5 research outputs found

    Current Conditions and Projected Changes in Crop Water Demand, Irrigation Requirement, and Water Availability over West Africa

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    Climate variability and change greatly affect agricultural and water resource management over West Africa. This paper presents the current characteristics and projected change in regional crop water demand (CWD), irrigation requirement (IR), and water availability (WA) over West Africa. Observed and simulated daily rainfall, minimum temperature, maximum temperature, and evapotranspiration are used to derive the above agro-meteorological and hydrological variables. For future periods, high-resolution climate data from three regional climate models under two different scenarios, i.e., representative concentration pathway (RCP) 4.5 and 8.5, are considered. Evaluation of the characteristics of present-day CWD, IR, and WA indicated that the ensemble mean of the model-derived outputs reproduced the prevailing spatial patterns of CWD and IR. Moreover, the wetter part of the domain, especially along the southern coast, was correctly delineated from the drier northern regions, despite having biases. The ensemble model also simulated the annual cycle of water supply and the bimodal pattern of the water demand curves correctly. In terms of future projections, the outcomes from the study suggest an average increase in the CWD by up to 0.808 mm/day and IR by 1.244 mm/day towards the end of the twenty-first century, compared to the baseline period. The hot-spot areas, where there is higher projected increment in CWD and IR, are over Senegal, Southern Mali, and Western Burkina Faso. In most cases, WA is projected to decrease towards the end of the twenty-first century by −0.418 mm/day. The largest decline in WA is found to be over Guinea and most of the eastern parts of West Africa. Despite the current under-utilization of the existing groundwater resources, the threat of global warming in reducing future WA and increasing CWD suggested caution on the scale of irrigation schemes and management strategies. The outcomes from the study could be a crucial input for the agricultural and water managers for introducing effective measures to ensure sustainability of irrigated farm lands

    Assessment of WRF Land Surface Model Performance over West Africa

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    Simulations with four land surface models (LSMs) (i.e., Noah, Noah-MP, Noah-MP with ground water GW option, and CLM4) using the Weather Research and Forecasting (WRF) model at 12 km horizontal grid resolution were carried out as two sets for 3 months (December–February 2011/2012 and July–September 2012) over West Africa. The objective is to assess the performance of WRF LSMs in simulating meteorological parameters over West Africa. The model precipitation was assessed against TRMM while surface temperature was compared with the ERA-Interim reanalysis dataset. Results show that the LSMs performed differently for different variables in different land-surface conditions. Based on precipitation and temperature, Noah-MP GW is overall the best for all the variables and seasons in combination, while Noah came last. Specifically, Noah-MP GW performed best for JAS temperature and precipitation; CLM4 was the best in simulating DJF precipitation, while Noah was the best in simulating DJF temperature. Noah-MP GW has the wettest Sahel while Noah has the driest one. The strength of the Tropical Easterly Jet (TEJ) is strongest in Noah-MP GW and Noah-MP compared with that in CLM4 and Noah. The core of the African Easterly Jet (AEJ) lies around 12°N in Noah and 15°N for Noah-MP GW. Noah-MP GW and Noah-MP simulations have stronger influx of moisture advection from the southwesterly monsoonal wind than the CLM4 and Noah with Noah showing the least influx. Also, analysis of the evaporative fraction shows sharp gradient for Noah-MP GW and Noah-MP with wetter Sahel further to the north and further to the south for Noah. Noah-MP-GW has the highest amount of soil moisture, while the CLM4 has the least for both the JAS and DJF seasons. The CLM4 has the highest LH for both DJF and JAS seasons but however has the least SH for both DJF and JAS seasons. The principal difference between the LSMs is in the vegetation representation, description, and parameterization of the soil water column; hence, improvement is recommended in this regard
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