Assessment of CHADFDM satellite-based input dataset for the groundwater recharge estimation in arid and data scarce regions

Abstract

Aquifer natural recharge estimations are a prerequisite for understanding hydrologic systems and sustainable water resources management. As meteorological data series collection is difficult in arid and semiarid areas, satellite products have recently become an alternative for water resources studies. A daily groundwater recharge estimation in the NW part of the Lake Chad Basin, using a soil–plant-atmosphere model (VisualBALAN), from ground- and satellite-based meteorological input dataset for non-irrigated and irrigated land and for the 2005–2014 period is presented. Average annual values were 284 mm and 30°C for precipitation and temperature in ground-based gauge stations. For the satellite-model-based Lake Chad Basin Flood and Drought Monitor System platform (CHADFDM), average annual precipitation and temperature were 417 mm and 29°C, respectively. Uncertainties derived from satellite data measurement could account for the rainfall difference. The estimated mean annual aquifer recharge was always higher from satellite- than ground-based data, with differences up to 46% for dryland and 23% in irrigated areas. Recharge response to rainfall events was very variable and results were very sensitive to: wilting point, field capacity and curve number for runoff estimation. Obtained results provide plausible recharge values beyond the uncertainty related to data input and modelling approach. This work prevents on the important deviations in recharge estimation from weighted-ensemble satellite-based data, informing in decision making to both stakeholders and policy makers.

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ORCID for Justin Sheffield: orcid.org/0000-0003-2400-0630

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