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Shows effective water balance modeling in various climate conditions, suggesting improved management strategies.
In this paper, a comprehensive semi-distributed water balance model is presented for basins under anthropogenic impacts. It benefits from data in different time resolutions for estimation of surface and groundwater exchanges and water withdrawals for various purposes. Ground-based data such as vegetation cover and topography have been used to determine the model parameters. The performance of the proposed model was tested for 38 sub-basins in Iran representing various climate conditions, vegetation covers, and agricultural practices. The results demonstrated a good performance in terms of estimating streamflows at the basin outlet, with more than 90% of sub-basins having a correlation coefficient above 0.9. However, the model showed a relatively weaker performance in the estimation of annual aquifer storage volume change. Correlation coefficients above 0.6 were calculated for more than half of the aquifers in the study area.
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Poorsepahy-Samian et al. (2022) studied this question.
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