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Abstract: Sustainable decisions in water resources management require scientifically sound information on water availability. Central support in hydrological decision making arises from hydrological modelling which in turn depends on meteorological input. This work intends to show how integration of atmospheric science and hydrology, particularly the joint modelling of atmospheric and terrestrial water cycle, allows to provide decision support for two fundamental problems in sustainable water management: (1) the impact of global climate change on water availability, and (2) the near-real time estimation of recent resources and fluxes. The performance of joint atmospheric-hydrological simulations and its application for decision support is demonstrated for the Volta Basin of West Africa. First, the impact of global warming on water availability in the Volta Basin is assessed by joint regional climate-hydrology simulations. Time slices of ECHAM4 global climate scenario IS92a are dynamically downscaled to a resolution of 9×9km2 with the mesoscale meteorological model MM5 and the terrestrial water balance is subsequently calculated by the distributed hydrological model WaSiM. Results indicate a slight increase in total annual precipitation by 5%, but also a significant decrease of precipitation in April (in total 20%, for specific regions up to 70%), at the beginning of the rainy season. Terrestrial water balance variables react highly nonlinear to changes in precipitation and temperature. Second, the performance of joint atmospheric-hydrological simulations as a tool for near-real-time, model based water monitoring system for the White Volta subcatchment is assessed. Operational available GFS (Global Forecasting System) global analyses are dynamically downscaled to 9×9km2 resolution and meteorological fields subsequently applied for calculating the terrestrial water balance. Albeit a bias in precipitation simulations can be observed when comparing to point measurements, modelled river discharge agrees well with observations in 2004. It is concluded that particularly in areas with weak infrastructures, where few meteorological observations are available (or only in long delay), atmospheric models can provide reasonable meteorological information for hydrological modelling and therefore facilitate decision support. [Copyright &y& Elsevier]

Climate model simulations typically exhibit a bias, which can be corrected using statistical approaches. In this study, a geostatistical approach for bias correction of daily precipitation at ungauged locations is presented. The method utilizes a double quantile mapping with dry day correction for future periods. The transfer function of the bias correction for the ungauged locations is established using distribution functions estimated by ordinary kriging with anisotropic variograms. The methodology was applied to the daily precipitation simulations of the entire CORDEX‐Africa ensemble for a study region located in the West African Sudanian Savanna. This ensemble consists of 23 regional climate models (RCM) that were run for three different future scenarios (RCP 2.6, RCP 4.5, and RCP 8.5). The evaluation of the approach for a historical 50‐year period (1950–2005) showed that the method can reduce the inherent strong precipitation bias of RCM simulations, thereby reproducing the main climatological features of the observed data. Moreover, the bias correction technique preserves the climate change signal of the uncorrected RCM simulations. However, the ensemble spread is increased due to an overestimation of the rainfall probability of uncorrected RCM simulations. The application of the bias correction method to the future period (2006–2100) revealed that annual precipitation increases for most models in the near (2020–2049) and far future (2070–2099) with a mean increase of up to 165mm⋅a−1 (18%). An analysis of the monthly and daily time series showed a slightly delayed onset and intensification of the rainy season. [ABSTRACT FROM AUTHOR]

Renewable energy development is growing fast and is expected to expand in the next decades in West Africa as a contribution to addressing the power demand and climate change mitigation. However, the future impacts of climate change on solar PV and the wind energy potential in the region are still unclear. This study investigates the expected future impacts of climate change on solar PV and wind energy potential over West Africa using an ensemble of three regional climate models (RCMs). Each RCM is driven by three global climate models (GCMs) from the new coordinated high-resolution output for regional evaluations (CORDEX-CORE) under the RCP8.5 scenario. Two projection periods were used: the near future (2021–2050) and the far future (2071–2100). For the model evaluation, reanalysis data from ERA5 and satellite-based climate data (SARAH-2) were used. The models and their ensemble mean (hereafter Mean) show acceptable performance for the simulations of the solar PV potential, the wind power density, and related variables with some biases. The Mean predicts a general decrease in the solar PV potential over the region of about −2% in the near future and −4% in the far future. The wind power density (WPD) is expected to increase by about 20% in the near future and 40% in the far future. The changes for solar PV potential seem to be consistent, although the intensity differs according to the RCM used. For the WPD, there are some discrepancies among the RCMs in terms of intensity and direction. This study can guide governments and policymakers in decision making for future solar and wind energy projects in the region. [ABSTRACT FROM AUTHOR]

The Volta Basin in West Africa is a region sensitive to water shortage. Future climate conditions therefore may put additional stress on the competition for the scarce water resources between industry, agriculture, and households. For an investigation of the sensitivity of the hydrological regime to global climate change in the data-sparse and poorly gauged region of the Volta Basin, joint regional climate-hydrology simulations were performed. MM5 was used as a regional climate model to downscale two time slices of a global ECHAM4 simulation to a resolution of 9 km. These regional climate simulations were used to drive a physically based, distributed hydrological model at 1 km resolution. The performance of the model components and the joint model system was evaluated for different historical periods. Results show that discharge in the Volta Basin reacts highly sensitively to precipitation differences. The pronounced rainfall decrease at the beginning of the rainy season is not transferred to discharge changes. During the rainy season most of the surplus rainfall evaporates due to a strong increase in evaporation as a consequence of higher near-surface air temperatures. The average change signal in precipitation, as well as surface and subsurface hydrology variables, lies in most variables within the range of inter-annual variability, but regionally stronger signals are also observed. [ABSTRACT FROM AUTHOR]