Dynamic Adaptation of Water Resources Systems Under Uncertainty by Learning Policy Structure and Indicators

The challenge of adapting water resources systems to uncertain hydroclimatic and socioeconomic conditions warrants a dynamic planning approach. Recent studies have designed policies with structures linking infrastructure and management actions to threshold values of indicator variables observed over time. Typically, one or more of these components are held fixed while the others are optimized, constraining the flexibility of policy generation. Here we develop a framework to address this challenge by designing and testing dynamic adaptation policies that combine indicators, actions, and thresholds in a flexible structure. The approach is demonstrated for a case study of northern California, where a mix of infrastructure, management, and operational adaptations are considered over time in response to an ensemble of nonstationary hydrology and water demands. We first identify a subset of non-dominated policies that are robust to held-out scenarios, and then analyze their most common actions and indicators compared to non-robust policies. Results show that the robust policies are not differentiated by the actions they select, but show substantial differences in their indicator variables, which can be interpreted in the context of physical hydrologic trends. In particular, the most frequent statistical transformations of indicator variables highlight the balance between adapting quickly versus correctly. Additionally, we determine the indicators most frequently associated with each action, as well as the distribution of action timing across scenarios. This study presents a new and transferable problem framing for adaptation under uncertainty in which indicator variables, actions, and policy structure are identified simultaneously during the optimization.