A proper estimation of future water
availability is vital information for water planners. However, most
contemporary quantitative hydrological predictions are mostly
streamflow-centred which makes them fundamentally uncertain. Since,
total streamflow represents only 35% of the total incoming rainfall at
the global scale and even less than that in regions like West Africa, an
alternative of using soil moisture and evapotranspiration is a
possibility. This study explored these alternative avenues for more
accurate hydrological prediction. From a theoretical perspective, water
resources were treated as blue water (BW, sum of streamflow and deep
aquifer recharge) and green water (GW, sum of actual evapotranspiration
and soil moisture). The theoretical aspect also addressed the
uncertainties associated with the use of a single hydrological model and
adopted a multi-model evaluation instead. This theoretical framework
was applied to the Benin Portion of the Niger River Basin, a
conglomerate of four understudied and poorly gauged basins, Coubéri,
Gbassè, Yankin, and Kompongou. This area provides a number of ecosystem
services whose sustenance requires better hydrological knowledge. To
this purpose, four objectives were addressed in order to assess the
impact of climate change on future BW and GW availability in the study
area. The first objective was to identify within a set of hydrological
models the most suitable ones to better simulate streamflow and soil
moisture. The performance of four hydrological models (HBV-light,
UHP-HRU, SWAT and WaSiM) to simulate daily streamflow and the ability of
three of these models (UHP-HRU, SWAT and WaSiM) to reproduce daily
remotely-sensed soil moisture dynamic were compared. The results showed
that none of the hydrological models clearly outperformed the others in
the simulation of streamflow in all the basins. While WaSiM was the most
suitable to mulate streamflow in the Yankin and Kompongou basins,
HBV-light was the best for the Coubéri and Gbassè basins. However,
regardless of the basin, UHP-HRU was the most adequate model to simulate
soil moisture. The second objective dealt with the downscaling of three
regional climate models outputs (HIRHAM5, RCSM, and RCA4) under RCP4.5
and RCP8.5 for the historical period (1976-2005) and the future
(2021-2050). To this end, the Statistical DownScaling Model (SDSM) was
used. The results suggested that rainfall will increase (1.7 to 23.4%)
for HIRHAM5 and RCSM under both RCPs but will show mixed-trends (-8.5 to
17.3%) for RCA4. Mean temperature will also increase (-0.1 to 0.48°C)
for HIRHAM5 and RCSM but decrease for RCA4 (-0.37 to 0.1°C). On the
basis of the results of the two previous objectives, the third objective
was to quantify the future BW only with the models found robust to
simulate streamflow and future GW solely with the models found suitable
to simulate soil moisture. It was found that GW will increase in all the
four investigated basins while BW will only increase in the Kompongou
basin.
The last objective was about the quantification of the overall
uncertainty associated with the evaluation of future BW and GW. This
was done by computing the interviuartile range of the total number of
model realizations for ach basin. The results show that BW evaluation is
associated with larger uncertainty than GW quantification. To cope with
the projected decrease in BW that could adversely impact livelihoods
and food security of the local population, some recommendations for the
development of adequate adaptation strategies including the rational use
of BW are briefly discussed.