 266 ppm. It was 246, 253, 243, and 238 ppm for 0.2, 0.6,
0.9, and 1.1 m depths, respectively, on 71 DAP. The Ci decreased with age
after 71 DAP. Almost similar trends were observed during the growing season
of 1993. Figure 10 shows that Ci increased with time after 56 DAP and peaked
on 86 DAP and then decreased thereafter. The maximum Ci obtained on 86
DAP was 235, 264, 266, 260, and 238 ppm for 0.2, 0.3, 0.6, 0.9, and 1.1 m
depths, respectively.
Figure 11 shows Ci as function of time and WTD for lysimeter plots at
the Ames site for 1992 and 1993. According to this figure. Ci values increased
with time and peaked on 86 DAP as 356.6, 339.3, and 350.2 ppm for 0.3, 0.6,
and 0.9 m depths, respectively, and then dropped with the plant age. The
decrease in Ci with plant age was a result of increased stomatal resistance.
Although, Ci values were higher with 0.3 m depth in comparison with 0.6 and
0.9 m depths, but, statistically these differences were not significant.
Relationship between Ci and water table depths for 1993 is also shown in
Figure 11. This figure shows that the Ci increased with time until 71 DAP for
0.3 m depth, and until 86 DAP for 0.6 and 0.9 m depths and decreased
thereafter. Figure 11 also indicates that the 0.3 m depth gave slightly higher Ci
values than did 0.6 and 0.9 m WTDs during 56 to 98 DAP. However,
statistically the differences were not significant between treatments at the 0.05
probability level.
Effects of WTD on chlorophyll content
Leaf chlorophyll content was determined on the same leaves used for
photosynthesis, transpiration, and stomatal conductance measurements.
Comparison of chlorophyll meter readings as a function of time and WTD at the
Ankeny site for 1992 and 1993 are shown in Figure 12. Figure 12 shows that
chlorophyll meter readings significantly increased under all WTDs after water
treatment began in 1992. As the growing season progressed, chlorophyll
readings increased with time until 86 DAP, and then decreased thereafter. The
60
highest chlorophyll readings observed on 86 DAP were 50.9, 55.3, 53.8, 52.5,
and 50.3 for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths, respectively. The 0.3 m
depth showed higher chlorophyll readings as compared to all other WTDs for
the period between 56 through 110 DAP. Comparison between chlorophyll
readings for 1993 under different WTDs is also shown in Figure 12. Similar
trends were observed in 1993. The chlorophyll readings increased for 0.3, 0.6,
0.9, and 1.1 m depths as the growing season progressed and peaked on 86
DAP and then decreased. However, no significant response in chlorophyll
readings was observed at 0.2 m depth. Flooded conditions due to heavy
rainfalls were the major cause of no response in chlorophyll readings at this
particular depth. The highest values observed on 86 DAP were 43.4, 51.9,
51.2, 50.9, and 44.8 for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths, respectively.
Although comparison of chlorophyll readings between WTDs showed higher
chlorophyll values at 0.3 m depth in comparison with other depths. These
values were not significantly different between 0.3, 0.6, and 0.9 m depths, but
were significantly different than 0.2 and 1.1 m depths at 0.05 probability level
during 56 to 110 DAP.
The analysis of variance (ANOVA) was performed using SAS procedures
on the entire data set to determine the differences between chlorophyll means
under five WTD treatments for individual year. The ANOVA results are
presented in Table 2. The ANOVA results for 1992 show that the means for
61
0.2, 0.3, 0.6, 0.9, and 1.1 m depths were 43.0, 47.1, 45.5, 44.6, and 42.5
SPAD unit, respectively, with F-value = 8.82, and Pr > F = 0.0026, which
indicates that these means were significantly different at the 0.05 probability
level. In 1993, the means were 39.3, 47.5, 45.5, 45.6 and 41.6 at 0.2, 0.3,
0.6, 0.9, and 1.1 m depths, respectively, with F-value = 6.39, and Pr > F =
0.0081, which indicates that these means were significantly different at the
0.05 probability level.
Relation between chlorophyll meter readings as a function of time and
WTDs for lysimeter plots at the Ames site for 1992 and 1993 are shown in
Figure 13. Also, similar trends were observed at this site. Higher chlorophyll
meter readings were obtained at shallow water depth of 0.3 m. These values
decreased with lowering WTD. Previous studies have also reported a decrease
in chlorophyll concentration for alfalfa when moisture decreased from 70 to
40% (Parjol et al. 1976 and Estill et al. 1991).
At the 0.3 m depth, chlorophyll meter readings were higher than at 0.6
and 0.9 m depths in both years (Fig. 13). This figure shows that, in 1992, the
highest chlorophyll readings as 57.7, 54 and 49.1 for 0.3, 0.6, and 0.9 m
depths were observed on 86 DAP, respectively, and those for 1993 were 53.3,
50.1, and 40.1 at 0.3, 0.6, and 0.9 m depths, respectively, for the same plant
phenological age.
The analysis of variance (ANOVA) was performed using SAS procedures
62
on the entire data set to determine the differences between chlorophyll means
under three WTD treatments for individual year. The ANOVA results are
presented in Table 2. The ANOVA results for 1992 show that the means for
0.3, 0.6, and 0.9 m depths were 49.56, 48.17, and 44.35 SPAD unit,
respectively, with F-value = 6.76, and Pr > F = 0.030, which indicates that
these means were significantly different at the 0.05 probability level. For 1993,
the means were 46.1, 44.0, and 38.5 for 0.3, 0.6, and 0.9 m depths,
respectively, with F-value = 8.31, and Pr > F = 0.0187, which indicates that
these means were significantly different at the 0.05 probability level.
Crop canopy temperature and water table depth
Canopy temperature is used to characterize drought stress effects in
many field crops. When stomata close, transpiration is reduced and
consequently the cooling effect is diminished leading to leaf temperature
increases. Diurnal variation in evaporative demand is also mainly due to leaf
temperature. The closer the leaf temperature stays to air temperature, the
closer the evaporative demand experienced by the leaf reflects the saturation
vapor deficit of the air. Reduction in leaf temperature has another indirect
benefit in terms of photosynthesis. The cooler the leaf the larger is the stomatal
conductivities corresponding to any given evaporation rate.
In this study, A portable photosynthesis system was used to measure the
63
leaf (Te) and air (Ta) temperatures inside the canopy. Leaf and air temperatures
differentials during growing seasons of two years for the Ankeny and Ames
sites are presented in Figures 14 and 15. Leaf air temperature differentials for
the subirrigation field at the Ankeny site under various WTDs are shown in
Figure 14. Figure 14 shows that, in 1992, leaf temperatures were lower than
air temperatures until 86 DAP under all but 0.2 m WTD, whereas, the higher
leaf temperature values were observed from 71 through 130 DAP. The 0.3 m
depth always showed higher leaf-air temperatures as compared to 0.2, 0.6, 0.9,
and 1.1 m depths. The highest leaf-air temperature differential as -1.6°C was
observed at the 0.3 m depth only 6 days after WTD was raised, and was
significantly different than all other WTDs. The leaf-air temperature differentials
for 0.2, 0.6, 0.9, and 1.1 m depths were -0.6, -1.0, -1.1, and -0.6°C,
respectively. The temperature differentials decreased with the plant age after
56 DAP. In 1993, the temperature differentials were positive for all
subirrigation plots before the treatment began. After WTDs were raised, the
leaf temperatures were higher than air temperatures in all treatment plots but
were not significantly different between WTDs. The leaf temperature increased
thereafter and remained above the air temperature for 0.2 and 1.1 m depths
during the rest of the growing season. For 0.3, 0.6, and 0.9 m depths, the leaf
temperature remained above air temperature after 86 DAP. It was because of
water table fluctuations due to heavy rainfall during the entire growing season
of 1993 which in turn caused excessive soil moisture conditions in the root
zone. Therefore increased leaf temperature could be anticipated.
Figure 15 shows the effects of water table depth on leaf-air temperature
in the lysimeter plots at Ames site for 1992 and 1993. This figure shows that
leaf temperatures were lower than air temperatures in all three WTDs. The leaf-
air temperature differentials were negative for all the lysimeter plots before
water table treatment began in 1992. After water table depths were raised to
0.3, 0.6, and 0.9 m depth, Tc - Ta significantly decreased in all treatment plots.
The maximum temperature differentials recorded on 56 DAP were -0.2, -1.0,
and -0.7°C for 0.3, 0.6, and 0.9 m depths, respectively, and were significantly
different for different water tables at the 0.05 probability level. In 1993, the
temperature differentials were positive for all the lysimeter plots before the start
of water table depth (Fig. 15). Almost similar trends were observed in 1993. A
significant decrease in Tc - Ta was observed on 56 DAP after water table
treatment began. The maximum Tc - Ta differentials observed on 56 DAP for
0.3, 0.6, and 0.9 m depths were -0.8, -0.7, -0.2°C, respectively. The 0.3 and
0.6 m depths showed lower leaf temperatures between 56 to 98 DAP, whereas,
the higher leaf temperature were recorded for 0.9 m depth between 71 to 98
DAP.
The data on leaf and air temperature as a function of WTD for 1992 and
1993 at the Ankeny and Ames sites were subjected to linear regression
65
analysis. Figure 16 gives a relationship between leaf and air temperatures along
with the upper and lower 95% confidence intervals. It can be seen from Figure
16 that a strong correlation exists between leaf and air temperatures and the
upper and lower 95% confidence intervals form a very narrow band on the
predicted line. The data points are almost (falling) on the line of best fit, and
the correlation is high. The value of the coefficient of correlation (R^) is 0.98.
The regression equation for the relationship between leaf and air temperature Is
given below:
T-Leaf = 1.43 + 0.94 T-Air
where T-Leaf is leaf temperature and T-Air is air temperature. The 45° dashed
line describes a relation if leaf temperature (Tc) is equal to air temperature (Ta).
Relationships between photosynthesis and chlorophyll readings
Linear regression was used to determine the "best fit" relationships on
average values of photosynthesis versus chlorophyll readings and are shown in
Figures 17 and 18 for the Ankeny and Ames sites, respectively. The
corresponding regression equations and their respective R-square values for
different WTDs are given below:
66
Ankeny site 1992
WTD = 0.2 m, PHO - 1.17 CHL- 19.8 R2 = 0.77
WTD = 0.3 m, PHO = 1.34 CHL- 28.6 R2 0.89
WTD = 0.6 m. PHO = 1.27 CHL- 25.6 R2 0.87
WTD = 0.9 m, PHO — 1.07 CHL- 16.8 R2 0.91
WTD = 1.1 m, PHO = 1.16 CHL- 20.3 R2 = 0.85
Ankeny site 1993
WTD = 0.2 m. PHO = 0.88 CHL- 11.5 R2 = 0.47
WTD = 0.3 m, PHO 1.48 CHL- 40.6 R2 = 0.50
WTD = 0.6 m, PHO 1.52 CHL- 40.4 R2 = 0.82
WTD = 0.9 m, PHO 1.17 CHL- 26.6 R2 = 0.53
WTD = 1.1 m, PHO 1.19 CHL- 25.0 R2 = 0.58
Ames site 1992
WTD = 0.3 m, PHO = 1.57 CHL - 48.7 R2 = 0.61
WTD = 0.6 m, PHO = 1.68 CHL - 54.9 R2 = 0.65
WTD = 0.3 m, PHO = 2.04 CHL - 65.4 R2 = 0.84
Ames site 1993
WTD = 0.3 m, PHO = 1.52 CHL- 42.6 R2 = 0.70
WTD = 0.6 m, PHO = 1.54 CHL - 42.2 R2 = 0.86
WTD = 0.3 m, PHO 2.38 CHL- 67.5 R2 0.79
where WTD is water table depth, PHO is photosynthesis rate in /y mol m"^ s \
67
and CHL is chlorophyll reading in SPAD units. These models show a positive
correlation between photosynthesis versus chlorophyll readings for all WTDs at
Ankeny and Ames sites, for 1992, and 1993.
Leaf chlorophyll readings at Ankeny site for 1992 were a good predictor
of photosynthesis rates, accounting for, on the average 86% of the variation in
photosynthesis rates (Fig. 17). The higher values under all depths indicate
that the linear models were appropriate to explain the relationship between
these parameters. Comparison between WTDs based on values showed that
the 0.9 m depth y ie lded h igher R^ va lues than d id 0.2, 0 .3, 0 .6, and 1 .1m
depths, but, the differences were not significant, suggesting that all models
were fitting the data well.
In 1993, significant positive relationships between photosynthesis and
chlorophyll were observed (Fig. 17). Although, leaf chlorophyll readings were
good predic tor o f photosynthesis rates, and accounted for , on the average 59%
of the variation in photosynthesis rates, but were not as good as those of 1992.
The R^ values were very much close for all WTDs except for 0.6 m depth,
which showed higher R^ values. This model was a good predictor of
photosynthesis rates as compared to other models.
A positive correlation between photosynthesis and chlorophyll for 0.3,
0.6, and 0.9 m WTDs for the Ames site were observed in 1992 and 1993 (Fig.
18). The equations of linear regression were appropriate to explain the
68
relationship between photosynthesis rates versus chlorophyll readings,
accounting for, on the average 70 and 78% of the variation in photosynthesis
rates for 1992 and 1993, respectively. Leaf chlorophyll readings were good
predictor of photosynthesis rates, and accounted for 61, 65, and 84% in 1992,
and 70, 86, and 79% of the variation in photosynthesis rates in 1993 at 0.3,
0.6, 0.9 m depths, respectively.
Linear regression was used also performed to determine the "best fit"
re lat ionships between photosynthesis versus ch lorophyl l readings us ing raw
data for the individual year and are shown in Figures 17a and 18a for the
Ankeny and Ames sites, respectively. The corresponding regression equations
and their respective R-square values for different WTDs are also given in Figures
17a and 18a. These best fit lines show trends similar to those observed with
average values of these parameters and a strong positive relationship between
photosynthesis and chlorophyll were observed. However, the coefficient of
correlation (R^' values using raw data were lower than those observed using
average data.
Relations between stomatal conductance and transpiration rates
Relationships between transpiration rates and stomatal conductance as
determined by linear regression analysis for Ankeny and Ames sites are shown
in Figures 19 and 20, respectively. The corresponding regression equations and
69
their respective R-square values for different WTDs are given below:
Ankeny site 1992
WTD = 0.2 m, TR = 29.79 COND • 7.48 R2 = 0.68
WTD = 0.3 m, TR = 24.26 COND - 4.14 R2 = 0.81
WTD = 0.6 m, TR = 19.88 COND - 2.64 R2 = 0.68
WTD = 0.9 m, TR = 26.09 COND - 5.37 R2 = 0.66
WTD = 1.1 m, TR 21.38 COND - 2.03 R2 = 0.61
Ankeny site 1993
WTD = 0.2 m, TR = 23.10 COND - 7.07 R2 = 0.84
WTD = 0.3 m, TR = 13.42 COND - 1.27 R2 = 0.90
WTD = 0.6 m, TR = 18.20 COND - 2.42 R2 = 0.82
WTD = 0.3 m, TR = 15.37 COND - 2.15 R2 = 0.80
WTD = 1.1 m, TR 19.33 COND - 4.81 R2 = 0.94
Ames site 1992
WTD = 0.3 m, TR = 32.79 COND - 6.18 R2 = 0.92
WTD = 0.6 m, TR = 23.87 COND - 2.61 R2 = 0.95
WTD = 0.9 m, TR = 21.51 COND - 3.69 R2 = 0.77
Ames site 1993
WTD = 0.3 m, TR = 22.33 COND - 3.61 R2 = 0.75
WTD = 0.6 m, TR 20.77 COND - 3.81 R2 = 0.80
WTD = 0.9 m, TR = 19.11 COND - 2.74 R2 = 0.88
70
where WTD is water table depth, TR is transpiration rate in mm/day, and COND
is stomatal conductance in mol m^ s \ These models show a positive
correlation between transpiration versus stomatal conductance values for all
WTDs at the Ankeny and Ames sites, for 1992, and 1993.
Stomatal conductance values at Ankeny site for 1992 were a good
predictor of transpiration rates, accounting for, on the average 69% of the
variation in transpiration rates (Fig. 19). The high values for under all depths
indicate that the linear models were appropriate to explain the relationship
between these parameters and were fitting well to their respective data sets.
Comparison between WTDs based on R^ values showed that the 0.3 m depth
yielded higher R^ values than did 0.2, 0.3, 0.6, and 1.1m depths. This
provides the evidence that adequate supply of water to the root zone
accelerates the stomatal conductivity that in turn increases the transpiration
rates. The lower values of R^ with 1.1 m depth, might explain that water stress
did affect the stomatal conductivity that reduced the transpiration rates.
In 1993, significant positive relationships between transpiration rates and
stomatal conductance were observed {Fig. 17). Although, stomatal
conductances values were good predictor of transpiration rates, and accounted
for, on the average 86% of the variation in transpiration rates, but no significant
differences were found between water table depth treatments, due to extremely
wet conditions. Regardless of WTD, the models were good predictors of
71
transpiration rates.
A positive correlation between transpiration rate and stomatal
conductance for 0.3, 0.6, and 0.9 m WTDs for Ames site were observed in
1992 and 1993 (Fig. 20). The equations of linear regression were appropriate
to explain the relationship between transpiration rates versus stomatal
conductance values, accounting for, on the average 88 and 77% of the
variation In transpiration rates for 1992 and 1993, respectively. In 1992,
stomatal conductance responses under 0.3, 0.6, and 0.9 m were very clear and
models were good predictor of transpiration rates, and accounted for, on the
average 92, 95, and 77% of the variation, respectively. Although, stomatal
conductances values were good predictor of transpiration rates, and accounted
for, on the average 77% of the variation in transpiration rates regardless of
WTD, during 1993, but opposite trends In values were observed. The 0.9 m
depth showed high correlation coefficient than did 0.3 and 0.6 m depth. The
excessive soil moisture conditions in the root zone, due to heavy rainfalls, at
0.3 m depth might have caused plant leaves to go under stress which in turn
resulted in stomata closure. The relationships between transpiration rate and
stomatal conductance for 1992, 1993 suggest that effects of water table
management can be predicted during dry seasons.
72
Crop yield
Corn yields for 1992, and 1993 for the Ankeny and Ames sites are
presented in Table 4. At the Ankeny site, the highest corn yield was obtained
from the plots under the 0.9 and 1.1m depths, and the lowest yield was
obta ined f rom the p lots under the 0.2 m depth in 1992. In 1993, however , 1 .1
m depth gave the highest, and 0.2 m depth gave the lowest yield. At 0.2 m
depth crop yield was very poor in both years. High rainfalls caused almost
surface flooding conditions for a few days during 1992, and almost all the time
during the growing season of 1993, at the 0.2 m depth, which in turn
significantly affected the yield at this location. Yields for 1992 were higher
than those for 1993. The extremely wet condition were responsible for the
decrease in the yield for 1993. However, the 0.3 m depth showed slightly
higher yields than did the 0.6 m depth for both years. Relationships between
chlorophyll and yield as a function of WTD for 1992 and 1993 are shown in
Figure 21. This figure shows that corn yield increased with lowering WTD.
However the relationship between chlorophyll and yield was not clear and data
points are more scattered rather than following any specific trends.
The analysis of variance (ANOVA) was performed using SAS procedures
to determine the differences between yield means under five WTD treatments
for individual year. The ANOVA showed no significant differences between the
means under different WTDs at the 0.05 probability level during 1992.
73
However, the means were significantly different between 0.2, 0.9, and 1.1m
WTDs at the 0.05 probability level, but those were not significantly different
between 0.3, 0.6, 0.9, and 1.1m WTDs during 1993.
At the Ames site, the highest yield was obtained from the plots under the
0.9 m depth, and the lowest yield was obtained from the plots under the 0.3 m
depth during both study years (Table 4). Almost similar results were observed
during both years at this site. The water tables were maintained by pumping
the excessive rainfall water at this site, therefore, no significant differences in
corn yields between two years were observed. Relationships between
chlorophyll readings and yield under different WTDs for 1992 and 1993 are
shown in Figure 21. This figure shows that corn yield increased with lowering
WTD. The relationship between chlorophyll and yield was not clear at the 0.3
and 0.6 m WTDs and data points are more scattered rather than following any
specific trend. However, Figure 21 shows that yield increased with increasing
chlorophyll readings at the 0.9 m WTD.
The analysis of variance (ANOVA) was performed using SAS procedures
to determine the differences between yield means under three WTD treatments
for individual year. The ANOVA showed no significant differences between the
means observed at the 0.6 and 0.9 m depths at the 0.05 probability level during
both study years. However, the means for the 0.3 and 0.9 m depths were
significantly different at the 0.05 probability level during both study years.
74
CONCLUSIONS
Field experiments were conducted to study the effects of water table
depths on various plant physiological parameters. Data for 1992 and 1993
were collected at two experimental farms owned by the Iowa State University.
These two research sites were located near Ankeny and Ames. This study
resulted in the following conclusions:
1. Photosynthesis rates, stomatal conductance, transpiration rates, intercellular
COj, and chlorophyll were significantly affected at a WTD of 0.2 m due to
surplus water and at 1.1 m depth due to inadequate supply of water. In 1993,
an extremely wet year, values of these parameters were lower than those in
1992 under all WTDs at the Ankeny site. Almost similar trends were observed
at the Ames site. The 0.3 m WTD showed higher values of these plant
parameters as compared to those observed at 0.6 and 0.9 m WTDs during both
study years.
2. Photosynthesis, stomatal conductance, transpiration, intercellular COg,
canopy temperatures, and chlorophyll exhibited similar relations with various
WTDs during the growing season. The highest values of these physiological
parameters were observed on 86 DAP under all WTDs and then decreased
thereafter. However, the 0.3 m WTD had higher values of these physiological
parameters as compared to all other WTDs.
75
3. Corn yields significantly increased as WTDs were lowered from 0.3 to 0.9 m
at the Ames site during both study years. At the Ankeny site, yields increased
as WTDs were lowered from 0.2 to 1.1 m. However, yields were not
significantly different between WTDs at the 0.05 probability level for the
growing season of 1992. In contrast, yields were significantly different
between WTDs at the 0.05 probability level during 1993, and shallow water-
table depths (0.2 and 0.3 m) significantly reduced corn yield due to excessive
wet conditions.
4. Statistical analysis of the data showed the means for photosynthesis
between WTDs for the Ames site were significantly different at the 0.05
probability level during both years, whereas those differences were not
significant for 1993 at Ankeny site. However, the means for chlorophyll
readings between WTDs were significantly different at the 0.05 probability level
for both years at the Ankeny site. The stomatal conductances were not
significant at the 0.05 probability level, except for 1992 at Ames site, where,
these differences were significant.
5. Relationships between different plant parameters were developed by fitting
lines of linear regression. The regression analysis showed strong positive
relations between photosynthesis and leaf chlorophyll readings for 1992 and
1993, at both experimental sites. Finding of these analysis reveal that leaf
chlorophyll could be used as a good predictor of photosynthesis rates regardless
76
of water table treatment depth. Also, a strong positive relation between
stomatal conductance and transpiration rates was observed. The regression
analysis revealed that the transpiration rates were highly dependent on the
stomatal behavior.
6. The overall results of this study indicate that leaf chlorophyll should be the
best single plant parameter which can be related to crop yields and
photosynthesis rates with confidence.
Table 1. Selected physical properties of the soils at the Ankeny and Ames experimental sites
Depth Sand m %
Silt %
Clay %
PH Bulk density Mg m'3
Organic matter %
Nicollet loam soil at the Ankeny site*
0.15 29.5 44.3 26.2 5.9 1.25 3.2
0.30 31.5 40.4 28.1 6.6 1.49 2.3
0.60 38.6 34.1 27.3 7.1 1.46 1.5
Nicollet loam soil at the Ames site^
0.15 31.3 43.6 25.1 7.3 1.20 4.3
0.30 31.2 42.8 26.0 6.7 1.30 4.0
0.60 27.7 42.2 30.1 6.9 1.35 2.9
^Charkhabi (1990); ^Kanwar et al. (1988)
Table 2. Analysis of variance comparing means of different plant physiological parameters at Ankeny and Ames sites
WTD
Site Year Parameter 0.2 0.3 0.6 0.9 1.1 LSD F Pr >
Ankeny 1 2
PHO PHO
30. r 23. r
34.4= 29.5*
32.3" 28.8*
30.7"c 26.8*"
28.y 24.0"c
1.87 2.06
12.8 7.9
0.0006 0.0038
1 2
CON CON
0.49c 0.56'"
0.62» 0.63*
0.57*" 0.56*"
0.55*" 0.61*"
0.50' 0.52"
0.06 0.10
9.5 1.6
0.0019 0.2500
1 2
CHL CHL
43.0"' 39.3c
47.1* 47.5*
45.5*" 45.5*"
44.6"c 45.6*
42.5" 41.3"'
1.97 4.25
8.8 6.4
0.0026 0.0081
Ames 1 2
PHO PHO
29.2* 27.3'
26.1" 25.8*
25.2" 24.1*
2.20 3.36
10.7 2.7
0.0104 0.1482
1 2
CON CON
0.52* 0.63*
0.50*" 0.60*"
0.45" 0.54"
0.06 0.08
3.4 4.8 .
0.1033 0.0568
1 2
CHL CHL
49.6* 46.1*
48.2* 44.0*"
44.3" 38.5*
3.61 4.73
6.8 8.3
0.0290 0.0187
PHO - Photosynthesis rate; CON - Stomatal conductance; CHL - Chlorophyll; 1 - 1992; 2 - 1993; means followed by same letter in a row are not significantly different at the 0.05 probability level
79
Table 3. Maximum photosynthesis rates (// mol m'^ s^) and their range as a function of time observed during four years study period
Ames site Ankeny site
Year DAP WTD Maximum Range DAP WTD Maximum Range
1989* 70 0.3 36.6 31.0-36.6
70 0.6 34.8 24.7-34.8
70 0.9 36.1 25.7-36.1
1990* 48 0.2 37.5 04.9-37.5
84 0.3 99.1 12.5-99.1 48 0.3 70.7 17.8-70.7
77 0.6 100.9 16.8-100.9 48 0.6 83.7 21.4-83.7
77 0.9 110.4 13.7-110.4 48 0.9 86.0 23.6-86.0
48 1.1 94.7 30.9-94.7
1992 86 0.2 38.0 15.9-38.0
86 0.3 47.7 8.8-47.7 86 0.3 52.0 21.2-52.0
86 0.6 39.8 7.1-39.8 86 0.6 47.4 18.3-47.4
86 0.9 35.0 6.3-35.0 86 0.9 42.9 19.0-42.9
86 1.1 39.7 15.5-39.7
1993 86 0.2 34.0 15.8-34,0
86 0.3 39.0 12.1-39.0 86 0.3 42.0 18.4-42.0
86 0.6 34.6 11.9-34.6 86 0.6 40.6 19.9-40.6
86 0.9 30.2 10.1-23.1 86 0.9 38.6 17.5-38.6
86 1.1 35.6 16.3-35.6
DAP - days after planting; WTD - water table depth;('After Kalita and Kanwar, 1992)
80
Table 4. Corn yield kg/ha as a function of water table depth at Annes and Ankeny sites for 1992 and 1993.
WTO, m Ames Ankeny
Year 1992
0.2 7033*
0.3 5216* 8400*
0.6 6970*" 8348*
0.9 8732" 9280*
1.1 9293*
Year 1993
0.2 3671*
0.3 4930* 5226*
0.6 7914" 5150*"
0.9 8860" 6960"'
1.1 7399"'
Means followed by same letter in a column are not significantly different at the 0.05 probability level within year and site
bilgailofi
Gudtn
S 120cm
CoffitgfttM M#»%k Sump (4icmOO) Coif ufaitd Hasiictik
(lOcmOO) r I pUsiU •ailier I—I (0 2$ mm lliuk)
00
12 j fVCfU.ihltlfcMt Sumpfump-
Figure 1. An isometric view of the lysimeter with sump and float assembly (after Kalita and Kanwar, 1992)
82
City of Amts Main Water Supply Line
Water Meter Pit
Hydrant
O 0
Additional Drain Valve
Oo-
Oo
60
Water Storage Tank (1.3 m diameter, 1.6 m height)
•PVC Main Irrigation Supply Pipe (diameter 7.5 cm)
Oo
Co
60
o'o I
"T" I
0 lo
I
O ' O
-CU
J— Irrigation ! Lateral
•Water Meter
I
a jo
1"" 0.25 mm Plastic Barrier (1.2 m deep)
I 3 m .
9m
36 m
O Corrugated Plastic Sump —— 0.25 mm PVC Flexible Liner o <3 Observation Weils (1.7 m deep)
Figure 2. Layout of the experimental plots at the Ames site (after Kalita and Kanwar, 1992)
f
Reservoir Pump
Irrigation Lines
Drainage Lines
Return
Drainage Pump
Figure 3 A schematic sketch of the dual-pipe subirrigation system at the Ankeny site (after Kallta and Kanwar, 1992)
60 WTD =0.2 m 1992
50
WTO =0.6 m
WTD=0.9m Ô40
•30
20
Water table treatment started 10
40 60 80 100 120 140
60 1993
SO WTD=0.6m
S 30
s. I 20
I Water table treatment started
10
40 80 100 140 60 120 Days after planting Days after planting
Figure 4. Photosynthesis rate for the subirrigation field at Ankeny site, 1992,93
60
WTD =0.3 m 1992
50 WTD=0.6 m
30
£20
Water table treatment started 10
40 60 80 100 120 140
60
1993
SO
5 30
1 20
Water table treatment started 10
40 80 60 100 120 140 Days after planting Days after planting
Figure 5. Photosynthesis rate for the lysimeter plots at Ames site, 1992, 93
1993
0.8
WTD=0.9m
S 0.6
0.4
0.2 40 60 80 100 120 140
1992
WTD=0.6 m 0.8
WTD =0.9 m
WTD = 1.1 m
•0.6
0.2 40 60 80
Days after planting 100 120 140
Figure 6. Stomatal conductance for the subirrigation field at Ankeny site, 1992,93
00 C7I
1992
WTD=0.9m M 0.8
0.6
EO.4
0.2 40 80 60 100 120 140
1993
w 0.8
0.6
0.2 40 60 80 100 120 140
Days after planting Days after planting
Figure 7. Stomatal conductance for the lysimeter plots at Ames site, 1992, 93
I
Water table treatment started
& • WTD =0.2 m
WTO =0.3 m
WTD =0.6 m
m WTD =0.9 m
ED WTD = 1.1 m
IIiBL 86 98 110
Days after planting 120 130
25
20
u
1993
_d?L
i l l
Water taWe treatment started
• Wn>=0.2m
WTD=0.3m
sa WTD=0.6 m
WTD=0.9m
• WTD = 1.1 m
40 56 71 86 98 Days after planting
rft fB. 110
Figure 8. Transpiration rate for the subirrigation field at Ankeny site, 1992, 93
25
ts
! 10
Water table treatment started • WTD =0.3 m
WTD =0.6 m
• WTD =0.9 m
71 86 98 110 120 Days after planting
130
25
20
I,. 5 10
Water table treatment started • WTD=0.3 m
ea WTD=0.6m
WTD=0.9 m
71 86 Days after planting
110
Figure 9. Transpiration rate for the lysimeter plots at Ames site, 1992, 93
00 O)
300
1992
WTD-0.3 m 280
WTD-0.6
o. 260
WTD-1.1
m 240
220
200 Water tfutment »t«ned
160
J. JL
1993
WTD-0.3 280
WTD-0.6m
o. 260 WTO-0.9
240
220
200 Water table treatment started
180
40 80 120 140 60 100
Days after planting Days after planting
Figure 10. Intercellular C02for the subirrigation field at Ankeny site, 1992, 93
00
400 1992
WTD-0.3
WTD-0.6 m 350
WTO'0.9 m
I cT 300 u
1 £ 250
Water table treatment uarted 200
40 60 80 100 120 140
400 1993
WTD-0.3
350
WTO-0.9 m
O 300
250
200
40 60 80 120 140 Days after planting Days after planting
Figure 11. Intercellular COg for the lysimeter plots at Ames site, 1992, 93
60 1992
55
WTD-0.6 m
S 50
WTD-1.1 m
Water table treatment started U 35
30 40 60 80 100 120 140
60 1993
55
2 50
WTD-1.1
Water tabie treatment start;
w 35
30 40 60 80 100 120 140
Days after planting Days after planting
Figure 12. Chlorophyll meter readings for the subirrigation field at Ankeny site, for 1992, 93
00 00
60 WTD-0.3 1993 WTD-0.6 8 55 WTDrO.9
S 50
Water table treatment started W 35
30 40 60 80 100 120 140
60
1992 WTD-0.3
2 55
WTD-0.9 m
f 50
S 45
Water taWe treatment started W 35
30 40 60 80 100 120 140
Days after planting Days after planting
Figure 13. Chlorophyll meter readings for the lysimeter plots at Ames site, for 1992, 93
I I 1
Water table treatment stacted
40 56 86 98 no 120 130
WTD-0.2 m WTD«0.3m WTD-0.6m WTO«0.9m WTD-1.1 m
71 86 98 110 120
Days after planting
cP O S
I | . , . S
Water table treatment started
WTD-0.2 m WTD-0.3m WTD-0.6m WTD-03m WTD-1.1 m # —B e A —•
Days after planting
Figure 14. Leaf-air temperature differential for the subirrigatin field at Ankeny during 1992 and 93
00 CO
(P
s. E
Water
•0.5
•1.5
40 56 110 120 130
WTD-0.2 WTD-0.3ffl WTD-0.6
<F o.s -
71 B6 98 110
Days after planting
Water table treatment started
WTD-0.2 m WTD«0.3m WTD-0.6 m B O
Days after planting
Figure 15. Leaf-air temperature differential for the lysimeter plots at Ames during 1992 and 93
L95% Cl 34
U95% Cl T-Leaf = 1.41 + 0.94 T-Air 0.98 32
Predicted
30
28
= 26
24
22
20
20 22 24 26 28 32 30 34
Air temperature, °C
Figure 16. Relation between leaf and air temperature with upper and lower 95% confidence
intervals for the two study years at two sites (Ankeny and Ames)
I 40
L L PHO • 1.17 CHL-19.8 — PHO - 1.34 CHL-28.6
PHO - 1.27 CHL -25.6 PHO - 1 07 CHL . 16 8
— PHO - 1.16 CHL-20.3
40 45 50 Chlorophyl mctef fuding (SPAO Uniu)
55
-fi3 PHO 0.88 CM.-11.5 0.47 PHO - 1.48 CHL-40.6 0.50 PHO . 1.52 CM.- 40.4 0.82 PHO • 1.17 CHL • 26.6 0.52 PHO - 1.19CHL- 25.0 0.58
40 45 50 ChkMophy# m*t*f nodng (SPAO Uniu)
Figure 17. Relationship between photosynthesis and chlorophyll readings at Ankeny site, for 1992 and 1993
CO
60 1993
PHO - 1.52 CHL-4X6 0.70 PHO - 1.54 CHL" 42.2 0.86 PHO - 2.3^ Ck.. 67.5 0.79
SO
"E I ̂
20
I as 45 CNofophv# m#*#f r«4dmQ (SPAO Unitt) 60 60 Unitt)
60 1992
PHO - 1.57 CHL-48.7 PHO • 1.68 CHL-54.9 PHO - 2.04 CHL • 65.4
0.61 0.65 0.84
50
IE » i
I 40 CWofophy# mtur rtading ISPAO Uniu) 45 65 60
Figure 18. Relationship between photosynthesis and chlorophyll readings at Ames site, for 1992 and 1993
WTO - 1.1 m
WTD - 0.9 m
PHO - 1.21 CHL-22.6 PHO - 1.09 CHL-17.8 PHO - 1.09 CHL - 17.5
0.76 0.81 0.75
40 45 50
Chlofophyll meter reading ISPAO uruts)
55
WTO - 1.1 m
WTD » 0.9 m
WTD - 0.6 m - B -
WTO - 0.3 m
WTD « 0.2 m
PHO - 0.88 at PHO - 1.34 CHL PHO . 0.73 CHL PHO - 1.07 CHL PHO - 1.19CHL
40 45 50
Chlorophyll meter reacfing (SPAO units)
Figure 17a. Relationship between photosynthesis and chlorophyll readings at Ankeny site, for 1992 and 1993 (using raw data)
60
WTD « 0.9 m 1993
50 -WTD - 0.6
£ "I 40 - WTD « 0.3 m
i 30 -
»o
20 -
0.51 0.58 0.54
I PHO - 1.24 CHL-29.8 PHO - 1.11 CHL-23.0 PHO - 1.46 CHL-32.2
10
35 30 40 45 55 50 60
60 1992 WTO - 0.9
PHO « 1.41 CHL-39.9 0.63 PHO • 1.33 CHL-47.7 0.58 PHO - 1.22 CHL-29.1 0.44
50 WTD > 0.6
E
I 0.3 m
30 -
20 -
I 10 -
30 35 40 45 50 55 60
Chlorophyll meter reading (SPAD units) Chlorophyll meter reatfing (SPAO units)
Figure 18b. Relationship between photosynthesis and chlorophyll readings at Ames site, for 1992 and 1993 (using raw data)
25
20
. 15
m 10
1992
0.4 0.6
Stomatai conductance, mol m^s
0.8 •1
16
14
12
E 10
1993
0.4 0.8 1
1
Figure 19. Relationship between transpiration rate and stomatai conductance at Ankeny site, for 1992 and 1993
25
20
15
S
J g 10
2 5
1992
H
0.4 0.6 0.8 Stomatai conductance, moi m'^s*^
16
14
. 12
E 10
1993
0.4 0.6 Stomatai conductance, moi m'^s*^
0.8 1
Figure 20. Relationship between transpiration rate and stomatai conductance at Ames site, for 1992 and 1993
94
12000
Ankeny
10000 00
mm
00
8000
* • Jm
6000
o o m
IPWTO - 0.2 m 4000
WTO - 0.3 m
WTO " 0.8 m
2000 WTD - 0.9 m
I WTD « 1.1 m
•a
Ames
10000
P»' 8000 O .00"
o o- off6^(?" o
6000 o o o «#
4000
WTD • Ô.3 m
WTD - 0.6 m 2000
WTD - 0.9 m
35 25 30 40 46 50 55 60
Chlorophyll reading (SPAD unit)
Figure 21. Relationship between chlorophyll content and corn yield at Ankeny and Ames sites (pooled data for 1992 and 1992)
95
PAPER II. EFFECTS OF WATER TABLE DEPTHS ON THE TRANSPORT
OF NO3-N INTO GROUNDWATER
96
ABSTRACT
The field experiments were conducted at two researcli farms of Iowa
State University near Aniceny and Ames to study the effects of water table
management practices on groundwater quality. Data were collected during the
growing seasons of 1992 and 1993 at these research farms, and average NO3-
N concentrations in groundwater as affected by different WTDs were measured.
Water samples for NO3-N analysis were collected by using suction tubes and
piezometers installed at different depths in the soil profile. The average NO3-N
concentrations in groundwater were reduced by maintaining WTDs between 0.3
to 0.6 m during the two growing seasons. The average concentrations in
groundwater generally decreased with increased sampling depth and time during
the growing season. The highest NO3-N concentrations in groundwater were
mostly observed before the water table treatments began. However, NO3-N
concentrations were significantly reduced after WTD treatments started and in
most cases these concentrations in groundwater were less than 10 mg/L under
0.3 m WTD treatment. Generally decreasing trend of NO3-N concentration in
groundwater with increasing sampling depth under two sampling methods was
consistent in both study years at both experimental sites.
The residual soil NO3-N concentrations seem to be concentrated in the
upper 0.15 to 0.6 m of the soil profile and the NO3-N levels decreased with the
97
increased soil depth under all water table treatments. However, at the 0.9 m
WTD, the NO3-N concentrations were higher in comparison with those observed
at the 0.3 and 0.6 depths at the Ames site. At the Ankeny site, similar trends
were observed, the highest concentrations were observed at the 1.1 m WTD as
compared to other four WTDs. The soil samples collected at the time of harvest
showed low values of NO3-N concentrations with statistically significant
differences in the amounts for the different water table treatments.
Corn yields significantly increased as water-table depths lowered from
0.2 to 1.1 m in 1992 and 1993 at the Ankeny site. The highest yields were
observed at the 1.1 m WTD and the lowest yields were observed at the 0.2 m
WTD. The yields were also affected by wet conditions in 1993, and were less
than those observed during 1992 at this site. In the lysimeter plots at Ames,
crop yields were higher under a WTD of 0.9 m as compared to those observed
at 0.3 and 0.6 m WTDs during both study years. Findings of this study show
that, although, the 0.3 WTD is most suitable for groundwater quality control, it
is not appropriate for the highest crop yields are desired. For highest crop
yields a WTD between 0.6 to 1.1 m would be desired. Therefore, the results of
this study conclude that a WTD between 0.6 to 0.9 m would be the Best Water
Table Management Practice for crop productivity and groundwater quality
control.
98
INTRODUCTION
The use of fertilizers and pesticides is an integral part of crop production
in the U.S. and elsewhere. As a result of their use, crop quality and quantity
have improved tremendously in the past few decades, and the cost of food is
less than it would have been otherwise. But the question arises, however,
about the considerable impacts, direct or indirect, on the environment. There is
a growing public awareness over the long term threat to both surface and
groundwater quality from the contaminants derived from these chemicals. The
contamination of surface and groundwater due to the leaching of these
chemicals is becoming a serious threat to human health, wildlife, and the
environment (Prunty and Montgomery, 1991). Particularly, nitrate leaching into
groundwater has become one of the major pollution concerns facing agriculture
today (Hallberg, 1984). Though, it is practically impossible to uproot the
environmental pollution problem caused by fertilizers and pesticides, the growth
of this problem can be decelerated. Improved agricultural water table
management practices can undoubtedly reduce movement of these chemicals
into surface and groundwater systems. Active research are being carried out to
figure out the best possible alternatives, which will not hamper the crop
production system either quantitatively or qualitatively but will reduce their
potential threat to the environment.
99
Studies during the past decade have documented the detrimental effects
of agriculture on water quality (Hallberg, 1989; Schaller and Baily, 1983;
Hamlett et al., 1990). These studies suggest that surface and groundwater
resources are vulnerable to non-point pollution from agricultural activities. NO3-
N concentrations exceeding the 10 mg/L safe drinking water limit, have been
detected in both surface and ground water supplies all across the midwestern
and in other states in the U.S (Hubbard and Sheridan, 1989). The public is
especially concerned, because, the NO3-N concentrations in excess of 10 mg/L
in drinking waters cause serious health problems (such as methemoglobinemia)
in infants who drink this water. Therefore, the problems receiving the most
attention from researchers are the contribution of nutrients to eutrophication of
surface water resources, and the increased levels of NO3-N in the drinking
water. In the past two decades, much work has been done to characterize
nutrient losses through drainage systems and the effect of these losses on
water quality and crop productivity. Several studies conducted in Iowa (Baker
and Johnson, 1981; Kanwar et al., 1985; Kanwar et al., 1988; Kanwar, 1991;
Kanwar and Baker, 1991) have shown that great quantities of NO3-N were
rapidly leaching to shallow groundwater. In 1988 through 1989, a survey of
private rural wells in Iowa found that 18% of the water in all wells had NO3-
N concentrations above the 10 mg/L drinking water standard, over 35% of
the samples from wells less than 50 ft deep had NO3-N concentrations above
100
the standard (Anonymous, 1990). These and other studies across the U.S.,
have reported that NO3-N concentrations in subsurface drainage from row-crop
land usually exceeded the 10-mg/L drinking water standard, and as fertilization
increased, NO3-N concentrations in tile drainage water sometimes approached
100 mg/L (Kanwar, 1991). Fitter and IVIanger (1985) and Lowrance (1981)
reported that NO3-N concentrations in subsurface drainage from agriculturally
influenced areas ranged from 20 to 47 mg/L on coastal plain soils. Skaggs et
al. (1982) found wide variability in NO3-N losses from drainage systems on
muck and clay soils in North Carolina.
Water-table management (WTM) practices, especially controlled drainage
and drainage-subirrigation, have shown potential for inducing denitrification and
reducing the concentration of agricultural chemicals reaching water supplies
(Skaggs and Gilliam, 1981; Gilliam and Skaggs, 1986; Evans and Skaggs,
1985; Evans et al., 1989a; Kalita and Kanwar, 1990; Kanwar and Kalita, 1990;
Kalita and Kanwar, 1993; Wright et al., 1989; Wright, 1990).
During the last few years, several studies have addressed the effects of
WTM practices under different soils, crops, and climatic conditions, such
as, in Iowa (Kanwar, 1990; Kanwar et al., 1991; Kalita and Kanwar, 1993),
Michigan (Belcher and IVIerva, 1991), Ohio (Fausey et al., 1991), North Carolina
(Skaggs et al., 1991), Louisiana (Bengtson et al., 1991), Georgia (Thomas et
al., 1987a; Thomas et al., 1991). The main focus in these studies has been
101
crop yields, economic benefits, and ground water modeling. Few other studies
have been reported in the literature which address the benefits of WTM
practices in relation to reducing nutrient transport in drainage outflow.
Bengtson et al. (1988) studied the influence of subsurface drainage
practices on nitrogen and phosphorus losses on a Commerce clay soil in lower
Mississippi River Valley. Compared to undrained areas, they found that
subsurface drainage reduced surface runoff by 34%, erosion by 30%, and
nitrogen and phosphorus losses by 20 and 36%, respectively. Thomas et al.
(1987b, 1991) measured NO3-N concentrations in shallow subsurface wells and
outlets of a controlled drainage-subirrigation system in a blueberry field in the
Georgia flat-woods. Their results showed that NO3-N concentrations in the
groundwater were less than the 10 mg/L, the maximum contaminant level
(MCL) for public drinking supplies for all outflow samples, although 6% of the
shallow groundwater samples within the field exceeded this limit.
Evans et al. (1989a) presented a compilation of data from North
Carolina supporting the classification of controlled drainage as a best
management practice. Their data showed that controlled drainage reduced both
surface and subsurface nitrogen losses as opposed to uncontrolled drainage.
They found the average loss reduction resulting from drainage control in North
Carolina to be 45%. They concluded that denitrification accounted for the
reduced nitrogen transport from controlled drainage sites in eastern North
102
Carolina where conditions are conducive to denitrification. In another study,
Evans et al. (1989b) reported that controlled drainage reduced the annual
transport of total nitrogen (NO3-N and TKN) at the field edge by 46.5% and
total phosphorus by 44%. In previous studies, similar results have been
reported using simulation methods (Skaggs and Gilliam, 1981; Deal et al.,
1986).
Gilliam et al. (1979) compared nitrate concentration from uncontrolled
and controlled drained fields, and found nearly a 50% reduction under controlled
drainage. While comparing nitrate losses through controlled and conventional
drainage systems, Gilliam and Skaggs (1986) observed 32% reduction in nitrate
losses with controlled drainage as compared to conventional drainage. Bottcher
et al. (1981) measured mean annual sediment, nitrogen, and phosphorus losses
of 94.0, 8.7, and 0.2 kg ha \ respectively, from a subsurface drained area near
Woodburn, Indiana. Their results showed that losses of sediment and nutrient
were reduced by subsurface drainage. They recommended that on a suitable
soil, subsurface drainage may well be preferred as a best management practice
for water quality control. Kladivko et al. (1991) determined field scale NO3-N
losses to subsurface drainage on a low organic matter and poorly structured silt
loam soil under typical agricultural management practices in Indiana. They
found that the annual NO3-N losses in subsurface drain flow ranged from 18 to
70 kg ha \
103
Hubbard et al. (1991) determined transport of NO3-N by surface runoff,
and shallow subsurface flow on a sandy coastal plain soil having plinthic sub
soil material. They observed that most of the NO3-N leached from the upper 30
cm of the root zone within 1 % month after N application. NO3-N
concentrations in surface runoff were very small, with monthly loads not
exceeding 0.3 kg ha'\ However, NO3-N concentrations in shallow groundwater
(at 0.9 to 1.8 m sampling depth) were between 11 to 19 mg/L.
Weight et al. (1992) simulated controlled drainage-subirrigation (CD-SI)
system to investigate the effects of different WTM practices on water quality.
The results from their CD-SI simulations indicate that raising the water table
during the fallow season can reduce nitrogen leaching by increasing
denitrification. It can also increase the amount of nitrogen lost in runoff and in
sediment. They pointed that, water table management using a CD-SI system
increased predicted runoff nitrogen by 340% and increased predicted sediment
nitrogen loss by 118%, it decreased nitrogen leaching by 35.1%. They
concluded that, the predicted total average nitrogen non point source pollution
losses were 17.8% less for the CD-SI system than for the subsurface drainage
system.
Studying effects of WTM on NO3-N transport to shallow groundwater,
Kalita and Kan war (1993) found that nitrate concentration reduced by
maintaining a shallow WTD in the range of 0.3 to 0.6 m. In the unsaturated
104
zone of the soil profile NO3-N concentration as high as 285 nag/L was observed,
but the average NO3-N concentrations in the groundwater never exceeded the
10 mg/L drinking water standard. Drury et al. (1991); and Myrold and Tiedje
(1985), found that the average NO3-N concentrations in groundwater were
generally lower where shallow water table depths were maintained. Present
study was initiated in 1992 on the already established plots with the aim of
developing a better understanding of water-table management practices on crop
yield and groundwater quality, following were the specific objectives of this
study:
1. To evaluate the impacts of different water table depths on the movement of
NO3-N into the groundwater.
2. To determine the residual NO3-N distribution in the soil profile at various
depth.
3. To determine the crop yield responses under various water table depths.
105
MATERIALS AND METHODS
Description of experimental sites
The experiments were conducted during growing seasons of 1992 and
1993 on the research farms owned by Iowa State University. The experimental
sites are located near Ames and Ankeny. The soils at Ankeny site are Nicollet
loam, and those at Ames site are predominantly Nicollet loam (Aquic Hapludolls)
in the Clarion Nicollet-Webster soil association. Table 1 lists some of the
physical properties of the soils at these sites.
Experimental setup at the Ames site
Nine experimental plots with surface slopes ranging from 1 to 3% were used
to construct field lysimeters. The lysimeters (each 3 m wide and 6 m long)
were installed during 1986. A 0.2 m wide and 1.2 m deep trench around the
perimeter of each lysimeter was made using a Ditch Witch trencher, and the
bottom of the trench was finished manually with a "tile trench crumber." The
lysimeter soil remained undisturbed during trench the digging process.
Following the digging of the trench, the each lysimeter was completely enclosed
using a plastic barrier (0.25-mm-thick, polyethylene sheet) which extended from
the soil surface to the bottom of the trench. The purpose of this plastic barrier
was to "isolate" the lysimeter from its surroundings and to minimize any lateral
106
subsurface water movement between plots. A corrugated, perforated plastic
tube (lOO-mm diameter) was installed at the bottom of the trench inside the
plastic barrier. A 0.9 m wide ditch was dug to a depth of 1.35 m with a back
hoe mounted on the Ditch Witch trencher to install a 1.5 m tall corrugated
plastic pipe (0.46-m OD X 0.032-m wall) at the corner of each lysimeter. The
bottom of 1.5 m tall sump was located 1.35 below the soil surface, and the top
of the sump was 0.15 m above the soil surface. The two ends of the
perforated plastic tubes at right angles to each other were inserted into the
sump at a height of 0.15 m from the bottom of the sump. The trenches were
back-filled with the excavated soil. In 1989, all lysimeters were enclosed with
another 0.25 mm-thick PVC (poly-vinyl-chloride) flexible liner to a depth of 1.7
m. Each liner encased a square area (9 m X 9 m) with the 3 X 6 m original field
lysimeter located in the center of the enclosed area to ensure that subsurface
water did not move laterally between lysimeters to a depth of 1.7 m. A detailed
procedure for the lysimeter installation is described by Kalita and Kanwar
(1990), and is also shown in Figure 1. Figure 1 shows an isometric view of the
lysimeter with installed sump and float assembly. A float mechanism was
installed in each sump to maintain the desired water level in the lysimeter plot
area. Each lysimeter was connected to the main water-supply tank using a 75-
mm diameter PVC irrigation pipe. The main water-supply tank (1.6-m high and
1.3-m inside diameter) was raised 2 m from the soil surface on a concrete floor
107
to maintain sufficient hydraulic head for gravity flow of water from the tank to
all lysimeters for maintaining water tables in the plot area. The layout of the
experimental area is shown in Figure 2.
Experimental setup at Ankeny site
In 1988, a dual pipe subirrigation system was installed at this site on a
0.5-ha area with significant natural ground slope of 2.5 percent. The basic
concept of the dual-pipe subirrigation system is illustrated in Figure 3. Shallow
irrigation pipes (51-mm diameter) were installed at a depth of 0.5 to 0.6 m
parallel to and midway between drainage pipes, which were installed at a depth
of 1.2 m. Drainage lines discharged into a sump from which water is pumped
into a storage reservoir. The storage reservoir has a storage capacity of
approximately 900 cubic meters. During irrigation, water is pumped from the
reservoir into a head tank at the top of the plot area, where the water is
distributed to the laterals by a sub-main line equipped with valves to control
pressure in the supply line. Because of the natural ground slope along the
length of the field, water tables could be maintained at various depths below
the soil surface by controlling the subsurface drainage outflows and by
supplying irrigation water through the subirrigation pipes.
108
Water table management treatments
At the Ames site, water table depths were maintained at 0.3, 0.6, and
0.9 m in 1992 and 1993. Each water table depth treatment was replicated
three times. Water table depths were maintained to the desired depths from
day 49 to 110th day after planting (DAP) during the growing season of 1992,
and from 50 to 98 DAP during the growing season of 1993. The elapsed time
of about 50 days from planting to the start of water-table treatment allowed
corn roots to develop within 0.3 to 0.9 m soil profile. It took almost three days
to bring the water tables to the required depths during 1992, whereas, during
1993, the record wet year, there was no problem in bringing the water tables
near the surface but many times water tables had to be lowered using a sump
pump. Observation wells (25-mm diameter and 1.2-m long PVC pipes) were
installed in the center of each lysimeter to monitor water levels.
At the Ankeny site, the average water table depths at five major locations
marked as A, B, C, D, and E (where monitoring devices were installed in the
subirrigation) were maintained at 0.2, 0.3, 0.6, 0.9, and 1.1 m, respectively.
However, the water table depths ranged from 0.05 to 1.2 m during the growing
season. A maximum water-table depth of 1.2 m was observed at the highest
elevation site (north boundary) of the field at the beginning of the 1992 season.
The minimum water table depth of 0.05 m was observed at the lowest elevation
site of the field twice during the growing season of 1992, and most of the time
109
during growing season of 1993 due to heavy rainfall.
Each major location was divided into three subplots, where the
monitoring devices were installed. This combination provided three replications
per each depth treatment along the row. Water table depths, however, were
maintained from 49 to 110 DAP in 1992 and from 50 to 98 DAP in 1993. An
elapsed period of about 50 days between planting and start of subirrigation
allowed corn roots to develop uniformly in this field to a depth of 0.2 to 1.1 m.
Groundwater water sampling
Ground water samples were collected using suction tubes and
piezometers on a monthly basis in 1992 and 1993 from both sites for NO3-N
analysis. Solute suction tubes were made by coupling a 200-kPa porous
ceramic cup to the end of a 38-mm diameter PVC pipe. The top ends of these
tubes were sealed with rubber stoppers. At the Ames site, suction tubes were
installed at the center of all nine lysimeters (three replications per treatment) at
0.3, 0.6, 0.9, 1.5, and 2.1 m depths to collect water samples. A vacuum
pump was used to create a vacuum in the solute suction tubes one day before
sample collection, and water samples were collected the following day.
Piezometers were made of 25-mm diameter PVC pipes by making perforations
at the lower end to be placed in the ground. The lower ends were sealed with
rubber stoppers. The piezometers were installed in each lysimeter plot at 1.2,
110
1.8, and 2.4 m depths to collect groundwater samples and to monitor
piezometric heads. The piezometers were pumped out one day before sampling,
and water samples were collected on the following day. All water samples
collected; were then preserved in a cold chamber at 4 °C until analysis.
At the Ankeny site, solute suction tubes were installed at 0.9, 1.5, and
2.1 m depths at three locations (B, C, and D locations as shown in Figure 3)
with three replications at each location. Whereas, piezometers were installed at
three locations (A, C, E locations as shown in Figure 3) at 1.2, 1.8, 2.4 m
depths with three replications per location. Similar procedures (those at Ames
site) were followed to collect water samples.
Soil sampling and analysis methods
Soil samples at two experimental sites (Ankeny and Ames) were collected
from the middle quarter of each plot at 0.3, 0.6, 0.9, 1.2, 1.5, and 1.8 m
depths from the soil surface. The sampling locations in a plot were spaced
across most of this area and were consistent from plot to plot. All cores were
taken from row centers. After cores were removed, the resulting man-made
macropores in the soil were back filled with bentonite clay granules. In 1992, a
set of soil samples was collected on June 11,34 days after planting and N
fertilization. Another set of soil samples was collected in late summer on
October 31 at the time of harvest. In 1993, a set of soil samples was collected
I l l
on May 4,16 days before planting and N fertilization, and another set of soil
samples was collected in late summer on October 19 at the time of harvest at
both sites.
To collect soil samples, a zero-contamination hand sampler was pushed
into the soil, each core slide into a clean liner made of PETG (polyethlene
terephthalate, glycol-modified) plastic to protect the sample from contamination.
The samples were frozen promptly after collection. The cores were sectioned
into a set of 6 samples representing the following depths: 0-0.15, 0.15-0.3,
0.3-0.6, 0.6-0.9, 0.9-1.2, and 1.2-1.5 m. Three cores per treatment were
collected and were combined to yield a single composite sample for each
treatment at each soil sampling depth. The samples were wrapped in aluminum
foil, then over wrapped with a labelled polyethylene bag. The foil protected the
soil from any possible contamination by plasticizer in the plastic. The samples
were stored frozen until they were needed for laboratory analysis.
Soil nitrate extraction and analysis
A representative soil sample was used for soil moisture content. This
was done by weighing a subsample of soil, drying it at 104 "C for 24 hr,
reweighing the cooled sample, and calculating the soil moisture as the
percentage on a dry soil basis. For NO3-N analysis, a 100 g sample of wet soil
was mixed with 435 g of 2N (normal) KCI (potassium chloride). The mixture
112
was shaken for 65 minutes, then allowed to settle for overnight. The following
day solvent was filtered and poured into 100 ml test tube. The NO3-N in the
solvent was analyzed with a lachat Model AE ion analyzer. The analyzer first
converted the colorless NO3-N in the filtrate to a pink water soluble dye, and
then measured the color intensity by spectrophotometry. The color intensity
was proportional to the NO3-N concentration. Results are reported as mg/L
NO3-N on a dry soil basis.
Plant culture
The corn variety Pioneer 3379 was planted at both sites (with no till
practices). In 1992, seeds were planted on May 8, while, they were planted on
May 21 in 1993 at both sites. The plant population was 67,000 per ha with a
row-to-row spacing of 0.75 m and seed-to-seed distance of 0.2 m at each site.
Plants were hand harvested on November 6 in 1992 in the lysimeter plots at
Ames site, and were harvested using a combine on the same day at Ankeny. In
1993, the plants were hand harvested on October 21 in the lysimeter plots at
Ames site, and were harvested on October 31 using a combine at Ankeny.
Grain yield was determined by harvesting and shelling all the heads in each plot.
The moisture content of the grain was determined and all yields were adjusted
to 15.5 percent moisture content basis (wet basis). Urea nitrogen [N = (46-0-0)
HgNCONHg], phosphorus [P = (0-43-0) PgOg], and potassium [K = (0-0-54) KgO]
113
fertilizers were surface applied at planting time at both sites every year at the
rate of 200 kg-N ha'\ 60 kg ha'\ and 40 kg ha'\ respectively. Herbicides
atrazine and lasso were applied at the rate of 2.2 kg ha'\ in both years at the
Ankeny and Ames sites.
114
RESULTS AND DISCUSSIONS
The 1992 season was relatively dry as compared to 1993 season. The
rainfall between May through October totalled 475 mm and 427 mm at Ames
and Ankeny sites, respectively, during 1992. The 1993 season was an
extremely wet, with rainfall totals of 1199 mm and 1127 at the Ames and
Ankeny sites, respectively, for May through October. Monthly precipitation
patterns for the Ames and Ankeny sites during 1992 and 1993 are presented in
Table 2.
NO3-N concentrations in piezometer water samples at the Ankeny site
The average concentrations as a function of DAP and WTD in the
subirrigation field at Ankeny site are shown in Figure 4. The figure shows that
the NO3-N concentrations in groundwater samples were different at different
water table depths during the growing season of 1992. The 0.2 m depth
a l w a y s s h o w e d l o w e r N O 3 - N c o n c e n t r a t i o n s i n c o m p a r i s o n w i t h 0 . 6 a n d 1 . 1 m
depths. NO3-N concentration decreased with time under all WTDs. In the early
part of growing season of 1992, the higher NO3-N concentrations at 1.2, 1.8,
and 2.4 m piezometer depths were observed than in the later part of the
growing season. The higher concentrations are associated with greater
amounts of NO3-N available in the soil profile due to residual NO3-N and applied
115
N fertilizers. Therefore, higher NO3-N concentrations could be anticipated.
Figure 4 connpares the NO3-N concentrations at 1.2, 1.8, and 2.4 m piezometer
water sampling depths, under 0.2, 0.6, and 1.1m WTDs. Figure shows that
the NO3-N concentrations generally decreased with increased sampling depth in
the soil profile under all WTDs. The NO3-N concentrations at the 1.2 m
piezometer depth showed higher concentrations than did the 1.8 and 2.4 m
piezometer depths. The NO3-N concentrations decreased with time, however,
at all three piezometer depths in the soil profile. At the 1.2 piezometer depth,
concentrations of NO3-N in groundwater samples varied from 10.3 to 1.6, 11.7
to 4.5, and 23.8 to 4.9 mg/L for 0.2, 0.6, and 1.1 m WTDs, respectively.
Similarly, NO3-N varied from 7.5 to 1.6, 9.9 to 3.6, and 16.9 to 5.2 mg/L at 1.8
m piezometer depth, and 3.7 to 1.6, 7 to 3.5, and 8.5 to 3.3 mg/L at 2.4 m
piezometer depth for 0.2, 0.6, and 1.1m WTDs, respectively.
Figure 4 also shows the average concentrations of NO3-N in piezometer
water samples in 1993 as a function of WTD and DAP. Similar trends in NO3-N
concentrations were observed in 1993 in comparison with those observed in
1992. However, the highest NO3-N concentrations of 9.4, 11.7, 23.8 mg/L at
1.2 m piezometer depth in the soil profile were observed on 48 DAP (2 days
before the water table treatments began). The NO3-N concentrations were
significantly reduced after water table treatments were initiated. These
concentrations were different at different WTDs, as well as, were different for
116
various piezometer sampling depths in the soil profile. The NO3-N
concentrations generally decreased with increasing soil depth under all three
WTDs. These concentrations also decreased with time, significantly higher
NO3-N concentrations were observed during the early part of the growing
season. Heavy rainfalls during the early part of the growing season of 1993
perhaps caused NO3-N movement from the surface layer to the deeper depths
immediately after N application. Figure 4 compares the NO3-N concentrations at
different piezometer depths. Higher NO3-N concentrations were observed at the
1.2 m piezometer depths than at 1.8 and 2.4 m depths. These values ranged
from 31 to 2, 40.9 to 2.7, and 103 to 6.6 mg/L at the 1.2 m piezometer depth
under 0.2, 0.6, and 1.1 m WTDs, respectively. NO3-N concentrations ranged '
from 31 to 2.8, 32.2 to 3.1, and 30.6 to 3 mg/L at 1.8 m piezometer depth,
8.6 to 0.4, 17.8 to 0.1, and 27.5 to 1.4 mg/L at 2.4 m piezometer depth under
0.2, 0.6, and 1.1m WTDs, respectively. These results indicate that average
NO3-N concentrations were lower at the 0.2 m WTD than at 0.6 and 1.1 m
WTDs at all piezometer depths during 1992 and 1993 seasons.
NO3-N concentrations In suction tube water samples at the Ankeny site
Samples were taken at 0.9, 1.5, and 2.1 m suction tube depths in the
soil profile under 0.3, 0.6, and 0.9 m WTDs. The NO3-N concentration data as
a function of DAP and WTD are plotted in Figure 5 for subirrigation field at
117
Ankeny site during 1992 and 1993. The data presented in Figure 5 show that
the highest NO3-N concentrations of 6.4, 11, and 10.5 mg/L were observed in
the water samples collected at the 0.9 m soil depth. These concentrations
were observed on 38 DAP in 1992 and water table depths were under natural
conditions. The NO3-N concentrations significantly decreased after WTDs were
raised which shows the effect of water table depths on the movement of NO3-N
in the soil profile. Figure 5 shows that, the trends in NO3-N concentrations
were similar to those in piezometer water samples. The 0.3 m WTD showed
lower NO3-N concentrations as compared with 0.6 m and 0.9 m depths for all
suction tube sampling depths. Figure 5 also shows that NO3-N concentrations
decreased with increasing depth in the soil profile under all water table
treatments depths. NO3-N concentrations at the 0.9 m suction tube depth
ranged from 6.4 to 1.3, 11 to 4.4, and 10.5 to 4.6 mg/L for 0.3, 0.6, and 0.9
m WTDs, respectively. Also, similar trends were observed at the 1.5 and 2.1 m
suction tube depths. The NO3-N concentrations ranged from 6.4 to 0.2, 5.8 to
1, and 7.3 to 1.9 mg/L at the 1.5 m, and from 7.2 to 1.6, 6.2 to 1.5, and 7.1
to 0.1 mg/L at the 2.1 m suction tube depth in the soil profile for 0.3, 0.6, 0.9
m WTDs, respectively. Although, data in Figure 5 indicated an increase In NO3-
N concentrations at the 0.9 m suction tube depth on 168 DAP (at the end of
season) under all WTDs, but showed different responses with WTDs.
Figure 5 also shows the relationship between average NO3-N
118
concentrations at various suction tube depths as function of WTD and DAP for
subirrigation field at Ankeny during 1993. It can be seen in this figure that the
highest NO3-N concentrations of 19.6, 49.9 and 50 mg/L were observed on 48
DAP (2 days before WTD treatment began), at the 0.9 m suction tube depth,
for 0.3, 0.6, and 0.9 m WTDs, respectively. Heavy rainfalls in 1993 caused
leaching of residual and applied N fertilizer from surface layer to deeper depths,
therefore, higher amounts be anticipated. Also, WTD treatments were not
started at this point, which in turn, would have helped in reducing the
downward leaching of NO3-N. Although, rainfall continued throughout the
growing season, the NO3-N concentrations were affected by WTDs. The higher
NO3-N concentrations were observed at the 0.9 m WTD as compared with 0.3
and 0.6 m WTDs. The NO3-N concentrations for the rest of the growing season
(after WTD treatments were started) ranged between 3.3 to 0.5, 4.7 to 1.5,
and 6.3 to 3.5 mg/L at the 0.9 m suction tube depth for 0.3, 0.6, and 0,9 m
WTDs, respectively. NO3-N concentrations ranged from 1.7 to 0.4, 2.2 to 1.6,
and 3.4 to 2.6 mg/L at the 1.5 m suction tube depth, and from 1.4 to 0.3, 2.1
to 1.5, and 2.6 to 1.5 mg/L at the 2.1 m suction tube depth, under 0.3, 0.6,
0.9 m WTDs, respectively.
119
NO3-N concentrations in piezometer water samples at the Ames site
The data for Ames site were plotted differently than those at the Ankeny
site only to compare the trends of NO3-N concentration by depth and for each
sampling day as a function of WTD. This way a clear differences between WTD
treatments for any given sampling day could be monitored. The average NO3-N
concentrations as a function of WTD and piezometer depth for each sampling
DAP for the growing season of 1992 are plotted in Figure 6. The highest NO3-N
concentrations were observed In the water samples collected on 39 DAP at all
piezometer depths. Those ranged from 95.5 to 212, 21.6 to 125.7, and 7.2 to
54.8 mg/L at 1.2, 1.8, and 2.4 m piezometer depths, respectively, in the soil
profile. These samples were collected 10 days before the actual water table
treatments began. Figure 6 shows that NO3-N concentrations significantly
decreased after WTDs were raised. Those ranged from 18.1 to 1.4, 19.5 to
1.9, and 27.5 to 5.9 mg/L at the 1.2 piezometer depth after WTDs were raised
to 0.3, 0.6, 0.9 m, respectively. NO3-N concentrations ranged from 3.9 to 0.4,
7.7 to 2.5, and 25.4 to 4 mg/L at the 1.8 m piezometer depth, and ranged from
6.2 to 2.6, 19.3 to 21.1, and 19.5 to 3.1 mg/L at the 2.4 m piezometer depth
under 0.3, 0.6, and 0.9 m WTDs, respectively. Although, there was a
decreasing trend in average NO3-N concentrations in groundwater samples with
time, a slight increase in the NO3-N concentrations in groundwater samples
collected at the 1.8 and 2.4 m piezometer depths was observed at the end of
120
the season (on 169 DAP), under all three WTDs. However, at the 1.2 m
piezometer depth samples were not available for analysis, therefore, no definite
conclusion could be made for this piezometer depth for 169 DAP. Figure 6 also
compares the NO3-N concentrations in groundwater samples by depth under all
WTDs. The data show that the NO3-N concentrations decreased with increased
piezometer depth in the soil profile. The higher concentrations were observed in
the water samples collected at the 1.2 m piezometer depth as compared with
the 1.8 and 2.4 m piezometer depths.
The data on average NO3-N concentrations, for 1993, as a function of
WTD are presented in Figure 7. This figure shows distinct trend of decreasing
NOgrN concentrations in groundwater samples with time at all piezometer
depths during the growing season. The average concentrations decreased with
increased sampling depths, and 1.2 m piezometer depth, most of the time,
showed lower concentrations as compared to 1.8 and 2.4 m piezometer depths.
Figure 7 also shows that the highest NO3-N concentrations were observed at all
sampling depths on 48 DAP (2 days before water treatment began), and those
significantly decreased after water table treatments were initiated, which shows
the effects of water table depth practices. The average NO3-N concentrations
in groundwater at the 1.2 m piezometer depth decreased from 27.8 to 0.8,
20.8 to 2.6 and 53.6 to 3.9 mg/L under 0.3, 0.6, 0.9 m WTD, respectively.
Similarly, NO3-N concentrations decreased from 18.6 to 0.8, 18.9 to 1, and
121
38.3 to 3.9 mg/L at the 1.8 m piezometer depth, and decreased from 15.7 to
0.3, 12.6 to 0.6, and 34.1 to 1.8 mg/L at the 2.4 m piezometer depth under
0.3, 0.6, and 0.9 WTDs, respectively.
NO3-N concentrations in suction tube water samples at the Ames site
The average NO3-N concentration in groundwater at 0.3, 0.6, 0.9, 1.5,
and 2.1 m suction tube depth as a function of WTD, for 1992, in lysimeter plots
at the Ames site are presented in Figure 8. Figure shows that NO3-N
concentrations under the 0.3 m WTD were lower than those observed at 0.6
and 0.9 m WTDs, almost during the entire growing season. Comparison
between suction tube sampling depths shows that the NO3-N concentrations
decreased with the increased suction tube depth in the soil profile. These
concentrations decreased from 30.3 to 3.2 mg/L at the 0.3 m suction tube
depth with a WTD of 0.3 m, after water table was raised, and those decreased
from 63.8 to 6.7 mg/L, and from 115.3 to 5.1 mg/L with 0.6 and 0.9 m WTDs,
respectively, at the same suction tube depths. Similar trends in NO3-N
concentrations decrease at 0.6, 0.9, 1.5, and 2.1 m suction tube depths were
observed under all three water table depths. Regardless of suction tube
sampling depth, the NO3-N concentrations decreased with time under 0.3, 0.6,
0.9 m WTDs, and significant differences between WTD treatments were
observed. However, a slight increase in NO3-N concentrations at the end of
122
season on 169 DAP was observed at the 0.3 and 0.9 m suction tube sampling
depth under 0.6 and 0.9 m WTD.
The data on NO3-N concentration as a function of WTD and water
sampling depths in the soil profile for 1993 are shown In Figure 9. Figure
shows that NO3-N concentrations decreased with increasing suction tube
sampling depth, and also decreased with time. The highest NO3-N
concentration of 67.1, 95.5, 40.9 mg/L on 48 DAP were observed at 0.3, 0.6,
and 0.9 m suction tube depths, respectively, with 0.9 m WTD. However, those
under 0.3 m WTD were 21.6, 17.5, and 10.1 mg/L at 0.3, 0.6, and 0.9 suction
tube depths, respectively, and were 16, 5.1, 4.7 mg/L under 0.6 m WTD at
0.3, 0.6, and 0.9 m suction tube depths, respectively. Heavy rainfalls during
the early part of the growing season of 1993 caused leaching of residual and
applied N fertilizer from the surface layer to deeper depths, therefore, higher
amounts of NO3-N could be anticipated. The average NO3-N concentrations in
groundwater at all suction tube depths, after 48 DAP, were always less than 10
mg/L under all WTDs for the rest of the growing season.
The analysis of the data at both sites (Ankeny and Ames) shows that
NO3-N concentration were lower at the 0.3 m (shallow) WTD as compared to
0.6, 0.9, and 1.1 m (deep) WTDs. These results are in agreement with the
previous reports by Kalita and Kan war (1992). They found that nitrate
concentration were reduced by maintaining a shallow water table depths in the
123
range of 0.3 to 0.6 m. In the unsaturated zone of the soil profile NO3-N
concentration as high as 285 mg/L was observed, but the average NO3-N
concentrations in the groundwater never exceeded the 10 mg/L drinking water
standard. They hypothized that the reduction of NO3-N concentration at
shallow water table depths was possibly enhanced by increased denitrification.
In the saturated zone where air in the pore spaces may be replaced by water,
the bacterial reduction of NO3-N to nitrogen gas may have been greatly
enhanced. Myrold and Tiedje (1985) also stated that under saturated soil
conditions, the denitrification capacity could be significantly increased.
Distribution of NO3-N in the soil profile
Table 3 shows the effect of WTDs on average seasonal residual soil NO3-
N concentrations as a function of sampling depth in the soil profile at the
Ankeny and Ames sites. The table shows the NO3-N concentrations in the soil
profile on two sampling dates during the 1992 and 1993 seasons. In 1992,
higher NO3-N concentrations were observed at both sites in the soil samples
collected during the early part of the growing season. These soil samples were
collected on 34 DAP, therefore, higher concentrations due to cumulative NO3-N
(applied plus residual) could be anticipated. Data in this table show that NO3-N
concentrations to be seem concentrated in the upper 0,15 to 0.6 m of the soil
profile and that the NO3-N levels decreased with the increased soil depth under
124
all water table treatments. However, at the 0.9 m depth, NO3-N concentrations
were higher in comparison with those observed at 0.3 and 0.6 depths at the
Ames site. At the Ankeny site, similar trends were observed, the highest
concentrations were observed at the 1.1m WTD as compared to other four
WTDs. The soil samples collected at the time of harvest showed low values of
NO3-N concentrations with statistically significant differences in the amounts for
the different water table treatments.
In 1993, the samples were collected before N fertilizer application, and at
harvesting, therefore, the data in Table 3 reflect the average residual NO3-N
concentrations. The NO3-N concentrations were significantly reduced during
this year. Precipitation received in 1993 was sufficient to flush out some of the
cumulative NO3-N amounts into the drainage as well as into surface runoff
waters. However the higher NO3-N concentrations were concentrated in the
upper 0.3 m of soil depth under all WTDs. This trend decreased with increasing
soil depth. The top soil layer lost accumulated NO3-N which moved to deeper
depths in the soil profile. Although, low values of NO3-N concentrations were
observed at all sampling depths in 1993, the 0.9 m WTD depth gave
comparatively higher NO3-N levels than did other WTDs at the Ames site. An
opposite trend was observed at Ankeny site, and higher concentrations were
observed at 0.2 m WTD In comparison with other four WTDs. Data In Table 3
shows that NO3-N accumulated more in the upper soil profile (top 0.15 to 0.6 m
125
depth) and gradually decreased with depth. The trend of NO3-N concentrations
was influenced very much by climatic variations. A wet year (1993) gave lower
amounts of NO3-N under all WTDs implicating that more NO3-N was either
utilized by the plants or flushed out through the drainage or in surface runoff.
Figure 10 shows the best fit regression lines comparing residual NO3-N In
the soil profile under different WTD treatments at the Ankeny and Ames sites.
Regression equations and their R^ values are shown in this figure. Results
indicate that WTD treatments significantly affected the residual NO3-N
distribution in the soil profile at all sampling depths. The difference is quite
significant for the top 0.3 m depth and this difference gradually tends to
approach a constant value at greater depths. The best fit curves (Fig 10) show
that NO3-N levels in the soil profile exponentially decreased with increasing
sampling depth in the soil profile at both sites. The coefficient of correlation R^
ranged between 0.58 to 0.95 at the Ankeny site and it ranged between 0.88
and 0.97 for the Ames site under different WTDs.
Figure 11 shows the best fit regression lines comparing residual NO3-N in
the soil profile under different WTD treatments using pooled data observed at
the Ankeny and Ames sites. Regression equations and their R^ values are
shown in the figure. Results indicate that WTD treatments significantly affected
the residual NO3-N distribution in the soil profile at all sampling depths. The
difference is quite significant for the top 0.3 m depth and this difference
126
gradually tends to approach a constant value at greater depths. The best fit
curves (Fig 11) show that NO3-N levels in the soil profile exponentially
decreased with increasing sampling depth in the soil profile. The correlation
coefficient ranged between 0.79 to 0.98 with pooled data. These values
were very high as compared to those observed for the individual site.
Crop yield
Corn yields for 1992, and 1993 for the Ankeny and Ames sites are
presented in Table 4. At the Ankeny site, the highest corn yield was obtained
from the plots under the 0.9 and 1.1 m depths, and the lowest yield was
obtained from the plots under the 0.2 m depth in 1992. In 1993, however, the
1.1 m depth gave the highest, and the 0.2 m depth gave the lowest yield. At
the 0.2 m depth crop yield was very poor in both years. High rainfalls caused
almost surface flooding conditions for a few days during 1992, and almost all
the time during the growing season of 1993, at the 0.2 m depth, which in turn
significantly affected the yield at this location. Yields for 1992 were higher
than those for 1993. The extremely wet condition were responsible for the
decrease in the yield for 1993. However, the 0.3 m depth showed slightly
higher yields than did the 0.6 m depth for both years.
The analysis of variance (ANOVA) was performed using SAS procedures
to determine the differences between yield means under five WTD treatments
127
for individual year. The ANOVA showed no significant differences between the
means under different WTDs at the 0.05 probability level during 1992.
However, the means were significantly different between 0.2, 0.9, and 1.1m
WTDs at the 0.05 probability level, but those were not significantly different
between 0.3, 0.6, 0.9, and 1.1 m WTDs during 1993.
At the Ames site, the highest yield was obtained from the plots under the
0.9 m depth, and the lowest yield was obtained from the plots under the 0.3 m
depth during both study years (Table 4). Almost similar results were observed
during both years at this site. The water tables were maintained by pumping
the excessive rainfall water at this site, therefore, no significant differences in
corn yields between two years were observed.
The analysis of variance (ANOVA) was performed using SAS procedures
to determine the differences between yield means under three WTD treatments
for individual year. The ANOVA showed no significant differences between the
means observed at the 0.6 and 0.9 m depths at the 0.05 probability level during
both study years. However, the means for the 0.3 and 0.9 m depths were
significantly different at the 0.05 probability level during both study years.
128
CONCLUSIONS
Field experiments were conducted to study the effects of water table
depths on groundwater quality. Average NO3-N concentrations in groundwater
as affected by different WTDs were measured in Iowa for two growing seasons
(1992 and 1993). Data for 1992 and 1993 were collected at two research
sites owned by the Iowa State University. These two research sites are located
near the Ankeny and Ames. This study resulted in the following conclusions:
1. The average NO3-N concentrations in groundwater were reduced by
maintaining WTDs between 0.3 to 0.6 m during the growing season. The
average concentrations in groundwater generally decreased with increased
depth and time during the growing seasons. The highest NO3-N concentrations
in groundwater were observed before the water table treatments were initiated.
However, NO3-N concentrations were significantly reduced after WTD
treatments started and in most cases these concentrations in groundwater were
less than 10 mg/L under 0.3 m WTD.
2. Generally decreasing trends in groundwater NO3-N concentrations with
increasing sampling depths under two sampling methods were consistent in
both study years at both experimental sites.
3. The residual soil NO3-N concentrations seem to be concentrated in the upper
0.15 to 0.6 m of the soil profile and the NO3-N levels decreased with the
129
increased soil depth under all water table treatments. However, at the 0.9 m
WTD, the NO3-N concentrations were higher as compared to those observed at
the 0.3 and 0.6 depths at the Ames site. At the Ankeny site, similar trends
were observed, the highest concentrations were observed at the 1.1m WTD as
compared to other four WTDs. The soil samples collected at the time of harvest
showed low values of NO3-N concentrations with statistically significant
differences in the amounts for the different water table treatments.
4. At the Ankeny site, the highest corn yield was obtained from the plots under
the 0.9 and 1.1m WTDs, and the lowest yield was obtained from the plots
under the 0.2 m WTD in 1992. In 1993, however, the 1.1 m WTD gave the
highest, and the 0.2 m WTD gave the lowest yield. At the 0.2 m depth crop
yield was very poor in both years at this site. At the Ames site, the highest
yield was obtained from the plots under a WTD of 0.9 m, and the lowest yield
was obtained from the plots under a WTD of 0.3 m during both study years.
5. Findings of this study show that, although, the 0.3 WTD is most suitable for
groundwater quality control, it is not appropriate if the highest crop yields are
desired. The best water table management practice for best crop yields and
groundwater quality control would be somewhere between 0.6 to 1.1 m WTD
for Iowa's Nicollet loam soils.
Table 1. Selected physical properties of the soils at the Ankeny and Ames experimental sites
Depth Sand m %
Silt %
Clay %
pH Bulk density Mg m'3
Organic matter %
Nicollet loam soil at the Ankeny site*
0.15 29.5 44.3 26.2 5.9 1.25 3.2
0.30 31.5 40.4 28.1 6.6 1.49 2.3
0.60 38.6 34.1 27.3 7.1 1.46 1.5
Nicollet loam soil at the Ames site"
0.15 31.3 43.6 25.1 7.3 1.20 4.3
0.30 31.2 42.8 26.0 6.7 1.30 4.0
0.60 27.7 42.2 30.1 6.9 1.35 2.9
^Charkhabi (1990); "Kanwar et al. (1988)
131
Table 2. Monthly rainfall (mm) at the Ames and Ankeny during 1992 and 1993
Ames Ankeny
Month 1992 1993 1992 1993
Jan 30.2 20.3 22.6 27.4
Feb 38.4 19.8 35.6 31.5
March 62.7 82.8 70.4 73.2
April 98.6 65.0 85.3 74.4
May 26.4 185.7 26.7 198.6
June 14.7 193.8 38.4 145.5
July 259.3 416.3 232.7 282.7
August 56.6 263.9 29.5 326.9
Sept 103.6 101.3 93.2 130.6
Oct 13.7 38.4 6.4 42.2
Nov 117.1 28.2 85.6 3.8
Dec 46.2 46.2
Total 867.7 1415.5 772.4 1336.8
132
Table 3. NOg-N (mg/L) distribution pattern in the soil profile under different water table treatnnents at the Ankeny and Ames sites.
Water Table Depth
Site Sampling Date
Ankeny 06-11-92
10-31-92
05-04-93
10-19-93
Ames 06-11-92
10-31-92
05-04-93
Depth 1.1 m m
0.15 23.36 0.30 72.41 0.60 18.36 0.90 7.60 1.20 6.71 1.50 5.04 0.15 0.19 0.30 28.83 0.60 18.08 0.90 3.21 1.20 1.72 1.50 0.25 0.15 16.63 0.30 7.15 0.60 3.63 0.90 1.06 1.20 0.89 1.50 0.97 0.15 0.86 0.30 0.73 0.60 0.31 0.90 0.46 1.20 0.91 1.50 0.95
0.15 0.30 0 . 6 0 0.90 1 . 2 0 1.50 0.15 0.30 0 . 6 0 0.90 1 . 2 0 1.50 0.15 0.30 0 . 6 0 0.90
0.9 0.6 m m
10.68 11.05 7.03 6.60 4.44 3.85 4.53 3.78 2.67 3.76 2.15 3.59 0.20 0.05 46.37 13.98 8.06 1.24 1.02 0.26 0.61 0.51 0.34 0.26 8.90 10.43 13.58 3.88 3.12 1.57 1.06 0.86 0.60 0.70 2.89 0.37 0.59 0.93 0.80 0.60 0.37 0.44 0.51 1.61 0.71 1.32 0.53 1.03
76.82 93.32 40.45 21.52 23.80 16.20 11.58 11.75 10.07 8.19
5.22 8.21 12.49 11.25 10.80 8.31 5.46 5.04 4.15 1.83 1.42 0.59 0.25 0.29 17.17 18.31 6.37 4.22 6.31 4.31 3.99 2.56
0.3 0.2 m m
8.18 8.39 4.62 2.81 2.61 1.72 1.94 1.34 1.99 1.59 1.86 2.23 0.67 0.05 8.92 7.02 0.72 0.89 0.30 0.39 0.20 0.34 0.24 0.15 14.50 9.10 2.81 2.35 1.37 1.23 0.82 0.69 0.45 0.54 0.05 0.63 0.78 1.27 0.54 0.78 0.61 2.31 0.98 2.00 0.71 1.55 0.77 1.26
31.90 27.35 15.78 15.31
7.82 6 .36 7.57 6.71 3.03 3.07 0.48 0.14 12.18 3.64 4.02 1.35
133
Table 3 (continued)
1.20 1.80 L .08 0.85 1.50 1.43 0, .94 0.46
10-19-93 0.15 0.33 0, .47 0.38 0.30 8.71 2, ,19 1.42 0.60 4.05 2, ,01 1.13 0.90 3.14 1. ,30 0.73 1.20 1.25 0. 68 0.53 1.50 0.50 0. 53 0.34
134
Table 4. Corn yield kg/ha as a function of water table depth at Ames and Ankeny sites for 1992 and 1993.
WTD, m Ames Ankeny
Year 1992
0.2
CO
CO
o
0.3 5216' 8400'
0.6 6970'" 8348'
0.9 8732" 9280'
1.1 9293'
Year 1993
0.2 3671'
0.3 4930' 5226'
0.6 7914" 5150'"
0.9 8860" 6960"'
1.1 7399"'
Means followed by same letter in a column are not significantly different at the 0.05 probability level within year and site
Iirigallon
S3 Corf ugalcd HmIk lump CacmOO) Cofiygatcd flailicTilt
PVCricBibU Lintr
Sump f ump
w en
Figure 1. An isometric view of the lysimeter with sump and float assembly (after Kalita and Kanwar, 1992)
i
136
City of Ames Main Water Supply Line
Water Meter Pit —
Hydrant ^3—Water Storage Tank Xy/ (1.3 m diameter,
1.6 m height)
L.
a 0
r" s at
Additional Drain Valve
0c-
T
•PVC Main Irrigation Supply Pipe (diameter 7.5 cm)
Ô0
Co-
Co
I I
0 lo
•T"
0 lo
.1..
0 0
Mc.
1 I
•-1— Irrigation Lateral
• Water Meter
o,o
0.25 mm Plastic Barrier (1.2 m deep)
I 3 m .
9m
36 m
O Corrugated Plastic Sump ———0,25 mm PVC Flexible Liner
o o Observation Wells (1.7 m deep)
Figure 2. Layout of the experimental plots at the Ames site (after Kalita and Kanwar, 1992)
Reservoir
Irrigation Lines!
Drainage
Lines
Return
Drainage Pump
Figure 3 A schematic sketch of the dual-pipe subirrigation system at the Ankeny site (after Kalita and Kanwar, 1992)
35 30
25
20
IS
10
5
0
30
25
20
15
10
S
0
30
25
20
15
10
5
0
At 1.2 m depth from soil surfact
J J J J • WTD-0.2n<
Q WTD-0.6m
• WTD-1.1 m
jLi (1992)
At 1.8 m depth from sofl surf»c«
a J . 1
At 2.4 m depth from soil surface
<NS - no wxtcr sample availal
^ lÉ d d b TI
sample available for analysis)
38 54 82 112 140 168
Days after planting
E »
I -I " Z 10 S s
At 1.2 m depth from soi surface
• WTD-0.2m
IS WTD.0.6m • WTD-I.I m
I
At 1.8 m depth from soil surface
At 2.4 m depth from soil surface
J 68 88 116 144
Days after planting
4. Nitrate-N concentration in piezometer water samples at Ankeny site, 92, 93
14
12
10
8
6
4
2
0 14
12
10
8
6
4
2 0
14
12
10
S
6
4
2
0
At 0.9 m depth from sofl suf1«cc
At I.SmdtpttifromsoiisurfKC
At 2.1 m depth from soil surface
• WT0-0.3m Q WTO-O.6m B WTD " 0.9 m
1 m
NS NS
38 54 82 112 140 168
Days after planting
14
12
10
8
! 2
0
14
E 12 c o 10
S 10
c 8 o 8
u c 6 o 6 o Z 4
o s
2
A z 0
14
12
10
6
4
2
0
49.9 SO
At 0.9 m depth from soil surf
Ax 1.5 m depth from soM surfj
At 2.1 m depth from soil surface
(1993)
• WTD«0.3m
tS WTD-0.6m • WTD-O^m
68 88 116
Days after planting
5. Nitrate-N concentration in suction tube samples at Ankeny site, 92, 93 {NS - no water sample available for analysis)
DAP - 55
DAP - 61
E « 25 g
jL 20
'•20 1.80 2.40
Depth below soil surface, m
§ O 10
i : 25
20
15
10
5
0
• WTD»0.3m
E3 WTD-OGm
• WTD«0.9m
1
1.20 1.80 2.40
Depth below soil surface, m
Fig. 6. Nitrate-N concentration in piezometer water samples at Ames site, 1992.
120
20
IS
10
S
0 120
20
IS
10
S
0
15
10
S
0
115.3
DAP « 55
DAP - 81
0.60 0.90 1.50
Depth below soil surface, m
IS _ • WTD-0.3m
ES WTD-0.6m
10 - • WTD-0 j m
as
{"
L
à A A
J -iil -Bl Jh
0.60 0.90 1.50
Depth below soil surface, m
7. Nitrate-N concentration in suction tube samples at Ames site, 1992 (NS - no water sample available for analysis)
I
O) E
i
1 1
48 DAP
WTD«0.3m 116 DAP
a a WTO«0.6m
WrD»0.9m
is 6
O *
S 2
144 DAP
to
Depth below soil surface, m Depth below soil surface, m
Figure 8. Nitrate-N concentration in piezometer water samples at Ames site, 1993
60
10
8
6
4
2
0
8
6
4
2
0
8
6
4
2
0
67.1 g
a^M .DH 409 a » iB
48 DAP
WTD-0.3m
IS WTD-0.6m
WTD-0.9m
0.30 0.60 0.90 1.50 2.10
Depth below soil surface, m
i: 1.
1.
WTD-0.3fn
IS3 WTO-O.6m
WTD«0.9fn
iJi -ji ̂0.60 0.90 1.50 2.10
Depth below soil surface, m
9. Nitrate-N concentration in suction tube samples at Ames site, 1993
144
NItrate-N, ppm (dry soil) 10 15
o- Ankeny site
WTD • 0.3 m
WTD - 0.3 m
• • I A • • I
WTD - 0.6 m
WTD • 0.9 m
NOy N - 04.49 MP I" 1.13 D)
NOy N • 03.67 MP
NO 3* N - 05.31 MP
(. 1.61 01
NOy N « 60.85 MP (• 3.84 0)
M * NOg. N - 38.24 MP
R:
0.91
0.63
Ames site
WTD - 0.3 m
M • ÛH • • I
WTD " 0.8 m
# « # # » # # «
NOj- N - 07.07 MP (• 2.12 01
NOg. N - 09.68 MP .(•2.11 Dl
NOg.N - 18.07 Mp' I-1.14 0)
0.97
Figure 10. Residual Nitrate-N pattern in the soil profile as a function of
water table depth at the Ankeny and Ames sites
Nitrate-N, ppm (dry soil basis)
10 20 30 25 0
0.2
0.4
0.6
0.8 1-1.1213 01 WTD = 0.2 m NO3-N = 04.16 exp 0.81
1 (-1.4855 01 NO 3. N = 10.77 exp*' 0.95 WTD = 0.3 m
I-1.5492 D) NO3-N = 14.60 up 0.88 WTD = 0.6 m
(. 1.8943 0) 0.98 NOy N = 25.96 exp ̂WTD = 03m
1.4 I- 2.0081 01 0.79 NO3- N = 24.81 exp'' WTD = 1.1 m
1.6
Figure 11. Residual nitrate-N distribution pattern as a function of sampling depth in the soil profile under different WTDs (using pooled data for two sites)
146
PAPER III. MOVEMENT OF PESTICIDES INTO SHALLOW GROUNDWATER
AS AFFECTED BY WATER TABLE MANAGEMENT
147
ABSTRACT
Field experiments were conducted at two research farms of Iowa State
University near Ames and Ankeny to evaluate the effects of water table depths
(WTD) practices on the movement of two surface applied herbicides, atrazine
and alachlor, into the groundwater. Data were collected by using piezometers
and suction tubes during the growing seasons of 1992 and 1993 at these
research farms, and average concentrations of atrazine and alachlor in
groundwater (as affected by different WTDs) were measured.
The average atrazine and alachlor concentrations in groundwater were
reduced by maintaining shallow WTDs between 0.3 to 0.6 m during the two
growing seasons. The average herbicide concentrations in groundwater
generally decreased with increased sampling depth and time. It was also
observed that alachlor concentrations were lower than those of atrazine under
similar WTD treatments. Alachlor was not detected in many samples, however,
atrazine was detected in almost all water samples. However, atrazine
concentrations were significantly reduced after WTD treatments started which
shows a positive influence of WTD practices in reducing pesticide
concentrations.
Regression analysis show that atrazine concentrations in the soil profile
linearly decreased with increased sampling depths under all WTD treatments.
148
However, atrazine concentrations were always higher under deep WTD
treatment, and those decreased for shallow WTDs, The best fit regression lines
for alachlor data show that alachlor concentration in the soil profile linearly
decreased with increased sampling depth in the soil profile under all WTD
treatments. Alachlor concentrations in most cases were higher under deep
WTD treatment, and those decreased under shallow WTDs.
Corn yields significantly increased as water-table depths increased from
0.2 to 1.1 m in 1992 and 1993 at the Ankeny site. A shallow water-table
depth of 0.2 to 0.3 m significantly reduced corn yield in the wet season of
1993 at this site. In the lysimeter plots at the Ames, crop yields were
maximum under a WTD of 0.9 m, whereas, in the subirrigation field, the highest
yields were observed at 1.1 m WTD. The yields were also affected by wet
conditions in 1993 at the Ankeny site, and were less than those observed
during 1992. However those were not affected by wet conditions at the Ames
site. Findings of this study show that, although, the 0.3 WTD is most suitable
for groundwater quality control, it is not ideal for obtaining the highest crop
yields. The best water table management practice for best crop yields and
groundwater quality would be somewhere between 0.6 to 1.1 m WTD for
Iowa's Nicollet loam soils of central Iowa.
149
INTRODUCTION
Modern agriculture is heavHy dependent on the use of agrichemicals,
particularly fertilizers and pesticides. For economic reasons, continued use of
pesticide and fertilizers is expected for the foreseeable future in U.S. agriculture
Willis et al., 1992). The greatest volume of pesticides used in agriculture is
accounted for by herbicide application in crop production (Leonard, 1990). As
of 1982, the pesticide usage in the Corn Belt States was nearly 300 million
kilograms, and 85 percent of this usage was in the Corn Belt States, such as,
Iowa, Illinois, Indiana, Ohio, and Michigan (Hallberg, 1986). A major concern is
that low concentrations of less soluble but widely used pesticides have been
detected in shallow aquifers under a wide range of agricultural and climatic
condition. In 1986 the Environmental Protection Agency (EPA) reported the
presence of 17 pesticides in groundwater in 23 states (Cohen et al., 1986).
However, during recent years, this figure has gone up, and the reported cases
increased to 77 pesticides in groundwater in 39 states (Williams et al., 1988).
Herbicide presence in surface and groundwater bodies has been
documented in the literature. Some of these studies reported on the following:
Lower Mississippi River (Pereira and Posted, 1990; Pereira et al., 1992); River
Basins of the Midwestern U.S. (Thurman et al., 1991); Little Vermilion River
(Mitchell et al., 1993), few other studies have reported the presence of
150
herbicide in groundwater systems (Bengtson et al., 1990, 1993); Southvwck et
al., 1990a, 1990b; Fausey et al., 1990; Kanwar, 1990; Kalita and Kanwar,
1989, 1990; and Kalita, 1992).
During the past decade numerous studies have been conducted to
characterize the fate and movement of applied pesticides and their impact on
surface and groundwater. This is of particular concern because groundwater is
the predominant source of domestic water in most rural areas in the United
States (National, 1985). It is estimated that 97% of the nation's rural
population relies on groundwater as its source of drinking water (Moody, 1990).
According to Ritter (1986), widely used herbicides such as atrazine,
alachlor, metolachlor, and cyanazine have been detected in groundwater
systems of several states. He further reported that atrazine and alachlor
together accounted for 25% of all pesticides sold in U.S. during 1982. Isensee
et al. (1988) reported that three corn production herbicides, atrazine [2-chloro-
4-(ethylamino)-6-(isopropylamino)-S-triazine], alachlor [2-chloro-2',6'-diethyl-N-
(methoxymethyl) acetanilide], and cyanazine [2-chloro-4-(cyano-1-methylamino)-
6-ethylamino-S-triazine], have been detected in groundwater in many states
because of their wide application. They found that atrazine concentration in
shallow groundwater was between 0.2 to 1.8 ppb and that of alachlor was 0.3
ppb. These concentrations were far below the health advisory limits for atrazine
(3 ywg/L) and alachlor (2 ywg/L). Mitchell et al. (1993) reported that atrazine
151
concentrations as high as 9.6 ppb were observed from the sub-surface tile flow
station outlets located in East Central Illinois. Alachlor and metolachlor were
also detected on 20 occasions, and trifluralin was detected on 19 occasions in
the tile flow.
Alachlor has been found to be less persistent than atrazine in soil profiles
(Buhler et al., 1993). In their tests of drain outflow, alachlor was found in only
2% of samples whereas atrazine was detected in 97% of the samples taken in a
6 year period. Alachlor has been detected in groundwater samples in Iowa,
Nebraska, Maryland, and Pennsylvania at residue levels of 0.1-10 //g/L (Cohen
et al., 1986). Alachlor concentration in groundwater as high as 16//g/L was
found in Iowa (Kelley et al., 1986). Libra et al. (1986) and Kelley et al. (1986)
reported that atrazine concentrations of 10 //g/L were detected in a karst aquifer
In Iowa. In a study, Smith et al. (1990) found that atrazine concentration in the
soil water at a depth of 0.61 m reached 350//g/L after 19 days of application.
They also reported that atrazine concentration as high as 90 //g/L was observed
in the shallow groundwater after 16 months of its application, however, alachlor
was not detected in the soil below the depth of 0.36 m, they hypothized that
apparently most of the alachlor had degraded during their experimental period.
Workman et al. (1993) presented atrazine and alachlor concentration data
from soil cores taken to a depth of 0.9 m and partitioned into the increments of
0.0-0.15, 0.15-0.3, 0.45-0.6, and 0.75-0.9 m, and observed that herbicide
152
remained in the top 0.15 m of the soil profile during their two year study period.
The chemicals had degraded for approximately two half-lives for atrazine and 3-
4 half-lives for alachlor. The computed rate constant, k, and half-life, was
0.02 days'^ and 35 days for atrazine, respectively. A rate constant of 0.04
days^ and half life of 17 days computed for alachlor. In addition, they reported
that chemical seem to adsorb to the clays and organic matter in the soil since
the residual level of atrazine remained relatively high during the winter (50-100
ppb).
While determining the leaching potential of atrazine in a sandy loam soil
in Southern Quebec Canada, Smith et al. (1992) found a large variation in
atrazine concentration in soil solution at various depths and in leachate. The
maximum levels in the leachate ranged from 0.0 to 11.2 /yg/L. Higher solution
concentrations in the top 5 cm were correlated with higher moisture contents,
suggesting desorption of atrazine with water. They further observed that the
Deisopropylatrazine, one of the metabolites of atrazine, was detected near the
soil surface but did not leach beyond the 15 cm depth.
In a study conducted in Denmark on leaching of atrazine into
groundwater, Folding (1992) found that atrazine leaching was significantly
affected by high water tables and only small quantities of atrazine were
observed in the upper groundwater zone. The samples were taken from the
upper 1.5 m ground water zone at three well drained levels. The atrazine
153
content was between 0.01 to 0.05 //g/L. The highest concentrations being
found at the top of groundwater table.
There is a scant literature on pesticide management with water table
management practices. However, recently these practices have received
attention as potential measure to reduce pollution hazards to groundwater
system. Few studies have shown that water table management (WTM)
practices that include controlled drainage, and controlled drainage-subirrigation
could reduce pesticide concentrations in shallow groundwater and improve crop
yield (Baker, 1980; Baker and Johnson, 1976; Bengtson et al., 1990, 1993;
Evans et al., 1989; Fausey et al., 1990; Kanwar, 1990; Kanwar et al., 1988;
Kalita and Kanwar, 1989, 1990; and Kalita, 1992).
Baker (1980) and Baker and Johnson (1976) found that the concentration
of most herbicides and insecticides were higher in surface runoff than in
subsurface drainage, but chemical that were not adsorbed, such as anionic
herbicides, usually had higher concentrations in the subsurface drainage.
Kladivko et al. (1991) determined field scale pesticide losses to subsurface
drainage on a low organic matter and (poorly structured) silt loam soil under
typical agricultural management practices. They observed small amounts of
carbofuran, atrazine, cyanazine, and alachlor in subsurface drain flow within 3
weeks of pesticide application. The annual carbofuran losses in subsurface
drain flow ranged from 0.8 to 14.1 g/ha, whereas, the losses of all other
154
pesticides were ^ 0.06% of the amount applied. Bengtson et al. (1990)
reported that atrazine and metolachlor losses were reduced by 55 and 51 %,
respectively, in the areas where subsurface drainage systems were used. They
concluded that subsurface drainage substantially reduced atrazine losses, and
about 2/3 of the losses occurred within 30 days after herbicide application.
They also found that atrazine concentrations were substantially greater than
EPA's advisory level for drinking water. In another study, Bengtson et al.
(1993) reported that subsurface drainage reduced alachlor and norflurazon
losses by 34 and 31%, respectively. They found alachlor and norflurazon
losses under nondrained fields were 48 and 59%, respectively. Based on their
findings, they concluded that subsurface drainage may offer a management tool
for decreasing pesticide input from non-point agricultural sources into aquatic
areas of the Lower Mississippi Valley.
In previous study conducted in Iowa, Kalita (1992) observed that under
different water table depths, pesticide concentrations were lower at shallow
water table depths, however, this trend increased with increasing water table
depth. Higher concentrations of atrazine and alachlor were observed at water
table depth of 0.9 m or deeper. Results of this and other studies have stressed
on the need of further research on the use of WTM practices to reduce
groundwater quality degradation caused through the use of pesticides.
Because of the growing concern over the herbicide use which may lead to
155
significant contamination of both surface and groundwaters, information on the
pollution potential from herbicides and possible ways to reduce or control non-
point pollution is of great importance. Thus, the objectives of this study were
to investigate the effects of WTM practices on the movement of herbicides into
shallow groundwaters. The specific objective of this study was to discuss the
effects of WTM practices on the movement of two surface applied herbicides,
atrazine and alachlor, to shallow groundwater during the growing seasons of
1992 and 1993.
156
MATERIALS AND METHODS
Description of experimental sites
Field studies were conducted during growing seasons of 1992 and 1993
on two research farms owned by Iowa State University. These research farms
are located near Ames and Ankeny. The soils at these sites are predominantly
Nicollet loam (Aquic Hapludolls) in the Clarion-Nicollet-Webster soil association.
Table 1 lists some of the physical properties of these soils at these two sites.
At the Ames site, nine field lysimeters (each 3 m wide and 6 m long)
were installed in 1986. A 0.2 m wide and 1.2 m deep trench around the
perimeter of each lysimeter was dug using a Ditch Witch trencher, and each
lysimeter was completely enclosed using a plastic barrier 0.25-mm-thick to
minimize any lateral subsurface water movement between lysimeters. A
corrugated, perforated plastic tube (100-mm diameter) was installed at the
bottom of the trench inside the plastic barrier. A 0.9 m wide ditch was dug to a
depth of 1.35 m with a back hoe to install a 1.5 m tall corrugated plastic pipe
(used as sump) at the corner of each lysimeter. The bottom of 1.5 m tall sump
was located 1.35 m below the soil surface, and the top of the sump was 0.15
m above the soil surface. The two ends of the perforated plastic tubes at right
angles to each other were inserted into the sump at a height of 0.15 m from the
bottom of the sump. In 1990, all lysimeters were enclosed with another 0.25-
157
mm-thick PVC (poly-vinyl-chloride) flexible liner to a depth of 1.7 m. Each liner
encased a square area (9 m X 9 m) with the 3 X 6 m original field lysimeter
located in the center of the enclosed area to ensure that subsurface water did
not move laterally between lysimeters to a depth of 1.7 m. A detailed
procedure for the lysimeter installation is described by Kalita and Kanwar
(1990), and is also shown in Figure 1. Figure 1 shows an isometric view of the
lysimeter with installed sump and float assembly. A float mechanism was
installed in each sump to maintain the desired water level in the lysimeter plot
area. Each lysimeter was connected to the main water-supply tank using a 75-
mm diameter PVC irrigation pipe. The layout of the experimental area for this
site is shown in Figure 2.
At the Ankeny site, a dual pipe subirrigation system was installed in 1988
on a 0.5-ha area with a significant natural ground slope of 2.5 percent. The
basic concept of the dual-pipe subirrigation system is illustrated in Figure 3.
Shallow irrigation pipes (51-mm diameter) were installed at a depth of 0.5 to
0.6 m parallel to and midway between drainage pipes, which were installed at a
depth of 1.2 m. Because of the natural ground slope along the length of the
field, water tables could be maintained at various depths below the soil surface
by controlling the subsurface drainage outflows and by supplying irrigation
water through the subirrigation pipes.
158
Water table management treatments
At the Ames site, water table depths were maintained at 0.3, 0.6, and
0.9 m in 1992 and 1993. Each water table treatment depth was replicated
three times. Water table depths were maintained to the desired depths from
day 49 to 110th day after planting (DAP) during the growing season of 1992,
and from 50 to 98 DAP during the growing season of 1993. The elapsed time
of about 50 days from planting to the start of water-table treatment allowed
corn roots to develop within 0.3 to 0.9 m soil profile. It took almost three days
to bring the water tables to the required depths during 1992, whereas, during
1993 the record wet year, there was no problem in bringing the water tables
near the surface but water tables had to be lowered using a sump pump.
Observation wells (25-mm diameter and 1.2-m long PVC pipes) were installed in
the center of each lysimeter to monitor water levels.
At the Ankeny site, WTDs were maintained at 0.2, 0.3, 0.6, 0.9, and 1.1
m, respectively. However, the water table depths ranged from 0.05 to 1.2 m
during the growing season. A maximum water-table depth of 1.2 m was
observed at the highest elevation site (north boundary) of the field in the
beginning of the 1992 season. The minimum water table depth of 0.05 m was
observed at the lowest elevation site of the field twice during the growing
season of 1992, and most of the time during growing season of 1993 due to
heavy rainfall.
159
Each treatment location was divided into three subplots, where the
monitoring devices were installed. This combination provided three replications
per each water table depth treatment along the row. Water table depths,
however, were maintained from 49 to 110 DAP in 1992 and from 50 to 98 DAP
in 1993. An elapsed period of about 50 days between planting and start of
subirrigation allowed corn roots to develop uniformly in this field to a depth of
0.2 to 1.1 m.
Groundwater sampling
Ground water samples were collected using suction tubes and
piezometers on monthly basis in 1992 and 1993 from both sites for pesticide
analysis. Solute suction tubes were made by coupling a 200-kPa porous
ceramic cup to the end of 38-mm diameter PVC pipe. The top ends of these
tubes were sealed with rubber stoppers. At the Ames site, suction tubes were
installed at the center of all nine lysimeters (three replications per treatment) at
0.3, 0.6, 0.9, 1.5, and 2.1 m depths to collect water samples. A vacuum
pump was used to create a vacuum in the solute suction tubes one day before
sample collection, and water samples were collected the following day.
Piezometers were made of 25-mm diameter PVC pipes by making perforations
at the lower end to be placed in the ground. The lower ends were sealed with
rubber stoppers. Piezometers were installed in each lysimeter plot at 1.2, 1.8,
160
and 2.4 m depth to collect ground water samples and to monitor piezometric
heads. The piezometers were pumped out one day before sampling if any water
was sitting in the piezometers and water samples were collected on the
following day. All water samples collected, were then preserved in a cold
chamber at 4 °C for analysis.
At the Ankeny site, solute suction tubes were installed at 0.9, 1.5, and
2.1 m depths at three locations (B, C, and D locations as shown in Figure 1)
with three replications at each location. Piezometers were also installed at three
locations (A, C, E locations as shown in Figure 1) at 1.2, 1.8, 2.4 m depths
with three replications per location. Similar procedures (those at Ames site)
were followed to collect water samples.
Herbicide extraction procedures
The 300 ml water sample plus 100 ml of methylene chloride [CHg CIg]
were placed in a separation funnel. This mixture was hand shaken for 2
minutes and the solvent was collected. This procedure was repeated 3
additional times using 50 ml of methylene chloride each time. The solvent was
then evaporated to dryness and the residues dissolved in approximately 10 ml
of methanol. The extract was stored at 4 °C for further analysis.
Analysis of herbicide: The extracts were analyzed using a Varian 3400 gas
chromatograph (fused-silica megabore DBS-column; TSD detector) equipped
161
with an integrator and an auto-sampler, in the water quality laboratory of
Agricultural and Biosystems Engineering Department. A very small portion of
the extract was injected into a tracer 560 GC with a N-P thermionic detector.
Operating conditions were: column oven at 160 °C, inlet at 245 °C, detector at
245"'C, Helium carrier gas at the rate of 18 cm^ min'\ Hydrogen reaction gas at
the rate of 3.5 cm^ min \ and air reaction gas at the rate of 100 cm^ min'\
Herbicides were separated using a 3% OV-1 column.
Planting, harvesting, and chemical management system
The corn genotype Pioneer 3379 was planted at both sites. In 1992,
seeds were planted on May 8, and were hand harvested on November 6 in the
lysimeter plots at Ames site, and were harvested using a combine at the
Ankeny site in 1992. In 1993, seeds were planted on May 21 at both sites,
and were hand harvested on October 21 in the lysimeter plots at Ames site, and
were harvested on October 31 using a combine at the Ankeny site. The plant
population was 67000 per ha with a row-to-row spacing of 0.75 m and seed-to-
seed distance of 0.2 m at each site. Urea nitrogen, phosphorus, and potassium
fertilizers were surface applied at planting time at both sites every year at the
rate of 200 kg-N ha \ 60 kg ha % and 40 kg ha'\ respectively. Herbicides
atrazine (C3H14CIN5) and alazhlor (trade name lasso, Ci^HgoCINOg) were applied
at the rate of 2.2 kg ha \ in both years at the Ankeny and Ames sites.
162
RESULTS AND DISCUSSION
Atrazlne concentrations in piezometer water samples at the Ames site
Atrazine concentrations as a function of WTD and piezometer sampling
depth for 1992 are plotted in Figure 4. At this site, WTDs were constantly
maintained at 0.3, 0.6, 0.9 m depths during the growing seasons of 1992 and
1993. Figure 4 shows that atrazine concentrations were lower at WTD of 0.3
m in comparison with WTDs of 0.6, and 0.9 m. Atrazine concentrations
generally decreased with time and increased with piezometer sampling depth.
Figure 4 shows that atrazine concentrations in groundwater samples at 1.2 m
were lower than at 1.8 and 2.4 m piezometer sampling depths with few
exceptions. At the 1.2 m sampling depth, concentrations in groundwater
ranged between 3.9 to 2.1, 5.2 to 1.2, and 18.3 to 5.4//g/L under 0.3, 0.6,
and 0.9 m WTD, respectively, during the growing season of 1992. Atrazine
concentrations at the 1.8 and 2.4 m piezometer sampling depths also showed,
on the average, an increasing trend with lowering WTD. Similarly, atrazine
concentrations ranged between 7.2 to 0.9, 9.7 to 1.4, and 33.9 to 0.6//g/L at
the 1.8 m depth, and ranged between 6.0 to 0.4, 8.6 to 1.1, and 14.5 to 2.1
)[yg/L at the 2.4 m depth under 0.3, 0.6, and 0.9 m WTDs, respectively.
However, the highest concentrations of 18.3, 33.9, and 14.5 //g/L were
observed under the 0.9 m WTD at 1.2, 1.8, and 2.4 m piezometer sampling
163
depth, respectively, on 55 DAP.
Atrazine concentrations in piezometer water samples for 1993 as a
function of WTD and DAP are presented in Figure 5. The figure shows a
distinct trend of decreasing concentrations with time and increasing piezometer
depth. Higher atrazine concentrations were observed at the 0.9 m WTD as
compared to those observed at the 0.3 and 0.6 m WTDs. At the 1.2 m depth,
most of the time, lower atrazine concentrations were observed as compared to
the 1.8 and 2.4 m piezometer sampling depths. Figure 5 also shows that the
highest atrazine concentrations of 128.8 and 626.1 yc/g/L were observed at the
1.8 and 2.4 m piezometer sampling depths under 0.9 m WTD on 48 DAP. This
might be the result of quick transport of atrazine due to excessive rain activity
in 1993. The average atrazine concentrations in groundwater at the 1.2 m
piezometer sampling depth ranged between 5.2 to 1.0, 7.0 to 1.8 and 8.6 to
0.8 yt/g/L under 0.3, 0.6, 0.9 m WTD, respectively. Similarly, concentrations
ranged between 11.6 to 0.7, 7.8 to 1.2, and 128.8 to 8.8 //g/L at the 1.8 m
piezometer depth, and those ranged between 4.5 to 1.5, 22.5 to 3.0, and
626.1 to 2.8ywg/L at the 2.4 piezometer depth under 0.3, 0.6, and 0.9 WTDs,
respectively.
164
Atrazine concentrations in suction tube water samples at tlie Ames site
Concentrations of atrazine in suction tube water samples in 1992 are
shown in Figure 6. Water samples were collected using suction tubes at 0.3,
0.6, 0.9, 1.5, and 2.1 m depths during the growing season, but no water
samples could be collected for analysis from 0.3, 0.6, and 0.9 m suction tube
depths on 39 DAP because of drier soil conditions. Also, very few samples
were available for analysis at those suction depths on 141 and 169 DAP. This
was due to unsaturated soil profile particularly when WTD was maintained at
0.6 and 0.9 m depths. Figure 6 shows that atrazine concentrations under the
0.3 m WTD were lower than those observed at the 0.6 and 0.9 m WTDs. The
highest atrazine concentration of 66.8 ywg/L on 39 DAP was observed at the 0.9
m WTD in comparison with 24.4//g/L at the 0.6 m WTD. Figure 6 also
compares the atrazine concentrations by sampling depth in the soil profile. The
atrazine concentrations were generally higher at shallow sampling depths as
compared to deep sampling depths in the soil profile under all WTDs with few
exceptions. These concentrations decreased from 4.9 to 1.9 //g/L at the 0.3 m
suction tube depth with a WTD of 0.3 m, after water table treatment was
started, and those decreased from 7.9 to 0.9 //g/L and from 26.2 to 3.8 //g/L
under 0.6 and 0.9 m WTDs, respectively, at the same suction tube depth.
Similar trends of decrease in atrazine concentrations under three WTDs were
observed at 0.6, 0.9, 1.5, and 2.1 m suction tube sampling depths.
165
The data on atrazine concentration as a function of WTD and water
sampling depths in the soil profile for 1993 are plotted in Figure 7. Figure 7
shows that atrazine concentrations decreased with increasing suction tube
sampling depth, and also decreased with time with few exceptions. The
highest atrazine concentrations of 19.9, 31.8, 60.3 //g/L on 48 DAP were
observed at 0.3, 0.6, and 0.9 m suction tube depths, respectively. These
concentrations were observed under 0.9 m WTD. However, those under 0.3 m
WTD were 20.9, 17.5, and 21.4 jt/g/L at 0.3, 0.6, and 0.9 suction tube depth,
respectively, and were 19.1, 2.8, 26.0yc/g/L under 0.6 m WTD at 0.3, 0.6, and
0.9 suction tube depths, respectively. The atrazine concentrations ranged
between 26.0 to 1.1, 23.7 to 0.7, and 60.3 to 2.6 ywg/L under 0.3, 0.6, and 0.9
m WTDs, respectively, during the growing season. The average atrazine
concentrations in groundwater at all suction tube depths, after 48 DAP, were
always less under all WTDs for the rest of the growing season. These results
show significant differences in atrazine concentrations between WTD
treatments, and reveal a positive influence of WTDs in reducing atrazine
concentrations in groundwater. Another noticeable observation was that, at the
Ames site, atrazine concentrations in suction tube water samples were higher
than those in piezometer water samples.
166
Atrazine concentrations in piezometer water samples at the Ankeny site
Atrazine concentrations in piezometer samples for the growing season of
1992 at the Ankeny site are presented in Figure 8. Water table depths were
maintained at 0.2, 0.6, and 1.1 m at this site. The average concentrations as a
function of DAP and WTD in the subirrigation field at Ankeny site show that the
atrazine concentrations in groundwater samples were different at different
WTDs during the growing season of 1992. The 0.2 m WTD showed lower
atrazine concentrations in comparison with those observed at the 0.6 and 1.1 m
WTDs. Atrazine concentration decreased with time under all WTDs. In the
early part of growing season of 1992, higher concentrations were observed at
1.2, 1.8, and 2.4 m piezometer depths than In the later part of the growing
season. The higher concentrations are associated with greater amounts of
atrazine available In the soil profile due to applied herbicide. Therefore, higher
atrazine concentrations could be anticipated. The highest atrazine concentration
o f 2 1 . 6 j u g / L w a s o b s e r v e d a t t h e 2 . 4 m p i e z o m e t e r d e p t h 5 4 D A P u n d e r 1 . 1 m
WTD treatment. With sublrrigatlon practice, atrazine concentrations in
groundwater decreased significantly. Figure 8 also compares the atrazine
concentrations at 1.2, 1.8, and 2.4 m piezometer water sampling depths, under
0.2, 0.6, and 1.1 m WTDs. Figure 8 shows that the atrazine concentrations
generally decreased with increased depth in the soil profile under all WTDs with
few exceptions. The atrazine concentrations decreased with time, however, at
167
all three piezometer sampling depths in the soil profile. At the 1.2 piezometer
depth, concentrations of atrazine in groundwater samples varied from 10.1 to
0.5, 13.6 to 1.9, and 19.6 to 1.1 yt/g/L for 0.2, 0.6, and 1.1 m WTDs,
respectively. Similarly, those varied from 8.8 to 0.5, 19.9 to 1.7, and 11 to 0.5
yug/L at the 1.8 m piezometer depth, and from 1.6 to 0.2, 1.4 to 0.2, and 21.6
to 2.1 //g/L at the 2.4 m piezometer depth for 0.2, 0.6, and 1.1 m WTDs,
respectively.
The average atrazine concentrations in piezometer water samples for
1993 as a function of WTD and DAP are plotted in Figure 9. Similar trends in
atrazine concentrations were observed in 1993 as compared to those observed
in 1992. However, the highest concentrations of 22.2, 21.3, 16.6 //g/L on 68
DAP were observed at 1.2, 1.8, and 2.4 m piezometer depths in the soil profile
under 1.1 m WTD. The atrazine concentrations were significantly reduced with
time. These results show a definite influence of WTD treatments on pesticide
concentrations in groundwater. The atrazine concentrations were different at
different WTDs, and were different for various piezometer sampling depths in
the soil profile. Data for 1993 also indicate that atrazine concentrations were
lower under 0.2 m WTD than at 0.6, and 1.1 m WTDs, and generally decreased
with increased sampling depth in the soil profile under all three WTDs. The
concentrations also decreased with time, significantly higher concentrations
were observed during the early part of the growing season. Heavy rainfalls
168
during the early part of the growing season of 1993 perhaps caused leaching of
applied herbicide from the surface layer to the deeper depths. Atrazine
concentrations ranged between 12.0 to 1.2, 8 to 1.8, and 22.2 to 10.9 ,ug/L at
the 1.2 m piezometer depth under 0.2, 0.6, and 1.1m WTDs, respectively.
Similarly, atrazine concentrations ranged between 8.5 to 2.8, 611.2 to 1.5, and
23 to 9.3 //g/L at the 1.8 m piezometer depth, 4.7 to 1.2, 6.7 to 5.8, and 16.6
to 1.9/yg/L at 2.4 m piezometer depth under 0.2, 0.6, and 1.1 m WTDs,
respectively. Comparison between atrazine concentrations at different
piezometer depths shows that greater amounts were observed at the 1.8 m
piezometer depths than those observed at 1.2 and 2.4 m piezometer depths.
Atrazine concentrations in suction tube water samples at the Aniceny site
Atrazine concentrations in groundwater samples collected from the
suction tubes during 1992 are shown in Figure 10. Figure shows that atrazine
concentrations ranged between 114.6 to 0.2, 14.4 to 1.2, and 36.2 to 0.2 //g/L
for 0.3, 0.6, and 0.9 m WTDs, respectively. The highest atrazine
concentrations of 114.5 /yg/L was observed at 0.9 m suction tube depth on 38
DAP. Those at 1.5, and 2.1 m suction tube depths were 22.7 and 9.9/yg/L,
respectively. However, the atrazine concentrations were significantly reduced
at the 0.9, 1.5, and 2.1 m suction tube depths under all WTDs after
subirrigation was started. The atrazine concentrations decreased with time and
169
increased suction tube depth. At the end of the growing season, atrazine
concentrations in groundwater samples decreased to 0.2, 0.8, and 0.7 //g/L at
0.9, 1.5, and 2.1 m soil depths, respectively. Water samples from suction tube
also showed higher atrazine concentrations at the 2.1 m soil depth than those
at 1.5 and 0.9 m soil depths towards the end of the growing season when
subirrigation was cut off.
The data on average atrazine concentration as a function of WTD and
suction tube depths in the soil profile for 1993 are illustrated in Figure 11.
Figure 11 shows that atrazine concentrations decreased with increasing suction
tube sampling depth and also decreased with time. The highest atrazine
concentrations of 36.4, 3.4, 1.4//g/L on 48 DAP were observed at 0.9, 1.5,
and 2.1 m suction tube depths, respectively, at 0.9 m WTD. However, those
under 0.3 m WTD were 2.7, 1.5, and 0.5 //g/L at 0.9, 1.5, and 2.1 suction tube
depths, respectively, and were 4.5, 0.5, and 10.2//g/L under 0.6 m WTD at
0.9, 1.5, and 2.1 suction tube depths, respectively. During the early part of the
growing season of 1993 greater atrazine concentrations were observed. Heavy
rainfall in the early part of the growing season caused leaching of applied
herbicides from surface layer to deeper depths, therefore, higher amounts could
be anticipated. It was observed that atrazine concentrations in groundwater
were significantly lower with 0.3 m WTD than with 0.6 and 0.9 m WTDs under
all sampling depths. However, almost similar trends in atrazine concentrations
170
were observed in piezometer and suction tube water.
Alachlor concentrations at the Ames site
The results of the alachlor concentrations in piezometer and suction tube
water samples for the two growing seasons (1992-93) are presented in Table 2.
Alachlor was not detected in many samples collected on different dates in 1992
and 1993. Table 2 shows only the dates when alachlor was detected in
groundwater samples during the two years. In 1992, alachlor was detected in
only ten piezometer water samples, and the results were inconsistent. It was
detected only in nine suction tube samples and the trends were similar to those
in piezometer samples. The highest concentration of 18.3 /yg/L was observed in
piezometer samples at 0.9 m WTD on 81 DAP. Alachlor has been found less
persistent than atrazine in soil profiles (Buhler et al., 1993). In their tests,
alachlor was found in only 2% of samples whereas atrazine was detected in
97% of the samples taken in a 6-year period. Nash (1988) reported that under
normal agricultural use conditions, 90% of alachlor was degraded within 30 to
100 days of application. Wu and Fox (1981) reported that the time for 90%
loss from the upper 0.3 m zone was 298 days for atrazine, and only 45 days for
alachlor. Their study shows that alachlor was detected 77 days after its
application with a concentration of 1.1 /yg/L at the 2.1 m soil depth.
In 1993, alachlor concentrations were detected at almost all sampling
171
depths in piezometer samples collected on 48, 68, 90, and 116 DAP. However,
those concentrations were not detected in many suction tube samples and
results were inconsistent. The highest concentrations were observed in
piezometer samples on 48 DAP. Alachlor concentration in piezometer samples
ranged between 58.4 to 1.2, 4.3 to 0.8, and 37.3 to 2.1 yug/L under 0.3, 0.6,
and 0.9 m WTDs, respectively. These concentrations were lower in 1992 than
in 1993. However a shallow WTD significantly reduced alachlor concentrations
at all depths.
Alachlor concentrations at the Ankeny site
Table 3 presents alachlor concentrations in piezometer and suction tube
water samples for the two growing seasons (1992-93) in the subirrigation field
at the Ankeny site. Similar trends in alachlor concentrations at this site were
observed. Alachlor concentrations were detected only on three occasions
during the growing season of 1992 in piezometer samples. Those were
d e t e c t e d o n 3 8 , 5 4 , a n d 8 2 D A P i n p i e z o m e t e r w a t e r s a m p l e s a t 0 . 6 a n d 1 . 1 m
WTDs. However, alachlor concentrations were not detected in any of the
suction tube water samples during the growing season of 1992. The highest
concentration of 1.2 //g/L was observed in piezometer samples collected on 54
DAP. In 1993, alachlor concentrations were detected in almost all suction tube
samples collected on 48 DAP under all three WTD treatments. The highest
172
concentration of 11.5, 6.7, and 3.1 /yg/L were observed at 0.9, 1.5, and 2.1 m
sampling depths under 0.9 m WTD. These concentrations were higher than
those observed at 0.3 and 0.6 m WTDs. However, alachlor concentrations
were detected only in two samples collected at 0.6 m WTD on 68 DAP. In
piezometer samples, alachlor concentrations were observed in about 50% of the
samples collected on four sampling dates (i.e. 48, 68, 88, and 116 DAP).
Atrazine and alachlor distribution pattern in the soil profile
Relative sampling depths from the soil surface in the soil profile versus
the atrazine and alachlor concentrations under different WTDs fit the respective
regression relations. The regression analysis was performed on the pooled data
collected at both sites during the two year study period. Equations of
regression lines and their respective R-square values for atrazine and alachlor
concentration as a function of sampling depth under different WTDs are given
below:
Regression equations using atrazine data
WTD — 0.2 m. Atra = 6.95 - 2.39 D R2 = 0.80
WTD = 0.3 m. Atra = 8.94 - 2.85 D R2 = 0.40
WTD = 0.6 m. Atra = 10.95 - 3.36 D R2 = 0.37
WTD = 0.9 m. Atra = 18.95 - 5.05 D R2 = 0.36
WTD — 1.1 m. Atra = 21.46 - 5.47 D R2 = 0.98
173
Regression equations using alachlor data
WTD = 0.2 m, Alac = 3.35 - 1.25 D R2 = 0.60
WTD = 0.3 m, Alac = 3.61 - 0.88 D R2 = 0.69
WTD = 0.6 m, Alac = 2.36 - 0.49 D R2 = 0.44
WTD = 0.9 m, Alac = 10.56 - 5.73 D R2 = 0.77
WTD = 1.1 m, Alac = 3.31 - 0.75 D R2 = 0.83
where WTD is water table depth, Atra is atrazine concentration in //g/L, D is
water sampling depth in the soil profile in m, and Alac is alachlor concentration
in //g/L. The respective best fit regression lines for atrazine data are shown in
Figure 12a. Figure 12a shows that atrazine concentration in the soil profile
linearly decreased with increased sampling depth in the soil profile under all
WTD treatments. However, atrazine concentrations were always higher under
deep WTD treatments, and those decreased for shallow WTDs. Figure 12b
shows best fit regression lines for alachlor data. Figure 12b shows that alachlor
concentration in the soil profile linearly decreased with increased sampling depth
in the soil profile under all WTD treatments. Alachlor concentrations in most
cases were higher under deep WTD treatments, and those decreased under
shallow WTDs. However, the differences between WTD treatments were not
clear in some cases.
The analysis of variance (ANOVA) was performed using SAS procedures
on the entire data set to determine the differences between atrazine means
174
under five WTD treatments. The ANOVA results for atrazine are presented in
Table 4. The ANOVA results by water table treatment depth for atrazine show
that, regardless of sampling method and site, the means for 0.2, 0.3, 0.6, 0.9,
and 1.1 m depths were significantly different at the 0.05% probability level.
These results show a positive effect of WTD on the atrazine movement. The
ANOVA results by sampling depth are also presented in Table 4. Table 4 shows
that atrazine means were significantly different for the suction tube samples,
but, were not significantly different for the piezometer samples at both
experimental sites.
The analysis of variance (ANOVA) was performed using SAS procedures
on the entire data set to determine the differences between alachlor means
under different WTD treatments. ANOVA results by WTD treatment show that,
alachlor means were not significantly different at the 0.05% probability level
with piezometer samples at both sites, whereas, those were significantly
different with suction tube samples. Almost, similar trends in alachlor means
were observed with ANOVA performed on alachlor data by sampling depth in
the soil profile.
Crop yield
Corn yields for 1992 and 1993 for the Ankeny and Ames sites are
presented in Table 5. At the Ankeny site, the highest corn yield was obtained
175
from the plots under the 0.9 and 1.1m depths, and the lowest yield was
obtained from the plots under the 0.2 m depth in 1992. In 1993, however, 1.1
m depth gave the highest, and 0.2 m depth gave the lowest yield. At 0.2 m
depth crop yield was very poor in both years. High rainfalls caused almost
surface flooding conditions for a few days during 1992, and almost all the time
during the growing season of 1993, at the 0.2 m depth, which in turn
significantly affected the yield at this location. Yields for 1992 were higher
than those for 1993. The extremely wet condition were responsible for the
decrease in the yield for 1993. However, the 0.3 m depth showed slightly
higher yields than did the 0.6 m depth for both years.
The analysis of variance (ANOVA) was performed using SAS procedures
to determine the differences between yield means under five WTD treatments
for individual year. The ANOVA showed no significant differences between the
means under different WTDs at the 0.06 probability level during 1992.
However, the means were significantly different between 0.2, 0.9, and 1.1 m
WTDs at the 0.05 probability level, but those were not significantly different
between 0.3, 0.6, 0.9, and 1.1 m WTDs during 1993.
At the Ames site, the highest yield was obtained from the plots under the
0.9 m depth, and the lowest yield was obtained from the plots under the 0.3 m
depth during both study years (Table 5). Almost similar results were observed
during both years at this site. The water tables were maintained by pumping
176
the excessive rainfall water at this site, therefore, no significant differences in
corn yields between two years were observed.
The analysis of variance (ANOVA) was performed using SAS procedures
to determine the differences between yield means under three WTD treatments
for individual year. The ANOVA showed no significant differences between the
means observed at the 0.6 and 0.9 m depths at the 0.05 probability level during
both study years. However, the means for the 0.3 and 0.9 m depths were
significantly different at the 0.05 probability level during both study years.
177
CONCLUSIONS
Field experiments were conducted at two research farms of Iowa State
University near Ankeny and Ames to evaluate the effects of water table depth
(WTD) practices on the movement of two surface applied herbicides, atrazine
and alachlor into the groundwater. Data were collected by using piezometers
and suction tubes during the growing seasons of 1992 and 1993 at these
research farms, and average concentrations of atrazine and alachlor in
groundwater as affected by different water table depths (WTDs) were
measured. This study resulted in the following conclusion;
1. The average atrazine and alachlor concentrations in groundwater were
reduced by maintaining shallow WTDs between 0.3 to 0.6 m during the two
growing seasons. The average herbicide concentrations in groundwater
generally decreased with increased sampling depth and with time,
2. Alachlor was not detected in many samples and the results were
inconsistent, however, atrazine was detected in almost all water samples. The
highest atrazine concentrations in groundwater were mostly observed before the
water table treatments began. It was also observed that alachlor concentrations
were lower than those of atrazine under similar WTD treatments. However,
atrazine concentrations were significantly reduced after WTD treatments started
which shows a positive influence of WTM practices in reducing pesticide concentrations.
178
3. Regression analysis show that atrazine concentrations in the soil profile
linearly decreased with increased sampling depth in the soil profile all WTD
treatments. However, atrazine concentrations were always higher under deep
WTD treatment, and those decreased for shallow WTDs. The best fit regression
lines for alachlor data show that alachlor concentration in the soil profile linearly
decreased with increased soil depth under all WTD treatments. Alachlor
concentrations in most cases were higher under deep WTD treatment, and
those decreased under shallow WTDs. However, the differences between WTD
treatments were not clear in some cases.
4. Corn yields significantly increased as WTDs were lowered from 0.3 to 0.9 m
at the Ames site during both study years. At the Ankeny site, yields increased
as WTDs were lowered from 0.2 to 1.1 m. However, yields were not
significantly different between WTDs during 1992 but were significantly at the
0.05 probability level during 1993, and shallow water-table depths (0.2 and 0.3
m) significantly reduced corn yield due to excessive wet conditions.
5. These results indicate that pesticide concentrations in groundwater can be
significantly reduced while corn yield can be maintained at an optimum level by
adopting the right WTD. Therefore, appropriate use of WTD is recommended as
a best management practice for reducing pesticide residue movement into the
groundwater systems.
Table 1. Selected physical properties of the soils at the Ankeny and Ames experimental sites
Depth Sand m %
Silt %
Clay %
PH Bulk density Mg m'3
Organic matter %
Nicollet loam soil at the Ankeny site*
0.15 29.5 44.3 26.2 5.9 1.25 3.2
0.30 31.5 40.4 28.1 6.6 1.49 2.3
0.60 38.6 34.1 27.3 7.1 1.46 1.5
Nicollet loam soil at the Ames site"
0.15 31.3 43.6 25.1 7.3 1.20 4.3
0.30 31.2 42.8 26.0 6.7 1.30 4.0
0.60 27.7 42.2 30.1 6.9 1.35 2.9
®Charkhabi (1990); ''Kanwar et al. (1988)
Table 2. Aiachlor concentrations (//g/L) In suction tube and piezometer water samples at the Ames site In 1992 and 1993
Suction tube water samples Piezometer water samples
Sampling depth Sampling depth
DAP WTD. m 0.3m 0.6m 0.9m 1.5m 2.1m DAP WTD, m 1.2m 1.8m 2.4m
39 0.3 NS NS NS NS NS 39 0.3 ND ND NS 0.6 NS NS NS 4.6 18.2 0.6 ND ND 0.4 0.9 NS NS NS 7.2 ND 0.9 ND 7.4 3.2
55 0.3 ND ND 0.5 ND 1.2 55 0.3 ND ND ND 0.6 2.6 ND ND 1.3 ND 0.6 0.3 0.3 NS 0.9 ND ND ND ND ND 0.9 0.7 2.6 1.2
81 0.3 ND ND ND ND 0.8 81 0.3 ND ND ND 0.6 ND ND 1.0 ND ND 0.6 ND ND ND 0.9 ND 18.3 ND ND ND 0.9 ND ND 0.5
48 0.3 ND ND ND 2.0 ND 48 0.3 5.4 8.4 58.8 0.6 ND 1.6 1.8 0.8 ND 0.6 2.2 2.4 4.3 0.9 1.6 ND 3.8 1.2 ND 0.9 22.1 3.0 37.3
68 0.3 ND ND ND ND ND 68 0.3 3.9 9.4 2.9 0.6 1.7 ND 1.6 ND 0.5 0.6 3.7 4.3 1.1 0.9 ND ND ND 1.5 1.5 0.9 1.2 4.0 23.0
90 0.3 ND ND ND ND 4.8 90 0.3 1.6 2.6 1.2 0.6 ND 2.5 ND 0.8 0.4 0.6 1.4 0.9 1.2 0.9 ND ND ND 1.0 1.7 0.9 4.2 2.1 1.9
116 0.3 ND ND ND ND ND 116 0.3 1.2 2.0 1.7 0.6 ND ND ND 0.9 ND 0.6 ND 0.8 ND 0.9 ND ND ND 0.7 ND 0.9 1.1 ND 8.9
144 0.3 ND ND ND ND ND 144 0.3 ND 0.8 ND 0.6 ND ND ND 0.5 ND 0.6 ND ND ND 0.9 ND ND 2.0 0.9 ND 0.9 ND ND ND
Table 2. (continued)
Overall average 0.3 ND ND 0.5 2.0 2.3 0.3 3.0 4.6 16.2 0.6 2.2 2.1 1.5 1.5 6.4 0.6 1.9 1.7 1.8 0.9 1.6 18.3 2.9 2.1 1.6 0.9 5.9 3.8 10.9
DAP - days after planting; WTD - water-table depth; NS - no water sample available; ND - below detectable limit
182
Table 3. Alachlor concentrations (yt/g/L) in suction tube and piezometer water samples at the Ankeny site in 1992 and 1993
Suction tube water samples Piezometer water samples
Sampling depth Sampling depth
Year DAP WTD.m 0.9m 1.5m 2.1m DAP WTD,m 1.2m 1.8m 2.4m
1992 38 0.3 ND ND ND 38 0.2 ND ND ND 0.6 ND ND ND 0.6 ND ND ND 0.9 ND ND ND 1.1 ND ND 1.5
54 0.3 ND ND ND 0.2 ND ND ND 0.6 NS ND NS 0.6 ND 0.3 ND 0.9 NS NS ND 1.1 0.6 0.7 1.2
82 0.3 ND ND ND 0.2 ND ND ND 0.6 ND ND ND 0.6 ND ND ND 0.9 ND ND ND 1.1 ND ND 0.1
1993 48 0.3 2.4 0.9 ND 48 0.2 2.2 NS ND 0.6 1.7 2.2 4.1 0.6 ND 1.8 1.5 0.9 11.5 6.7 3.1 1.1 2.8 6.9 2.6
68 0.3 ND ND ND 68 0.2 ND 0.4 0.7 0.6 2.0 NS 0,4 0.6 6.4 ND ND 0.9 ND ND ND 1.1 1.1 0.9 0.7
88 0.6 0.4 ND ND 1.1 NS 0.4 1.1
116 0.2 ND 0.3 ND 0.6 0.4 ND ND
Overall averages 0.3 2.4 0.9 ND 0.2 2.2 0.4 0.7 0.6 1.9 2.2 2.3 0.6 3.4 1.0 1.5 0.9 11.5 6.7 3.1 1.1 1.5 2.2 1.4
DAP - days after planting; WTD - water table depth; NS - no water sample available; ND - below detectable limit
Table 4. Analysis of variance (ANOVA) on atrazine and alachlor i f jg/L) data as function of water table depth (WTD) and sampling depth using two years data.
ANOVA by sampling depth, m
Sampling mode Site 0.3 0.6 0.9 1.2 1.5 1.8 2.1 2.4 F Pr > F
Atrazine Suction tube Pi zometer Piezometer
both Ames Ankeny
8.4'" 10.7* 10.2* 8.4* 6.5*
5.6" 2.3' 4.3*" 6.9*
3.1" 4.3*
2.93 0.0220 2.96 0.0575 2.05 0.0575
Alachlor Suction tube Pi zometer Piezometer
both Ames Ankeny
1.9* i .r 1.3* 4.4*= 2.0*
1.5" 3.2" 1.5*
12.9' 1.2*
3.05 0.0377 2.01 0.1538 0.31 0.7391
ANOVA by WTD treatment, m
0.2 0.3 0.6 0.9 1.1 F Pr > F
Atrazine Suction tube Piezometer Piezometer
both Ames Ankeny 2.9*
4.5* 2.8*
5.3* 4.8*" 4.9"
10.4" 7.3"
10.3"
6.07 10.03 12.36
0.0028 0.0226 0.0001
Alachlor Suction tube Pi ezometer Pi ezometer
both Ames Ankeny 0.9*
1.6* 8.3*
2.4* 2.0* 1.6*
5.2" 9.2*
1.8*
2.60 1.34 0.11
0.0930 0.2780 0.8985
Mean followed by same letter in a row are not significantly different at 0.05% probability level
184
Table 5. Corn yield kg/ha as a function of water table depth at Ames and Ankeny sites for 1992 and 1993.
WTD, m Ames Ankeny
Year 1992
0.2 7033*
0.3 5216* 8400*
0.6 6970*" 8348*
0.9 8732" 9280*
1.1 9293*
Year 1993
0.2 3671*
0.3 4930* 5226*
0.6 7914" 5150*"
0.9 8860" 6960%
1.1 7399":
Means followed by same letter in a column are not significantly different at the 0.05 probability level within year and site
Iriigatlon
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m I I PUilUlatficf I—I jo 25 mm iliuk) 12 ] FVCfltiiblilbMt
Sump f ump -
Figure 1. An isometric view of the lysimeter with sump and float assembly (after Kalita and Kanwar, 1992)
00 oi
186
City of Water Supply Line
Water Meter Pit
Hydrant
Additional Drain Valve
L.
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Water Storage Tank (1.3 m diameter, 1.6 m height)
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• Water Meter
o,o • 0.25 mm Plastic Barrier (1.2 m deep)
, 3 m . 9m
36 m
O Corrugated Plastic Sump ———0.25 mm PVC Flexible Liner
o o Observation Wells (1.7 m deep)
Figure 2 . Layout of the experimental plots at the Ames site (after Kalita and Kanwar, 1992)
Reservoir Pump 2
Irrigation l.inesi__c— 'Locatio"
Drainage Lines
Return
Drainage Pump
Figure 3 A schematic sketch of the dual-pipe subirrigation system at the Ankeny site (after Kalita and Kanwar, 1992)
35
30
25
20
IS
10
S
0
30
25
20
IS
10
5
0
30
25
20
15
10
5
0
• WTO - 0.3 m
S WTO . 0.6 m
B WTO « 0.9 m
35
30 -
• WTO - 0 ̂m
Q WTD • 0.6 m
B WTD " 0.9 m
DAP - 55
1-2 1.8 2.4
Depth from the soil surface, m
S
I
J
'•2 1.8 2,4 •
Depth from the soil surface, m
jure 4. Atrazine concentrations in piezometer water samples at the Ames site in 1992 (NS - no water sample available for analysis)
189
Depth from the soil surface, m
Figure 5. Atrazine concentrations in piezometer water samples at the Ames site in 1993 (NS - no sample available)
70
30*
25
20
15
10
5
0
25
20
15
10
S
0
25
20
15
10
5
0
WTD • 0.3 m
WTD - 0.6 m
WTD - 0.9 m
DAP - 39
DAP . 81
0.60 0.90 1.50
Depth from the soil surface, m
I
I
I WTD . 0.3 m
j WTD • 0.6 m
I WTD • 0.9 m
a
1 s s
a 0.60 0.90 1.50
Depth from the soil surface, m
6. Atrazine concentrations in suction tube water samples at the Ames site in 1992 (NS - no water sample available for analysis; ND - below detectable level)
00
35 30 25 20
16
10
5 0
30 26
20
16
to
5 0
30
26
20
16
10
6
0
30
26
20
16
10
S
0
30
26
20
15 10
6
0
191
0,30 0 80 0.90 1.80 2.10
Depth from the soil surface, m
7. Atrazine concentrations in suction tube water samples at the Ames site in 1993 (NS - no sample available)
1.8
Depth from the soil surface, m
Figure 8. Atrazine concentrations in piezometer water samples at the Ankeny site in 1992
(NS - no water sample available for analysis)
2B
20
IB
10
S
0
20
IB
10
B
0
20
IB
10
B
0
20
IB
10
6
0
20
16
10
B
0
193
Wro • 0.2 m
BS WTO - 0.0 m
WTO - 1.1 m DAP - 48
DAP • 08
DAP • 60
Depth from the soil surface, m
e 9. Atrazine concentrations in piezometer water samples at the Ankeny site in 1993 (NS - no sample available)
6
5
4
3
2
1
0
6
5
4
3
2
1
0
6
5
4
3
2
1
0
DAP • 38
a
0.90 ISO 2.10
Depth from the soil surface, m
|: S 2
: <
• WTO - 0.3 m
• WID - 0.6 m
H WTO - 0.9 m
NS
OJO 1.60 2.10
Depth from the soil surface, m
jre 10. Atrazine concentrations in suction tube water samples at the Ankeny site in 1992 (NS - no water sample available for analysis)
195
).60
Depth from the soil surfece, m
Figure 11. Atrazine concentrations in suction tube water samples at the Aniceny site in 1993 (NS - no sample available)
196
25
WTD " 0.2 m
WTD - 0.3 20
WTD - 0.6 m
16 WTD " 0.9 m
WTD - 1.1 m
10
S
0 0 0.6 2.6 1 1.6 2
Sampling depth from the soil surface, m
Figure 12a. Atrazine pattern in the soil profile as a function of water table depth (using pooled data)
8
WTD - 0.2
7
WTD - 0.3 m
6 WTD - 0.6 m
6 WTD " 0.8 m
4 WTD - 1.1 m
3
2
1
0 2.5 0 0.5 1 1.5 2
Sampling depth from the soil surface, m
Figure 12b. Alachlor pattern in the soil profile as a function of water table depth (using pooled data)
197
OVERALL CONCLUSIONS
This study was conducted to investigate the effects of different water
table management practices on plant physiological parameters, crop yield,
and groundwater quality. Data for 1992 and 1993 were collected from field
experiments conducted at two sites near Ankeny and Ames. At the Ankeny
s i t e , t h e w a t e r t a b l e d e p t h s w e r e m a i n t a i n e d a t 0 . 2 , 0 . 3 , 0 . 6 , 0 . 9 , 1 . 1 m
depths on 0.5 ha subirrigation field, and were maintained at 0.3, 0.6, and
0.9 m depths in lysimeter plots at Ames site. Measurements on different
physiological parameters (photosynthesis rate, stomatal conductance,
transpiration rate, intercellular 00% (Ci),' and canopy temperatures) were
taken on biweekly basis using the leaf chamber techniques, and those on
chlorophyll were taken using a SPAD-502 chlorophyll meter. Water samples
for NO3-N and pesticide analysis were collected on monthly basis by using
suction tubes and piezometers installed at different depths in the soil profile.
This study resulted in the following conclusions:
Physiological parameters and WTDs
Analysis of the data show that photosynthesis rates, stomatal
conductances, transpiration rates. Ci, canopy temperatures, and chlorophyll
exhibited similar relation with various WTDs during the growing season. The
198
values of these parameters were significantly affected at the 0.2 and 1.1m
depths as compared to 0.3, 0.6, and 0.9 m depths. The 0.3 WTD had
higher values of these physiological parameters, and these values decreased
with lowering the WTDs. In 1993, a extremely wet year, the values of these
parameters were lower than those observed in 1992 under all WTD
treatments.
The statistical analysis of the data showed that means for
photosynthesis between WTDs for Ames site were significantly different at
the 0.05 probability level during both years, whereas, those were not
significant for 1993 at Ankeny site. However, the means for chlorophyll
readings between WTDs were significantly different at the 0.05 probability
level for both years. The stomatal conductances were not significant at the
0.05 probability level.
Relationship between different parameters were developed by fitting
lines of linear regression. The regression analysis showed strong positive
relations between photosynthesis and leaf chlorophyll readings for 1992 and
1993, at both experimental sites. Results of these analyses reveal that leaf
chlorophyll could be used as a good predictor of photosynthesis rates
regardless of water table treatment depth. Also, a strong positive relation
between stomatal conductance and transpiration rates was observed. The
regression analysis revealed that the transpiration rates were highly
199
dependent on the stomatal behavior.
NO3-N concentrations in groundwater
The average NO3-N concentrations in groundwater were reduced by
maintaining WTDs between 0.3 to 0.6 m during the two growing seasons.
The average concentrations in groundwater generally decreased with
lowering the WTD and time during the growing season. The highest NO3-N
concentrations in groundwater were mostly observed before the water table
treatments began. However, NO3-N concentrations were significantly
reduced after WTD treatments started, and in most cases these
concentrations in groundwater were less than 10 mg/L under the 0.3 m
WTD. Generally decreasing trend of NO3-N concentration in groundwater
with increasing sampling depth under two sampling methods was consistent
in both study years at both experimental sites.
The residual soil NO3-N concentrations seem to be concentrated in the
upper 0.15 to 0.6 m of the soil profile and that the NO3-N levels decreased
with the increased soil depth under all water table treatments. However, at
the 0.9 m WTD, the NO3-N concentrations were higher in comparison with
those observed at the 0.3 and 0.6 depths at the Ames site. At the Ankeny
site, also similar trends were observed, the highest concentrations were
observed at the 1.1 m WTD as compared to other four WTDs. The soil
200
samples collected at the time of harvest showed low values of NO3-N
concentrations with statistically significant differences in the amounts for the
different water table treatments.
Pesticide concentrations in groundwater
The average atrazine and alachlor concentrations in groundwater were
higher at the 0.9 and 1.1m WTDs In comparison with those observed at
0.2, 0.3, and 0.6 m WTDs. The average herbicide concentrations in
groundwater generally decreased with increased sampling depth and time.
Alachlor was not detected in many samples, however, atrazine was detected
in almost all water samples. The highest atrazine concentrations in
groundwater were mostly observed before the water table treatments began.
It was also observed that alachlor concentrations were lower than those of
atrazine under similar WTD treatments. However, atrazine concentrations
were significantly reduced after WTD treatments started which shows a
positive Influence of WTD practices In reducing pesticide concentrations.
Regression analysis show that atrazine concentrations In the soil profile
linearly decreased with increased sampling depth in the soil profile under all
WTD treatments. However, atrazine concentrations were always higher
under deep WTD treatment, and those decreased for shallow WTDs. The
best fit regression lines for alachlor data show that alachlor concentration in
201
the soil profile linearly decreased with increased soil depth under all WTD
treatments. Alachlor concentrations in most cases were higher under deep
WTD treatment, and those decreased under shallow WTDs. However,
trends between WTDs were not clear in some cases.
Corn yield
Corn yields significantly increased as water-table depths were lowered
from 0.2 to 1.1 m in 1992 and 1993 at the Ankeny site. A shallow water-
table depth of 0.2 to 0.3 m significantly reduced corn yield in wet season of
1993 at this site. In the lysimeter plots at Ames, crop yields were maximum
under a WTD of 0.9 m, whereas, in the subirrigation field, the highest yields
were observed at 1.1 m WTD. At the Ankeny site, the yields were also
affected by wet conditions in 1993 and were less than those observed
during 1992. However, at the Ames site, no significant differences in yields
were observed between the two study years. Findings of this study show
that, although, the 0.3 WTD is most suitable for groundwater quality control,
but is not appropriate if the highest crop yields are desired. For the highest
crop yields a WTD between 0.6 to 1.1 m would be desired. Therefore, the
results of this study conclude that a WTD between 0.6 to 0.9 m would be
the best water table management practice for crop productivity and
groundwater quality control.
202
RECOMMENDATIONS FOR FUTURE WORK
This study reports the effects of different water table management
practices on plant physiological parameters and on the movement of applied
chemicals on the groundwater quality. The data on plant physiological
parameters show that results were not conclusive for dry and wet seasons.
Even though, the effects of water table depths were clear for the individual
year. Therefore, further study is needed to develop the nature of the
relationship under different climatic conditions. Results of this study,
however, showed a strong relationship between physiological parameters
regardless of water table depth and climatic conditions. Further studies on
leaf chlorophyll and photosynthesis should be continued to determine
usefulness of relationships determined under this study between these
parameters. Also, N status in leaves as well as in the soil profile should be
determined at the time of chlorophyll measurements. This would provide
instantaneous information about nutrient uptake by plants under any water
table treatment depth, and would also help in determining the exact amount
of chemicals needed for plants at that particular growth stage.
Results of this study indicate the usefulness of water table
management practices to improve crop production and enhance groundwater
quality. However, this study shows that a compromise between crop yield
and groundwater could be made by maintaining water tables between 0.6
203
and 0.9 m from soil surface. Such a water table depth would minimize
leaching of chemical concentration in groundwater while maintaining crop
yield at an optimum level. Therefore, further water-table management
e x p e r i m e n t s a r e s u g g e s t e d w i t h w a t e r t a b l e d e p t h s b e t w e e n 0 . 6 a n d 1 . 1 m
in order to determine the appropriate WTD.
Results on NO3-N show that since a major portion of the applied
chemical had leached to deeper depths within the first few weeks of their
application (especially during the wet year, 1993), therefore it is strongly
recommended water table depth treatments should be started from the
beginning of the growing season. This would help prevent a significant
portion of chemical from leaching to deeper depths at the beginning of the
growing season. Also, soil and water samples should be collected right from
the time of planting and chemical application for a thorough understanding of
water table management effects on chemical transport to shallow
groundwater.
204
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ACKNOWLEDGEMENTS
Foremost, I am extremely grateful to most beneficent Allah, the Almighty,
who bestowed me good health, strength, and courage in accomplishing my
academic goals. Above all, I believe in Allah's boundless love and grace that
have filled my soul with hope and happiness and have Inspired me to live
through difficult times of my life.
I also wish to express my heartfelt gratitude and sincere appreciation to
those whose contributions collectively were of immeasurable value in my
educational pursuits. First, I wish to extend profound thanks and sincere
appreciation to my major professor. Dr. Rameshwar S. Kanwar, for his superb
guidance, constructive suggestions, timely help, and heartfelt cooperation and
counseling which enabled me accomplishing the objective of this research in
professional and scholarly manner. My gratitude for him is forever.
I would like to extend special appreciation and thanks to Drs. Stewart W.
Melvin, Thomas S. Colvin, Thomas E. Fenton, and Theodore B. Baily for serving
as members on my graduate study committee and for their professional
assistance. I must also express gratitude to all my primary and secondary
school, college, and university teachers at Sindh, Pakistan, for instilling in me
values and ideas that inspire me every day.
My father (who passed away on December 8, 1993) was the constant
221
source of support and encouragement throughout my study period. His
support, encouragement, unreserved love, and sacrifices helped me to reach
this stage In my career. I express the deepest sense of appreciation to my
father's soul late Gul Muhammad and my mother's soul late Sultani Mirjat and
dedicate this piece of work to both of them.
Words can not express my feeling for my wife Sahibzadi, daughter Sahar,
and sons Khadim, Mukhtiar, and Zahid, who suffered from not having husband
and a father at home for long three and half years. Their devotion and sacrifice
have been unflinching. I owe them all my achievements. I also extend thanks
to my brothers, sisters, and other relatives especially my cousins and brother-in-
laws for their moral support and everything they did for me during this study
period.
My dear friends/brothers Mr. Alimuddin K. Brohi, Mr. Khadim Hussain
Mirjat, Mr. Muhammad Luqman Mirjat, Dr. Karam All Mirjat, Mr. Mir Khan
Mirjat, Mr. Ghulam Nabi Mirjat, Mr. All Gohar Mirjat, Mr. Muhammad Hayat
Nizamani, Mr. Hafeezullah Baluch, and several others who were extremely
helpful in many ways for which I am grateful to them.
My special thanks to Mr. Loren Shiers for analysis of soil and water
samples for my research. Thanks to Mr. Carl Pedarson for his extreme
cooperation and full assistance in carrying out the field work. The help of Mr.
Ashok Verma in collection of the field data is acknowledged.
222
Thanks to many of my friends and fellow graduate students in the
Department of Agricultural and Biosystems Engineering for their cooperation and
handy help during this study. I appreciate all the help and encouragement
received from Dr. Bherulal T. Devrajani during the course of this study.
Very special thanks are also expressed to Dr. Abdul Qadir Mughul and
Mr. Imam Bux Koondhar, Professors, Sindh Agriculture University Tandojam
Pakistan, for their keen interest in my professional development. Dr. Mughul's
timely help in many official and un-official matters back in Pakistan is
particularly acknowledged.
I extend my sincere thanks to Sindh Agriculture University Tandojam,
Government of Pakistan, and USAID for their financial support in sponsoring my
studies at Iowa State University without whose support I would have never
been able to achieve my career goals. As s scholarship recipient, I feel honored
and grateful. I recognize the valuable assistance from Department of
Agricultural and Biosystems Engineering, Graduate College, College of
Agriculture International Agriculture Program office, and office of the
International Students and Scholars, Iowa State University for providing me an
excellent educational environment and a pleasant stay in Ames, Iowa.
Last but not least, my gratitude extends to the villagers of Hayat Khan
Nizamani and Bahar Khan Mirjat for sharing part of their life with me. Their
sincere cooperation made this study possible.
223
APPENDIX: SUMMARIZED DATA ON PLANT PHYSIOLOGICAL
PARAMETERS NO3-N AND PESTICIDE
224
Table 1. Mean photosynthesis rate (// mole m'^ s'^) under different water table depths for Ankeny and Ames sites in 1992 and 1993
Water table depth, m
Site DAP 0.2 0.3 0.6 0.9 1.1
Ankeny 40 29.8 29.7 28.0 28.6 28.3 1992 56 31.4 35.4 31.5 31.9 30.4
71 33.1 44.7 42.8 38.3 34.3 86 38.0 52.0 47.4 42.9 39.7 98 37.6 39.3 36.9 35.1 34.4 110 31.2 30.5 31.4 31.9 31.5 120 23.4 22.7 22.1 20.5 17.9 130 15.9 21.2 18.3 19.0 15.5
1993 40 21.9 23.7 24.2 24.3 21.1 56 20.9 29.9 28.5 22.1 22.3 71 22.6 32.1 30.1 29.8 23.7 86 34.0 42.0 40.6 38.6 35.6 98 26.7 30.6 29.4 28.5 25.4 110 15.8 18.4 19.9 17.5 16.3
Ames 40 29.6 28.5 29.9 1992 56 29.9 28.4 30.0
71 38.5 34.6 31.4 86 47.7 39.8 35.0 98 40.9 30.0 28.8 110 25.2 25.5 22.2 120 12.9 15.2 18.1 130 8.8 7.1 6.3
1993 40 23.4 23.8 23.1 56 30.1 30.7 27.8 71 35.6 31.3 29.5 86 39.0 34.6 30.2 98 23.5 22.9 24.1 110 12.1 11.9 10.1
DAP - Days after planting
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Table 2. Mean stomatal conductance (mole m'^ s'^) under different water table depths for Ankeny and Ames sites in 1992 and 1993
Water table depth, m
Site DAP 0.2 0.3 0.6 0.9 1.1
Ankeny 40 0.33 0.32 0.29 0.33 0.26 1992 56 0.50 0.67 0.62 0.52 0,46
71 0.58 0.83 0.72 0.65 0.60 86 0.60 0.94 0.76 0.70 0.63 98 0.62 0.74 0.71 0.66 0.63 110 0.47 0.66 0.63 0.61 0.56 120 0.45 0.47 0.46 0.45 0.42 130 0.41 0.37 0.43 0.45 0.40
1993 40 0.55 0.54 0.52 0.59 0.51 56 0.63 0.71 0.63 0.72 0.62 71 0.70 0.85 0.77 0.76 0.65 86 0.72 0.93 0.72 0.79 0.71 98 0.43 0.46 0.42 0.45 0,38 110 0.33 0.31 0.31 0.33 0.29
Ames 40 0.36 0.31 0.34 1992 56 0.61 0.56 0.51
71 0.69 0.63 0.60 86 0.77 0.72 0.66 98 0.68 0.69 0.67 110 0.45 0.44 0.41 120 0.34 0.33 0.28 130 0.29 0.26 0.23
1993 40 0.39 0.41 0.41 56 0.57 0.52 0.45 71 0.72 0.74 0.66 86 0.94 0.87 0.79 98 0.60 0.53 0.56 110 0.44 0.42 0.35
DAP - Days after planting
226
Table 3. Mean transpiration rate (mm/day) under different water table depths for Ankeny and Ames sites in 1992 and 1993
Water table depth, m
Site DAP 0.2 0.3 0.6 0.9 1.1
Ankeny 40 5.1 7.3 6.1 5.8 4.6 1992 56 7.4 10.8 8.3 8.6 4.7
71 9.0 14.6 12.0 13.1 10.0 86 13.9 22.8 16.2 16.3 12.7 98 10.1 13.5 11.1 10.4 10.0 110 5.1 8.7 7.2 6.9 4.6 120 4.9 6.0 5.5 5.8 3.8 130 2.5 4.4 4.2 4.1 2.9
1993 40 4.9 5.7 6.5 5.3 4.8 56 6.2 8.4 8.0 7.3 5.8 71 7.7 8.6 10.2 10.3 7.8 86 12.3 12.7 13.5 11.7 10.1 98 2.8 4.1 5.0 4.5 2.5 110 1,3 3.8 3.7. 4.1 1.2
Ames 40 5.2 4.9 4.4 1992 56 11.3 10.0 8.8
71 16.8 14.2 12.3 86 22.0 14.7 11.1 98 14.0 12.4 7.3 110 9.3 8.8 3.1 120 5.4 4.9 1.6 130 4.0 3.2 1.5
1993 40 5.7 4.7 5.5 56 10.8 8.2 6.9 71 14.8 11.2 10.6 86 15.1 13.6 11.2 98 11.5 9.9 8.8 110 2.1 2.0 2.1
DAP - Days after planting
227
Table 4. Mean Intercellular CO2 concentration (ppm) under different water table depths for Ankeny and Ames sites in 1992 and 1993
Water table depth, m
Site DAP 0.2 0.3 0.6 0.9 1.1
Ankeny 40 204.2 187.2 214.1 206.4 208.0 1992 56 211.4 228.3 224.9 220.0 214,5
71 246.1 265.8 252.8 243.4 237.7 86 242.8 255.0 249.8 238.0 233.1 98 221.5 246.4 244.3 238.3 229.2 110 185.8 227.5 211.7 207.7 207.2 120 209.1 231.8 221.9 223.4 225.6 130 206.2 204.3 205.8 206.3 204,9
1993 40 224.6 257.5 231.0 234.5 232.0 56 221.3 238.9 228.9 220.2 228.1 71 224.8 257.6 245.5 234.9 232.1 86 234.8 264.0 266.2 259.8 238.1 98 213.8 219.2 205.8 221.9 212.1 110 180.7 196.2 190.2 180.9 174.7
Ames 40 240.0 239.2 268.3 1992 56 333.2 269.7 341.1
71 303.3 314.2 310.6 86 356.6 339.3 350.2 98 282.9 242.3 201.4 110 280.6 265.1 232.4 120 290.1 281.2 274.8 130 241.8 234.3 229.0
1993 40 206.4 206.7 199.9 56 223.9 220.7 219.6 71 283.5 277.3 269.3 86 282.1 278.1 279.6 98 226.7 219.8 218.5 110 202.2 198.5 204.6
DAP - Days after planting
228
Table 5. Mean chlorophyll content (SPAD units) under different water table depths for Ankeny and Ames sites in 1992 and 1993
Site DAP
Water table depth, m
Site DAP 0.2 0.3 0.6 0.9 1.1
Ankeny 40 42.7 43.7 43.4 43.2 41.9 1992 56 43.3 50.2 50.1 48.7 46.2
71 48.5 53.7 51.4 50.5 49.7 86 50.9 55.3 53.8 52.5 50.3 98 46.7 53.6 50.4 50.7 45.7 no 39.7 46.7 44.2 42.9 39.3 120 36.2 36.8 35.4 34.3 33.7 130 35.8 36.5 35.0 34.0 33.3
1993 40 41.2 41.8 40.8 41.5 41.1 56 42.4 46.1 44.2 44.0 43.4 •71 39.4 47.7 46.7 43.7 42.3 86 43.4 51.6 51.2 50.9 44.8 98 38.8 51.9 48.7 51.7 42.8 110 30.3 45.7 41.3 41.9 33.2
Ames 40 41.7 43.4 43.2 1992 56 47.1 46.7 45.4
71 54.8 51.9 46.6 86 57.7 54.0 49.1 98 55.6 52.6 48.1 110 52.7 51.1 44.8 120 47.3 45.9 41.5 130 39.5 39.7 35.9
1993 40 39.5 41.4 37.8 56 44.8 44.7 38.9 71 50.9 49.2 42.6 86 53.3 50.1 40.1 98 46.3 41.0 37.3 110 41.3 37.7 34.4
DAP - Days after planting
229
Table 6. Mean air temperature (°C) under different water table depths for Ankeny and Ames sites in 1992 and 1993
Site DAP
Water table depth, m
Site DAP 0.2 0.3 0.6 0.9 1.1
Ankeny 40 29.0 31.8 30.4 30.7 29.8 1992 56 26.8 30.3 28.5 29.1 27.8
71 31.2 31.4 31.5 32.1 31.5 86 27.9 28.6 29.6 29.0 28.3 98 33.3 31.3 31.6 30.9 30.9 110 31.5 28.5 29.8 28.9 30.3 120 27.5 28.0 27.1 28.6 27.2 130 26.7 23.9 27.8 25.8 27.0
1993 40 29.1 29.5 30.3 29.7 29.6 56 28.6 27.8 27.8 26.4 26.1 71 28.8 29.7 30.3 30.2 30.0 ' 86 31.3 31.6 31.5 29.6 30.9 98 26.2 25.7 25.5 25.7 25.8 110 21.0 21.8 21.6 24.0 23.8
Ames 40 29.5 29.7 29.9 1992 56 34.9 33.5 32.4
71 31.5 31.0 30.4 86 28.7 28.2 26.7 98 23.4 23.4 24.4 110 25.3 24.6 24.1 120 21.7 23.6 24.5 130 22.1 21.2 22.4
1993 40 28.4 29.0 28.4 56 31.9 31.6 31.6 71 29.7 29.4 29.1 86 31.9 31.7 31.2 98 21.2 22.7 23.2 110 16.9 17.3 17.3
DAP - Days after planting
230
Table 7. Mean leaf tennperature (°C) under different water table depths for Ankeny and Ames sites in 1992 and 1993
Site DAP
Water table depth, m
Site DAP 0.2 0.3 0.6 0.9 1.1
Ankeny 40 28.4 30.3 29.7 29.9 29.0 1992 56 26.2 28.7 27.5 28.0 27.2
71 31.1 30.7 31.1 31.6 31.2 86 27.9 28.1 29.5 28.8 28.1 98 33.6 31.0 31.5 30.7 31.2 110 31.9 28.7 29.9 29.3 30.5 120 28.0 28.2 27.3 28.8 27.4 130 27.2 24.1 27.7 25.9 27.1
1993 40 29.2 29.6 30.4 29.8 29.7 56 28.1 27.3 27.2 26.0 25.8 71 29.0 29.6 30.1 29.9 30.1 86 31.7 31.8 31.7 29.9 31.3 98 26.7 26.0 25.8 26.0 26.2 110 21.8 22.3 21.9 24.3 24.3
Ames 40 29.3 29.5 29.7 1992 56 33.3 32.5 31.7
71 30.6 30.4 30.0 86 28.1 27.7 26.7 98 22.9 23.0 24.5 110 25.0 24.3 24.3 120 21.4 23.4 24.8 130 21.9 21.1 22.8
1993 40 28.5 29.1 28.5 56 31.1 31.0 31.4 71 29.1 29.2 29.2 86 31.5 31.3 31.7 98 21.2 22.4 23.9 110 17.2 17.8 17.8
DAP - Days after planting
231
Table 8. Mean leaf-air temperature differentials (°C) under different water table depths for Ankeny and Ames sites in 1992 and 1993
Water table depth, m
Site DAP 0.2 0.3 0.6 0.9 1.1
Ankeny 40 -0.6 -1.4 -0.7 -0.8 -0.8 1992 56 -0.6 -1.6 -1.0 -1.1 -0.6
71 -0.1 -0.6 -0.5 -0.5 -0.3 86 0.1 -0.4 -0.2 -0.2 -0.2 98 0.3 -0.3 -0.1 -0.1 0.3 110 0.4 0.2 0.1 0.3 0.2 120 0.4 0.2 0.2 0.1 0.3 130 0.6 0.3 -0.1 0.1 0.1
1993 • 40 0.1 0.1 0.1 0.1 0.1 56 -0.5 -0.5 -0.5 -0.5 -0.3 71 0.2 -0.2 -0.2 -0.3 0.2 86 0.4 0.2 0.2 0.2 0.4 98 0.5 0.3 0.3 0.3 0.4 110 0.8 0.5 0.4 0.3 0.5
Ames 40 -0.2 -0.2 -0.2 1992 56 -1.6 -1.0 -0.7
71 -0.9 -0.7 -0.5 86 -0.6 -0.5 -0.0 98 -0.5 -0.4 0.1 110 -0.4 -0.4 0.1 120 -0.3 -0.3 0.3 130 -0.2 -0.1 0.4
1993 40 0.1 0.1 0.0 56 -0.8 -0.7 -0.2 71 -0.6 -0.2 0.2 86 -0.5 -0.4 0.5 98 -0.0 -0.3 0.7 110 0.3 0.5 0.5
DAP - Days after planting
232
Table 9. Mean plant height (cm) under different water table depths for Ankeny and Ames sites in 1992 and 1993
Site DAP
Water table depth, m
Site DAP 0.2 0.3 0.6 0.9 1.1
Ankeny 40 69.7 67.5 60.9 58.1 50.0 1992 56 137.9 126.2 133.8 146.5 134.3
71 186.3 179.2 187.1 203.5 184.6 86 246.3 249.7 247.7 255.3 252.7 98 249.7 255.3 250.7 259.3 253.7 110 249.7 255.3 250.7 259.3 253.7 120 249.7 255.3 250.7 259.3 253.7 130 249.7 255.3 250.7 259.3 253.7
1993 40 90.1 105.8 100.5 86.5 103.8 56 133.8 160.6 152.4 127.0 144.2 71 154.9 198.1 186.5 165.4 168.9 86 210.0 248.6 230.5 222.2 217.8 98 217.8 249.6 234.7 222.8 218.8 110 217.8 249.6 234.7 222.8 218.8
Ames 40 57.9 59.1 56.1 1992 56 112.0 115.4 111.8
71 168.0 175.7 165.7 86 234.3 236.0 233.3 98 242.3 241.0 236.7 110 242.3 241.0 236.7 120 242.3 241.0 236.7 130 242.3 241.0 236.7
1993 40 101.1 104.4 99.6 56 154.9 153.8 137.7 71 205.1 205.2 179.8 86 240.4 239.8 216.1 98 247.3 245.2 225.2 110 247.3 245.2 225.2
DAP - Days after planting
233
Table 10. NO3-N concentrations (mg/L) In piezometer water samples for 1992 and 1993
Ames site Ankeny site
Sampling depth Sampling depth
Year DAP WTD, m 1.2m 1.8m 2.4m DAP WTD, m 1.2m 1.8m 2.4m
1992 39
55
81
113
141
169
1993 48
68
90
116
144
0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9
0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9
95.5 21.6 7.2 38 0.2 9.4 7.5 2.5 NS 41.2 19.2 0.6 11.7 9.9 7.0
212.0 125.7 54.8 1.1 23.8 16.9 8,5 18.1 3.9 6.2 54 0.2 10.3 5.9 3.7 19.5 7.7 19.3 0.6 10.5 6,0 4,9 27.5 25.4 19.5 1.1 16.4 6.7 6.3 2.2 2.1 1.9 82 0.2 4.7 4,4 2.0 3.8 2.9 1.1 0.6 11.3 7.8 4,0 9.8 7.9 5.3 1.1 12.0 6,7 4.5 8.6 2.2 1.4 112 0.2 2.1 1.9 1,6 8.6 4.2 2.6 0.6 4.1 3.6 3.5 11.1 6.6 4.5 1.1 6.9 5.2 4.7 1.4 0,4 2.6 140 0.2 2.7 3.1 2.0 1.9 2.5 2.1 0.6 NS NS NS 5.9 4.0 3.1 1.1 4.9 5.5 3.3 NS 5.9 6.2 168 0.2 1.6 1.6 4.5 NS 5.1 4.9 0.6 4.5 5.1 3.3 NS 5.6 4.5 1.1 NS NS NS
27.8 18.6 15.7 48 0.2 31.0 31.0 8.6 20.8 18.9 12.6 0.6 40.9 32.2 17,8 53.6 38.3 34.1 1.1 103.0 30.6 27.5 12.3 7.3 3.9 68 0.2 9.7 5.2 2.2 5.0 2.8 3.2 0.6 13.3 8.3 3.5 29.5 17.2 3.4 1.1 24.0 9.0 8.2 3.8 2.4 1.7 88 0.2 5.8 4.5 1.0 3.6 2.3 1.1 0.6 6,7 5.8 5.5 8.7 6.1 3.2 1.1 11.7 7.1 4.5 1.6 2.2 1.7 116 0.2 3.4 2.8 0.4 1.0 2.0 2.2 0.6 5.9 4.2 1.9 3.9 3.3 3.0 1.1 8.8 8.4 3.5 0.8 0.8 0.3 144 0.2 2.0 NS 1.3 2.6 1.0 0.6 0.6 2.7 3.1 0,1 8.7 2.1 1.8 1.1 6.6 3.0 1.4
DAP - days after planting; WTD - water table depth; NS - no water sample available for analysis
Table 11. NO3-N concentrations (mg/L) in suction tube samples for 1992 and 1993
Ames site Ankeny site
Suction tube depth Suction tube depth
DAP WTD, m 0.3 m 0.6 m 0.9 m 1.5 m 2.1 m DAP WTD, m 0.9 m 1.5 m 2.1 m
39 0.3 NS NS NS 0.0 14.3 38 0.3 6.4 6.4 3.9 0.6 NS NS NS 16.4 3.9 0.6 11.0 5.8 6.2 0.9 NS NS 120.9 4.1 5.3 0.9 10.5 7.3 7.1
55 0.3 30.3 22.0 22 .2 4.2 4.9 54 0.3 3.6 2.2 2.1 0.6 63.8 48.6 47.2 2.7 0.8 0.6 5.0 3.8 NS 0.9 115.3 108.0 92.8 14.3 3.7 0.9 6.8 2.6 1.9
81 0.3 9.1 6.7 3.5 3.3 0.8 82 0.3 2.6 2.6 2.4 0.6 11.8 10.0 10.8 2.3 1.8 0.6 6.4 3.4 2 .4 0.9 19.2 10.1 11.4 2.7 1.9 0.9 9.2 4.5 3.5
113 0.3 3.3 1.0 0.5 0.6 1.2 112 0.3 3.0 1.9 1.6 0.6 7.1 2 .6 1.9 1.7 1.7 0.6 4.4 3.3 1.8 0.9 7.1 4.6 4.3 0.7 0.8 0.9 4.6 4.1 2.7
141 0.3 3.2 1.4 NS 0.2 0.8 140 0.3 1.3 0.2 NS 0.6 5.1 1.2 2.3 3.4 2.1 0.6 NS NS NS 0.9 NS NS 4.0 3.4 1.5 0.9 5.3 1.9 0.1
169 0.3 NS NS NS 0.7 0.2 168 0.3 4.5 1.0 NS 0.6 6.7 NS 1.1 1.1 0.8 0.6 4.9 1.5 NS 0.9 10.4 NS 9.8 1.4 0.3 0.9 7.2 NS NS
48 0.3 16.0 5.1 4.7 1.4 0.8 48 0.3 19.6 3.3 0.9 0.6 21.6 17.5 10.1 2.5 1.6 0.6 49.9 4.2 1.2 0.9 67.1 95.5 40.9 1.0 3.2 0.9 50.0 11.5 1.5
68 0.3 3.6 3.5 3.2 1.3 1.0 68 0.3 2.5 1.5 1.4 0.6 5.1 3.7 4.0 2.8 1.6 0.6 2.8 1.6 1.5 0.9 7.2 6.6 6.2 3.3 3.2 0.9 3.5 2.6 2.1
90 0.3 3.2 1.4 1.8 1.6 0.3 88 0.3 0.5 0.4 0.6 0.6 4.5 1.9 1.3 1.5 0.7 0.6 2.6 1.7 1.6
1992
1993
Table 11 (continued)
116
144
0.9 0.3 0.6 0.9 0.3 0.6 0.9
6.8 1 . 8 5.0 5.1 1 .8 3.3 6.0
4.5 1.7 2.9 3.2 NS 3.1 3.5
2 . 1 1.4 1.1 2.4 1.2 1.4 2.3
2.8 1.1 0.7 1.5 0.5 0 .8 2 . 1
DAP - days after planting; WTD - water-table depth
0.4 0.1 0.5 1.6 0.4 0.8 2.0
116
144
0.9 0.3 0.6 0.9 0.3 0.6 0.9
3.7 3.3 4.7 5.9 1.3 1.5 6.3
3.4 1.7 2 . 1 2.5 0.9 2.2 2.4
2.5 0.4 1.0 2.1 0.3 2.1 2.6
M W Ol
Table 12. Atrazine concentrations i j j g /L ) in suction tube and piezometer water samples at the Ames site for 1992 and 1993
Suction tube water samples
Year
Sampling depth
Piezometer water samples
Sampling depth
DAP WTD. m 0.3m 0.6m 0.9m 1.5m 2.1m DAP WTD, m 1.2m 1.8m 2.4m
39 0.3 NS NS NS NS NS 39 0.3 1.8 7.2 0.4 0.6 NS NS NS 24.4 16.5 0.6 NS 9.7 8.6 0.9 NS NS NS 66.8 5.6 0.9 1.4 6.1 6.1
55 0.3 4.9 ND 8.7 18.2 2.9 55 0.3 ND 4.2 6.0 0.6 6.2 4.0 42.1 15.2 1.7 0.6 3.2 8.5 8.6 0.9 26.2 15.0 23.0 12.2 10.9 0.9. 18.3 33.9 14.5
81 0.3 5.5 7.1 11.2 6.3 3.7 81 0.3 3.9 2.1 2.4 0.6 7.9 25.0 10.0 4.8 3.1 0.6 5.2 3.4 4.1 0.9 6.3 26.0 12.4 7.6 3.2 0.9 7.2 5.0 4.4
113 0.3 1.1 ND 3.4 3.5 1.4 113 0.3 2.1 0.9 3.2 0.6 0.9 4.8 4.5 3.0 1.5 0.6 1.2 2.1 2.0 0.9 3.8 6.3 3.3 8.7 1.4 0.9 10.0 0.6 4.4
141 0.3 1.9 0.9 8.0 0.7 0.2 141 0.3 NS NS NS 0.6 NS NS NS 1.1 ND 0.6 NS 2.3 1.1 0.9 NS NS NS NS NS 0.9 5.4 1.3 3.9
169 0.3 NS NS NS NS 1.3 169 0.3 NS 1.2 3.3 0.6 2.4 3.2 0.9 1.1 NS 0.6 NS 1.4 2.8 0.9 NS NS NS 4.6 2.0 0.9 NS 4.5 2.4
48 0.3 19.1 2.8 26.0 9.1 12.2 48 0.3 1.0 0.7 1.5 0.6 20.9 17.5 21.4 8.1 5.6 0.6 1.8 1.2 22.5 0.9 19.9 31.8 60.3 14.8 10.9 0.9 0.8 128.8 626.1*
68 0.3 3.0 7031.8 18.5 4.5 7.2 68 0.3 1.7 1.5 2.9 0.6 4.8 13.6 20.1 2.2 6.0 0.6 7.0 3.3 11.7 0.9 9.8 13.5 33.3 18.7 9.0 0.9 8.0 29.8 20.1
1992
1993
Table 12 (continued)
90 0.3 3.3 NS 7.0 3.6 4.6 90 0.3 2.0 11.6 4.5 0.6 1.2 23.7 6.7 14.3 4.0 0.6 6.0 7.0 7.5 0.9 12.6 7.9 17.2 12.0 9.5 0.9 8.6 20.9 16.0
116 0.3 1.1 NS 2.9 3.9 2.5 116 0.3 5.2 5.7 3.2 0.6 0.9 18.2 8.3 13.1 2.8 0.6 6.5 7.8 5.1 0.9 7.8 17.8 4.3 9.6 3.0 0.9 8.4 14.9 8.9
144 0.3 NS NS NS 3.7 1.9 144 0.3 NS 2.7 NS 0.6 0.7 NS NS 7.8 2.8 0.6 NS 6.9 3.0 0.9 3.7 NS 11.0 7.5 2.6 0.9 NS 8.8 2.8
DAP - days after planting; WTD - water-table depth; NS - no water sample available for analysis; ND - non detectable level; * - outlier fo
w
238
Table 13. Atrazine concentrations (//g/L) Suction tube and piezometer water samples at the Ankeny site in 1992 and 1993
Suction tube water samples Piezometer water samples
Year DAP WTD,
Sampling depth
DAP WTD.
Sampling depth
Year DAP WTD, m 0.9m 1.5m 2.1m DAP WTD. m 1.2m 1.8m 2.4m
1992 38 0.3 114.6 22.7 0.1 38 0.2 1.5 8.8 1.6 0.6 14.4 5.1 6.3 0.6 7.5 2.6 1.4 0.9 36.2 14.0 9.8 1.1 NS NS 17.5
54 0.3 5.9 NS 1.6 54 0.2 10.1 3.2 1.1 0.6 NS 6.6 NS 0.6 13.6 19.9 0.5 0.9 NS NS 5.0 1.1 19.6 11.0 21.6
82 0.3 1.6 2.0 0.4 82 0.2 2.4 1.2 0.5 0.6 NS 1.1 1.7 0.6 6.5 6.2 0.3 0.9 2.3 0.1 2.6 1.1 7.5 1.5 5.8
112 0.3 0.5 0.8 0.2 112 0.2 0.6 0.6 NS 0.6 4.9 0.9 1.2 0.6 1.9 1.7 0.3 0.9 2.1 1.7 0.2 1.1 5.6 1.6 2.1
140 0.3 0.3 NS 0.6 140 0.2 0.5 0.5 0.2 0.6 NS NS NS 0.6 NS NS 0.2 0.9 NS NS NS 1.1 1.1 0.5 NS
168 0.3 0.2 NS NS 168 0.2 NS 0.5 0.2 0.6 NS NS NS 0.6 NS 1.7 0.2 0.9 NS NS NS 1.1 NS NS NS
1993 48 0.3 2.7 1.5 0.5 48 0.2 12.0 NS 2.9 0.6 4.5 0.6 10.2 0.6 2.9 1.5 5.8 0.9 36.4 3.4 1.4 1.1 10.9 21.7 5.4
68 0.3 2.5 1.1 0.8 68 0.2 2.8 8.5 4.7 0.6 5.2 NS 1.5 0.6 5.2 611.2 5.9 0.9 30.5 3.1 2.6 1.1 22.2 21.3 16.6
88 0.3 NS 0.9 0.4 88 0.2 1.8 5.7 3.6 0.6 NS 2.7 0.6 0.6 8.0 7.2 6.4 0.9 1.9 16.4 0.5 1.1 Ns 23.0 4.1
116 0.3 1.0 0.9 0.6 116 0.2 1.2 3.0 1.2 0.6 1.3 NS 0.7 0.6 1.7 7.1 6.7 0.9 2.3 2.6 0.8 1.1 11.5 11.2 1.9
144 0.3 0.7 0.7 0.3 144 0.2 NS 2.8 NS 0.6 NS NS 0.4 0.6 3.9 5.2 NS 0.9 NS 0.7 NS 1.1 NS 9.3 2.0
DAP - days after planting; WTD - water table depth; NS - no water sample available for analysis
239
Table 14. Raw data on different plant physiological parameters at Ames and Ankeny sites for 1992 and 1993
Data for Ames site during 1992
DAP WTD REP PHO COND CHL CI T-Air T-Leaf
40
56
71
86
Data for Ames site during 1992
98
0.3 0.3 0.3 0 . 6 0 . 6 0.6 0.9 0.9 0.9 0.3 0.3 0.3 0 . 6 0.6 0 . 6 0.9 0.9 0.9 0.3 0.3 0.3 0.6 0 . 6 0 . 6 0.9 0.9 0.9 0.3 0.3 0.3 0.6 0.6 0.6 0.9 0.9 0.9 0.3 0.3 0.3 0 . 6 0 . 6
1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2
29.7 30.1 29.1 31.4 26.7 27.6 34.2 25.2 30.3 26.5 32.0 31.1 27.8 23.9 33.6 27.6 31.2 31.3 39.1 37.3 39.1 34.6 32.5 36.7 26.2 32.3 35.6 47.8 47.8 47.4 37.4 39.3 42.8 39.4 31.9 33.8 39.3 40.8 42.8 28.5 34.1
0.44 0.38 0.27 0.46 0.31 0.39 0.32 0.41 0.21 0 .66 0.48 0.70 0.39 0 .62 0.66 0.46 0.49 0.57 0.60 0.67 0 . 8 0 0.71 0.58 0 .61 0.71 0.46 0.63 1.13 0 . 8 0 0.56 0.70 0.50 0.95 0 .62 0.51 0.84 0.73 0.67 0.65 0.76 0.69
46.9 38.4 39.7 40.4 43.8 46.2 41.9 43.2 44.6 48.9 44.6 47.9 44.6 46.1 49.5 44.4 43.7 48.0 54.3 55.2 54.9 54.5 50.2 50.9 47.9 46.0 45.8 57.9 56.1 59.0 53.6 54.5 53.9 46.1 48.3 53.0 56.2 55.0 55.7 51.7 55.5
249.0 234.7 236.3 237.1 254.9 225.4 257.7 276.3 271.0 367.4 254.7 377.4 249.4 270.5 289.1 403.3 326.0 294.1 296.5 317.9 295.4 323.7 316.3 302.6 300.3 314.6 316.9 366.0 356.1 347.7 339.4 338.1 340.6 341.9 364.6 344.2 306.2 326.1 216.5 213.6 314.2
29.4 29.5 29.6 29.9 29.8 29.4 29.7 29.7 30.2 36.3 35.5 34.7 34.3 33.3 32.8 33.8 32.7 30.7 29.6 30.4 31.3 31.3 31.1 30.7 30.9 31.4 32.1 25.7 27.5 27.8 28.3 28.4 27.2 29.0 29.3 27.7 24.8 24.3 24.1 23.3 23.4
29.0 28 .8 29.1 29.6 29.0 29.3 29.9 29.9 29.6 33.3 33.0 33.6 32.8 32.5 32.2 33.4 31.9 29.9 29.1 29.7 30.7 30.9 30.6 29.8 29.9 30.5 31.4 25.8 26.9 27.3 28 .1 27.3 27.8 27.9 2 8 . 2 27.2 24.5 23.8 23.7 23.0 22.9
240
Table 14. (continued)
0.6 3 27.3 0.63 50.6 199.2 23.9 23.0 0.9 1 31.2 0.76 41.9 153.7 23.5 23.4 0.9 2 27.8 0.55 47.2 232.2 23.5 23.1 0.9 3 27.3 0.68 55.2 218.2 23.1 22.6
110 0.3 1 25.2 0.46 53.5 276.3 24.8 24.8 0.3 2 23.7 0.54 53.5 276.1 24.4 24.1 0.3 3 26.6 0.34 51.2 289.5 23.5 23.1 0.6 1 24.6 0.61 51.2 259.8 24.3 24.2 0.6 2 25.6 0.43 52.1 264.5 25.2 24.6 0.6 3 26.2 0.30 50.0 271.1 24.5 24.0 0.9 1 21.6 0.34 39.3 230.7 25.0 25.0 0.9 2 24.0 0.55 45.1 243.5 25.7 25.5 0.9 3 21.0 0.33 50.2 223.1 25.3 24.4
120 0.3 1 7.8 0.30 49.5 308.4 21.0 20.5 0.3 2 11.8 0.33 48.0 276.4 21.7 21.2 0.3 3 19.0 0.39 44.5 285.6 22.5 22.4 0.6 1 14.8 0.35 47.4 274.6 23.8 23.4 0.6 2 15.8 0.39 47.5 288.0 23.9 23.6 0.6 3 15.1 0.23 42.8 280.9 23.3 23.1 0.9 1 17.4 0.27 39.2 252.2 24.3 24.9 0.9 2 16.9 0.28 42.2 279.9 24.7 24.9 0.9 3 20.0 0.30 43.1 292.4 24.9 24.5
130 0.3. 1 6.9 0.28 43.3 257.0 23.0 22.8 0.3 2 7.1 0.27 40.4 230.3 22.2 22.1 0.3 3 12.4 0.32 34.9 238.0 22.5 22.4 0.6 1 6.0 0.22 39.0 228.8 21.8 21.6 0.6 2 7.2 0.27 40.2 240.0 22.2 22.0 0.6 3 7.9 0.30 40.0 234.1 22.3 22.1 0.9 1 5.4 0.20 33.5 210.2 21.3 21.1 0.9 2 7.4 0.25 37.2 233.3 21.2 21.1 0.9 3 6.0 0.25 37.1 243.7 21.1 20.9
40
56
Data for Ames site during 1993
0.3 1 23.3 0.32 39.8 188.0 28.6 28.7 0 .3 2 20.3 0.42 42.8 211.0 29.0 29.1 0 .3 3 26.6 0.44 35.9 220.0 27.6 27.7 0 .6 1 21.9 0.51 40.2 209.6 29.0 29.2 0 ,6 2 25.7 0.34 41.7 195.5 29.2 29.2 0, .6 3 23.9 0.38 42.2 215.1 28.8 28.9 0, ,9 1 23.6 0.41 36.2 211.0 28.6 28,7 0, ,9 2 21.8 0.35 36.5 225.9 28.4 28.5 0, ,9 3 23.9 0.46 40.6 162.8 28.2 28.2 0, 3 1 30.9 0.64 42.6 215.7 32.4 31.8 0, 3 2 27.6 0.51 47.3 224.1 31.7 30.8 0. 3 3 31.7 0.55 44.5 231.8 31.5 30.8 0. 6 1 35.3 0.47 41.9 216.6 31.8 30.8 0. 6 2 27.0 0.57 44.8 230.7 31.5 31.1
241
Table 14. (continued)
47.2 214.9 31.6 31.0 37.4 220.0 31.7 31.4 35.3 213.9 31.1 30.9 44.0 224.8 32.0 31.8
71 0.3 1 35.3 0.66 49.5 273.6 29.4 28.8 52.7 292.5 29.9 29.2 50.6 284.4 29.8 29.2 49.6 273.9 29.5 29.4 46.6 279.4 29.4 29.4 51.6 278.7 29.3 28.9 41.9 267.5 29.7 29.7 41.1 278.5 28.9 29.0 44.9 262.0 28.7 29.0
86 0.3 1 41.2 0.95 52.9 309.2 31.8 31.2 54.2 284.4 31.6 31.0 53.0 252.6 32.4 32.3 45.3 289.0 31.7 31.9 51.1 276.6 31.5 30.9 54.0 268.7 31.9 31.2 38.4 283.8 31.6 31.8 38.4 285.5 31.1 31.7 43.6 269.6 30.9 31,6
98 0,3 1 24.2 0.59 49.5 227.9 20.8 21.0 48.1 248.0 21.7 21.8 43.4 204.1 21.2 20.9 36.2 213.8 22.9 22.6 39,2 223.0 22.8 22.7 47.6 222.6 22.3 21.9 33.2 221.3 23,3 24.0 40.3 226.3 23.2 23.8 38.3 207.9 23.1 23.9
110 0.3 1 9.9 0.51 42.4 200.4 16.5 16.8 41.4 198.4 16.5 17.0 40.1 207.8 17.7 17.7 36.2 195.3 17.5 17.8 35.8 207.0 17.6 17.8 41.0 193.2 16.9 17.7 31.2 198.3 17.9 18.4 36.9 209.1 17.0 17.5 35.0 206.2 17.1 17.5
40
0.6 3 29.9 0.53 0.9 1 25.9 0.52 0.9 2 25.8 0.45 0.9 3 31.7 0.38 0,3 1 35.3 0.66 0.3 2 33.8 0.63 0.3 3 37.8 0.87 0.6 1 32.7 0.76 0.6 2 31,3 0.86 0.6 3 29.9 0.61 0.9 1 26.6 0.59 0.9 2 28.8 0.70 0.9 3 33.1 0.70 0.3 1 41.2 0.95 0.3 2 35.8 0.87 0.3 3 40.1 1.37 0.6 1 35.9 1.03 0.6 2 32.0 0.84 0.6 3 35.8 1.03 0.9 1 29.1 0.73 0,9 2 30.1 0,81 0.9 3 31.5 0,83 0,3 1 24.2 0.59 0,3 2 24.0 0.59 0.3 3 22.4 0.63 0.6 1 20.7 0.49 0.6 2 22.1 0.51 0.6 3 25.7 0.60 0.9 1 21.3 0.45 0.9 2 22.8 0.65 0.9 3 28.1 0,56 0.3 1 9.9 0,51 0.3 2 15.7 0,48 0.3 3 10.8 0.34 0.6 1 8.9 0,39 0.6 2 14.0 0.47 0.6 3 12.9 0,41 0.9 1 6.7 0,34 0.9 2 8.7 0,33 0.9 3 14.7 0,38
Data for Ankeny site during 1992
0.2 1 30.3 0.29 43.4 201.7 29.3 28.6 0.2 2 29.5 0.37 44.0 196.7 29.1 28.4 0.2 3 29.7 0.34 40.8 214.1 28.7 28.2 0.3 1 28.9 0,30 41.2 191.5 32.6 31.3 0.3 2 31.5 0.40 42.0 181.6 31.6 30.0
242
Table 14. (continued)
0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2
28.6 0.27 26.0 0.34 29.3 0.23 28.6 0.30 28.8 0.37 32.0 0.35 25.0 0.28 25.6 0.29 31.7 0.24 27.4 0.25 31.0 0.46 31.2 0.59 31.9 0.46 35.1 0.64 37.4 0.72 33.6 0.66 30.8 0.57 32.2 0.71 31.6 0.58 31.6 0.61 33.1 0.47 31.1 0.48 30.0 0.55 28.2 0.49 32.9 0.35 32.7 0.69 34.2 0.54 32.4 0.50 43.8 0.80 43.5 0.89 46.8 0.78 47.4 0.69 40.7 0.64 40.3 0.83 32.7 0.74 43.9 0.73 38.3 0.48 37.7 0.44 36.8 0.60 28.4 0.76 41.5 0.48 35.5 0.55 36.9 0.76 52.7 1.10 48.7 0.74 54.5 0.96 44.1 0.94 51.4 0.67
47.8 188.6 43.2 206.9 44.0 217.1 43.0 218.2 41.6 199.9 43.8 200.1 44.3 219.2 42.4 202.7 41.3 216.2 42.0 205.1 47.8 196.0 46.2 218.2 35.8 219.9 52.0 224.7 48.8 230.4 49.9 229.8 49.2 220.1 52.2 228.3 49.1 226.2 50.8 223.5 50.7 220.0 44.7 216.5 47.7 207.7 45.9 212.0 45.1 223.7 47.8 235.4 48.0 261.7 49.7 241.3 55.5 255.1 51.3 274.0 54.3 268.2 49.6 263.9 52.7 232.2 52.0 262.3 50.8 258.0 50.8 237.9 50.0 234.2 50.2 226.5 51.1 250.4 47.7 236.3 52.0 233.8 48.5 263.0 52.3 231.6 55.0 245.5 55.1 253.8 55.8 265.6 56.2 258.9 53.7 247.7
31.2 29.7 30.7 29.9 30.3 29.6 30.2 29.5 30.7 30.1 30.6 29.5 30.9 30.2 29.9 29.2 29.7 28.6 29.9 29.2 27.3 26.4 26 .8 26 .1 26.3 26.0 31.0 29.4 30.1 28.4 29.8 28.3 28.8 27.8 28.5 27.4 28.4 27.5 28.8 27.9 29.1 27.7 29.5 28.4 27.8 27.1 27.7 27.3 28.0 27.1 31.1 31.0 31.3 31.1 31.1 31.0 31.8 31.0 31.4 30.9 31.0 30.2 31.2 30.9 31.4 31.0 31.9 31.3 32.3 31.8 32.3 31.6 31.7 31.2 31.8 31.5 31.7 31.2 31.1 31.0 28.4 28.4 28.0 28.1 27.2 27.3 28.8 28.3 28.6 28.2 28.3 27.9 29.8 29.4 29.9 29.6
Table 14. (continued)
0.6 3 46.8 0. 0.9 1 43.9 0. 0.9 2 39.1 0. 0.9 3 45.9 0. 1.1 1 38.0 0. 1.1 2 40.4 0. 1.1 3 40.6 0. 0.2 1 34.4 0. 0.2 2 38.4 0. 0.2 3 40.1 0. 0.3 1 41.9 0. 0.3 2 40.1 0. 0.3 3 36.0 0. 0.6 1 35.4 0. 0.6 2 37.0 0. 0.6 3 38.3 0. 0.9 1 33.3 0. 0.9 2 35.7 0. 0.9 3 36.4 0. 1.1 1 34.6 0. 1.1 2 35.1 0. 1.1 3 33.6 0. 0.2 1 28.5 0. 0.2 2 34.4 0. 0.2 3 30.8 0. 0.3 1 39.0 0. 0.3 2 25.2 0. 0.3 3 27.3 0. 0.6 1 27.7 0. 0.6 2 31.2 0. 0.6 3 35.4 0. 0.9 1 34.5 0. 0.9 2 29.7 0. 0.9 3 31.6 0. 1.1 1 28.4 0. 1.1 2 35.6 0. 1.1 3 30.6 0. 0.2 1 21.6 0. 0.2 2 19.5 0. 0.2 3 29.2 0. 0.3 1 23.5 0. 0.3 2 24.8 0. 0.3 3 19.7 0. 0.6 1 22.5 0. 0.6 2 22.6 0. 0.6 3 21.3 0. 0.9 1 18.6 0. 0.9 2 23.0 0.
51.5 242.7 29.2 29.4 54.9 249.0 28.8 29.0 52.3 237.0 28.9 28.5 50.3 227.9 29.4 28.9 49.1 242.0 28.3 28.2 52.0 236.3 28.4 28,2 49.8 221.1 28.2 27.9 46.6 205.9 32.3 32.6 46.2 229.1 33.4 33.5 47.2 229.6 34.1 34.6 54.0 227.2 30.8 30.4 53.0 253.9 31.4 31.1 53.6 258.1 31.6 31.5 50.3 258.3 31.5 31.3 49.0 266.1 31.6 31.4 51.8 208.6 31.7 31.7 50.2 226.0 30.9 30.8 50.3 252.7 30.6 30.4 51.8 236.4 31.G 31.0 49.4 237.3 31.0 31.2 43.8 221.6 30.9 31.3 43.9 228.7 30.9 31.1 41.4 162.2 31.0 31.4 40.7 145.2 31.7 31.9 37.0 249.9 31.7 32.3 48.5 209.8 27.7 27.8 46.2 256.2 29.1 29.2 45.6 216.5 28.6 29.1 45.8 219.2 29.2 29.3 44.0 201.6 30.3 30.5 43.0 214.2 29.9 30.0 43.6 203.6 29.1 29.3 43.9 201.0 28.9 29.0 41.1 218.4 28.8 29.4 42.3 211.5 30.8 31.0 40.8 216.7 29.9 30.0 34.8 193.4 30.1 30.4 38.3 208.6 27.2 27.6 35.9 200.7 27.5 28.0 34.4 218.0 27.9 28.3 38.8 206.1 27.9 28.0 35.3 281.7 27.9 28.1 36.5 207.6 28.1 28.4 36.6 220.3 27.4 27.6 35.2 214.9 26.8 27.1 34.4 230.5 27.1 27.2 34.9 216.1 28.5 28.5 35.1 231.3 28.5 28.6
68 57 86 68 46 63 80 69 61 55 78 75 70 74 62 77 64 63 72 62 67 60 30 20 90 59 71 67 72 54 63 64 58 61 66 56 46 47 46 42 52 48 41 56 39 42 47 43
244
Table 14. (continued)
0.9 3 20.0 0.46 32.9 222.8 28.9 29.1 130 1.1 1 17.3 0.47 33.9 231.7 27.3 27.6
1.1 2 17.9 0.47 32.6 229.3 27.3 27.4 1.1 3 18.6 0.33 34.5 215.9 26.9 27.3 0.2 1 8.8 0.44 37.9 208.4 27.2 28.2 0.2 2 23.4 0.45 35.5 213.5 26.0 26.'3 0.2 3 15.5 0.35 34.1 196.7 26.7 27.3 0.3 1 18.1 0.33 38.4 211.1 22.5 22.9 0.3 2 26.6 0.41 34.9 195.5 23.9 24.1 0.3 3 18.9 0.36 36.1 206.4 24.5 24.7 0.6 1 16.0 0.45 36.2 200.7 30.4 30.5 0.6 2 23.3 0.45 34.9 202.6 26.6 26.6 0.6 3 15.6 0.40 34.0 214.0 26.4 26.0 0.9 1 18.1 0.48 34.5 191.8 26.8 27.1 0.9 2 15.9 0.41 34.7 214.8 25.4 25.5 0.9 3 16.3 0.45 32.6 212.3 25.1 25.2 1.1 1 19.0 0.35 33.5 206.3 27.5 27.7 1.1 2 13.2 0.45 32.3 205.9 27.1 27.0 1.1 3 14.2 0.41 34.2 202.5 26.5 26.6
Data for Ankeny site during 1993
40 0.2 1 21.7 0.59 39.3 229.8 29.2 29.3 0.2 2 21.6 0.57 42.7 215.8 28.9 29.0 0.2 3 22.5 0.47 41.6 228.2 29.2 29.3 0.3 1 24.4 0.51 42.1 266.0 29.2 29.4 0.3 2 26.9 0.63 41.3 259.0 29.6 29.8 0.3 3 19.7 0.48 41.9 247.4 29.6 29.7 0.6 1 21.7 0.47 43.2 226.2 30.4 30.5 0.6 2 29.2 0.66 42.3 243.7 30.6 30.6 0.6 3 21.9 0.44 37.0 223.1 29.9 29.9 0.9 1 26.2 0.61 41.0 245.7 29.4 29.5 0.9 2 23.3 0.57 41.3 211.2 29.7 29.7 0.9 3 23.3 0.60 42.2 246.7 30.2 30.3 1.1 1 20.3 0.54 40.4 228.5 29.6 29.8 1.1 2 19.7 0.51 41.0 225.9 29.6 29.7 1.1 3 23.3 0.48 42.0 241.7 29.7 29.7
56 0.2 1 19.2 0.70 42.4 227.3 28.3 27.8 0.2 2 20.7 0.63 43.1 224.6 28.4 27.9 0.2 3 22.8 0.57 41.7 212.1 29.0 28.6 0.3 1 32.1 0.67 45.2 232.7 28.2 27.9 0.3 2 29.6 0.77 45.5 247.8 27.6 27.2 0.3 3 28.1 0.68 47.5 236.2 27.5 26.9 0.6 1 30.1 0.56 45.6 197.8 27.4 26.9 0.6 2 31.4 0.81 44.0 273.3 27.8 27.2 0.6 3 24.2 0.53 43.1 215.5 28.0 27.6 0.9 1 22.7 0.66 46.3 227.7 26.9 26.4 0.9 2 21.5 0.82 42.4 213.7 26.4 25.9
245
Table 14. (continued)
0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2
21.9 0.67 17.6 0.59 23.1 0.62 26.2 0.64 21.9 0.79 21.9 0.68 24.1 0.62 30.6 0.84 34.7 0.83 31.0 0.88 27.1 0.84 34.0 0.76 29.3 0.73 28.7 0.81 32.6 0.71 28.2 0.77 22.6 0.60 21.1 0.56 27.4 0.79 33.3 0.55 33.4 0.77 35.2 0.84 42.3 1.57 43.8 0.54 39.9 0.68 41.4 0.74 37.6 0.77 42.8 0.65 40.1 0.77 36.5 0.85 39.3 0.75 31.7 0.70 31.8 0.73 43.1 0.70 23.5 0.43 30.0 0.39 26.7 0.47 28.7 0.63 34.3 0.38 29.0 0.37 30.1 0.44 30.8 0.46 27.2 0.36 29.0 0.42 28.9 0.49 27.7 0.43 25.5 0.41 27.9 0.38
43.3 219.1 44.5 222.0 43.0 230.4 42.7 231.9 36.3 228.4 40.9 216.1 41.1 230.0 47.8 266.3 49.7 259.2 45.6 247.5 50.0 269.3 49.0 244.4 41.2 222.8 44.3 246.0 44.2 211.6 42.5 247.0 41.0 228.6 42.0 225.9 44.0 241.7 41.0 235.6 42.9 237.5 46.3 231.3 51.6 262.9 51.6 274.8 51.5 254.3 52.4 289.6 55.0 225.6 46.2 283.2 50.2 269.4 51.7 267.7 50.9 242.2 45.2 241.6 39.5 240.9 49.8 231.8 36.7 220.7 39.0 160.6 40.7 260.1 53.0 223.7 53.2 203.8 49.4 230.1 51.7 221.7 51.6 178.1 42.9 217.4 50.4 249.0 52.0 208.7 52.6 208.1 41.8 217.6 38.8 223.0
26.1 25.7 25.9 25.7 26.2 25.8 26.1 25.8 28.6 28.9 28.8 28.9 29.0 29.3 29.7 29.4 29.8 29.6 29.8 29.7 30.3 30.1 30.8 30.5 29.9 29.7 29.9 29.7 30.0 29.7 30.6 30.3 29.9 30.1 29.9 30.0 30.0 30.2 31.3 31.7 31.2 31.7 31.4 31.7 32.1 32.4 30.7 30.8 32.0 32.3 31.1 31.3 31.4 31.6 31.9 32.2 29.2 29.4 29.5 29.8 30.2 30.4 31.1 31.5 30.9 31.3 30.7 31.1 24.9 25.5 25.5 25.9 28 .1 28 .6 25.3 25.6 25.9 26.3 25.8 26.1 25.8 26.1 25.3 25.6 25.5 25.7 25.4 25.7 2 6 . 0 2 6 . 2 25.8 26.1 25.8 26.3 26.0 26.4
246
Table 14. (continued)
1.1 3 22.9 0.34 47.9 195.8 25.5 25.9 110 0.2 1 15.9 0.34 32.4 172.3 20.8 21.4
0.2 2 14.5 0.28 31.0 180.1 21.0 22.1 0.2 3 17.1 0.37 27.4 189.6 21.1 21.9 0.3 1 15.9 0.33 47.2 192.5 21.6 21.6 0.3 2 20.2 0.28 44.3 179.0 22.0 22 .8 0.3 3 18.9 0.31 45.7 217.2 21.7 22.5 0.6 1 18.5 0.33 48.2 210.9 22.7 23.0 0.6 2 22.0 0.33 43.7 156.6 20.9 21 .3 0.6 3 19.2 0.27 31.9 203.1 21.1 21.5 0.9 1 17.4 0.34 41.1 189.8 23.0 23.4 0.9 2 20.0 0.34 40.5 174.7 24 .7 25.0 0.9 3 15.3 0.30 44.2 178.3 24.2 24.5 1.1 1 16.8 0.30 34.2 204.3 24.0 24.6 1.1 2 16.1 0.29 29.0 160.7 23 .3 23.8 1.1 3 15.9 0.27 36.4 159.1 24.0 24.6
DAP - days after planting; WTD - water table depth; REP -replications; PHO - photosynthesis; COND - stomatal conductance; CHL - chlorophyll; CI - intercellular carbon dioxide; T-Air -crop canopy air temperature; T-Leaf - leaf temperature
247
Table 15. NO3-N concentrations (mg/L) in suction tube and piezometer water samples at Ames and Ankeny site for 1992 and 1993
Suction tube depth Piezometer depth
DAP WTD REP 0.3 0.6 0.9 1.5 2.1 WTD 1.2 1.8 2.4 m m m m m m m m m m
Data for Ames site during 1992
4.1 6.4 0.9 NS 40.3 10.2 NS 5.1 212.6 165.2 61.7 NS 4.4 NS 171.4 92.4 5.3 6.0 0.6 NS 22.1 0.2 17.3 4.2 NS 53.5 14.5 26.6 1.5 NS 48.0 43.0 NS NS 0.3 113.9 Ns 6.2 NS 14.3 77.2 21.6 9.1 NS NS NS NS 6.2
55 0.9 1 NS 219.1 38.4 4.1 3.5 0.9 22.7 14.1 11.1 2.2 2.6 34.0 27.3 23.5 36.7 5.1 26.0 34.7 24.0 2.4 1.4 0.6 21.9 4.7 18.0 7.8 3.0 34.7 4.9 19.7 •2.4 0.4 2.0 13.4 20.2 0.2 0.0 0.3 5.6 5.3 4.8 0.5 1.4 35.0 4.5 9.6 7.5 0.8 13.7 1.8 4.2
81 0.9 1 0.8 19.7 2.0 4.5 3.1 0.9 7.4 8.8 3.1 3.2 1.6 12.5 7.9 3.1 0.3 1.0 9.5 6.9 9.7 0.5 4.2 0.6 1.6 1.5 2.3 5.0 0.7 9.3 6.2 0.1 1.3 0.6 0.6 1.0 0.8 0.4 0.4 0.3 0.1 0.8 0.2 2.1 0.0 6.2 1.6 2.6 7.5 2.0 0.3 3.9 2.8
113 0.9 1 2.2 5.0 4.3 0.6 0.8 0.9 ND 6.7 4.2 NS NS 18.3 8.5 4.5 0.9 NS 4.0 4.7 5.0 0.8 1.7 0.6 1.9 2.5 3.9 3.2 NS 17.5 6.6 2.9 0.9 NS 6.3 3.6 1.0 0.0 1.5 0.3 9.0 3.3 0.5 0.2 2.0 11.9 2.4 2.9 1.0 0.2 5.0 1.1 0.9 4.3 1.0 0,9 5.7 5.0 4.0 3.2 1.2 8.0 4.5 2.7 2.8 2.4 3.9 2.5 2.7 0.5 3.7 0.6 3.5 2.0 1.7
0,9 1 NS NS 123,2 2 NS NS 118,6 3 NS NS NS
0.6 1 NS NS NS 2 NS NS NS 3 NS NS NS
0.3 1 NS NS NS 2 NS NS NS 3 NS NS NS
0.9 1 NS 219.1 38.4 2 NS 68,9 NS 3 115.3 36,0 147.3
0.6 1 17.0 0.7 ND 2 70.5 61.8 48.9 3 3.6 3.4 17.6
0.3 1 117.1 48.2 52.6 2 50.4 NS 35.1 3 23.9 48.9 54.0
0.9 1 0.8 19.7 2.0 2 17.1 7,1 18.6 3 39.6 3,4 13.6
0.6 1 0.0 1,1 2.3 2 28.6 19,4 25.8 3 6.6 9,5 4.3
0.3 1 3.9 5.4 1.2 2 0.8 9.0 0.6 3 22.7 5.9 8,8
0.9 1 2.2 5.0 4,3 2 0.6 3.8 NS 3 18.4 4.9 NS
0.6 1 0.9 4.3 NS 2 14.9 3.1 1,0 3 5.7 0.4 2,7
0.3 1 0.2 NS 0,9 2 8.6 1.7 NS 3 1.1 0,3 0,1
0,9 1 NS NS 1,7 2 NS NS 0,5 3 NS NS 9.9
0,6 1 ND 0,5 NS
248
Table 15. (continued)
2 7.5 1.7 3.8 1.9 2.3 1.7 1.6 4.6 3 2.7 1.3 0.7 7.9 0.4 0.4 3.9 0.2
0.3 1 0.6 1.3 NS 0.2 0.9 0.3 NS 0.3 0.9 2 3.2 1.2 NS ND 0.7 1.4 0.5 4.3 3 5.8 1.9 ND ND ND ND 0.3 2.5
0.9 1 10.5 NS 10.4 1.4 0.3 0.9 NS 6.1 3.4 2 NS NS 9.2 0.3 0.2 NS 7.5 5.0 3 NS NS NS 2.5 0.3 NS 3.2 5.1
0.6 1 2.8 NS NS NS NS 0.6 NS 3.0 2.5 2 10.7 NS 1.0 2.1 1.2 NS 7.0 5.2 3 NS NS 1.2 0.1 0.4 NS 5.2 7.0
0.3 1 NS NS NS NS 0.1 0.3 NS 0.8 0.3 2 NS NS NS NS 0.3 NS 11.5 4.3 3 NS NS NS 0.7 NS NS 5.3 8.1
Data for Ames site during 1992
48 0.9 1 63.6 92.6 7.8 1.5 4.5 0.9 12.0 17.0 5.9
68
90
2 93.9 109.6 109.8 1.6 1.2 3 43.9 84.3 5.0 0.1 4.0
114.1 14.6 5.0 34.9 83.4 91.2
0.6 1 42.4 34.0 5.4 0.8 3.5 0.6 16.2 4.1 3.5 2 0.9 18.3 13.4 3.3 0.7 20.4 20.9 0.2
3.5 0.7 25.7 35.0 34.1 1.1 0.0 0.3 11.7 7.1 27.2 3.1 1.5 36.8 3.9 8.1 0.2 0.7 35.0 45.6 7.9 1.4 5.4 0.9 8.8 6.9 4.4 4.9 1.8 63.4 9.1 3.4 3.8 2.4 16.4 35.7 2.4 1.1 1.9 0.6 2.4 3,1 4.8 3.2 1.7 4.6 2.6 4.3 4.1 1.1 8.0 2.6 0.5 1.1 0.6 0.3 4.2 14.7 2.5 2.4 0.6 18.1 3.5 1.3 0.3 1.7 14.7 3.7 7.9 5.0 NS 0.9 6.5 6.4 3.8 1.4 NS 14.6 2.1 1.8 1.9 0.4 5.0 9.6 4.2 1.3 0.2 0.6 3.5 2.2 1.2 1.5 0.2 1.7 2.5 1.1 2.1 0.6 5.5 2.3 1.1 1.2 0.0 0.3 0.6 4.8 2.2 1.9 0.3 4.6 0.9 1.0 NS 1.7 6.1 1.5 1.8 2.3 0.3 0.9 3.5 4.0 2.8 0.8 2.4 3.5 1.2 3.5 2.2 2.2 4.9 4.6 3.3 0.7 0.0 0.6 1.0 1.9 2.3
3 NS 0.2 11.5 0.3 1 7.2 2.8 7.6
2 30.7 5.3 5.5 3 10.0 7.2 1.0
0.9 1 7.5 9.7 3.8 2 7.2 4.3 5.5 3 6.8 5.8 9.4
0.6 1 2.0 2.7 1.9 2 4.2 4.2 5.5 3 9.1 4.2 4.7
0.3 1 3.6 6.3 3.8 2 3.7 2.5 2.5 3 3.5 1.5 3.2
0.9 1 4.1 2.5 0.9 2 9.5 6.0 3.4 3 NS 5.0 2.0
0.6 1 0.7 1.4 2.1 2 1.8 1.2 1.8 3 7.1 1.6 1.4
0.3 1 3.2 3.2 1.8 2 4.1 1.5 0.5 3 6.2 0.9 1.4
0.9 1 NS NS 4.2 2 5.1 5.7 1.3 3 NS 0.7 1.6
0.6 1 4.6 2.1 NS
Table 15. (continued)
249
54
82
2 4.8 2.2 2.1 0.4 0.2 2.3 3.3 3 5.5 4.3 1.1 1.1 1.4 1.1 1.9 0.9
0 .3 1 2.4 0.7 1.0 1.4 0.1 0.3 1.0 4.0 3.1 2 2.1 1.5 1.6 1.9 0.1 1.2 1.6 0.3 3 0.9 2.8 1.6 ND NS 2.6 0.9 1.9
0 .9 1 NS NS NS 3.7 0.7 0.9 19.5 2.5 • 0.7 2 10.1 5.6 1.1 1.2 1.9 3.1 1.7 3.3 3 2.0 1.4 3.6 1.3 3.5 3.5 NS 1.4
0, ,6 1 NS NS 0.7 0.5 0.7 0.6 NS 0.9 0.6 2 0.2 NS 1.8 1.2 0.8 2.8 1.4 0.2 3 6.4 3,1 1.8 0.6 NS NS 0.8 1.0
0, 3 1 1.0 NS 1.5 NS 0.1 0.3 0.8 0.6 0.5 2 1.6 NS 2.0 NS 0.5 NS 0.5 0.2 3 2.7 NS ND 0.5 0.8 NS 1.3 0.1
38
112 0
Data for Ankeny site during 1992
0.9 1 0.0 NS NS 1.1 34.5 8.6 3.6 2 7.7 1.0 6.7 NS 7.6 1.5 3 13.2 7.3 7.5 13.1 6.4 NS
0.6 1 3.7 6.2 NS 0.6 19.5 13.8 12.6 2 4.6 5.5 4.5 5.8 6.7 7.0 3 24.6 5.8 7.9 9.6 9.1 5.9
0.3 1 11.8 10.2 6.0 0.2 7.5 NS 2.6 2 0.9 2.5 1.8 7.5 5.4 3.2 3 NS NS ND 13.1 28.5 15.3
0.9 1 0.0 2.6 ND 1.1 8.4 11.0 3.5 2 6.7 NS 1.9 7.2 5.3 3.5 3 6.9 NS 0.2 15.2 1.4 4.2
0.6 1 3.8 3.1 NS 0.6 8.6 7.5 4.8 2 5.0 3.1 NS 12.4 5.9 5.3 3 6.3 5.3 NS NS 4.6 4.6
0.3 1 3.8 ND 0.6 0.2 19.2 1.9 11.0 2 1.2 0.4 2.0 13.6 6.2 1.1 3 5.9 2.2 2.2 159.5 12.0 6.9
0.9 1 7.5 1.2 0.5 1.1 10.4 2.3 2.8 2 10.9 5.6 3.5 2.1 4.1 0.8 3 0.1 6.7 0.1 23.5 13.7 2.5
0.6 1 4.4 3.9 1.7 10.1 9.7 1.3 2 8.6 2.4 2.4 0.6 14.8 7.1 3.8 3 6.1 3.9 3.2 9.0 6.7 6.9
0.3 1 2.5 1.9 ND 5.5 5.9 4.5 2 1.6 0.9 0.4 0.2 4.5 3.2 5.2 3 3.7 5.0 4.3 4.0 4.1 3.7
0.9 1 NS ND 3.6 1.1 8.3 5.1 0.6 2 4.1 NS 2.1 7.5 3.7 6.8 3 5.0 4.1 2.3 4.9 6.7 6.7
250
Table 15. (continued)
0 .6 1 1.0 3.5 0.0 0.6 4.4 3.6 1.4 2 6.1 2.5 1.8 4.9 3.7 4.0 3 6.0 4.0 ND 3.1 3.6 5.0
0.3 1 4.2 1.0 ND 0.2 0.8 0.9 3.0 2 1.7 1.2 1.5 3.0 0.7 1.0 3 0.3 3 .5 1.7 2.4 4.0 • 1.0
140 0.9 1 5.4 0.4 0.1 1.1 6.8 6.7 0.6 2 4.9 3.4 NS 5 .9 5.3 3.4 3 5.6 NS NS 2.1 4.4 5.9
0.6 1 NS NS NS 0.6 NS NS NS 2 NS NS NS NS NS NS 3 NS NS NS NS NS NS
0.3 1 1.3 0 .2 ND 0.2 2.0 1.8 NS 2 NS NS NS NS 3.2 0.9 3 NS NS NS 2.1 4.5 4.5
168 0.9 1 3.2 ND NS 1.1 NS NS NS 2 11.2 0.9 NS NS NS NS 3 7.1 1.1 NS NS NS NS
0.6 1 1.4 1.6 NS 0.6 6.0 5.8 0 .6 2 8.5 1.4 NS 4.0 4.8 3.4 3 0.6 0.3 NS 3 .4 4.6 6.0
0.3 1 4.7 ND NS 0.2 1.6 0.8 7 .2 2 4.5 NS NS NS 1.9 3.3 3 4.5 ND NS NS 2.0 3.1
Data for Ankeny site during 1993
48 0.9 1 35.7 1.2 0.6 1.1 90 .0 36.9 9 .3 2 35.7 29.6 2.2 61.2 38.6 7.4 3 78.7 3.9 0.8 157.7 16.2 9 .2
0.6 1 43.8 4.7 0.6 0.6 11.9 42 .9 16.8 2 39.4 3.9 0.3 50.3 36 .6 35.9
0.3 1 22 .5 7.0 1.1 0.2 4.7 22 .9 5.4 2 22 .7 2.0 0.8 44.7 36 .2 NS 3 13.7 0.9 ND 17.3 34.0 49.6
68 0.9 1 NS 0.2 1.9 1.1 42 .3 1.6 13.6 2 5 .0 5 .8 2 .2 23 .5 19.5 6.0 3 5.4 1.8 ND 6.3 5.8 5.1
0.6 1 NS 1.8 1.5 0.6 13.2 11.4 8 .2 2 2.4 2.0 1.5 13.2 5.2 0.5 3 6.0 0.1 ND 13.4 1.8 2.0
0.3 1 0.0 0.5 0.4 0.2 9.1 7.5 0.7 2 4.5 2.5 0.5 1.3 3.0 4.2 3 0.5 ND 3.4 18.8 4.9 1.8
88 0.9 1 NS ND 2.3 1.1 3.5 2.2 10.3 2 1.0 8.6 2.6 14 .2 11.2 2 .5 3 66.4 3.9 3 .6 60.6 17.0 0.8
251
Table 15. (continued)
3 6.5 1.6 0.4 17.5 7.8 0.7 0.6 1 3.7 1.0 1.0 8.8 8.1 NS
2 1.0 3.4 3.8 0.6 4.7 5.5 2.8 3 3.2 0.7 0.1 0.4 3.7 8.2
0.3 1 1.0 NS ND 5.7 9.5 1.7 2 0.2 ND 0.5 0.2 5.9 2.8 • 1.2 3 0.4 0.4 0.7 0.1 1.4 0.2
116 0.9 1 3.2 0.4 2.3 1.1 1.3 2.5 2.0 2 6.0 6.0 1.2 14.2 8.5 1.5 3 8.4 1.2 2.7 11.1 14.3 6.9
0.6 1 0.7 1.8 0.8 0.6 10.3 7.7 NS 2 1.8 NS 2.1 4.2 2.0 2.8 3 11.7 2.4 0.1 3.3 3.1 1.0
0.3 1 1.8 NS 0.2 0.2 3.6 2.4 NS 2 7.3 3.5 0.3 5.3 2.5 NS 3 0.8 ND 0.7 1.4 3.5 0.4
144 0.9 1 NS 0.1 3.8 1.1 1.6 1.7 0.7 2 6.3 4.7 3.6 11.4 1.3 2.3 3 NS NS 0.5 6.6 6.0 1.3
0.6 1 NS 0.1 0.5 0.6 5.1 5.9 NS 2 1.5 2.2 2.2 1.5 2.4 0.1 3 NS 0.1 3.5 1.7 0.9 0.1
0.3 1 NS 0.8 ND 0.2 5.2 NS NS 2 1.9 1.8 ND 0.1 NS NS 3 0.7 0.2 0.3 0.7 NS 1.3