Estimating recharge distribution using remote sensing: A case study from the West Bank

Estimating groundwater recharge to the aquifer system is a very important element in assessing the water resources in regions of the world with poorly developed hydrological measurement stations such as the West Bank. Previous studies have developed analytical recharge models that are based on the longterm annual rainfall data. These models have been shown to be inadequate and changes over shorter periods, e.g. monthly estimates, must be known in order to study the temporal distribution of recharge. The approach used in this research integrates data derived from satellite images (e.g. land cover, evapotranspiration, precipitation, and digital elevation model) with hydrogeological data in a Geographic Information System (GIS) model to identify surface recharge areas on a pixel-by-pixel basis. The Surface Energy Balance Algorithm for Land (SEBAL) is applied to time series of MODerate Resolution Imaging Spectroradiometer (MODIS) Level 3 data of reflectance and surface temperature measurements to estimate monthly evapotranspiration; precipitation is derived from the monthly data sets of the Tropical Rainfall Measuring Mission (TRMM); runoff is given assumed values of 1.0 mm month(-1) and 0.5 mm month(-1) for the months of January and February, respectively. Recharge is quantified from November until March by applying the water balance method where evapotranspiration estimates and runoff are subtracted from precipitation. Results show good agreement between available numbers reported in literature and the remote sensing-based analysis. Empirical models that are based on long term rainfall measurements result values between 800 and 836 MCM yr(-1) while the remote sensing based model results a recharge estimate of between 650 and 750 MCM yr(-1). (C) 2011 Elsevier B.V. All rights reserved.