Many objective direct policy search in Dez and Karoun multi-reservoir system, Iran

Contemporary environmental decision-making problems are generally framed in het- erogeneous socio-economic contexts involving a myriad of conflicting, non-commensurable operating objectives which represent social, environmental, and sustainability cri- teria. Population growth, climate change, and rapid economic developments are challenging historical water management strategies which have limited understand- ing of their multi-objective impacts. Most reservoirs operation worldwide had been defined in prior decades, where planning methods required strong a priori assump- tions on the preferences (or priorities) of decision makers across a limited number of operating objectives. This thesis contributes a decision analytic framework to design Pareto-optimal operating policies allowing the exploration of the tradeoffs between the conflicting objectives. The framework combines direct policy search, multi-objective evolutionary algorithms, and visual analytics to discover the key tradeoffs between the alternative policies in the system to eventually aid the selec- tion of few candidate compromise solutions balancing the competing objectives. The approach is demonstrated on Dez and Karoun multi-reservoir system, Iran, where the dimensionality of the system, the dry climate, and the presence of competing demands pose a number of challenges to water planners and managers. The three power plants connected to the main reservoirs in the modeled system (i.e., Dez, Karoun, and Masjed Soleyman) account for 20% of the national hydropower gen- eration capacity. Irrigation and domestic supply, especially to the city of Ahwaz, are also strategic objectives, along with flood protection downstream of the dams. Given the complexity of the Dez and Karoun system and the multiple interests in- volved, the design of Pareto-optimal operating policies via many-objective direct policy search, combined with their a posteriori evaluation, represents an effective tool to support sustainable water reservoirs management in Iran. The results show that the proposed decision analytic framework allowed the identification of the set of Pareto-optimal policies and discovered key tradeoffs to eventually aid the selection of few candidate compromise solutions that balance the competing objectives. Since evaporation is an important factor in the climatic condition of the region under study, a simple model to estimate the evaporation losses of the reservoirs depending on the temperature is constructed. The application of this model and the obtained policy produces significant differences in the estimated performance of the operating policies. These results suggest that the evaporation should be taken into consideration using more accuarate models, in order to provide more effective decision making support in the design of the system regulation.