Water balance is one of the most important issues in water resources management and water consumption planning.ABCD water balance conceptual model is a very suitable simulation tool due to its simplicity, low requirement of input data, and providing various components of the water balance. As the lack of data is always a major challenge in many developing countries, remote sensing technology was used to collect the required data for the Zarandeh subbasin in Neyshabur in the Northeastern Iran. To do so, IMERG precipitation satellite products and ERA5 temperature reanalysis data were used. Outputs were evaluated using five statistical indices including Pearson Correlation Coefficient (R), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Nash-Sutcliffe Efficiency Coefficient (NSE), and BIAS Coefficient. The Results indicated that products are accurate, and there is a high correlation between outputs and observed data. To calculate the water balance, remote sensing products were applied in the form of the ABCD model. The uncertainties in the model parameters were assessed through Fuzzy numbers. In addition, the Monte Carlo method was employed to calibrate them with two different objective functions including NSE and Coefficient of Determination (R 2 ). The results showed that the ABCD water balance model is an accurate tool for simulating the surface runoff of the Zarandeh sub-basin. Finally, the model was applied to the Sebi sub-basin located in Torbat-e-Heydariyeh, which had a moderate performance showing that the model parameters should be recalibrated in each region.
Water balance is one of the most important issues in water resources management and water consumption planning. ABCD water balance conceptual model is a very suitable simulation tool due to its simplicity, low requirement of input data, and providing various components of the water balance. As the lack of data is always a major challenge in many developing countries, remote sensing technology was used to collect the required data for the Zarandeh sub-basin in Neyshabur in the Northeastern Iran. To do so, IMERG precipitation satellite products and ERA5 temperature reanalysis data were used. Outputs were evaluated using five statistical indices including Pearson Correlation Coefficient (R), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Nash-Sutcliffe Efficiency Coefficient (NSE), and BIAS Coefficient. The Results indicated that products are accurate, and there is a high correlation between outputs and observed data. To calculate the water balance, remote sensing products were applied in the form of the ABCD model. The uncertainties in the model parameters were assessed through Fuzzy numbers. In addition, the Monte Carlo method was employed to calibrate them with two different objective functions including NSE and Coefficient of Determination (R2). The results showed that the ABCD water balance model is an accurate tool for simulating the surface runoff of the Zarandeh sub-basin. Finally, the model was applied to the Sebi sub-basin located in Torbat-e-Heydariyeh, which had a moderate performance showing that the model parameters should be recalibrated in each region.
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