INTERNATIONAL JOURNAL OF CLIMATOLOGY

Int. J. Climatol. 24: 1883–1896 (2004)

Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/joc.1077

SEASONAL TO INTERANNUAL VARIATIONS OF SOIL MOISTUREMEASURED IN OKLAHOMA

BRADLEY G. ILLSTON,* JEFFREY B. BASARA and KENNETH C. CRAWFORD

Oklahoma Climatological Survey, University of Oklahoma, 100 East Boyd, Suite 1210, Norman, OK 73019-1012, USA

Received 20 November 2003Revised 29 May 2004Accepted 31 May 2004

ABSTRACT

Agriculture is a $2 billion component of the state economy in Oklahoma. As a result, meteorological, climatological,and agricultural communities should benefit from an improved understanding of soil moisture conditions and how thoseconditions vary spatially and temporally. The Oklahoma Mesonet is an automated observing network that provides real-time hydrometeorological observations at 115 stations across Oklahoma. In 1996, sensors were installed at 60 Mesonetsites to provide near-real-time observations of soil moisture.

This study focuses on 6 years of soil moisture data collected between 1997 and 2002 to analyse the annual cycle andtemporal characteristics of soil moisture across Oklahoma. The statewide analysis of the annual cycle of soil moisturerevealed four distinct soil moisture phases. In addition, the four statewide phases were also observed in each of the nineclimate divisions across Oklahoma, although the temporal characteristics of each phase were unique for each division.Further analysis demonstrated that, at shallow soil depths (5 and 25 cm), the spatial variability of soil moisture acrossOklahoma was most homogeneous during the winter and spring periods and most heterogeneous during the summer andautumn periods. Conversely, at greater depths (60 and 75 cm), soil moisture was most heterogeneous during the winterperiod and the most homogeneous during the late spring. Copyright 2004 Royal Meteorological Society.

KEY WORDS: soil moisture; Oklahoma Mesonet; phases; annual cycle; climatology

1. INTRODUCTION

Soil moisture is a critical component of a feedback system that conveys meteorological memory to the climatesystem over land surfaces (Delworth and Manabe, 1988, 1993). On the local scale, soil moisture controls thepartitioning of mass and energy between the land surface and the atmosphere through surface fluxes of latentand sensible heat; it also mitigates the soil heat flux (Brubaker and Entekhabi, 1996).

Soil moisture conditions also contribute to the natural and agricultural productivity of a region by definingthe root water that is available for uptake into the vegetation canopy (Hillel, 1998). In turn, water is transpiredfrom the vegetated surface to the atmosphere during photosynthesis, thus increasing low-level atmosphericmoisture on both a local and regional basis.

The spatial and temporal variability of soil moisture conditions (specifically the total amount of watercontained within a given soil mass or volume) are influenced by a number of competing factors. Thefactors include soil properties and organic material (Reynolds, 1970a,b; Henninger et al., 1976; Miller, 1977;Dingman, 1994; Hillel, 1998), topography (Hills and Reynolds, 1969; Reid, 1973; Moore et al., 1988; Nyberg,1996; Famigletti et al., 1998), mean soil moisture content (Hills and Reynolds, 1969; Bell et al., 1980; Hawleyet al., 1983; Laogue, 1992; Nyberg, 1996; Famigletti et al., 1998, 1999), depth of the water table, vegetation

* Correspondence to: Bradley G. Illston, Oklahoma Climatological Survey, University of Oklahoma, 100 East Boyd, Suite 1210, Norman,OK 73019-1012, USA; e-mail: illston@ou.edu

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(Lull and Reinhart, 1955; Reynolds, 1970b,c; Hawley et al., 1983; Francis et al., 1986) and meteorologicalparameters, including precipitation and solar radiation (Famigletti et al., 1998).

Persistent weather patterns that result from anomalous conditions within the land surface can enhancephenomena such as droughts and floods. Using climate records for the continental USA between 1905 and1984, Zhao and Kahil (1993) determined that a strong negative correlation existed between precipitation andsurface temperature with the strongest correlation in the central USA and the Great Plains. Huang and vanden Dool (1993) included a lag correlation investigation into their analysis, which revealed that a negativeprecipitation anomaly (less than average rainfall amounts) led to a decrease of near-surface soil moisture thatpreceded above-average summer temperatures by 1 month. Other studies have shown how a positive feedbackbetween lower near-surface soil moisture conditions and warmer temperature anomalies exists (Rind, 1982;Shukla and Mintz, 1982; Durre et al., 2000).

Delworth and Manabe (1989; Manabe and Delworth, 1990) used a numerical model to demonstratethat persistent anomalies of soil moisture can have a significant impact upon the variability of the lowertroposphere. Surface air temperature and humidity are significantly altered by persistent wet soil anomalies,owing to an increase of latent heat flux and a reduction of sensible heat flux. Delworth and Manabe(1989) further concluded that persistent soil moisture anomalies have their greatest impact on the atmosphereacross large spatial scales. Furthermore, moisture recycling is a major component in the potential sustenanceof wet anomalies and can be a prime source of daytime convection (Zangvil et al., 1993); recycled moisturecan account for up to 30% of the annual precipitation over large land areas (Brubaker et al., 1993).

Until recently, the predominant method for collecting soil moisture observations involved destructivesampling, whereby soil was excavated for laboratory analysis. As a result, the total number of datasetscollected for long-term analysis of the spatial and temporal variability of soil moisture is limited. Althoughlegacy datasets have been collected in Europe and Asia (Robock et al., 2000), very few soil moisture observa-tions have been collected in the USA (Hollinger and Isard, 1994; Robock et al., 2000). Thus, to estimate soilmoisture, previous studies relied upon the collection of related variables such as precipitation, solar radiation,and soil type to estimate soil moisture over extended periods of time using modelling techniques (DeLibertyand Legates, 2003; Mahmood and Hubbard, 2003). Some studies (Hollinger and Isard, 1994; Schneider et al.,2003) have used observational data of soil moisture to demonstrate general soil moisture trends; however, theirspatial and/or temporal scales of observations were not of high enough resolution to detect fine-scale features.

Recognizing the need for long-term measurements of soil moisture (Emmanuel et al., 1995; Entekhabiet al., 1999), sensors were installed at Oklahoma Mesonet stations (Brock et al., 1995). As a result, this studyfocuses on soil moisture observations collected at 58 sites during a 6 year period between 1997 and 2002 toexamine the seasonal and interannual variability of soil moisture in Oklahoma. The data from the extensivenetwork of soil moisture sensors provide a unique opportunity to obtain an insight into the physical nature ofnear-surface soil moisture across Oklahoma. In turn, a better understanding of regional climate in the southernplains of the USA should benefit the agricultural industry of Oklahoma (a $2 billion component of the stateeconomy; USDA, 2000).

2. INSTRUMENTATION

The Oklahoma Mesonet (Brock et al., 1995) is a statewide meteorological observing network that providesreal-time data from 115 stations, with at least one station in every county. Data are recorded every 5 min andinclude meteorological variables such as air temperature, wind speed and direction, and rainfall.

In 1996, soil moisture sensors were installed at 60 Mesonet sites at depths of 5, 25, 60, and 75 cm toprovide continuous observations of soil moisture (Basara and Crawford, 2000). The sensor of choice wasa heat dissipation sensor manufactured by Campbell Scientific and known as their 229-L. This sensor waschosen over other soil moisture sensors because of its easy incorporation into an automated network, the sensorminimally disturbs the soil, the increased vertical resolution (due to small size of the sensor), and the absenceof harmful radiation (Basara, 1998). The sensor is limited in ability to measure soil moisture conditions insandy soils accurately; however, this drawback impacts very few sites in the Oklahoma Mesonet. The soil

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moisture sites collect observations every 30 min with the data quality assured using multipass procedures(Shafer et al., 2000).

Since the soil moisture network was installed, two of the 60 original soil moisture sites have beendecommissioned. The remaining 58 sites (Figure 1) span the entire state, as well as the varying meteorological,hydrological and geophysical conditions. Based upon the initial success of data collection from the soilmoisture network, soil moisture sensors were installed at an additional 43 Mesonet sites during 1998 and1999. However, this study focuses on data collected from the original 58 sites for the period between 1997and 2002. This allows a complete, consistent 6 year dataset to be utilized without comparing sites with longerdata histories with those that have shorter data histories.

The 229-L sensors are heat dissipation sensors. Thus, the sensors measure the sensor’s change in temperatureafter a heat pulse has been introduced (Reece, 1996; Basara and Crawford, 2000). During installation of thesoil moisture sensors, soil cores from each site and each depth are analysed for the soil characteristics. Usingthe measured temperature difference of the sensor before and after heating (i.e. heat dissipation) and the soilcharacteristics, hydrological variables such as soil water content and soil matric potential can be calculated.Unfortunately, because soil water content depends heavily upon soil texture, and because soil matric potentialis exponentially related to soil wetness, these two variables are difficult to analyse on a regional or statewidescale. Thus, an alternative measure of soil wetness was chosen for the analysis used in this study: fractionalwater index (FWI).

FWI is a normalized version of the calibrated sensor’s response (Schneider et al., 2003). Because FWIhas no limitations due to soil texture and does not utilize exponential scales, it is an ideal variable for usein analysing soil conditions across Oklahoma. The unitless values of FWI range from very dry soil havinga value of zero to soil at saturation having a value of unity. The majority of vegetation across Oklahomawill flourish when FWI values are greater than 0.8, will strain and wilt from diminished moisture when FWIvalues are approximately 0.5, and begin to die when FWI values are 0.3 or less.

Mesonet soil moisture data were rigorously analysed and quality assurance procedures were developed andimplemented. The raw data values from each sensor undergo a series of quality assurance tests to ensure theirvalidity before being converted into the soil moisture variables. These tests include a step test (to check that

Figure 1. Oklahoma climate divisions with the 58 soil moisture sites. This figure is available in colour online at http://www.interscience.wiley.com/ijoc

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a sensor’s value does not wet or dry in an unrealistic manner), a range test (to check that a sensor’s valuedoes not exceed a preselected threshold), and other site-specific tests (e.g. analyses to detect the preferentialflow of water; Basara and Crawford, 2000).

The Oklahoma Mesonet collected 27 589 376 soil moisture observations between 1 January 1997 and 31December 2002 (Illston et al., 2003) that were determined to be ‘research quality’. The quantity and qualityof the soil moisture data for each year are shown in Table I. The approximately 27.6 million observationsequate to approximately 92% of the 30 million observations possible (the archives include research quality,suspect, and missing data). As a result of increasing the number of Mesonet sites that had soil moisturesensors during 1998 and 1999 (from approximately 60 to just over 100 sites), the number of soil moistureobservations increased from approximately 3.6 million annually to over 5.3 million. Even with the increasein soil moisture sensors to maintain, the quality of data increased from slightly under 90% to near 95% asimprovements in sensor installation and data collection were incorporated into the network.

3. CLIMATE REGIONS

Oklahoma is divided into nine climate divisions (Figure 1). These nine divisions correspond to the nine cropreporting divisions designated by the US Department of Agriculture. Each climate division also representsa section of the state that is considered to have homogeneous weather and climate patterns. The hottesttemperatures in the state usually occur in the south (16.3 °C), with cooler conditions towards the north (14.4 °C;OCS, 2003). In addition, the division that typically receives the least amount of precipitation (504 mm/year)is the extreme northwest division (the Oklahoma panhandle), while increased precipitation is observed towardthe southeast (1200 mm/year; OCS, 2003). As a result, the climate of Oklahoma varies significantly across thestate. Thus, the measure of soil moisture conditions in the nine climate divisions provides a unique opportunityto understand better how varying climate impacts soil moisture.

4. THE ANNUAL CYCLE OF SOIL MOISTURE IN OKLAHOMA

Synoptic plots of the statewide average values of soil moisture provide a clear picture of the spatial variabilityof the soil moisture at a given time period, but fail to capture the temporal variability of soil moisture fully.Conversely, time series plots not only provide an increased understanding of the temporal variations of soilmoisture, but also allow intercomparisons of drying and wetting trends and differences between different soildepths. Thus, time series plots were analysed for both the statewide values and those values within eachclimate division to document the spatial and temporal variability of soil moisture.

Averaged daily soil moisture values were calculated by averaging the 48 30 min raw (the sensor’stemperature change) soil moisture observations collected each day. For a daily average to be valid, at least

Table I. Soil moisture data statistics from the Oklahoma Mesonetbased on over 30 million possible observations. Reproduced by

permission of GEWEX (from Illston et al., 2003)

Year No. of research-qualitydata points

Research-qualitydata points (%)

1997 3 525 738 911998 3 659 388 891999 4 211 868 892000 5 381 817 932001 5 476 006 952002 5 334 563 936 Years 27 589 376 92

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50% of the observations must have been present and passed quality assurance procedures. From the averagedvalue of raw soil moisture data, other soil moisture variables, such as volumetric water content or FWI,were calculated. Time series plots were generated from the averaged daily data from each site in the regionover the 6 year study period (1997–2002). A 10 day running mean was applied to the data plots to filterhigh-frequency variations in soil moisture levels due to local-scale variations in meteorological conditionsthat might have impacted soil moisture. The analyses were performed for each of the nine climate divisions,as well as for the entire state.

The statewide-averaged time series of FWI (Figure 2) reveals four distinct phases of the soil moisture(indicated I–IV). The four phases are termed the moist plateau phase (I), the transitional drying phase (II),the enhanced drying phase (III), and the recharge phase (IV). This detailed pattern of the soil moisture cyclein Oklahoma is similar to the general annual cycle of soil moisture in Illinois shown by Hollinger and Isard(1994). However, the increased spatial and temporal resolution allowed the detection of features not capturedin other studies.

The moist plateau phase (I) is characterized by the highest FWI values and occurs between Novemberand mid-March. During this period, low sun angles and predominantly cloudy skies result in near-zeroevaporation of soil moisture. In addition, most vegetation during this period is dormant, which leads to verylittle evapotranspiration. Even though the statewide precipitation is minimal, soil moisture remains near fieldcapacity at all four measurement levels.

The transitional drying phase (II) occurs during mid-March to mid-June, the climatological wet season inOklahoma. The sinusoidal pattern observed in the upper two soil layers (5 and 25 cm) is created by a battlebetween the forces that remove or replenish soil moisture. Increased evapotranspiration due to the higher sunangle and the growing vegetation depletes the soil moisture, especially at the upper two measurement levels,even as soil moisture is replenished by frequent synoptic-scale events. The soil moisture at 60 and 75 cm

Figure 2. The annual cycle of FWI averaged across Oklahoma and illustrating four soil moisture phases (I–IV)

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depths revealed a dampened sinusoidal pattern. This scenario results from the buffer created by the soil above,which, in turn, limits the impact of bare soil evaporation and the capillary rise of moisture from below.

From mid-June to late August, the soils across Oklahoma undergo an enhanced drying phase (III). Thisperiod is characterized by the steep decline of FWI values at all measurement levels, as well as the overallminimum values of FWI reached during late summer. During phase III, spring precipitation ends abruptly asa strong mid-tropospheric ridge typically develops over the southern plains of the USA (Bluestein, 1993). Asa result, synoptic-scale subsidence increases in the lower atmosphere, precipitation decreases, and moisturereplenishment to the soil becomes limited. However, evapotranspiration continues to increase due to increasedvegetation coverage and density, as well as increased surface temperatures. Thus, the FWI values dry firstat the surface, where the impacts of evapotranspiration are initially the greatest, followed by depletion atgreater depths. Whereas the enhanced drying phase is a normal annual progression, continued drying beyondthe typical enhanced drying phase is indicative of drought conditions.

The recharge phase (IV) typically spans late August to November and completes the replenishment cycleof soil moisture from autumn precipitation. The harvesting of crops and the decline in plant biomass reducesthe evapotranspiration rate at which water leaves the soil. In addition, soil evaporation decreases during thisperiod due to the decreased sun angles. As a result, the soil moisture increases throughout the recharge phase,especially at the upper two measurement levels.

The annual sinusoidal patterns of soil moisture (Figure 2) reveal a phase shift with depth and the associatedinflection points between phases I and II and between III and IV. In the two drying phases (II and III), alag (approximately 2 to 3 weeks) exists between the drying of the soil at 5 cm and at greater depths. Duringthe transitional drying phase (II), the lag time (approximately 2 to 3 weeks) varies greatly due to the addedmoisture from frequent precipitation. However, during the enhanced drying phase (III), the response betweenthe 5 and 25 cm depths lags nearly a week, by almost 2 weeks between the 5 and 60 cm levels, and byapproximately 3 weeks between the 5 and 75 cm levels. Conversely, during the recharge phase (IV), therecharge lag between the wetting of soils at 5 cm and at greater depths is approximately 1 week for the25 cm level, between 2 and 3 weeks for the 60 cm level, and almost a month for the 75 cm level. Duringthe moist plateau phase (I), soil moisture does not change dramatically at any depth. Thus, the behaviour ofsoil moisture is nearly identical at all four measurement levels.

5. SPATIAL VARIATIONS OF SOIL MOISTURE

Meteorological and hydrological conditions vary significantly across Oklahoma. For example, temperaturesin the southern portion of the state (16.3 °C) are higher on average than in the northern portion (14.4 °C),and precipitation in the northwest portion of the state (504 mm/year) is much less than that in the southeast(1200 mm/year; OCS, 2003). Furthermore, because climate conditions are so variable, vegetation conditionsare also quite variable. To investigate the impact of local climate and vegetation conditions on the variabilityof soil moisture, the annual cycle of soil moisture was computed for each of the nine climate divisions.

The northeast and southwest climate divisions portray the two extremes of the annual cycle of soil moisturein Oklahoma (Figure 3). Because the northeast climate division was characterized by increased rainfall andcooler temperatures, the moist plateau phase spans a longer period of time and the enhanced drying phase ismuch shorter than the statewide average (Figure 2). Conversely, the southwest climate division received lessrainfall and experienced warmer temperatures. As a result, the annual cycle of soil moisture was characterizedby a shorter (and drier) moist plateau phase and a longer (and drier) enhanced drying phase.

It should be noted that all four phases of the annual cycle of soil moisture were observed in the time seriesplots from each of the nine climate divisions. However, temporal variations of phases exist amongst differentsoil depths. Even with the variations in soil type, vegetation cover, and meteorological and hydrologicalconditions, the four phases occur from division to division at varying temporal lengths.

To quantify the spatial variability of soil moisture across Oklahoma further, the mean FWI values for eachclimate division over the study period were subtracted from the statewide 6 year mean of FWI. Plots of theFWI deviations (Figure 4(a)–(c)) for each of the climate divisions illustrate the spatial variability of soilmoisture.

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Figure 3. The annual cycle of FWI for the northeast and southwest climate divisions in Oklahoma

Climate divisions 1, 4, and 7 (Figure 4(a)) are the westernmost divisions, and thus have drier climates. Thesoil moisture values (FWI) for those divisions were typically 0.0 to 0.3 below the statewide mean. In addition,climate division 1 experienced the largest statewide deviation toward the dry end of the spectrum, with FWIvalues more than 0.4 below the statewide mean during the winter months. On the other hand, the soils inclimate division 7 closely mirrored the statewide trends, with dry deviations of ∼0.1. In addition, climatedivisions 2, 5, and 8 (Figure 4(b)) experienced soil moisture conditions that were very near the statewideaverage. The overall deviations of FWI from the statewide annual cycle ranged between 0.1 and −0.1. Finally,climate divisions 3, 6, and 9 (Figure 4(c)) experienced very moist soil conditions throughout the year. Overall,soil moisture values (FWI) typically were 0.0 and 0.2 above the statewide mean. Furthermore, the largestdeviations in the state toward the moist end of the spectrum occurred in climate division 3 during the latesummer (0.25).

6. TEMPORAL VARIATIONS OF SOIL MOISTURE

To diagnose the interannual variability of soil moisture across Oklahoma during the study period, the yearlyaveraged FWI values were subtracted from the statewide 6 year mean (Figure 5). In addition, the annualsurplus/deficit of soil moisture for each year was calculated by averaging the daily deviations of FWI fromall four depths over the entire year.

During 1997, the soil moisture was more moist than the 6 year mean, with an average FWI deviation of0.10 above the 6 year mean. In addition, the largest moist deviations for 5, 25, 60, and 75 cm were recordedduring 1997; at times, the near-surface values were >0.4 above the 6 year average. Conversely, a severedrought that occurred during the summer of 1998 (Illston and Basara, 2003) created much lower FWI valuescompared with the 6 year mean during the late spring and summer months. Overall, average soil moistureconditions for 1998 nearly equalled the 6 year mean. This scenario resulted from, in part, above-averageprecipitation that fell early and late in 1998.

During 1999, soil moisture values were above the 6 year mean for most of the year until drier than averageconditions impacted the state during parts of the autumn and the winter. From late September to late October,the deviation of FWI at 5 cm transitioned from approximately 0.25 above to −0.4 below the 6 year average.This large swing in the FWI deviation (0.65 at 5 cm) is the largest statewide continuous dry down observedduring an annual cycle. Furthermore, the FWI deviation at 75 cm was nearly −0.3 drier than the 6 year mean,which is the largest statewide dry anomaly observed at 75 cm. Despite the dramatic decrease in soil moisture

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(a)

(b)

Figure 4. Deviations of the 6 year FWI from the statewide 6 year mean in Oklahoma for: (a) climate divisions 1, 4, and 7 (b) climatedivisions 2, 5, and 8; (c) climate divisions 3, 6, and 9. This figure is available in colour online at http://www.interscience.wiley.com/ijoc

during the latter part of 1999, soil moisture overall was nearly identical to the annual mean (an FWI deviationof 0.01 from the 6 year mean).

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(c)

(b) continued

Figure 4. (Continued )

In 2000, another severe drought impacted the entire state during the late summer and early autumn andcreated the largest dry anomalies observed at 25 and 60 cm. Unlike the 1998 drought, most of Oklahomareceived heavy precipitation just before (June and July) and just after (November) the drought in 2000. The

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Figure 5. Yearly deviations of the statewide FWI from the statewide 6 year mean in Oklahoma

precipitation after the drought allowed soil moisture at 5 cm to increase from an FWI deviation that was lessthan −0.4 below the 6 year mean to nearly 0.2 above the 6 year mean, which represents the largest wettingchange observed during an annual cycle of the 6 year data set. The drier winter and autumn drought createdoverall soil moisture conditions that were only −0.03 below the 6 year mean.

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Soil moisture in 2001 oscillated between wetter and drier than average conditions throughout the year.However, the year ended with a very dry winter to produce overall soil moisture conditions that were only−0.04 below the 6 year mean. Of the 6 years, soil moisture was the least variable during 2002 from a temporalstandpoint. Frequent synoptic-scale systems, evident as oscillations in the time series plot, and a wet summercreated a trend of increasing soil moisture throughout the year (with respect to the annual mean). Conditionsat 60 and 75 cm steadily transitioned from drier than the 6 year mean to near the 6 year mean values. Evenso, the overall soil moisture conditions for 2002 had an average FWI deviation of only −0.04 below the6 year mean.

Finally, a time series plot of the standard deviation of statewide FWI (Figure 6) best represents the temporalvariations of soil moisture in Oklahoma at each of the four depths. The average standard deviation of FWIfrom all four depths over the entire 6 year period is 0.14, which indicates a relative low variability in thesoil moisture. However, the plot clearly indicates that variability changes depending upon the season andsoil depth. Similar to the annual cycle of soil moisture, these results match the general annual cycle ofsoil moisture variability in Illinois shown by Hollinger and Isard (1994); however, the increased spatial andtemporal resolution allowed the detection of features not captured in other studies.

At the shallow depths (5 and 25 cm), the soil moisture was the least variable during the winter and springmonths following the recharge phase. The maximum standard deviation of FWI for the shallow depths occurredduring the summer months, and reflects the differential wetting and drying trends from year to year. However,the variability increased with depth between 25 and 75 cm. Thus, variability in the timing and amount ofprecipitation that fell during the recharge phase from year to year had significant impacts on the moisteningof the greater depths. Physically, the variability in the precipitation was likely due to the occurrences ofeither mesoscale convective systems (MCSs) or tropical systems versus drought-like conditions. As a result,FWI at the greater depths did not reach minimum variability until the peak of the wet season in Oklahoma

Figure 6. A time series plot of the standard deviation of FWI from the 58 soil moisture sites during the 1997–2002 period

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(April–May). This scenario likely means that root-zone soil moisture ended the rainy season at near fieldcapacity levels.

Overall, the greater depths (60 and 75 cm) revealed less temporal variability in the seasonal trends of thestandard deviation than did the near-surface (5 and 25 cm) layers. Because 60 and 75 cm had almost identicalstandard deviation profiles, these observations reflect the buffering by soil layers above mitigating the impactfrom short-term atmospheric changes. During the late summer and autumn, large ‘spikes’ in the standarddeviation values are evident in the near-surface data. These spikes result from synoptic- and local-scale rainevents, which mainly impacted the near-surface depths. The large spike in late June is attributed to the endof the spring storm season and the beginning of summer-like conditions. However, the progression of thesefeatures as they penetrate deeper into the soil is evident in the temporal lag between the peak variability nearthe surface and the peak variability at greater depths.

7. CONCLUSIONS

An analysis of time series plots of soil moisture revealed four distinct soil moisture phases (moist plateau,transitional drying, enhanced drying, and recharge). The characteristics of each phase were identified viathe physical processes that govern soil moisture. The moist plateau phase (November to mid-March)demonstrated how low evaporation, predominantly cloudy skies, and dormant vegetation resulted in increasedsoil moisture with minimal fluctuations. The transitional drying phase (mid-March to mid-June) revealed thebattle between forces removing moisture from the soil (evapotranspiration) and replenishing moisture to thesoil (precipitation). The enhanced drying phase (mid-June to late August) displayed the dramatic decrease insoil moisture levels caused by increased evapotranspiration and decreased precipitation. The recharge phase(late August to November) demonstrated how autumn precipitation and reduced biomass from harvestingincreases the moisture levels in the soil to complete the cycle.

All four phases were observed in all nine climate divisions; however, the temporal characteristics of eachphase varied from division to division. The climate divisions with more arid conditions had lengthened dryingphases; those with increased precipitation had shorter drying phases. Temporal variations in soil moisturewere also detected. The shallower depths showed more variability throughout the year than at greater depths.Additionally, variability in the soil moisture levels was less during the winter and spring than during thesummer and autumn.

These results will benefit the meteorological, climatological, and agricultural communities by the increasedunderstanding of soil moisture variability from season to season. Knowledge of the magnitude of spatialand temporal scales of the cycle of soil moisture will allow a framework of climatological conditions uponwhich further analysis can be constructed. With the added understanding of the variability of soil moistureconditions, climate and agricultural modelling can be enhanced to provide more accurate information to servethe public better.

ACKNOWLEDGEMENTS

The successful collection of soil moisture observations by the Oklahoma Mesonet was made possible, in part,by an NSF-EPSCOR grant (EPS-9550478) and an NSF MRI grant (ATM-9724594), which provided fundsto add soil moisture sensors to the Oklahoma Mesonet. The NOAA Office of Global Programs and theirGCIP and GAPP programs provided funds to support the Oklahoma Mesonet and the soil moisture network(NA17RJ1227). We would like to thank the entire Mesonet team for their hard work and dedication to thecontinuous support and maintenance of the Oklahoma Mesonet.

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