![]() Gis-based recharge estimation by coupling surface-subsurface water balances. Wetspass: a flexible, gis based, distributed recharge methodology for regional groundwater modelling. University of Missouri-Kansas City.īatelaan, O., & De Smedt, F. Impacts of precipitation, land use land cover and soil type on the water balance of Lake Chad Basin. Groundwater contribution and recharge estimation in the upper blue nile flows, ethiopia. Journal of Hydrology: Regional Studies, 27, 100658.Īsmerom, G. H. Spatial and temporal recharge estimation of the basement complex in nigeria, west africa. Swat: Model use, calibration, and validation. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 26, 607–611.Īrnold, J. Determination of spatially and temporally highly detailed groundwater recharge in porous aquifers by a svat model. Arabian Journal of Geosciences, 9, 1–14.Īrmbruster, V., & Leibundgut, C. Application of wetspass model to estimate groundwater recharge variability in the nile delta aquifer. M., Negm, A., Yoshimura, C., & Valeriano, O. International Journal of Sustainable Energy and Environment, 1, 136–149.Īrmanuos, A. Effect of climate change on the groundwater resources (gaza strip case study). Arabian Journal for Science and Engineering, 35, 155.Ījjur, S., & Mogheir, Y. Distributed recharge estimation for groundwater modeling using wetspass model, case study gaza strip, palestine. Environmental Earth Sciences, 76, 198.Īish, A. A distributed monthly water balance model: formulation and application on black volta basin. R., Van Griensven, A., Huysmans, M., & Batelaan, O. Further, it was found that GWR is highly sensitive to the parameter such as average rainfall intensity factor.Ībdollahi, K., Bashir, I., Verbeiren, B., Harouna, M. The estimated average seasonal GWR is 32.5 mm/yr and 47.6 mm/yr in the summer and winter seasons, respectively. From the modeling results, it was found that the maximum average monthly GWR of 13.4 mm occurs in July. The large-scale river basins such as the Omo river basin, Ethiopia, were chosen to demonstrate the potential of the WetSpass-M model under limited data conditions. In addition, the study conducted the sensitivity analysis of model parameters to assess the significant variation of GWR. This paper aimed at investigating the spatial and temporal distribution of the GWR at monthly, seasonal and annual scales using the WetSpass-M physically distributed hydrological model, which is not requiring the detailed catchment information. Hence, this calls for alternate suitable modeling approaches that are applicable with the limited data and, however, includes the detailed assessment of the spatial–temporal distribution of different water balance components especially the GWR component. However, such analyses might not be possible when the models require detailed hydro-climate and hydrogeological data in data-scarce regions. This helps in identifying critical zones in which GWR largely varies and thus leads to negative consequences. The systematic assessment of spatial and temporal distribution of groundwater recharge (GWR) is crucial for the sustainable management of the water resources systems, especially in large-scale river basins. ![]()
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