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Evaporation from wetland versus open water: a theoretical explanation and an
application with satellite data over the Sudd wetland
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Y.A. Mohamed1,2, W.G.M. Bastiaanssen3,4, H.H.G. Savenije1,4, B.J.J.M. van den Hurk5 and C.M. Finlayson1
ABSTRACT Is the total evaporation from a wetland surface (i.e., open water evaporation, plant transpiration and
wet/dry soil evaporation) similar, lower, or higher than evaporation from an open water surface
under the same climatic condition? This has been a long debate; the literature does not show a
consensus. In this paper we contribute to the discussion through three steps: First, we present a
theoretical analysis of evaporation from a wetland with emergent vegetation (Ea) versus open water
evaporation (Ew) by applying the Penman-Monteith equation to identical climate input data, but
with different biophysical characteristics of each surface. Second, we assess the variability of Ea/Ew
through a literature review of selected wetlands. Thirdly we apply a theoretical framework in
conjunction with satellite images from over the Sudd wetland to unravel the seasonal variability of
wetland biophysical properties, and the variation of Ea/Ew.
We demonstrate that the ratio Ea/Ew is site-specific, and a function of the biophysical properties of
the wetland surface. The monthly variability of Ea/Ew over the Sudd ranges from 60% in the dry
months up to 90% in the wet season due to the presence of seasonal swamps with emergent
1 Corresponding author, [email protected], IWMI-NBEA, PO Box 5689, Addis Ababa, Ethiopia 2 UNESCO-IHE, P.O. Box 3015, 2601 DA Delft, The Netherlands. 3 WaterWatch, Generaal Foulkesweg 28, 6703 BS Wageningen, The Netherlands. 4 Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands 5 Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730 AE De Bilt The Netherlands.
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vegetation. Formerly, the evaporation of the Sudd was assumed to behave as if it was an open water
body; this has a significant impact on the total water consumption of this vast wetland, and water
allocation to wetlands in river basin planning.
Key words: evaporation; biophysical properties; wetland; Sudd; Nile
1 Introduction Wetlands are characterized by permanently wet or intermittently flooded areas often with a diverse
and productive flora and fauna and vary in size from the huge tundra wetlands in North America
and Russia to small natural and man made wetlands with some covering less than a few hectares
(Mitsch and Gosselink 2007). The Sudd wetland (38,500 km2), located in the Nile basin (Fig. 1), is
one of the largest wetlands in Africa.
Fig. 1: Location of the Sudd wetland
Many of the world's wetlands are threatened by changes in their water regimes with often adverse
consequences for their biota and the provision of ecosystem services of importance to many people
(Finlayson and D’Cruz 2005). As a consequence there are increasing recommendations to commit
more surface water resources to maintain or restore at least some features of the original water
regimes, noting that in many cases this may be limited by the timing and extent of suitable water
supplies. More accurate determination of the various components of the water regime (including
precipitation, evaporation, inflow, outflow, storage and interaction with groundwater) could lead to
more informed decisions about the conservation, development and management of wetlands. As
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many wetlands are dependent on surface water inflows in addition to direct rainfall, maintaining or
restoring the water regime (at least in part) may require an allocation of the annual renewable water
resource, especially where water loss through evaporation is a major component of the water
balance. While evaporation may comprise a major component of the water budget of a wetland it
has proven difficult to measure accurately (Linacre et al. 1970, Lott and Hunt 2001).
Although there is a wealth of literature on crop water requirements, the heterogeneity of wetland
vegetation and variable water levels (surface and ground water) makes determining the water
requirements of wetlands a complex issue. Better information on wetland evaporation is seen as
important for determining the water balance of wetlands and supporting integrated water resources
and environmental management. Here, we refer to wetland evaporation as all forms of water
transfer from the wetland surface into the atmosphere. This includes open water evaporation, plant
transpiration and wet/dry soil evaporation.
Numerous field experiments have been conducted world wide to measure and model actual wetland
evaporation Ea. However, the results seem to be site-specific and difficult to extrapolate to a
regional context (Lafleur and Rouse 1988, Souch et al. 1998, Drexler et al. 2004). Many assume
that Ea from a wetland with emergent vegetation resembles the evaporation from open water (Ew);
Penman (1963) pointed out that evaporation measured from swamps in the Sudd corresponded with
estimates of open water evaporation. There are other authors who assume that Ea resembles
potential evaporation Ep, i.e. evaporation from vegetative cover with no water constraint (e.g. Lott
and Hunt 2001).
A wetland system is a mixed composition of vegetation types, open-water bodies and (un)saturated
soil with dynamic shallow water table fluctuations. Depending on the structure of the vegetation
canopy (Leaf Area Index INDV, and vegetation height h), the emergent wetland vegetation intercepts
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a certain amount of incoming solar radiation. If the vegetation growth has a high INDV and an
aerodynamically rough surface, transpiration may be high. A classical wetland evaporation research
question is: does the transpiration of a wetland with emergent vegetation shading the surface water,
an aerodynamic rough canopy, pen stomata and a longer pathway of water through the plant, exceed
the evaporation from open water (Gilman 1994)? As there are contradictory answers to this question
we aim to demonstrate that a sound theoretical framework can explain the ambiguity.
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Thus, we re-examined the value of the Ea/Ew ratio from a theoretical point of view by applying the
Penman-Monteith equation to two different wetland surfaces: a purely open-water wetland surface,
and a wetland surface with water and emergent vegetation. Mean values of biophysical properties
over wetland surfaces, such as vegetation characteristics and radiation properties, were obtained
from an extensive literature review. Secondly, we review the ratio of Ea/Ew over some wetlands
around the world to test the hypothesis that evaporation from wetlands is unequal to open water
evaporation, and that a better understanding of wetland biophysical properties is essential to
estimate evaporation. In a third step, we validated the variability of Ea/Ew in relation to biophysical
properties results computed from satellite images over the Sudd wetland.
As ground data from the Sudd are not available, the determination of Ea was done using remote
sensing and a surface energy balance model. Mohamed et al. (2004) provided Ea results for the
Sudd for the year 2000 using a remote sensing-based energy balance model with a closing error for
the annual water balance of less than 2% of Ea. Mohamed et al. (2005) and (2006) used these
estimates across larger areas to calibrate a regional climate model for the Nile Basin.
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2 Determination of wetland evaporation 1
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The actual evaporation from a wetland, Ea, depends on the atmospheric demand, the biophysical
characteristics of the vegetation (radiation properties and physical resistances in the plant internal
pathway), the area covered by vegetation, bare land and permanent swamps, and the soil water
potential in the root zone of the marshland vegetation. In wetlands with a regular water supply the
soil moisture is unlikely to be a binding constraint, and the soil water potential is low. Evaporation
from wetlands can become moisture controlled if large amounts of water arising from inundation
are drained away in the post-flood season.
In general, wetland evaporation has been determined by either direct in situ measurement with
dedicated field instruments or through biological or hydrological modeling. Both approaches make
use of the energy and water balance equations shown below to estimate wetland evaporation Ea.
Water balance
SQQQAPAE qoutina Δ−−−+= [m3s-1]…………………………………….. (1) 13
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Energy balance
HGRE na −−= 0ρλ [Wm-2] ………………..…………………. (2) 16
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Where A is the surface area of the wetland, P is the gross rainfall, Qin the river inflow, Qout the river
outflow, Qg the net water exchange with the groundwater, ΔS change in moisture storage, Rn net
incoming radiation, H the sensible heat flux, G0 ground heat flux (including heat stored in the water
table), and ρλEa the latent heat flux (λ in J/kg, is the latent heat of vaporization and ρ in kg/m3 is the
density of water).
In the energy balance approach Eq. (2) the Bowen ratio method (β=H/ρλEa) is used most frequently
to measure Ea (e.g. Rinks 1969, Burba et al. 1999, Josè et al. 2001) with Eddy correlation
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techniques being used in some other cases (e.g. Souch et al. 1998, Jacobs et al. 2002). The accuracy
of
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Ea in the water balance approach Eq. (1) depends on other components of the balance
(precipitation, runoff, interaction with groundwater). Lysimeter and water tank experiments are
based on water balance principles. Lysimeter measurements of wetland evaporation are not
common (e.g. Lott and Hunt 2001). Many of the older experiments on wetland evaporation were
made through water tank measurements (Butcher 1938, van der Weert and Kamerling 1974).
Some authors – in particular during earlier decades - believed that evaporation from wetlands with
emergent vegetation (Ea) was similar to open water evaporation (Ew), and could be determined
using the open water evaporation formula of Penman (1963). Examples of evaluating wetland
evaporation with the Penman open water formulae are given in Souch et al. (1998) and Koerselman
and Beltman (1988), among others.
The Priestley-Taylor equation was intended for apportioning net radiation into latent and sensible
heat over substantially saturated land areas (Priestley and Taylor 1972). Souch et al. (1998) and
Jacobs et al. (2002) show a review of Priestly-Taylor applications in wetlands with the so-called α
coefficient ranging from 1 to 1.26, confirming that the theory of atmospheric feedback suggested by
Priestley and Taylor can be applied, i.e., evaporation from wetlands reduced when the moving air
becomes saturated. Note that if α is unity, evaporation is the equilibrium evaporation determined
only by available energy. The Penman-Monteith (P-M) equation is commonly applied for
agricultural crops, some applications for wetland Ea have been established (e.g., Souch et al. 1998,
Jacobs et al. 2002). The main advantage of the P-M model is that once the vegetation biophysical
properties are known, detailed field measurements can be avoided or significantly reduced.
However, a potential difficulty with the P-M model is the prediction of heterogeneous vegetation
and soil moisture conditions.
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3 Penman-Monteith applied to a wetland and open water surface To understand the behavior of the controlling factors on Ea we explore the theoretical background of
the evaporation process using the P-M formula (Monteith 1965):
( )
)rr
+(1+
ree
c+)G-R( = E
a
s
a
asapn
a
γ
ρρλ
Δ
−Δ 0
…………………..……….…………. (3) 5
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where Δ (kPa/C°) is the slope of the saturated vapor pressure curve, cp (J/kg/K) the specific heat at constant
air pressure, ρa (kg/m3) the air density, (es-ea) the vapour pressure deficit (kPa), ra (s/m) the aerodynamic
resistance, γ (kPa/C°) the psychrometric constant, and rs (s/m) is the bulk surface resistance. The latter is a
mixture of canopy resistance rc (that dictates canopy transpiration), soil resistance r (that controls soil
evaporation), and the resistance for open water. The bulk surface resistance represents a heterogeneous
wetland ecosystem of a given size and is equal to
soil
rc if soil and water surfaces are completely covered.
If the climatic factors Δ and (es-ea) can be assumed to be constant over both the water body and the
wetland, then Rn, G0, rs and ra, are the remaining wetland parameters that affect Ea. For a water body
rs is zero, and the liquid particles are transferred freely into water vapor without passing through
stem and xylem. Wetland vegetation has a relatively lower ra due to tall vegetation stands, which
introduces a stronger coupling with the atmospheric boundary layer than a smooth water surface
(McNaughton and Spriggs 1986). Thus, vegetated wetland surfaces have a higher rs than a water
body, but a lower ra value, and these factors have compensating effects on evaporation. The
question therefore is: what is the combined ra-rs effect in conjunction with the variability of net
available energy (Rn-G0) on Ea? In fact this provides the basis of the primary question: why is Ea/Ew
smaller or larger than 1?
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The aerodynamic resistance ra depends on wind speed uz, vegetation structure (leaf area and
vegetation height) and buoyancy effects. For neutral atmospheric boundary layer conditions
(sensible heat flux over vast wet terrain is usually small), r
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a can be calculated by (Monteith and
Unsworth 1990):
z
hma uk
zdz
zdz
= r 200
]ln[]ln[ −−
…….……………….………………………….. (4) 5
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where z (m) is the reference height of wind measurements, d (m) the displacement height, z0m (m)
the roughness height for momentum transfer, z0h (m) the roughness height for heat and vapor
transfer and k is von Karman’s constant. Following the theoretical outline and the large variability
of vegetation heights, ra is expected to vary among different wetlands of the world. For instance, a
papyrus (Cyperus papyrus) stand with vegetation height of 4 to 6m imposes a smaller ra, than a
cattail (Typha species) vegetation of 0.4-0.6m height.
The bulk surface resistance rs can be broken down into a soil component that describes the soil
evaporation by means of a soil resistance rsoil and a vegetation component with a canopy resistance
rc:
soilcccs rvrv = r )1( −+ [s/m]………………..…......………….….……… (5)
where vc (-) is the fractional vegetation cover of a certain patch. Jarvis (1976) and Stewart (1988)
describe rc as a mathematical function of minimum stomatal resistance rc,min, INDV, incoming short
wave radiation (Rin), soil water potential (ψ), (es-ea) and air temperature (Tair) as shown by
( ) )()()( 4321min,
airasinNDV
cc TfeeffRf
Ir
= r −ψ [s/m]………......………….…………… (6) 19
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The coefficients of the functions f1, f2, f3 and f4 were determined from field measurements and from
laboratory experiments (e.g. Stewart and Verma 1992, Hanan and Prince 1997). The coupling
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between the conditions in the unsaturated zone and the stomatal aperture is reflected in the f2(ψ)
function. An alternative mathematical model approach to canopy resistance is to express r
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c as a
function of the photosynthetical process (e.g. Leuning et al. 1995). This is not further elaborated
here.
The computation of soil heat flux G0 is usually based on heat diffusion using soil thermal properties
and depth dependent soil temperatures. An alternative to the classical heat conduction equation is an
empirical estimation of the G0/Rn ratio. Field measurements have indicated that in hot deserts this
ratio can be approximately 0.4 and that for vegetated soil with light interception the fraction hardly
exceeds 0.05 during daytime hours. It is customary to apply a Leaf Area Index dependent light
extinction parameterization of the G0/Rn ratio (e.g. Choudhury et al. 1987). The G0/Rn fraction for
water surfaces can be as large as 0.5 during periods when the water body is warming.
Following this theoretical background, Annex 1 shows the possible range of the biophysical
characteristics measured over selected wetland surfaces around the world. The review includes leaf
area index INDV, surface albedo r0, surface resistance rs, roughness height zom, and additionally the
evaporative fraction Λ. The evaporative fraction Λ is not a property or state variable, but it is a key
parameter that describes the partitioning of the available energy (Rn-G0) into H and ρλEa following
land wetness conditions
βρλ
ρλρλ
+=
−=
+=Λ
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0GRE
HEE
n
…………..…..…….…………… (7) 18
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A summary of the data from Annex 1 is presented in Table 1 below, supplemented with literature
data on open water bodies, and values of G0/Rn. The aerodynamic parameters were derived from
measured vegetation height. These data are used with P-M equation to assess the variability of
Ea/Ew as given in the following section.
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Table 1: Representative values of covered wet soil and open water bodies. Mean values and standard deviation (std).
1 2
Parameter Open water Heterogeneous wetlands
Mean Mean Std
INDV (-) 0 2.4 1.5
Albedo r0 (-) 0.05 0.16 0.02
rs (s/m) 0 86 97
z0m (m) 0.0002 0.16 0.17
z0h (m) 0.00002 0.02 n.a
Λ (-) 1.0 0.73 0.24
G0/Rn (-) 0.3 0.1 n.a.
3 4
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These data exhibit a wide variation, illustrated by the high values of the standard deviation (std).
The INDV can be as low as 0.4 and as high as 5, which is a habitat dynamic characteristic. The albedo
varies between 0.11 and 0.18, since wetlands surfaces are relatively dark surfaces and low
reflectors. A large variation of canopy resistance is found (0 to 600 s/m) which reflects both wet and
dry wetland ecosystems respectively. The roughness height z0m varies between 0.009 to 0.41 m. The
evaporative fraction Λ varies between 0.16 and 1.0, which corresponds to a full range of soil water
availability.
Applying the P-M equation separately to a wetland, and an open water surfaces having mean
biophysical properties as provided in Table 1, permits comparison of the overall Ea/Ew ratio. A fixed
hypothesized climate condition is assumed over both the wetland and open water surface. The air
temperature is taken as 27 °C and the relative humidity as 75%. The mean 24-hour solar radiation
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incoming at the surface is assumed to be 250 W/m2. Net radiation at surface Rn is calculated with
the mean albedo values from Table 1.
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Applying the P-M equation using theses input values, and for a range of wind speeds, the result of
Ea/Ew is shown in Fig. 2a. The wind speed (at 2 m height) varies from 0.5 to 8 m/s. The computation
is repeated for different values of surface resistance rs: 50, 100, 150 and 200 s/m. Fig 2b shows the
same Ea/Ew against aerodynamic resistance ra. The aerodynamic resistance is computed by Eq. (4),
using the same set of wind speeds, and z0m for water as 0.0002 m and for wetland vegetation 0.16
m.
Fig. 2: Variability of Ea/Ew (-) for different wind speeds uz, (m/s) and surface resistances rs (s/m) using P-M equation, and fixed climatic condition over a wetland and open water.
The hypothesis that Ea/Ew is not unique and functions of the biophysical properties of the wetland
surface is verified by the results of Fig. 2. It shows that – for a given climate condition - Ea/Ew can
both be higher and lower than 1, depending on ra-rs combinations. The same wind speed blowing
across a water body or on a wetland, results in different Ea/Ew depending on the value of rs. For the
same rs value, Ea/Ew is changing with wind speed values, reflecting the coupling strength with
atmospheric boundary layer. This reveals that evaporation from a wetland cannot be determined
from a single indicator such as Ea/Ew, and instead, the biophysical system properties ought to be
known. This is an important conclusion to argue the generic statements such as wetlands
evaporation should be higher than that from open water evaporation (e.g. van der Weert and
Kamerling 1974), or to presume that Ea should be lower than Ew (Gavin and Agnew 2000). This
exercise teaches us that there is a wide range of characteristics that determines the evaporation from
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wetlands, and that the P-M equation is a physical-mathematical framework suitable for a wide
spectrum of wetland ecosystems. An analogous conclusion - although in a more general way- has
been attained by Drexler et al. (2004) who showed that, due to the variability and complexity of
wetlands, there is no single approach that is the best for estimating wetland E
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a, and that accurate
measurement of net radiation and soil heat flux is a key to improving measurements of wetland
evaporation. In our analysis, we are more specific to point to the knowledge of wetland biophysical
properties for robust estimation of wetland evaporation.
To verify results from the theoretical analysis by P-M equation, we have reviewed Ea measurements
from selected wetlands around the globe. Normalizing Ea with open water evaporation Ew provides
an opportunity to exclude effects originating from climatic factors. Table 2 gives a review of Ea/Ew.
Vegetation type and method of measurement are defined for each case.
Table 2: Measured Ea/Ew values of various wetlands spread around the world No. Ea/Ew Wetland Vegetation Location Source and methodology
1 0.7-0.9 Hydrophytes (bulrush, cattail,
white top)
Dakota,
USA
Eisenlohr (1966)
Water balance
2 0.6±0.15 Papayrus Uganda Rijks (1969)
Ea1, Ew
2
3 0.7 Typha Australia Linacre et al. (1970)
Ea3, Ew by miscellaneous formulae
4 ~ 1.5 Water haycinth Surinam Van der Weert and Kamerling (1974)
Ea measured in water tank, Ew from
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class A pan.
5 1±0.15 Sphagnum (papill osum and
majus), vascular plants
Minnesota,
USA
Kim and Verma (1996)
Ea1, Ew
2
6 0.34 – 0.77 Raised peat bog Sphagnum
(Empodisma minus)
New
Zealand
Campbell and Williamson (1997)
Ea1, Ew
2
7 ~ 1.0 Common arrowhead, yellow
pond lily, cattail
Indiana,
USA
Souch et al. (1998)
Ea3, Ew by P-M
8 0.75-1.0
reed grass (Phragmites
australis) early and peak
growth
Nebraska,
USA
Burba et al. (1999)
Ea1, Ew
2
9 0.8-1.5 Water hyacinth Kenya Ashfaque (1999), pp-A10
Ea1 Ew by P-M (rs=0)
10 0.84 – 1.10 Natural wetland grass England
Gavin and Agnew (2000)
Ea from soil moisture balance, Ew by
P-M (rs=0)
11 0.78 Palm, flooded herbaceous
(unburned) Venzuela
José et al. (2001)
Ea1, Ea
3 Ew is from type A tank
Avg.
std
0.87
0.26
Ea1 = wetland evaporation by Bowen ratio 1
2
3
Ew2 = Open water evaporation by Penman (1948)
Ea3 = wetland evaporation by eddy correlation
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In addition to the wide variability of Ea/Ew shown in Table 2, Gilman (1994) shows Ea/Ew ranges
between 0.85 and 2.5. Campbell and Williamson (1997) shows for four wetland locations that Ea/Ew
varies between 0.74 to 0.90. Dolan et al. (1984) in his review of the studies made in the 1960s and
70s shows that Ea/Ew ranges from 0.1 to 4.0. Linacre et al. (1970) reviewed Ea/Ew to lay between 0.6
to 2.5. Abtew (2005) gives a chronological review of Ea/Ew from studies mostly conducted on US
wetland sites, interestingly showing that Ea/Ew> 1 for earlier experiments, while it is ~ 1 or slightly
lower for the studies of the last decade of the 20th century. There are two interesting reports made
by Lafleur and Rouse (1988) and by Berger et al. (2001), on a transect of evaporation measurements
across wetlands covering open water, vegetation on water, and vegetation on the border with
relatively drier soil wetness. The climatic condition is more or less similar over the transect,
nevertheless the results confirmed that the presence of the vegetation canopy in the wetland
markedly reduced the evaporation efficiency compared to the open water site, and that the border
(drier) part of the wetland had the lowest Ea/Ew. This review demonstrates a substantial spatial
variation and that Ea/Ew is not equal to unity.
An aspect overlooked in wetland evaporation is the process of evaporation of intercepted water.
Evaporation from wet leaves is potentially higher than open water evaporation, because the
vegetation is able to withdraw more energy from the boundary layer. Interception is often
overlooked in hydrological studies (see Savenije 2004) and can be an important mechanism, both in
terms of the water balance and in the description of the temporal variability of evaporation.
Possible measurement limitations may affect the results of Table 2, which may have had direct
impact on the results. Dolan et al. (1984), Gilman (1994) and Souch et al. (1998) among others,
attributed the possible reasons of the wide range of Ea/Ew to be related to measurement limitations,
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e.g. duration of the measurements and location of the site relative to the surroundings (oasis effects,
land-sea breeze). Van der Weert and Kamerling (1974) attributed the high ratio of E
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a/Ew of 3.7 for
water hyacinth obtained by Timmer and Weldon (1967), and of 3.2 obtained by Penfound and Earle
(1948) to the border effects, i.e., significantly higher evaporation caused by the advected (drier) air
of the surroundings.
The very low value of Ea/Ew over the New Zealand wetland given in the table, was claimed to be
attributed to the severely restricted Ea by low nutrient soil conditions (Campbell and Williamson
1997). The position of the ground water table relative to the root depth, however, has direct control
on the wetland Ea (Jacobs et al. 2002, Kim and Verma 1996). Standard soil physical mechanisms in
combination with less drought tolerance of ecosystems that are used to grow in a surrounding of
abundant water supplies, confirm that the water uptake by roots will be reduced.
The main lesson we learned from this review of measured Ea/Ew that it confirmed the theoretical
analysis given by the P-M equation above, i.e., wetland evaporation is site specific, and a strong
function of the biophysical factors allied with vegetation type and water supply. These results are
verified in a third step, using remote sensing data over the Sudd wetland as presented in the
following section.
4 Remote Sensing Results over the Sudd wetland The wetland of the Sudd (Fig. 1) is composed of interconnected river channels, associated with
huge floodplains. Permanent swamps, usually close to the main river courses are permanently wet.
However, substantial parts of the Sudd are seasonal swamps created by flooding from the Nile and
its tributaries or when ponds are filled seasonally with rainwater. Depending on the definition, the
surface area is approximately 30,000 to 40,000 km2. During cloud free periods remote sensing
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techniques are used to describe the boundaries of the Sudd system, which is a function of the Nile
discharge (Travaglia et al. 1995, Mohamed et al. 2004). The average annual inflow and outflow for
the period 1961-83 are 49 and 21 Gm
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3/yr respectively. The average slope of the Sudd terrain is
around 0.01 %. The soils are generally clayish and poor in nutrients. Rain falls in a single season,
lasting from April to November ranges between 800 to 900 mm/yr. Temperatures average to 30-
33°C during the hot season, dropping to an average of 18°C in the winter season.
The Sudd environment supports a variety of vegetation species: Cyperus papyrus (papyrus),
Phragmites australis (reed); Typha species (cattail), and an abundance of submerged macrophytes in
the open water bodies. Oryza longistaminata (wild rice) and Echinochloa pyramidalis grasslands
dominate the seasonally inundated floodplains. Beyond the floodplain, Hyparrhenia rufa grasslands
cover the rain-fed wetlands. Acacia seyal and Balanites aegypticaca woodlands border the
floodplain ecosystem (Denny 1991). The swamps and floodplains of the Sudd support a rich biota,
as well as the pastoral economy of the local inhabitants. Further description of the study area is
given in Howell et al. (1988), and Mohamed et al. (2004, 2006) among others.
4.1 Temporal variability of biophysical properties over the Sudd Applications of remote sensing to estimate wetland evaporation – also categorized as energy
balance techniques - exist but are very limited. Bauer et al. (2002) for instance, computed the
evaporation of the Okavango swamps in Botswana using the SEBAL methodology. Farah and
Bastiaanssen (2001) used a similar approach for the Naivasha Basin in Kenya. Jacobs et al. (2004)
used the Geostationary Operational Environmental Satellite GOES-8 derived solar radiation with
limited additional surface measurements to compute evaporation estimates over (unstressed)
wetlands in Florida.
16
Accurate determination of the Sudd evaporation is hindered by its immense size and difficult
accessibility. Using SEBAL algorithm and NOAA-AVHRR images, Mohamed et al. (2004)
showed that for the year 2000, the annual rate of the Sudd E
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a amounted to 1636 mm/yr. This is 20%
less than open water evaporation, assumed in earlier hydrological studies (e.g., Sutcliffe and Parks,
1999). Here as well, the SEBAL algorithm has been used to compute the actual evaporation of the
Sudd from the NOAA-AVHRR images for 3 years 1995, 1999 and 2000. SEBAL is an energy-
partitioning algorithm on the basis of Evaporative Fraction over the land surface, which estimates
the actual evaporation from satellite images. Derivation and validation of SEBAL is given in a
number of articles (Bastiaanssen et al. 1998, 2005, Tasumi et al. 2003, Mohamed et al. 2004,
Koloskov et al. 2007). The main feature of SEBAL is the replacement of specific plant properties by
multi-spectral measurements in the visible, near-infrared and thermal infrared part of the spectrum.
SEBAL requires only limited input data from routine meteorological measurements. The SEBAL
parameters include surface albedo r0, Leaf Area Index INDV, the thermal infrared emissivity ε0 and
the surface roughness z0m. Secondly, SEBAL computes Rn and G0, and then the sensible heat H
through an iteration procedure that describes the buoyancy effects on aerodynamic resistance of the
land surface. Finally, the instantaneous latent heat flux ρλEa (at the time of satellite overpass) is
computed as the residue of Eq. (2). The instantaneous evaporative fraction Λ is accordingly
calculated by Eq. (7). By assuming constant evaporative fraction throughout the day (Brutsaert and
Sugita 1992), it is possible to obtain daily Ea.
We analyzed the temporal characteristic of the Sudd Ea over three years 1995, 1999 and 2000. The
3 years have different hydro-meteorological characteristics as measured by the ground stations in
the area, see Table 3.
17
Table 3: Measured climatic differences among the 3 years investigated 1995, 1999 and 2000. Mean values over the Sudd.
1 2
Parameter/Year 1995 1999 2000
Precipitation mm/yr1 930 1058 950
Inflow Gm3/yr 37.4 51.4 41.3
Outflow Gm3/yr 16.6 18.9 17.3
Air temperature (°C) 28.2 27.6 27.7
Vapor Pressure Deficit (es-ea) (kPa) 2.16 1.88 2.00
Wind speed (m/s) 2.56 2.58 2.64
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1 Average of Juba, Wau and Malakal stations
The mean monthly values of the biophysical parameters over the Sudd derived from SEBAL, have
been averaged for the three years 1995, 1999 and 2000. Results are shown in Fig. 3, for: evaporative
fraction Λ, leaf area index INDV, albedo r0, emissivity ε0, and roughness height z0m.
Fig. 3: Monthly fluctuations of evaporative fraction Λ (-), leaf area index INDV (-), albedo r0 (-), emissivity ε0 (-), and roughness height z0m (m) averaged over the Sudd wetland (monthly values averaged over the years 1995, 1999, 2000).
The INDV shows a clear seasonality, in accordance with rainfall season and river flooding. High INDV
values occur during the peak rainy season July to October, and don’t decay sharply during the post-
rainy season because flows from the incoming Nile supplies water to the ecosystem. The absolute
values on INDV are rather low (compared to Table 1) because large portions of the land are covered
with open water and bare soil. The roughness height z0m follows the INDV curve (by construction).
The albedo r0 behaves fairly stable in time, with a minimum value of 0.17 and a maximum of 0.20.
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The surface thermal infrared emissivity ε0 varies between 0.92 in the dry season to 0.96 in the rainy
season which agrees with the literature values presented by Buettner and Kern (1965).
Fig. 4 provides the mean monthly values of the climatology over the Sudd. The atmospheric
demand for evaporation (es-ea) reflects the seasonal climatology of the Sudd and its river flooding
regime. Lowest (es-ea) is recorded during the rainy season (July to October), while the driest air
coincides with the dry season (November to April). The net surface radiation Rn reflects variation of
the solar radiation, the cloud cover and the net long wave radiation. Due to the higher cloud
coverage during the summer when extra-terrestrial solar radiation is usually reaching maximum
values, the net radiation remains fairly stable over time.
Fig. 4: Monthly fluctuations of climate parameters: net surface radiation Rn (W/m2), vapor pressure deficit (es-ea) (kPa) and slope of the vapor pressure curve Δ (kPa/ C°) over the Sudd wetland (monthly values averaged over the years 1995, 1999, 2000).
The third influencing factor on evaporation is the hydrological control, which determines the bulk
surface resistance rs through soil moisture mechanisms. The bulk surface resistance rs has been
calculated backward using Eq. (3) and Ea from SEBAL. The results are presented in Fig. 5, which
shows a distinct seasonal variability of rs. This is consistent with the inter-seasonal variation of the
(es-ea), INDV as well as the river flow regime and the related ground water table fluctuations. Lowest
rs values are associated with the lowest (es-ea) and the highest INDV during the wet months July to
October in accordance with the theory of Eq. (5). The reverse occurs during the dry months of
February to April.
As mentioned earlier, the Sudd wetland is composed of permanent swamps, close to the river
course, and seasonal swamps created by river flooding and rainfall spells. The boundaries of both
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types of swamps are not accurately defined, and vary with time. The availability of water in the
unsaturated zone is an important source of moisture outside the rainy season. A crude calculation of
the amount of water within the root zone (not presented here) demonstrates that the high surface
resistance over the Sudd outside the rainy season between November and April can be attributed to
a dry soil moisture condition, which is related to a lower ground water table.
The aerodynamic resistance ra appears to be much smaller than rs, thus rs dictates the total resistance
for water vapor transport for most of the year over the Sudd. It should be noted that Fig. 5 is based
on manifold SEBAL computations that are based on satellite observations and weather data only.
The results of bio-physical properties are thus obtained. Considering the encouraging consistency,
the results are believed to be highly realistic.
Fig. 5: Monthly fluctuations of aerodynamic ra, surface rs resistances (s/m), rainfall P and inflow Qin (Gm3/month) over the Sudd wetland (monthly values averaged over the years 1995, 1999, 2000).
The temporal variability of the surface resistance rs is further investigated by the spatial analysis for
two months; a dry month of March, and a wet month of August. Fig. 6 reflects a Sudd that has
insufficient moisture in March to keep all vegetation green. It shows the frequency distribution of rs
values for the three years 1995, 1999, and 2000. More pixels have low rs values during the wet
month. The mode (most frequent pixels) for the three years in March lays approximately between
350 to 375 s/m. Wetness over the Sudd in March is mainly provided by the river as rainfall is
negligible. There are small differences of rs between the years, because in all 3 years there is a
drying process. During the wet season (August), rs reduces to very low values. In a wet year, the
mode is 0 s/m only, suggests that in these areas most likely water is ponding at the surface, and
20
wetland vegetations have very high INDV. In relatively dry years; 2000 and 1995, the mode is 50 s/m
and 100 s/m respectively, which means that soil is very wet but that there is less frequent rainfall.
The results of r
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s spatial and temporal variability indicates that substantial parts of the Sudd wetlands
– which have excessive Ea - may not really be inundated. This is an important conclusion, which
indicates that the Sudd is covered with open water only near the river bed. The adjacent wetland
environment undergoes seasonal flooding only.
Fig. 6. Frequency distribution of surface resistance rs (s/m) over the Sudd during the dry month of March and during the wet month of August (1 pixel ~ 1 km2) for the three years 1995, 1999, and 2000.
Given the climatic conditions, and hydrological control over the Sudd, the question is what impact
the variability of the biophysical properties has on evaporation from the Sudd wetland? This is the
discussion of the next section.
4.2 Temporal variation of the Sudd evaporation Monthly Ea values computed by SEBAL averaged over all the Sudd pixels is presented in Annex 2
for the years 1995, 1999 and 2000. The Sudd evaporation is 1460, 1935, and 1643 mm/yr for the
1995, 1999, and 2000, respectively. The year 1995 with 930 mm/yr had the lowest rainfall. The
wettest year was 1999 with 1058 mm/yr. This brief analysis shows that rainfall increases Ea over the
Sudd and that the variation of Sudd Ea is with ΔEa of 475 mm/yr significantly larger than for
rainfall (ΔP is 128 mm/yr). This can be explained by the large water volumes flowing into the plain
and swamps. The size of the area under the influence of floods varies according to rainfall and
inflow, and is thus not constant. The absence of fixed boundaries makes it difficult to define the
exact boundaries of the Sudd wetlands. Since the areal delineation cannot be done on the basis of
21
topography, vegetation types or plant species without extensive field surveys, we define the Sudd
area on the basis of the hydrological processes. The basic hydrological characteristic of a wetland is
that the E
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a is larger than the Ea of surrounding areas that are only rainfed. A map of the Ea can thus
be used to define the boundaries according to a well-defined criterion. The spatial pattern of Ea
(averaged for the three years) is given in Fig. 7. The catchment boundary is defined according to an
Ea threshold of 1550 mm/yr (38,500 km2). Fig. 7 shows that the highest annual evaporation occurs
at the permanent swamps close to the river channels, while the seasonal swamps evaporate
relatively less, but still much higher than the surrounding lands.
Fig. 7: Contour lines of average annual Ea in mm/yr (data presents annual average for the years 1995, 1999, 2000).
The monthly values of Ea averaged over the three years are depicted in Fig. 8. The same figure also
shows the variability of the open water evaporation Ew over the Sudd. Ew has been calculated with
the equation of Penman (1948).
Fig 8: Monthly fluctuation of the Sudd Ea and open water Ew (monthly values in mm/day averaged over the years 1995, 1999, 2000).
While Ew shows clear seasonality in accordance with (es-ea) (see Fig. 4), Ea is extremely stable due
to compensating effects. The possible explanation for the quasi-steady variation of Ea in contrast
with Ew, is that net radiation varies only between 120 to 150 W/m2 and that (es-ea) and rs have
cancelling effects due to their natural feedback mechanisms - a high vapour pressure deficit reduces
the stomatal aperture - as described by Jarvis (1976) and Stewart (1988). The monthly variability of
22
Ea/Ew over the Sudd wetland ranges from 60% in the dry months, up to 90% in the wet season. This
clearly shows that E
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a/Ew cannot be considered constant and is instead a direct function of the
biophysical properties and their seasonal dynamics. It is thus erroneous to assume the Sudd wetland
evaporation is similar to open water evaporation. Whilst in the wet season, the Sudd has behaviour
close to open water evaporation and Ea tend to Ew, this will by absence of continuous floods not
prevail throughout the year; large tracts of seasonal swamps reduce Ea/Ew to 0.6 outside the flood
season.
5 Conclusions The theoretical analysis of wetland evaporation Ea versus open water evaporation Ew using the
Penman-Monteith equation, and a literature review of Ea/Ew from measurements in selected
wetlands around the world, indicates that Ea/Ew is not generic. The Ea/Ew value depends on the
biophysical properties of the given wetland surface, the portion of permanent swamps, and the depth
of the water table. The monthly analysis of the biophysical properties: surface albedo, leaf area
index, roughness height, aerodynamic resistance, surface resistance, and evaporative fraction, over
the Sudd derived from NOAA-AVHRR satellite images using SEBAL, dictate a distinct seasonal
variability of Ea/Ew. The Sudd evaporation Ea doesn’t show much seasonal variability, while open
water evaporation Ew clearly follows the seasonal climatic variation. The quasi-steady state of Ea in
the Sudd is attributed to the lack of seasonality of net radiation and the canceling effect of the vapor
pressure deficit and surface resistance throughout the season. The seasonality of surface resistance
demonstrates that a majority of the Sudd is non-inundated and has a seasonal decaying vegetation
system. Only the lower parts near the river bed are permanently saturated.
23
Consequently, the concept of Ea being equal to Ew does not hold for the marshlands of the Sudd,
which implies that the evaporative depletion from the Sudd needs to be re-examined in view of
earlier assumptions commonly used in the Sudd hydrology. Appropriate attention has to be given to
other wetlands in monsoonal climate systems also, that may have a similar seasonality, e.g. the
Okavango.
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The difference in rainfall between dry (930 mm/yr) and wet years (1058 mm/yr) is 14 % only. The
resulting range of evaporation between dry years (1460 mm/yr) and wet years (1935 mm/yr)
exceeds with 33% the differences in rainfall, because Ea is to a large extent controlled by inflow.
This implies that evaporative depletion of the Sudd is sensitive to local and upstream rainfall
patterns, and that allocation of water to downstream wetlands is a relevant process in integrated
river basin management.
The Penman-Monteith equation appeared to provide a solid physical basis, but the spatial
distributed biophysical properties must be known. It is demonstrated in this paper that these
properties can be derived from remote sensing techniques, in particular the surface resistance to
evaporation that is by far the most important parameter of complex heterogeneous vegetation
systems.
Acknowledgement The material of this paper constitutes part of a larger research study on the moisture recycling over
the Nile Basin funded by the International Water Management Institute (IWMI), the International
Institute for Geo-Information Science and Earth Observation (ITC), and the UNESCO-IHE. Part of
the study has been carried out at the Royal Meteorological Institute of The Netherlands (KNMI).
24
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Annex 1: Measured biophysical properties over selected wetlands around the world:
1 2
No. INDV
(-)
r0
(-)
rs
(s/m)
z0m
(m)
Λ
(-) Vegetation type Source
1 0.70 Papayrus
(old papayrus)
Rijks (1969)
Uganda
2 0.12-0.16 Sphagnum-sedge bogs Berglund and Mace (1972)
Minnesota, USA
3 0.18 0.0 Water hyacinth Van der Weert and
Kamerling (1974), Surinam
4 1.9-2.5 50-107 0.04 Sedge (Carex paleacea) Lafleur and Rouse (1988)
Canada (Backshore)
5 1.9-2.5 39-87 Marches: carex paleacea, Lafleur and Rouse (1988)
Canada (Open water Marches)
6 5.0 24-37 0.41 Woodland (Alnus rugosa,
Salix bebbianna, others)
Lafleur and Rouse (1988)
Canada (Woodland)
7 0.4-0.7 0.11-0.17 80–250
0.76 – 1.0
Sphagnum (papill osum
and majus), vascular
plants
Kim and Verma (1996)
Minesota, USA
8 1.25-3.9 150-608 0.091 0.16-0.25
Raised peat bog
Sphagnum (Empodisma
minus)
Campbell and
Williamson (1997)
New Zealand
9 0-5
0.67– 0.74
Common arrowhead,
yellow pond lily, cattail
Souch et al. (1998)
Indiana USA
32
10 0.17 0.009 0.99 Water hyacinth Ashfaque (1999), pp-A10
11 1.2-2.6 0.12-0.16
0.27-0.38
(calculated
as 0.123h)
0.75 – 1.0
reed grass (Phragmites
australis) early and peak
growth
Bruba et al. (1999)
Nebraska, USA.
12 8-155 Natural wetland grass Gavin and Agnew (2000)
England
13 0.16 25-100
0.07-0.08
(calculated
as 0.123h)
0.78 Palm, flooded
Herbaceous (unburned)
Jose et al. (2001)
Venzuela
14 50 0.73 Maiden cane, mock
bisgop’s weed, dog fennel
Jacobs et al. (2002)
(wet period)
Florida, USA
Avg.
std
2.4
1.45
0.16
0.02
86
97
0.16
0.17
0.73
0.24
1 2
3
4
33
Annex 2: Monthly evaporation values Ea for a 38*106 ha area in the Sudd during 3 years.
1 2
3
Month Ea 1995
mm/day
Ea 1999
mm/day
Ea 2000
mm/day
Ea
Avg.
Ea/Ew
1995
Ea/Ew
1999
Ea/Ew
2000
Ea/Ew
Avg.
Jan 3.7 4.6 4.6 4.29 0.55 0.55 0.58 0.56
Feb 3.7 5.6 4.3 4.52 0.50 0.64 0.59 0.58
Mar 4.3 4.9 4.4 4.55 0.49 0.59 0.54 0.54
Apr 4.1 6.2 4.9 5.05 0.54 0.65 0.62 0.60
May 4.3 5.9 4.8 4.98 0.67 0.79 0.74 0.73
Jun 4.1 5.3 4.5 4.61 0.74 0.81 0.72 0.76
Jul 4.0 5.2 4.2 4.46 0.82 0.89 0.8 0.84
Aug 4.1 5.3 4.7 4.72 0.84 0.93 0.91 0.89
Sep 4.4 5.5 4.4 4.74 0.84 0.93 0.78 0.85
Oct 4.1 4.9 4.9 4.63 0.75 0.87 0.8 0.81
Nov 3.8 5.5 4.1 4.48 0.63 0.77 0.64 0.68
Dec 3.6 4.8 4.3 4.23 0.57 0.65 0.63 0.62
Avg. 4.0 5.3 4.5 4.61 0.66
0.76
0.70
0.70
4
34
FIGURES 1 2 3 4 5 6 7 8 9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Fig. 1: Location of the Sudd wetland Fig. 2: Variability of Ea/Ew (-) for different wind speeds uz,(m/s) and surface resistances rs (s/m) using P-M equation, and fixed climatic condition over a wetland and open water. Fig. 3: Monthly fluctuations of evaporative fraction Λ (-), leaf area index INDV (-), albedo r0 (-), emissivity ε0 (-), and roughness height z0m (m) over the Sudd wetland (monthly values averaged over the years 1995, 1999, 2000). Fig. 4: Monthly fluctuations of climate parameters: net surface radiation Rn (W/m2), vapor pressure deficit (es-ea) (kPa) and slope of the vapor pressure curve Δ (kPa/ C°) over the Sudd wetland (monthly values averaged over the years 1995, 1999, 2000). Fig. 5: Monthly fluctuations of surface rs, aerodynamic ra resistances (s/m), inflow Rin and rainfall P (Gm3/month) over the Sudd wetland (monthly values averaged over the years 1995, 1999, 2000). Fig. 6: Frequency distribution of surface resistance rs (s/m) over the Sudd during the dry month of March and during the wet month of August (1 pixel ~ km2) for the three years 1995, 1999, and 2000. Fig. 7: Contour lines of average annual Ea in mm/yr (data presents annual average for the years 1995, 1999, 2000). Fig 8: Monthly fluctuation of the Sudd Ea and open water Ew (monthly values in mm/day averaged over the years 1995, 1999, 2000).
35
1 2 3 4 5 6 7 8 9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
Fig. 1: Location of the Sudd wetland
0
0.5
1
1.5
2
0 2 4 6 8
Ea/Ew (-)
u (m/s)
(a)
0
0.5
1
1.5
2
0 20 40 60 80 100
Ea/Ew (-)
ra (m/s)
(b)rs=50 s/m
rs=100 s/m
rs=150 s/m
rs=200 s/m
rs=400 s/m
Fig. 2: Variability of Ea/Ew (-) for different wind speeds uz,(m/s) and surface resistances rs (s/m) using P-M equation, and fixed climatic condition over a wetland and open water.
28 29 30
36
0
0.2
0.4
0.6
0.8
1
1.2
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0
0.01
0.02
0.03
0.04
0.05
0.06
Λ, INDV, ,r0,
ε 0 (-)
z0m (m)
ΛINDV
r0ε0
z0m
1 2 3 4 5
6
7
Fig. 3: Monthly fluctuations of evaporative fraction Λ (-), leaf area index INDV (-), albedo r0 (-), emissivity ε0 (-), and roughness height z0m (m) over the Sudd wetland (monthly values averaged over the years 1995, 1999, 2000).
80
100
120
140
160
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0
1
2
3
4
Rn (W/m2)
’es-ea’ (kPa),
Δ (kPa/
ο C)
Rn
(es-ea)
Δ
8 9
10 11 12
Fig. 4: Monthly fluctuations of climate parameters: net surface radiation Rn (W/m2), vapor pressure deficit (es-ea) (kPa) and slope of the vapor pressure curve Δ (kPa/ C°) over the Sudd wetland (monthly values averaged over the years 1995, 1999, 2000).
37
1 2
0
100
200
300
400
500
600
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0
1.5
3
4.5
6
7.5
9
ra, rs (s/m)
P, Rin (Gm3/month)
rarsP
Rin
3 4 5 6 7
8 9
Fig. 5: Monthly fluctuations of surface rs, aerodynamic ra resistances (s/m), inflow Rin and rainfall P (Gm3/month) over the Sudd wetland (monthly values averaged over the years 1995, 1999, 2000).
0
200
400
600
800
1000
1200
0 100 200 300 400 500 600
no. of pixels
rs (s/m)
Aug
Mar
199519992000
0
200
400
600
800
1000
1200
0 100 200 300 400 500 600
no. of pixels
rs (s/m)
Aug
Mar
10 11 12 13 14
15 16
Fig. 6. Frequency distribution of surface resistance rs (s/m) over the Sudd during the dry month of March and during the wet month of August (1 pixel ~ km2) for the three years 1995, 1999, and 2000.
38
1
2 3 4 5 6 7
Fig. 7: Contour lines of average annual Ea in mm/yr (data presents annual average for the years 1995, 1999, 2000).
2
4
6
8
10
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0.2
0.4
0.6
0.8
1
Ea, Ew (mm/day)
Ea/Ew (-)
Ea
Ew
Ea/Ew
8 9
10 11
Fig 8: Monthly fluctuation of the Sudd Ea and open water Ew (monthly values in mm/day averaged over the years 1995, 1999, 2000).
39
