Robust optimization with equity and efficiency framework for basin-wide water resources planning

Identifying robust adaptive irrigation operating policies to balance deeply uncertain economic food production and groundwater sustainability trade-offs

Increasing irrigation demand has heavily relied on groundwater use, especially in places with highly variable water supplies that are vulnerable to drought. Groundwater management in agriculture is becoming increasingly challenging given the growing effects from overdraft and groundwater depletion worldwide. However, multiple challenges emerge when seeking to develop sustainable groundwater management in irrigated systems, such as trade-offs between the economic revenues from food production and groundwater resources, as well as the broad array of uncertainties in food-water systems. In this study we explore the applicability of Evolutionary Multi-Objective Direct Policy Search (EMODPS) to identify adaptive irrigation policies that water agencies and farmers can implement including operational decisions related to land use and groundwater use controls as well as groundwater pumping fees. The EMODPS framework yields state-aware, adaptive policies that respond dynamically as system state conditions change, for example with variable surface water (e.g., shifting management strategies across wet versus dry years). For this study, we focus on the Semitropic Water Storage district located in the San Joaquin Valley, California to provide broader insights relevant to ongoing efforts to improve groundwater sustainability in the state. Our findings demonstrate that adaptive irrigation policies can achieve sufficiently flexible groundwater management to acceptably balance revenue and sustainability goals across a wide range of uncertain future scenarios. Among the evaluated policy decisions, pumping restrictions and reductions in inflexible irrigation demands from tree crops are actions that can support dry-year pumping while maximizing groundwater storage recovery during wet years. Policies suggest that an adaptive pumping fee is the most flexible decision to control groundwater pumping and land use.

Improving robustness of water supply system using a multi-objective robust optimization framework

Due to the uncertainty of rainfall and water demand, the water supply of various participants has been challenged in such a way that this challenge has accelerated the failure of water supply system. Thus, this study proposes a multi-stage Adjustable Robust Optimization integrated to the multi-objective programming framework to drive water supply system to the failure safety zone and thereby improve robustness of system under different scenarios. Indeed, Adjustable Robust Optimization framework is applied to investigate the two uncertain factors of rainfall and water demand. A real arid area of Sistan basin in southeastern Iran is considered to analyze the proposed multi-objective programming model. Next, various comparative feasibilities under different levels of uncertainty are carried out to examine the robustness status in more detail. In the following, due to the deterioration of climatic patterns in the coming years, some managerial insights are highlighted. According to the final outputs, the domestic sector has reached more optimal value compared to that of the agricultural and industrial participants in all objectives due to less water intake, and as a result, it has a significant impact on the robustness of water supply system.