Robust strategies for climate change adaptation in the agricultural sector under deep climate uncertainty

Adaptive planning in climate change condition is a significant challenge for effective management of water resources and agricultural systems. One of the major controversial issues in climate change adaptation studies is deeply uncertain nature of such changes. This study aimed at planning optimal agricultural adaptation measures under deep climate uncertainty in a semi-arid basin in Iran (Tashk-Bakhtegan Basin) using a simulation-optimization (S-O) approach. To fulfil this objective, a modified version of Soil and Water Assessment Tool (SWAT) entitled SWAT-PARS was used to simulate the status of the basin regarding water resources and agricultural sector. By combining the SWAT model with a NSGA-II based robust optimization model, the optimal and robust type and location of robust agricultural management measures under climate uncertainty were determined. For this purpose, deficit irrigation, irrigation efficiency increase, cropping pattern change and cropping date change were considered as effective adaptation measures in the agricultural sector. The robustness of optimal measures was analyzed by a multi objective robust decision making approach using satisficing and regret robustness assessment methods. The robustness analysis of management strategies under climate change indicated different prioritization of strategies by "satisficing" and "regret" robustness assessment indicators. According to the results, irrigation management measures, and changes in the cropping pattern and date have been recommended in most strategies provided by different robustness methods. Most measures recommended have been able to reduce system vulnerability concerning in groundwater's quantitative changes and calorie of agricultural products, but did not cause any significant change in the system concerning inflow to the lake.