Integrated operation of water resources in climate change conditions, considering uncertainty based on coupled dynamic models of surface water and groundwater

Abstract In regions with arid and semi-arid climates, groundwater serves as one of the main sources of agricultural, industrial, and drinking water supply, constantly interacting with surface waters. The purpose of this study is to investigate changes in the level and volume of aquifer storage in Kermanshah by simulating the interaction of surface and groundwaters, using a coupling dynamic model WEAP-MODFLOW. This model is capable of calling and automatically running climate change scenarios and displaying their effects on the entire system. In this method, data and results between the MODFLOW and WEAP models are exchanged on a monthly basis, and the impacts of implementing each of the CMIP5 climate scenarios can be observed in both surface water and groundwater sections. The values of recharge, extraction, runoff, river levels, and water supply from the WEAP model are input into the MODFLOW model to calculate groundwater levels and changes in aquifer storage, with results fed back to the WEAP model. To apply model uncertainties and climate scenarios was developed a hybrid model based on the combination of predictions from 5 different AR5 models. The results showed that over a base period of 27 years (October 1991 to September 2018), the average groundwater level at the end of the period decreased by 4.3 meters, with a reservoir volume reduction of 253 million cubic meters. In the event of aquifer operation, based on the predicted climatic parameters derived from the hybrid model during the 81 years (October 2018 to September 2099), the level of reduction and volume of aquifer storage was predicted under the optimistic scenario of RCP2.6 in order of 2.52m and 251.51MCM and the pessimistic scenario RCP8.5, respectively 8.88m and 769.04 MCM. The results demonstrated that employing an integrated operation model in a dynamic link mode is an effective strategy for better river and aquifer management under climate change conditions. The effects of each climate scenario on the entire system are observable in this model, aiding decision-makers in implementing effective adaptation strategies to climate change.