Journal of Hydrology 375 (2009) 204–216
Contents lists available at ScienceDirect
Journal of Hydrology
journal homepage: www.elsevier.com/locate/jhydrol
Towards an understanding of coupled physical and biological processes
in the cultivated Sahel – 1. Energy and water
David Ramier a, Nicolas Boulain a, Bernard Cappelaere a,*, Franck Timouk b, Manon Rabanit a, Colin R. Lloyd c,
Stéphane Boubkraoui d, Frédéric Métayer d, Luc Descroix d, Vincent Wawrzyniak a
a
IRD - Hydrosciences, Montpellier, BP 64501, 34394 Montpellier Cedex 5, France
IRD/CESBIO, 18 Avenue Edouard Belin, bpi 2801, 31401 Toulouse Cedex 9, France
c
CEH, Crowmarsh Gifford, Wallingford OX10 8BB, UK
d
IRD/LTHE, BP 53, 38041 Grenoble Cedex 09, France
b
a r t i c l e
i n f o
Keywords:
Eddy covariance
Surface energy budget
Hydrologic cycle
Millet
Fallow savanna
Semi-arid
s u m m a r y
This paper presents an analysis of the coupled cycling of energy and water by semi-arid Sahelian surfaces,
based on two years of continuous vertical flux measurements from two homogeneous recording stations
in the Wankama catchment, in the West Niger meso-site of the AMMA project. The two stations, sited in a
millet field and in a semi-natural fallow savanna plot, sample the two dominant land cover types in this
area typical of the cultivated Sahel. The 2-year study period enables an analysis of seasonal variations
over two full wet–dry seasons cycles, characterized by two contrasted rain seasons that allow capturing
a part of the interannual variability. All components of the surface energy budget (four-component radiation budget, soil heat flux and temperature, eddy fluxes) are measured independently, allowing for a
quality check through analysis of the energy balance closure. Water cycle monitoring includes rainfall,
evapotranspiration (from vapour eddy flux), and soil moisture at six depths.
The main modes of observed variability are described, for the various energy and hydrological variables
investigated. Results point to the dominant role of water in the energy cycle variability, be it seasonal,
interannual, or between land cover types. Rainfall is responsible for nearly as much seasonal variations
of most energy-related variables as solar forcing. Depending on water availability and plant requirements, evapotranspiration pre-empts the energy available from surface forcing radiation, over the other
dependent processes (sensible and ground heat, outgoing long wave radiation). In the water budget, preemption by evapotranspiration leads to very large variability in soil moisture and in deep percolation,
seasonally, interannually, and between vegetation types.
The wetter 2006 season produced more evapotranspiration than 2005 from the fallow but not from the
millet site, reflecting differences in plant development. Rain-season evapotranspiration is nearly always
lower at the millet site. Higher soil moisture at this site suggests that this difference arises from lower
vegetation requirements rather than from lower infiltration/higher runoff. This difference is partly compensated for during the next dry season. Effects of water and vegetation on the energy budget appear to
occur more through latent heat than through albedo. A large part of albedo variability comes from soil
wetting and drying. Prior to the onset of monsoon rain, the change in air mass temperature and wind produces, through modulation of sensible heat, a marked chilling effect on the components of the surface
energy budget.
Ó 2008 Elsevier B.V. All rights reserved.
Introduction
The role of rapidly changing Sahelian land surfaces in the
dynamics of the West African monsoon system is generally
thought to be major, but still very poorly understood. Since the
pioneering work of Charney (1975), effects on climate of land use
(Xue and Shukla, 1993) or soil moisture (Koster et al., 2004) in this
* Corresponding author. Tel.: +33 467 149 017; fax: +33 467 144 774.
E-mail address: [email protected] (B. Cappelaere).
0022-1694/$ - see front matter Ó 2008 Elsevier B.V. All rights reserved.
doi:10.1016/j.jhydrol.2008.12.002
semi-arid area have been suggested through the use of GCMs. A
major effort towards a better understanding of these links has been
undertaken under the African Monsoon Multidisciplinary Analyses
project (AMMA; Redelsperger et al., 2006). Such an objective requires to significantly improve our knowledge of the functioning
of the terrestrial subsystem itself, in which complex physical and
biological processes are tightly coupled. To that aim, an important
component of the project is to carry out a comprehensive and
coherent in-situ surveying of the fluxes and stocks of energy and
matter that compose the basic geo–eco cycles in this area. Data
D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
sets of this kind are key to supporting in-depth analyses of the land
surface exchange processes and associated model development/
validation. For understandable reasons, they are particularly scarce
and difficult to acquire in Africa. In the West Niger area of the cultivated Sahel, the HAPEX-Sahel experiment of 1992 (Goutorbe
et al., 1997) yielded abundant data and study results (Dolman
et al., 1997), but denser, larger in area, longer in time, and more
consistent sampling of more variables are now needed to progress
towards objectives. HAPEX-Sahel sampling was generally limited
in time to only very short periods at the end of the 1992 rain season, and spatial location of the various types of instruments was
rather dispersed, making integration of variables difficult.
This paper presents an analysis of year-round dynamics of the
local energy and water cycles and their interactions, for the two
land cover types that now dominate in this area, namely semi-natural and cultivated. This analysis is based on the first 2 years of
data from the experimental setup installed in West Niger in
2005, more specifically from two surface flux stations and associated instruments located on a fallow and a millet site, respectively.
HAPEX-Sahel results (e.g., Lloyd, 1995; Verhoef et al., 1996; Gash
et al., 1997; Kabat et al., 1997; Lloyd et al., 1997; Braud, 1998)
pointed to a strong variability in surface exchanges but suffered
from the limitations mentioned above. A first driver of this flux
variability is the variability of rainfall. It is particularly large in
the region at any timescale including annual (Lebel et al., 2003),
and is a major factor of seasonality with a short wet season and
a long, totally-dry season. A dataset that covers two climatically
contrasted years, hence duplicating each season, offers a first insight into this variability. Land use is another important factor of
variability for these geo–eco cycles, which is investigated here
through thorough, homogeneous monitoring of the two major land
cover types. Besides the use of more accurate gas analysers, this
extended sampling distinguishes the work presented here from
the few other previous experiments in the region (e.g., Wallace
et al., 1991, in Niger; Schüttemeyer et al., 2006, and Bagayoko
et al., 2007, under the more humid Sudanian climate of the Volta
Basin in Ghana and Burkina-Faso, respectively). The seasonal vari-
205
ation of the surface energy balance was analysed by Verhoef et al.
(1999) for a tiger-bush and a savanna site in Niger, but only partially from direct measurements. In many regards, the dataset
being acquired as part of the AMMA programme in West Niger
stands as one of the largest and richest surface-energy data set in
West Africa.
Together with the energy and water cycles, those of vegetation and carbon, all in direct interaction, are investigated jointly,
and presented in the companion paper by Boulain et al. (2009).
While this new dataset serves here as the basis for a data-driven
analysis of physical and biological processes involved in the control of the local energy and water cycles, it is also a major information source for other works of the AMMA programme in this
area, including modelling (e.g., Boone and de Rosnay, 2007; Pellarin et al., 2009; Saux-Picart et al., accepted for publication;
Saux-Picart et al., 2009) or scaling studies (Boulain et al., 2009;
Ezzahar et al., 2009). Unlike most previous works in the region,
which focused on specific components or aspects of these cycles
at the land surface, this paper presents a more global and comprehensive view on their coupled dynamics, offered by the
dataset.
Materials and methods
Study area
The study area is part of the Wankama catchment (Fig. 1; 2.4°E,
13.4°N), 60 km east of Niamey, Niger. This semi-arid site belongs to
the AMMA-Niger observatory (Cappelaere et al., 2009), one of three
meso-sites along the West African latitudinal transect (Lebel et al.,
2009). It is a 1.9 km2 endoreic catchment, typical of the cultivated
Sahel (Peugeot et al., 2003). It essentially consists of a sandy hillslope (Fig. 1d) with slopes below 2%. Precipitation is limited to a
short monsoon season from June to September, with an annual
mean of 560 mm for the years 1905–2004 in Niamey (standard
deviation: 135 mm), and a very strong year-to-year and spatial
variability. Like the whole Sahel, the region was hit by a severe
Fig. 1. The Wankama catchment in the AMMA-Niger meso-site. Location of meso-site (square) in: (a) West Africa; (b) the Niger Republic; (c) Map of Wankama catchment
with location of EC systems (squares); and (d) Toposequence of Wankama catchment.
206
D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
drought in the 1970s and 1980s, with an average rain shortage as
high as 30%. The more recent period shows signs of a return to a
more normal interannual mean, but with still only 479 mm/year
in Wankama over the 1992–2006 period (standard deviation:
90 mm; Fig. 2). Rainfall occurs as short, intense convective storms,
which can produce strong, ephemeral surface runoff, flowing down
to a temporary endoreic pond at the catchment outlet (Fig. 1c,d).
Depth to the water table varies from 15 to 60 m.
Extensive rain-fed cultivation of millet is by far the main, if not
the only crop grown. Millet fields presently cover 58% of the catchment’s surface area. Traditional techniques are used, with little
chemical fertilizer and no pesticides. Shrubs and weeds are manually eliminated before the rain season. Some trees are preserved
along field edges. Hand-hoe weeding may be repeated once or
twice in the season, but some grass often persists. Sowing starts
with the first 5–10 mm rainfall (enough to wet the first 5 cm of
soil), and can be repeated several times as long as rainfall remains
erratic. It is performed as pockets, with a 1-m to 1.4-m spacing.
Mature millet is 2–3 m high at the study site. Harvest is done
shortly after the end of the rain season, in September or October,
removing the whole plant (ear and stem) from the field, and leaving bare soil through the dry season.
Significant fallow periods are necessary in this traditional agricultural system. In the catchment, fallow now represents 23% of
the total surface area. Most fallow fields are no more than five-year
old, which is now typical of the Niamey region. They include a
shrub layer with Guiera senegalensis as the dominant species (Meir
et al., 2007), and an annual grass layer whose composition mostly
depends on the rain distribution at the season beginning. The average height of the shrub layer is 2 m, against 0.6 m for the grass
layer. Shrub density averages around 700 individuals per hectare.
Trees exist as isolated individuals or small groups. Fallows represent the main energy supply for the local population. More details
on the vegetation cover can be found in Boulain et al. (2009).
Experimental setup
Instruments used for this paper are the following: (i) two eddy
covariance (EC) stations, measuring surface fluxes of sensible heat,
latent heat (i.e., evapotranspiration), momentum and CO2, together
with 4-component radiation, soil heat flux and profiles of soil temperature and moisture, for the two dominant land cover types (millet crop and fallow savanna; Fig. 1); (ii) a tipping-bucket recording
rain gauge, midway between the two stations; and (iii) eight vegetation monitoring plots, scattered over the catchment according to
land cover types (for description and methodology, see Boulain
et al., 2009). This setup started operating in June 2005. Table 1 summarizes the main characteristics of the duplicated EC systems and
associated instruments. EC data was processed with the EdiRe software (Version 1.4.3.1167, R. Clement, University of Edinburgh),
based on CarboEurope recommendations (Mauder and Foken,
2004), including despiking, double rotation, cross-correlation for
derivation of time lag between the sonic anemometer and the gas
analyser, spectral corrections, Webb corrections and atmospheric
stability test, with no gap filling. Fluxes as well as all other energy
and associated data were averaged over 30-min periods. Direct
Cumulated rain (mm)
700
600
2006
500
2005
400
300
200
100
0
april
may
june
july
august
september
october
Fig. 2. Cumulative rainfall at Wankama for the 15 rain seasons of the 1992–2006 period (2005: thick grey line; 2006: thick black line; other years: thin grey lines).
Table 1
Characteristics of the eddy covariance (EC) system and associated instruments at both sites (millet crop and fallow savanna).
Instrument
Measurements
Height or depth
Storage
interval
Above ground
Campbell CSAT-3 sonic anemometer (Campbell Scientific,
Inc., Logan, USA)
LI-COR LI-7500 infrared gas analyser (LI-COR Biosciences,
Lincoln, USA)
Kipp & Zonen CNR1 radiometer (Kipp & Zonen, Delft, The
Netherlands)
Vaisala HMP45C (Vaisala Oyj, Helsinki, Finland)
3D wind speed and direction
Sonic air temperature
CO2 and H2O concentrations
Air pressure
Shortwave (0.3–2.8 lm) and longwave (5–50 lm) incoming
and outcoming radiation
Air temperature and relative humidity
5.1 m (millet) and 4.95 m
(fallow)
5.1 m (millet) and 4.95 m
(fallow)
2.5 m (millet) and 3.4 m
(fallow)
2m
20 Hz
Soil measurements
Campbell CS616 water content reflectometers (6)
Soil volumetric water content
Campbell T108 temperature probes (6)
Soil temperature
Hukseflux HFP01SC heat flux plates (3, averaged) (Hukseflux,
Delft, The Netherlands)
Surface soil heat flux
.1, .5, 1, 1.5, 2 and
2.5 m
.1, .5, 1, 1.5, 2,
and 2.5 m
.05 m
20 Hz
1 min
1 min
1 min
1 min
1 min
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D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
measurements of soil heat flux were checked against estimates at
5 cm derived from soil temperature gradients, using surface temperature inverted from measured outgoing longwave radiation.
Study period and meteorological setting
Results presented in this paper cover the mid-June 2005–midJune 2007 period, thereby including two rain seasons (2005 and
2006) as well as the two subsequent dry seasons. Annual rainfall
was 495 mm from 47 events in 2005, against 572 mm in the 42
events of 2006 (Fig. 2). This makes the two wet seasons contrasted
in terms of total rainfall (difference amounting to one standard
deviation of the 1992–2006 period) and of mean event depth. Contrasts are even larger with respect to rain distribution along the
season (Fig. 2). The 2005 season had a rather early start, while
2006 had a very late one as well as an earlier end, making the
2006 season very short (115 days, i.e., one third less than the
165 days of 2005). Hence, the 2005 wet season was characterized
by comparatively smaller, sparser rain events, separated by longer
Air temperature (°C)
a
dry spells. In contrast to the millet crop, this rain pattern had significant adverse effects on the natural vegetation, as compared to
2006 (Boulain et al., 2009). Maximum event rainfall was
69 mm in 2006, against 49 mm in 2005, both in the wet month
of August. Variations of air temperature, relative humidity, and vapour pressure deficit (VPD) during the study period are shown in
Fig. 3. Also displayed are the rain event occurrences, showing the
late onset of the 2006 monsoon. The intertropical discontinuity
(ITD), materializing the shift in air mass and wind direction (from
east to south-west), crossed the study area in May 2006, and
around mid-April in 2007. The wet-season rise in humidity and fall
in temperature start several weeks before the first rainfalls, with a
lag of around two weeks. During the pre- and post-monsoon periods, sharp humidity variations are observed, linked to changes in
wind direction (Pagès et al., 1988), including daily cycles. Combining variations in temperature and humidity, VPD displays wet season lows below 1 kPa, against highs above 5 kPa in early May. A
relative low occurs shortly after the boreal winter solstice (December 24, 2005; January 1, 2007), due to lower temperatures.
40
35
30
25
20
15
Relative humidity (%)
b
100
80
60
40
20
0
VPD (kPa)
c
6
4
2
0
15/6/05
14/9/05
14/12/05
15/3/06
15/6/06
Date
14/9/06
14/12/06
15/3/07
15/6/07
Fig. 3. Time course of daily air temperature (a), relative humidity (b), and vapour pressure deficit (c), at the fallow site. Lines are 15-day moving averages. Bars at top
represent rain event occurrences.
208
D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
Results
Radiation
a
400
Sw in (W m -2)
Together with the seasonal cycle of potential, clear-sky solar
radiation Rso (estimated using Allen et al.’s relationship, 1998),
Fig. 4(a–d) shows the variations of daily components of the radiation budget at the fallow and millet stations: short wave incoming
(Swin) and outgoing (Swout), long wave incoming (Lwin) and outgoing (Lwout) radiation, respectively. Due to their close proximity,
incoming radiation at the two stations are nearly identical and only
the fallow site is presented.
The potential radiation Rso is highest (above 330 W m2)
through a long period spanning from mid-April to end of August,
then decreases to a low of 254 W m2 at the boreal winter solstice.
The upper envelope for the Swin values follows logically the same
300
overall cycle, with (i) virtually no loss from Rso during much of
the dry season (November to March, inclusive) and (ii) a loss factor
from April to October that appears well in phase with the monsoon
period, as timed by the seasonal relative humidity signal of Fig. 3b.
Occasional sharp drops in Swin are the consequences of major rain
or cloud events during the wet season, and of dust/aerosols events
in the dry season. Much less scattered than Swin, Lwin (Fig. 4c) is
also seasonally in phase with Rso, albeit with a few weeks lag indicating the thermal inertia of the Earth system. Except for a peak in
April 2006 due to highs in Swin and albedo (see ‘‘Albedo”), Swout
displays a relatively flat upper envelope (Fig. 4b), owing to the
phase lag between Swin and albedo. Fluctuations of Lwout are well
related to those of Lwin, except for the rain season.
Fig. 5a shows the net radiation Rn at both sites, together with
the combination Swin Swout + Lwin hereafter referred to as surface
forcing radiation Rf (plotted for the fallow site). The interest for Rf
200
100
0
b
120
Sw out (W m -2)
100
80
60
40
20
0
c
500
Lw in (W m -2)
450
400
350
300
250
Lw out (W m -2)
d
600
550
500
450
400
15/6/05
14/9/05
14/12/05
15/3/06
15/6/06
Date
14/9/06
14/12/06
15/3/07
15/6/07
Fig. 4. Time course of the four daily radiation components at the fallow (black dots) and millet (grey dots) sites. Line in (a) is potential solar radiation, Rso. Lines in (b) and (d)
are 15-day moving averages. Bars at top represent rain event occurrences.
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D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
700
250
600
Net radiation (W m -2)
200
500
150
400
300
100
200
50
100
0
b
Forcing radiation (W m -2)
a
0
0.5
Albedo (-)
0.4
0.3
0.2
0.1
15/06/05 14/09/05 14/12/05 15/03/06 15/06/06 14/09/06 14/12/06 15/03/07 15/06/07
Date
Fig. 5. (a) Daily forcing radiation Rf at fallow site (crosses) and net radiation Rn at fallow (black dots) and millet (grey circles) sites; (b) daily albedo at fallow (black) and millet
(grey) sites. Lines are 15-day moving averages. Bars at top represent rain event occurrences.
arises from the fact that, compared to Rn, it is not as directly interacting with the other, complementary components of the surface
energy balance (see ‘‘seasonal dynamics of surface energy cycle,
and interactions between components”). Both variables display
quite simple and smooth, yet distinct, seasonal patterns. Strong
mono-modal seasonality results from the summertime concomitance of high incoming with low outgoing radiation, in relation
to albedo and surface temperature. Whereas Rn exhibits a rather
brief, sharp peak in the second half of the rainy season, the summer
highs for Rf spread much longer, in closer relationship with the solar signal. In the dry season, short-timescale fluctuations in component radiations, linked to aerosol events (e.g., early January 2007),
are largely attenuated in Rn and Rf, due to compensation between
Swin and Lwin. A similar effect occurs in the pre-monsoon period
of transition from the dry to the wet season, when a drop occurs
in Swin concurrent with a peak in Lwin, presumably due to moister
air.
Albedo
Through much of the dry season, albedo (ratio of Swout to Swin,
Fig. 5b) displays values well above 0.3 at both sites, indicating that
a large fraction of the surface consists of dry bare soil. During the
short rain season, it is driven down by vegetation growth and soil
wetting, reaching lower values at the fallow site. A strong anti-cor-
relation with Rn comes more from the seasonal concomitance of
high insolation with rain and vegetation, and hence low Lwout, than
from the direct effect of Swout.
In the early monsoon period before rainfall actually arrives, albedo starts a gradual decrease, likely due to the spectral effect of
increasing air humidity (which shifts incident radiation composition from the near infrared to the visible domain where spectral albedo is lower, Samain et al., 2008). First rains produce more
scattered albedo values, related to changes in surface color from
wetting and drying sequences. In 2005, and to a lesser extent in
2006, a dry spell in July produced a new short period of albedo increase. During the rain season proper, albedo follows a very markedly decreasing general trend, but with significant short time scale
variability due to the wetting–drying effect. Day-to-day change in
daily albedo can amount to over half the whole seasonal variation,
while fluctuations can even be more pronounced at sub-daily
scale: a single storm can produce a drop in semi-hourly albedo of
over 0.15 in the first part of the wet season. Return to antecedent
value takes from 1 day at the season beginning to a few days in
the heart of the season. At this time, soil moisture and, most of
all, vegetation development smooth out variations due to storm
occurrences. Minimum values are reached in September (mid-August for the 2005 millet), together with the peak in leaf cover fraction (Boulain et al., 2009). Periods with no or little rain in the
wet season produce new, short-lived increases in albedo at both
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D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
sites, most notably in 2005. In addition to soil drying, this can logically be interpreted as periods of partial wilting of the grass layer,
and possibly of the millet or brush layer. The trend of albedo decrease resumes quickly afterwards, when a new rainstorm occurs.
From the albedo data, no weeding of the millet crop is apparent
during the growing season. Very little cultivation is performed on
millet in this area, often being limited to just soil tillage prior to
or at the start of the rain season (Peugeot et al., 2003).
Because it keeps a larger fraction of bare soil, the millet site almost always displays higher albedo than the fallow, except towards the end of the dry season. Differences build up rapidly
during the first part of the rain season, due to a more rapid drop
of fallow albedo, to reach as much as 0.07 in the second part of
the season (late August–early September). Dry-season highs are restored earlier for millet (by end of November) than for fallow,
although the latter’s rise does seem to be much faster than at the
more northern grassland site of Agoufou (Samain et al., 2008).
Some of the dry-season short drops in Swin (Fig. 4a) can be
traced in the albedo signal as very sudden and significant spikes
at both sites (such as those peaking on March 8, 2006, or on January 2, April 2, and May 28, in 2007), making daily albedo rise by as
much as 0.05. These short peaks are generally associated with major dust events (e.g., March 8, 2006; Slingo et al., 2006), which can
impact albedo by changing the spectral composition and the direct
versus diffuse proportions of incident radiation (Samain et al.,
2008).
Fig. 6 shows the variations in measured fluxes of sensible and
latent heat, H and LE, for the fallow (Fig. 6a) and millet (Fig. 6b)
sites. These are daytime contributions to daily fluxes (24-h averages), since nighttime boundary layer conditions are rarely suitable
for EC measurements. Nighttime fluxes are generally much smaller, especially for latent heat. Also plotted is the reference daily
evapotranspiration (ET0, 15-day moving average), as calculated
by the FAO Penman–Monteith formula (Allen et al., 1998). In the
wettest periods, measured evapotranspiration is close to ET0 for
fallow but largely below for millet, and roughly follows ET0 variations. This suggests a control by the climatic demand for a given
land cover type, whereas control is mostly by soil water during
the dry season and dry spells of the rain season.
The fallow site always evaporates significantly more water than
the millet site through the growing season. This is especially so in
the second part of the 2006 rain season, when, unlike the fallow
vegetation, the millet crop was not able to take advantage of the
abundant rainfall, because of insufficient plant development (see
Boulain et al., 2009). In all cases however, LE does largely dominate
H through the heart of the growing season (July–September). Higher evapotranspiration by natural over cultivated vegetation was
also reported in this area by Gash et al. (1997) and Wallace et al.
(1991). Conversely, rain-season H is higher at the cultivated site.
At both sites, but more so at the millet site (which shows more var-
200
Heat flux - fallow (W m-2)
6
150
5
4
100
3
2
50
1
b
0
0
200
7
Heat flux - millet (W m-2)
6
150
5
4
100
3
2
50
1
0
15/6/05
14/9/05
14/12/05
15/3/06
15/6/06
14/9/06
14/12/06
15/3/07
Evaporated water depth - fallow
(mm day -1)
7
Evaporated water depth - millet
(mm day -1)
a
Eddy fluxes
0
15/6/07
Date
Fig. 6. Daily(*) sensible heat flux (black dots) and latent heat flux (grey dots) at fallow (a) and millet (b) sites. Lines are 15-day moving averages. Thin black line on top of
each graph is 15-day average reference evapotranspiration ET0. Bars at top represent rain event occurrences. Right axes express values in equivalent evaporation fluxes.
((*): daytime 24-h averages).
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D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
iability in relation to a less developed rooting system), the effect of
the rainfall pattern within the wet season is clearly visible, particularly for the alternation of dry and wet spells during the 2005 season. At the end of the wet season, the rapid LE drop is
counterbalanced by a concurrent H increase. The latter is very
smooth at the millet site while transitions are more abrupt at the
fallow site. Because there is more soil water left at the end of the
wet season at the millet site (see ‘‘Soil water”), the ranking of the
two sites in LE is reversed, compared to the rain season, through
the whole recession phase in the first part of the dry season. LE
is extremely small during the second part of the dry season, when
water is accessible only to very deeply-rooted trees.
Ground heat
Fig. 7 shows recorded variations in daily soil temperatures (at
0.1, 1.0, and 2.5 m depths) at the fallow site, and heat fluxes (at
0.05 m depth; positive into the soil) for both sites. Temperatures
are very similar at the millet site (not shown). Like air temperature,
their seasonal pattern is bimodal with a summer low between
spring and fall highs. Hence, the temperature profile inverts several
times per year over the 2.5 m monitoring depth (downward gradient when temperatures increase, and vice-versa). The shallow
a
depth of heat flux measurements (5 cm) minimizes the deviation
from surface flux G for time steps in the order of days or above.
From the graph of measured daily heat flux (Fig. 7b) and differences
in daily soil temperatures with depth (Fig. 7a), it can be inferred
that the ground is mostly releasing heat in November–December–
early January, when soil temperatures are decreasing, and storing
in March–April–May when soil temperatures are rising. Things
are less clear in the monsoon (and pre-monsoon) period, with
greater day-to-day variability, due to the succession of wet and
dry spells for the topsoil and to the variability of LE. Dry spells tend
to increase ground heat (e.g., the rather long dry spell in July 2005),
whereas moister soil favours heat release (e.g., mid July and August–early September of 2006). Hence, an abundant monsoon season will decrease heat storage, whereas a deficient rain season
might result in increased ground storage. Smaller topsoil temperature gradients than in the rest of the year produce stronger flux
intensities, especially on the negative side (soil heat release) when
moisture is higher. Finally, a new short period of ground storing occurs at the switch from the wet to the dry season, in October. At the
daily timescale, ground heat flux is relatively small compared to the
other energy fluxes: in absolute mean, it is less than 7% of the sum
H + LE. At a multi-day scale, it becomes even smaller, as can be seen
in Fig. 7b for the 15-day time step. Differences between sites are
45
Soil temperature (°C)
40
35
30
25
20
b
20
Soil heat flux (W m-2)
10
0
-10
-20
-30
-40
15/6/05
14/9/05
14/12/05
15/3/06
15/6/06
14/9/06
14/12/06
15/3/07
15/6/07
Date
Fig. 7. (a) Daily soil temperature at fallow site, at 0.1 m (thin black), 1 m (grey), and 2.5 m (thick black) depths. (b) Daily soil heat flux (positive downward) at fallow
(black) and millet (grey) sites, lines are 15-day moving averages. Bars at top represent rain event occurrences.
D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
rather small. The orders of magnitude of ground heat fluxes found
here are quite similar to those reported by Verhoef et al. (1999).
a
200
LE + H + G - fallow (W m -2 )
212
150
Energy budget
Rn ¼ LE þ H þ G
ð1Þ
However, several practical reasons preclude perfect closure (Foken
et al., 2006), e.g., spatial scale discrepancies between measurements, and spatial heterogeneities (including farmer effects); storage between measurement levels (canopy and superficial soil);
so-called eddy flux losses; difficulties with ground flux estimation
(Heusinkveld et al., 2004; Guyot et al., 2009). Balance shortfalls
commonly stand between 10% and 40% of the available energy (Foken et al., 2006; Mauder et al., 2006). The relative effect of unaccounted storage, as well as of random errors, can potentially be
minimized by increasing the time step at which Eq. (1) is considered. However, because atmospheric conditions during the night
are often inadequate for EC measurements, the analysis is performed here with daily daytime fluxes. For each site, Fig. 8 compares the two sides of Eq. (1). Closure is quite satisfactory,
especially at the fallow site. Mean residuals (LE + H + G Rn) are
3.6 and 14.2 W m2 at the fallow and millet sites, respectively,
while root mean square residuals are 14.7 and 19.2 W m2, respectively. Absolute residuals represent, on average, 9.6% of net radiation for fallow and 12.9% for millet. For the former, 60% of
residuals are below 10% (considered as very good closure by
Schüttemeyer et al., 2006), and 92% are below 20%, against 45%
and 77% for the latter, respectively. The negative bias is likely due
to the effect of positive storage, in the shallow soil and canopy, during day time. Residuals do not seem to be particularly related to
seasons. The equivalent of Fig. 8 for day-round data at 30-min timestep (not shown) also indicates rather good closure of Eq. (1) at that
short timestep, with usually some positive storage during day time
and destorage overnight. Given these results and what is commonly
obtained with this type of instrumentation, it can reasonably be
concluded that precision on the various component fluxes is
satisfactory.
Soil water
Fig. 9 shows the variations in soil moisture measured at three
depths at the two sites, namely 0.10, 0.50, and 2.5 m. At the
smaller depth, there is very large short-timescale variability
throughout the rain seasons, showing that significant drying occurs between most rain events. This time variability largely supersedes differences between sites and years. At the fallow site, much
less water infiltrated down to the 0.50 m depth in the 2005 than
in the 2006 rain season, partly because of the lower total rainfall
amount but predominantly because of the longer dry spells between rain events that allowed for more soil drying. Oppositely,
more time-concentrated rainfall in 2006 allowed for a very sharp
and high peak in late August (Fig. 9c). Comparing sites at
0.50 m depth, the 2005 season did show higher soil moisture
through the season at the millet site. This may largely be attributed
to lower evapotranspiration (see ‘‘Eddy fluxes”), rather than to any
higher infiltration capacity (very little cultivation work is performed). The 2006 season produced similarly high moisture levels
to those at the fallow site but for a much longer period, starting
much earlier and lasting into the beginning of the dry season. Virtually no signal, except for a very slight rise in the period of September–December 2006, was recorded at the 2.5 m depth of
the fallow site through the two-year period. In contrast, the millet
100
50
0
0
50
100
150
200
Rn - millet (W m -2)
b
LE + H + G - millet (W m -2 )
Since all four components Rn, LE, H, and G of the surface energy
budget were measured, it is possible to check the closure of the
theoretical energy balance equation
200
150
100
50
0
0
50
100
150
200
Rn - millet (W m -2)
Fig. 8. Energy budget closure at fallow (a) and millet (b) sites, through the study
period. Grey dots correspond to the monsoon period (May 15–October 15). (Values
are daytime 24-h averages).
site recorded substantial propagation of the 2006 seasonal moisture signal, with a several-week delay relative to the start and
end of the rain season. Again this is due to the specific conditions
of the 2006 rain season, with a large cumulative rainfall in a relatively short duration in August, and to the comparatively low
evapotranspiration from the millet. Less favourable rainfall in
2005, in amount and distribution, did not allow for any substantial
deep infiltration even at the millet site.
Discussion
Seasonal dynamics of surface energy cycle, and interactions between
components
From the winter solstice to the pre-monsoon period, LE is very
small, and H, G, and Lwout follow a very gradual rise, reflecting a
tight balance in the sharing of the increasing Rf. In the pre-monsoon period, before first rains, Rf levels off but H keeps rising, as
the arrival of monsoon flux makes air temperature drop and wind
D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
213
Fig. 9. Time course of volumetric soil water content at three depths for the fallow (left: (a) 0.10 m, (c) 0.50 m, (e) 2.5 m) and millet (right: (b) 0.10 m, (d) 0.50 m, (f)
2.5 m) plots. Half-hourly data. Bars at top represent rain event occurrences.
speed increase (mid-May 2006 and early April in 2007). Energy
conservation triggers the Lwout decrease and change in G pattern.
When rain comes in, LE becomes the major driver in the partitioning of the relatively steady Rf, responding very clearly according to
precipitated amounts. Initially irregular and in low quantities,
water availability causes ephemeral bursts in LE and opposite variations in H. In July, when soil water starts building up, LE sets in
durably (but distinctly for the two land covers), producing the
sharp falls in H and Lwout. After the rain season, soil water and LE
decay rapidly while Rf is still high, yielding significant new rises
in H and Lwout.
Hence, including the pre-monsoon period of air mass change,
dry season fluctuations in H are strongly constrained by the tight
direct equilibrium that binds H to Lwout (and G) through the surface
temperature, in the partitioning of Rf. In comparison, LE is controlled by factors that are largely external to that thermal state
of the soil surface (i.e., soil moisture, vegetation, atmospheric conditions), allowing it to vary much more freely, and reach ET0 at the
fallow plot. Energy conservation in meeting Rf then causes these
variations to be compensated for by sharp adjustments in H, Lwout,
and G. This leads to frequent ground heat releases in the monsoon
season despite high radiative inputs. This strong external control
on the surface energy cycle, exerted in particular by the water
and vegetation cycles, is largely responsible for the shape of the
net radiation course with a sharp peak in the second part of the
rain season. Essential for latent heat, rainfall turns out about as
important as solar forcing for the seasonal variability of the other
surface energy outputs. It is largely dominant at interannual or infra-seasonal timescales, particularly during the first half of the rain
season.
Water cycle dynamics
Given the problems of discrepancies in spatial scale and representativeness, combined interpretation of measured water cycle
variables can only be tentative since, unlike the energy balance,
closure of the water balance cannot be checked. Fig. 10 shows
the time variations, from March 2006 to March 2007, of cumulative
rainfall and evapotranspiration (Pc and Ec, respectively) and of the
water storage (S) in the first 2.75 m of soil (abbreviated to ‘soil’ or
‘soil layer’ in this subsection), separately for the fallow and millet
sites. Storage is counted relative to the residual content at the start
of the period of analysis. Also plotted is the balance (Pc Ec S) for
these three observed variables, which theoretically represents the
sum of cumulative runoff, surface retention and deep storage (in
variation from initial amount). Evapotranspiration data is missing
for some days essentially in the first part of the period before the
rain season proper, i.e., when it is particularly low, and essentially
for the millet site. These few gaps, adding to nighttime flux omission, tend therefore to slightly underestimate the evapotranspiration course.
Some evapotranspiration does occur even before any rainfall at
the fallow site (Fig. 10a), which can be interpreted as transpiration
from sparse deep-rooted trees. The first rainfalls in June are
promptly and largely evaporated. When significant rain starts to
occur, as of July 9, the soil wets up and evapotranspiration rises,
but at different rates for the two sites through most of the season.
At the fallow site, about half the rainfall readily returns to the
atmosphere, leaving little water to increase soil storage. Oppositely, soil water builds up faster than cumulative evapotranspiration at the millet site. The 69-mm rainfall event of August 22
produces a marked soil storage increase at both sites, shortly before soil moisture depletion starts to occur (end of August–beginning of September). Since hardly any additional deep storage is
apparent from then on at the fallow site (see balance curve,
Pc Ec S), this soil water loss mostly corresponds to depletion
by evapotranspiration, partly fed also by last rainfalls. After rainfall
stops (September 24), the balance curve testifies to deep water uptake through the whole dry season, until the beginning of the next
season cycle.
D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
a
700
Water depth - fallow (mm)
214
600
PC
500
EC
400
300
200
P c -E c -S
100
S
b
700
Water depth - millet (mm)
0
15/3/06
600
14/6/06
13/9/06
Date
13/12/06
15/3/07
PC
500
400
P c -E C -S
300
EC
200
100
S
0
15/3/06
14/6/06
13/9/06
Date
13/12/06
15/3/07
Fig. 10. Time course of cumulative rainfall (Pc, thick black), cumulative evapotranspiration (Ec, thin black), water storage in the first 2.75 m (S, dark grey), and balance of three
previous terms (Pc Ec S, light grey) at the fallow (a) and millet (b) sites, for the March 15, 2006–March 15, 2007 period.
At the millet site, lighter September rainfall is still in excess of
evapotranspiration, and the rising balance curve suggests that the
substantial water loss from the monitored soil layer largely goes
to deeper storage. This deep storage continues after rainfall stops,
contributing still more than evapotranspiration to the soil layer
depletion until the end of October. By the end of November, net
deep storage reverses to become a major contributor to evapotranspiration, rapidly getting more significant than the soil layer, and
also more so than at the fallow site through much of the dry season.
Over the year, measured evapotranspiration represents some
65% of the rainfall at the fallow site and 45% at the millet site.
These figures are consistent with simulation results obtained with
an ecohydrological model by Boulain et al. (accepted for publication). The 2006 rain season being rather wet, with concentrated
rainfall, the remainder can largely be attributed to runoff and, at
least at the millet site, to some interannual deep storage. Compared to the various components of the energy cycle, including latent heat, differences between sites and years appear to be
amplified for the water cycle, especially for deep infiltration.
Effect of land cover type
For a lot of the investigated variables, the two land cover types
exhibit a quite similar behaviour, differences being often in the order of measurement precision. Major differences occur during the
growing season and beginning of the dry season, for variables that
are most directly linked with vegetation and/or water. Comprising
a dense grass layer together with abundantly-leaved shrub stands,
fallow vegetation shows clearly lower albedo, producing slightly
higher Rf. Millet is characterized by a low vegetation cover fraction,
due to low density and to restriction of grass development by tillage and soil crusting. Wet season LE is noticeably higher at the fallow site, entailing somewhat lower H and Lwout. Note that lower
evapotranspiration for millet, attributable to higher surface resistance (Gash et al., 1997) and lower leaf area, is not at the expense
of plant productivity, thanks to higher water use efficiency (Boulain et al., 2009). A switch occurs at the end of the growing season,
when millet evapotranspiration becomes larger (and conversely for
H, Lwout, and shallow soil temperatures), presumably due to more
water remaining in the soil. At the annual scale, evapotranspiration
appears to be higher at the fallow plot. Lower rain-season evapotranspiration at the millet site translates into much more deep percolation (beneath the 2.75-m-thick monitored zone) and probably
(although not measured nor estimated) more runoff than at the fallow site. Runoff increase from crop impingement on natural vegetation has been reported by several studies in the area (e.g.,
Leblanc et al., 2008; Séguis et al., 2004). However, since soil moisture remains higher at the millet site, this observed lower evapotranspiration is not in consequence of higher runoff. Lower
evapotranspiration at the millet site is coherent with the multidecadal water table rise recorded in this area, attributed to the
extensive land clearing (Favreau et al., 2009). Results from the fallow site are quite consistent with those obtained by Verhoef et al.
(1999) for an older fallow savanna. Not unexpectedly, among the
surface types investigated here and by Timouk et al. (2009) at
the Northern Sahelian site of AMMA-Gourma (Mali), greatest
resemblance in energy variables is found between our fallow site
and the Agoufou grassland.
D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
Interannual variability
The two rain seasons 2005 and 2006 differ by their total
amounts of precipitation of 495 and 572 mm, respectively, but
more so by their respective durations and time distributions of
events and precipitated depths along the season. The more abundant 2006 season was also by far the shortest and the one with
the smallest number of events, which were thus more concentrated and intense. It resulted in a wetter soil through most of
the season and over the whole monitored soil profile at both sites.
This allowed for better vegetation development, as evidenced by
the lower albedo values (hence, higher Rf) at both sites throughout
the growing season, and especially in August–September. Together
with the higher Rf, more water and vegetation produced higher
evapotranspiration fluxes, most significantly at the fallow site,
and thus lower H, Lwout (hence higher Rn), and soil temperatures.
For millet, the rainfall abundance of 2006 was counterbalanced
by the less favourable timing (season start and duration), to which
it is quite sensitive (Boulain et al., 2006). In natural vegetation, species diversity, particularly in the grass layer, ensures a variety of
growth cycles that makes the season timing less of a problem,
therefore water abundance will generally be the limiting factor.
Note that for millet, additional variability arises from human factors, such as sowing strategies in relation to uncertain monsoon
onset, or from variety properties. Abundant rainfall in late August
2006 produced a late growing season peak, as seen in the water
and energy cycles. Higher residual moisture at both sites led to
some more evapotranspiration during much of the following dry
season, resulting in slightly lower Lwout and soil temperature at
the winter solstice. Longer sampling of the strong interannual variability of precipitation (Fig. 2) should help to better characterize
its impact on the energy and water cycles, for the two land covers.
Conclusions
In this and the companion paper (Boulain et al., 2009), the extended, multi-disciplinary data set being acquired on the Sahelian
AMMA site of West Niger, has shown its capability to provide new
insights into the complex, interacting physical and biological processes that control the coupled cycles of energy, water, vegetation,
and carbon. At this stage, the hydrological cycle is still left partly
open since runoff and deep drainage are not included in the analysis explicitly. The importance of lateral redistribution of storm
water in this endoreic landscape calls for a catchment-scale approach, which is being pursued jointly to the local scale analysis
presented here (Boulain et al., accepted for publication; Ezzahar
et al., 2009).
This analysis points to the central role of the latent heat component, and therefore of water when available, in the control of the
energy balance. Sensible heat and soil heat, and, to an even greater
extent, outgoing long wave radiation are largely under its direct
subordination, the first two being partially buffered by air and soil
over different, limited timescales. Solar forcing remains of course
the first factor of seasonal variability, but rain water effects are almost as large, and dominant at all other timescales. The indirect effect of water through albedo is smaller than its ‘‘direct” effect, that
is, through latent heat. Latent heat modulation by vegetation is
important, as it varies markedly between land cover types, lower
for the millet than for the ‘‘natural” vegetation in the growing season. As effects on latent heat are partially offset by those on albedo,
overall differences are slight for a number of energy-related variables. However, because evapotranspiration dominates the water
budget so largely in this area, differences are amplified for
water-related variables, such as humidity in deeper soil horizons,
which come in play as residuals in this budget. Although cultivated
215
surfaces have been shown to produce more runoff than fallow or
natural land in this area (Casenave and Valentin, 1992; Peugeot
et al., 1997), our results indicate that runoff is not the prime cause
for the lower return of water to the atmosphere by millet fields,
since higher soil moisture levels were observed concomitantly to
this lower evapotranspiration. Conversely, because of soil crusting
and storm spacing, Hortonian runoff is only lightly modulated by
variations in evapotranspiration (Peugeot et al., 2003).
Good closure of the energy budget brings support to the reliability of the various component measurements, as does the agreement
found with spatially-integrated scintillometry measurements of
sensible heat at the catchment scale (Ezzahar et al., 2009). With
continued acquisition over several additional wet–dry seasons
cycles, this comprehensive and high-resolution data set represents
a unique source of information for investigation of land processes
and for calibration/validation of land surface models at different
scales in this region of Africa.
Acknowledgments
This work was financially supported through the AMMA programme,1 (including the AMMA-Catch O.R.E.), the French ECCOPNRH programme (project ‘‘Eau et Végétation au Niger”), and by
IRD. Stimulating exchanges with J.-L. Rajot, F. Lohou, M. Lothon, L.
Kergoat, J.-M. Cohard, E. Ceschia, and F. Said are warmly acknowledged. I. Zin and the anonymous reviewers are thanked for their
helpful comments.
References
Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop Evapotranspiration:
Guidelines for Computing Crop Requirements. Irrigation and Drainage. FAO,
Rome. 300 pp.
Bagayoko, F., Yonkeu, S., Elbers, J., van de Giesen, N., 2007. Energy partitioning over
the West African savanna: multi-year evaporation and surface conductance
measurements in Eastern Burkina Faso. Journal of Hydrology 334 (3–4), 545–
559.
Boone, A., de Rosnay, P., 2007. AMMA forcing data for a better understanding of the
West African monsoon surface–atmosphere interactions. In: Boegh, E. et al.
(Eds.), Quantification and Reduction of Predictive Uncertainty for Sustainable
Water Resource Management, vol. 313. IAHS Publ., pp. 231–241.
Boulain, N., Cappelaere, B., Seguis, L., Gignoux, J., Peugeot, C., 2006. Hydrologic and
land use impacts on vegetation growth and NPP at the watershed scale in a
semi-arid environment. Regional Environmental Change 6, 147–156.
Boulain, N., Cappelaere, B., Séguis, L., Favreau, G., Gignoux, J., accepted for
publication. Water balance and vegetation change in the Sahel: a case study
at the watershed scale with an eco-hydrological model. Journal of Arid
Environments.
Boulain, N., Cappelaere, B., Ramier, D., Issoufou, H.B.A., Halilou, O., Seghieri, J.,
Guillemin, F., Gignoux, J., Timouk, F., 2009. Towards an understanding of
coupled physical and biological processes in the cultivated Sahel - 2. vegetation
and carbon dynamics. Journal of Hydrology (AMMA-Catch Special Issue) 375
(1–2), 190–203.
Braud, I., 1998. Spatial variability of surface properties and estimation of surface
fluxes of a savannah. Agricultural and Forest Meteorology 89 (1), 15–44.
Cappelaere, B., Descroix, L., Lebel, T. et al., 2009. The AMMA-Catch experiment in the
cultivated Sahelian area of South-West Niger – Strategy, implementation, site
description, main results. Journal of Hydrology (AMMA-Catch Special Issue) 375
(1–2), 34–51.
Casenave, A., Valentin, C., 1992. A runoff capability classification-system based on
surface-features criteria in semiarid areas of West Africa. Journal of Hydrology
130 (1–4), 231–249.
Charney, J.G., 1975. The dynamics of deserts and droughts. Quarterly Journal of the
Royal Meteorological Society 101, 193–202.
Dolman, A.J., Gash, J.H.C., Goutorbe, J.P., Kerr, Y., Lebel, T., Prince, S.D., Stricker,
J.N.M., 1997. The role of the land surface in Sahelian climate: HAPEX-Sahel
results and future research needs. Journal of Hydrology 189 (1–4), 1067–1079.
Ezzahar, J., Chehbouni, A., Hoedjes, J.C., Ramier, D., Boulain, N., Boubkraoui, S.,
Cappelaere, B., Descroix, L., Mougenot, B., Timouk, F., 2009. Combining
1
Based on a French initiative, AMMA was built by an international scientific group
and is currently funded by a large number of agencies, especially from France, the UK,
the US and Africa. It has been the beneficiary of a major financial contribution from
the European Community’s Sixth Framework Research Programme. Detailed information on scientific coordination and funding is available on the AMMA International
website http://www.ammainternational.org.
216
D. Ramier et al. / Journal of Hydrology 375 (2009) 204–216
scintillometer and an aggregation scheme to estimate area-averaged latent heat
flux during AMMA experiment. Journal of Hydrology (AMMA-Catch Special
Issue) 375 (1–2), 217–226.
Favreau, G., Cappelaere, B., Massuel, S., Leblanc, M.J., Boucher, M., Boulain, N.,
Leduc, C., 2009. Land clearing, climate variability, and water resources increase
in semiarid south-west Niger: a review. Water Resources Research, in press.
doi:10.1029/2007WR006785.
Foken, T., Wimmer, F., Mauder, M., Thomas, C., Liebethal, C., 2006. Some aspects of
the energy balance closure problem. Atmospheric Chemistry and Physics 6,
4395–4402.
Gash, J.H.C., Kabat, P., Monteny, B.A., Amadou, M., Bessemoulin, P., Billing, H., Blyth,
E.M., deBruin, H.A.R., Elbers, J.A., Friborg, T., Harrison, G., Holwill, C.J., Lloyd, C.R.,
Lhomme, J.P., Moncrieff, J.B., Puech, D., Soegaard, H., Taupin, J.D., Tuzet, A.,
Verhoef, A., 1997. The variability of evaporation during the HAPEX-Sahel
intensive observation period. Journal of Hydrology 189 (1–4), 385–399.
Goutorbe, J.P., Lebel, T., Dolman, A.J., Gash, J.H.C., Kabat, P., Kerr, Y.H., Monteny, B.,
Prince, S.D., Stricker, J.N.M., Tinga, A., Wallace, J.S., 1997. An overview of HAPEXSahel: a study in climate and desertification. Journal of Hydrology 189 (1–4), 4–
17.
Guyot, A., Cohard, J.M., Anquetin, S., Galle, S., Lloyd, C.R., 2009. Combined analysis of
energy and water balances to estimate latent heat flux of a sudanian small
catchment. Journal of Hydrology (AMMA-Catch Special Issue) 375 (1–2), 227–
240.
Heusinkveld, B.G., Jacobs, A.F.G., Holtslag, A.A.M., Berkowicz, S.M., 2004. Surface
energy balance closure in an arid region: role of soil heat flux. Agricultural and
Forest Meteorology 122 (1–2), 21–37.
Kabat, P., Dolman, A.J., Elbers, J.A., 1997. Evaporation, sensible heat and canopy
conductance of fallow savannah and patterned woodland in the Sahel. Journal
of Hydrology 189 (1–4), 494–515.
Koster, R.D., Dirmeyer, P.A., Guo, Z., Bonan, G., Chan, E., Cox, P., Gordon, P.T., Kanae,
S., Kowalczyk, E., Lawrence, D., Liu, P., Lu, C.-H., Malyshev, S., McAvaney, B.,
Mitchell, K., Mocko, D., Oki, T., Oleson, K., Pitman, A., Sud, Y.C., Taylor, C.M.,
Verseghy, D., Vasic, R., Xue, Y., Yamada, T., 2004. Regions of strong coupling
between soil moisture and precipitation. Science 305, 1138–1140.
Lebel, T., Diedhiou, A., Laurent, H., 2003. Seasonal cycle and interannual variability
of the Sahelian rainfall at hydrological scales. Journal of Geophysical Research
108 (D8), 8389. doi:10.1029/2001JD001580.
Lebel, T., Cappelaere, B., Hanan, N., Levis, S., Descroix, L., Galle, S., Kergoat, L.,
Mougin, E., Peugeot, C., Séguis, L., Vieux, B., 2009. AMMA-CATCH studies in the
Sahelian region of West-Africa: an overview. Journal of Hydrology (AMMACatch Special Issue) 375 (1–2), 3–13.
Leblanc, M.J., Favreau, G., Massuel, S., Tweed, S.O., Loireau, M., Cappelaere, B., 2008.
Land clearance and hydrological change in the Sahel: SW Niger. Global and
Planetary Change 61 (3–4), 135–150.
Lloyd, C.R., 1995. The effect of heterogeneous terrain on micrometeorological flux
measurements – a case study from HAPEX-Sahel. Agricultural and Forest
Meteorology 73 (3–4), 209–216.
Lloyd, C.R., Bessemoulin, P., Cropley, F.D., Culf, A.D., Dolman, A.J., Elbers, J.,
Heusinkveld, B., Moncrieff, J.B., Monteny, B., Verhoef, A., 1997. A comparison
of surface fluxes at the HAPEX-Sahel fallow bush sites. Journal of Hydrology
188–189 (1–4), 400–425.
Mauder, M., Foken, T., 2004. Documentation and instruction manual of the eddy
covariance software package TK2. Report Nr. 26, U. Bayreuth – Abt.
Mikrometeorologie.
(<http://www.geo.uni-bayreuth.de/mikrometeorologie/
ARBERG/ARBERG26.pdf>).
Mauder, M., Liebethal, C., Göckede, M., Leps, J.-P., Beyrich, F., Foken, T., 2006.
Processing and quality control of flux data during LITFASS-2003. BoundaryLayer Meteorology 121, 67–88.
Meir, P., Levy, P.E., Grace, J., Jarvis, P.G., 2007. Photosynthetic parameters from two
contrasting woody vegetation types in West Africa. Plant Ecology 192 (2), 277–
287.
Pagès, J.-P., Frangi, J.-P., Durand, P., Estournel, C., Druilhet, A., 1988. Etude de la
couche limite sahélienne – Expérience Yantala. Boundary-Layer Meteorology
43, 183–203.
Pellarin, T., Laurent, J.-P., Decharme, B., Descroix, L., Cappelaere, B., Ramier, D., 2009.
Hydrological modelling and associated microwave emission of a semi-arid
region in South-Western Niger. Journal of Hydrology (AMMA-Catch Special
Issue) 375 (1–2), 262–272.
Peugeot, C., Esteves, M., Galle, S., Rajot, J.L., Vandervaere, J.P., 1997. Runoff
generation processes: results and analysis of field data collected at the East
Central Supersite of the HAPEX-Sahel experiment. Journal of Hydrology 188–
189 (1–4), 179–202.
Peugeot, C., Cappelaere, B., Vieux, B.E., Seguis, L., Maia, A., 2003. Hydrologic process
simulation of a semiarid, endoreic catchment in Sahelian West Niger. 1. Modelaided data analysis and screening. Journal of Hydrology 279 (1–4), 224–243.
Redelsperger, J.L., Thorncroft, C., Diedhiou, A., Lebel, T., Parker, D., Polcher, J., 2006.
African monsoon multidisciplinary analysis (AMMA): an international research
project and field campaign. Bulletin of the American Meteorological Society 87
(12), 1739–1746.
Samain, O., Kergoat, L., Hiernaux, P., Guichard, F., Mougin, E., Timouk, F., Lavenu, F.,
2008. Analysis of the in situ and MODIS albedo variability at multiple time
scales in the Sahel. Journal of Geophysical Research 113, D14119.
Saux-Picart, S., Ottlé, C., Perrier, A., Decharme, B., Coudert, B., Zribi, M., Boulain, N.,
Cappelaere, B., Ramier, D., accepted for publication. SEtHyS_Savannah: a
multiple source land surface model applied to Sahelian landscapes.
Agricultural and Forest Meteorology.
Saux-Picart, S., Ottlé, C., Decharme, B., André, C., Zribi, M., Perrier, A., Coudert, B.,
Boulain, N., Cappelaere, B., Descroix, L., Ramier, D., 2009. Water and energy
budgets simulation over the Niger super site spatially constrained with remote
sensing data. Journal of Hydrology (AMMA-Catch Special Issue) 375 (1–2), 287–
295.
Schüttemeyer, D., Moene, A.F., Holtslag, A.A.M., de Bruin, H.A.R., van de Giesen, N.,
2006. Surface fluxes and characteristics of drying semi-arid terrain in West
Africa. Boundary-Layer Meteorology 118, 583–612.
Séguis, L., Cappelaere, B., Milesi, G., Peugeot, C., Massuel, S., Favreau, G., 2004.
Simulated impacts of climate change and land-clearing on runoff from a small
Sahelian catchment. Hydrological Processes 18, 3401–3413.
Slingo, A., Ackerman, T.P., Allan, R.P., Kassianov, E.I., McFarlane, S.A., Robinson, G.J.,
Barnard, J.C., Miller, M.A., Harries, J.E., Russell, J.E., Dewitte, S., 2006.
Observations of the impact of a major Saharan dust storm on the atmospheric
radiation balance. Geophysical Research Letters 33, L27817.
Timouk, F., Kergoat, L., Mougin, E., Lloyd, C.R., Ceschia, E., Cohard, J.M., de Rosnay, P.,
Hiernaux, P., Demarez, V., Taylor, C.M., 2009. Response of sensible heat flux to
water regime and vegetation development in a central Sahelian landscape.
Journal of Hydrology (AMMA-Catch Special Issue) 375 (1–2), 178–189.
Verhoef, A., Allen, S.J., De Bruin, H.A.R., Jacobs, C.M.J., Heusinkveld, B.G., 1996. Fluxes
of carbon dioxide and water vapour from a Sahelian savanna. Agricultural and
Forest Meteorology 80 (2–4), 248.
Verhoef, A., Allen, S.J., Lloyd, C.R., 1999. Seasonal variation of surface energy balance
over two Sahelian surfaces. International Journal of Climatology 19, 1267–1277.
Wallace, J.S., Wright, I.R., Stewart, J.B., Holwill, C.J., 1991. The Sahelian energy
balance experiment (SEBEX): ground based measurements and their potential
for spatial extrapolation using satellite data. Advances in Space Research 11 (3),
131–141.
Xue, Y., Shukla, J., 1993. The influence of land surface properties on Sahel climate.
Part I: desertification. Journal of Climate 6, 2232–2245.