Quantification of groundwater recharge is a crucial prerequisite for sustainable groundwater resource management, particularly in semi-arid areas where there are large demands for groundwater supplies. This research presents an alternative approach for recharge estimation based on the soil water balance technique. The purpose is to develop a model which provides a suitable balance between physical credibility and data which realistically can be gathered. A spreadsheet model was written based on the conceptual representation of the principal physical processes which actually affect recharge in a semi-arid area. Alternative procedures were included in order to represent: (a) the estimation of runoff, (b) the inclusion of the period with predominant bare soil evaporation and (c) the accounting for evapotranspiration following rainfall on dry soil. The model was tested using real data from a semi-arid region (Northeast Nigeria) making use of selected periods of days and years in order to illustrate the principal model characteristics. The results were presented in the form of diagrams and graphs helping to visualise the interactions between the physical components and the effect of the additional procedures on recharge estimation. The credibility of the model was investigated using an alternative concept of "analysis of plausibility". This concept makes use of as wide as possible a range of quantitative and qualitative information from the hydrological system in order to verify the robustness of the model when extensive datasets required by conventional validation techniques are not available. The results suggested that the modelled recharge is physically sound and it is in line with the overall determination of recharge in semi-arid areas by a range of methods. The soil water balance model was utilised to explore important aspects of recharge in semi-arid regions showing the effect of the field variability on the model's output. The preliminary results show that the developed concept reasonably represents the inherent field variability, thus corroborating the strength of the approach for recharge estimation in semi-arid regions
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