| Abstrakt: |
Purpose: Hydrological modeling is an important tool for estimating hydrological responses, not only for current conditions but also for future scenarios by optimizing hydrological parameters. In cases where direct measurements are difficult to obtain, modeling can be used to fill in the gaps and provide vital information for water resources planning and management. However, it is important to note that hydrological models need to be calibrated and validated to ensure that the parameter values are optimized for the specific watershed being studied. Materials and methods: The Xinanjiang (XAJ) model have been used to estimate the potential hydrological responses under current and future scenarios. In this study, an attempt was made to optimize the parameters for the Dirima watershed with a total area of 162 km2using DEoptim algorithms. In this study, the calibrated parameters were used to simulate the watersheds’ hydrological response for baseline (1996–2009) and three climate change scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) from a CMIP6 multimodel ensemble (2015–2100). Results and discussion: The study shows that the baseline period of performance measure values is RMSE = 12, NSE = 0.76, PBIAS = 10.5% and R2= 0.78, and RMSE = 3.65, NSE = 0.85, PBIAS = 9.9%, and R2= 0.85 indicate that the model has performed well in simulating the streamflow in both the calibration and validation periods, respectively. Lower RMSE, higher NSE, and lower PBIAS indicate better model performance and suggest that the model has performed well in all these aspects. In the future (2015–2100) the average Tmax 1.59 , 1.93 and 2.48 °C, and Tmin will raise by 1.83 , 2.33 and 2.85 °C under SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Additionally, the mean annual future hydrological responses in the upper soil layer, including evaporation, soil moisture, and runoff will be 1.72, 1.71, and 1.79 mm, 0.63, 0.62, 0.64 mm, and 1.07, 0.97, and 1.18 mm under SSP2-4.5, SSP3-7.0, and SSP5-8.5. The future projections show an increase in average maximum and minimum temperatures under different SSP scenarios. Conclusion: The calibrated parameters of the XAJ model were critical to assess the future hydrological responses of the Dirima watershed under the three SSP scenarios. The precipitation and streamflow values are consistently lower than those of ET and temperature across all SSP scenarios. This indicates that future water availability is likely to be under pressure and calls for appropriate strategic measures to create a more resilient water resource system. |
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