Evaluation of Water Resources Allocation Scenarios of Mahabad Basin under the Influence of Climate Change using WEAP Model

Background and Objectives
Climate change has led to significant changes in hydrological processes and global access to water. Adopting appropriate water management strategies and understanding the interactions between climate change and water resources will help researchers and policy makers to mitigate the adverse effects of climate change, such as unplanned and over-exploitation of water resources. It is therefore necessary to adopt water supply and demand management policies that take into account the influence of climate change and assess the consequences of different climate scenarios. Given the importance of this issue, this study assessed different climate scenarios in the Mahabad watershed, in northwest of Iran.
Methodology
To study the impact of climate change on the supply and demand side, particularly agriculture and irrigation, models from the Intergovernmental Panel on Climate Change (IPCC) were extracted under two scenarios: RCP4.5 and RCP8.5. The extracted data were then scaled using the LARS_WG model. The IHACRES model was then used to simulate rainfall and runoff, and its outputs were used as inputs to the WEAP model. The WEAP model was used to simulate the effects of climate change on supply and demand sites under different climate scenarios.
Findings
The effects of climate change on supply and demand sites during the statistical period from 2020 to 2039 were predicted using the IHACRES rainfall-runoff model. It was found that the correlation coefficient and skewness error during the calibration period were 72% and 0.08, respectively. In the validation period, these values were 69% and 0.59, indicating an acceptable efficiency of the model in the region. Finally, the outputs of the IHACRES model were used as inputs for the WEAP model, which showed that the CMIP5 model (MIROC 8.5) had the highest amount of unestimated demand under the RCP 8.5 scenario, with a priority of one unit for drinking water and two units for agriculture. On the other hand, the CMIP5 model (GFDL4.5) showed the highest reliability under the RCP 4.5 scenario, with a volumetric reliability of 72% and a temporal reliability of 42%.
 
 
Conclusion
In general, the CMIP5 model (GFDL4.5) showed higher volumetric and temporal reliability compared to other scenarios and performed better in meeting the demand for agricultural and drinking water sites. Therefore, it is suggested to use this model in future research to estimate precipitation and temperature data and to perform hydrological simulations.