Description:... One of the key parameters in hydrological and climate change modeling is a good estimation of the soil hydrauic properties in the region of interest. This study investigates the spatial distribution and variability of soil physical properties, with emphasis on saturated hydraulic conductivity at two pilot sites in the Volta Basin of Ghana. It focuses on the potential of pedotransfer functions (PTFs) and artificial neural network (ANN) approach for estimating saturated hydraulic conductivity. Saturated hydraulic conductivity was observed to be highly spatially variable; however, it can be estimated using selected PTFs and ANN for soils in the Volta Basin based on soil parameters that can readily be obtained from detailed soil maps--From cover.
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شماره کارت : 6104337650971516 شماره حساب : 8228146163 شناسه شبا (انتقال پایا) : IR410120020000008228146163 بانک ملت به نام مهدی تاج دینی