The use of hydrological models, therefore, plays an essential role in providing information to support decision-making regarding the use of water resources, and also in understanding how climate and operational changes affect the hydrology of the Euphrates River Basin.
In this regard, we used the SWAT (Soil and Water Assessment Tool) model within ArcGIS to simulate the hydrology of the Euphrates River Basin.
This is the first time that this model has been applied at the scale of the Euphrates River.
The calibration results for R², NS, and RSR were 0.83, 0.77, and 0.46; whereas the validation results were 0.87, 0.83, and 0.23.
The uncertainty indices were greater during the validation period (probability coefficient 81% and correlation coefficient 0.91) than during the calibration period (probability coefficient 74% and correlation coefficient 0.87), indicating an increase in the reliability of the hydrological forecasts during the validation period.
Climate change is causing significant changes in the hydrology of the Euphrates River Basin, which has traditionally been one of the most important water basins in the region, due to climate change, changing surface runoff patterns, increasing water demand, and changing hydroclimate patterns (i.e., rainfall) over time. The use of hydrological models, therefore, plays an essential role in providing information to support decision-making regarding the use of water resources, and also in understanding how climate and operational changes affect the hydrology of the Euphrates River Basin. In this regard, we used the SWAT (Soil and Water Assessment Tool) model within ArcGIS to simulate the hydrology of the Euphrates River Basin. This is the first time that this model has been applied at the scale of the Euphrates River. Our findings show that by using 16 key parameters to calibrate the model, we were able to attain a greater degree of accuracy in simulating monthly discharge from the Birecik Dam to the Haditha Dam on the Euphrates River. Evidence suggests that the parameters SOL_BD, RCHRG_DP, GWQMN, and ESCO were found to be relatively more sensitive when compared with the more commonly used CN2 parameter to simulate hydrology (contrary to earlier findings). Our results indicate that the model was able to achieve satisfactory performance indicators during both the calibration and validation stages of the project. The calibration results for R², NS, and RSR were 0.83, 0.77, and 0.46; whereas the validation results were 0.87, 0.83, and 0.23. The uncertainty indices were greater during the validation period (probability coefficient 81% and correlation coefficient 0.91) than during the calibration period (probability coefficient 74% and correlation coefficient 0.87), indicating an increase in the reliability of the hydrological forecasts during the validation period. Additional findings of this study were the accurate estimation of the average annual depth of spatial runoff over 29 sub-basins, including point-source discharges, which is a key aspect of advanced hydrological studies. The additional capabilities provided by ArcGIS 10.5 provided additional spatial interpretations of this important variable.
