Actionable human-water systems modeling under uncertainty

Abstract

Abstract. This paper develops an actionable interdisciplinary model that thoroughly quantifies and assesses uncertainties in water resources allocation under climate change. To achieve this objective, we develop an innovative socio-ecological grand ensemble that combines climate, hydrological, and microeconomic ensemble experiments with a widely used Decision Support System for water resources planning and management. Each system is populated with multiple models (multi-model), which we use to evaluate the impacts of multiple climatic scenarios and policies (multi-scenario, multi-forcing) across systems, so as to identify plausible futures where water management policies meet or miss their objectives, and explore potential tipping points. The application of methods is exemplified through a study conducted in the Douro River Basin (DRB), an agricultural basin located in central Spain. Our results show how marginal climate changes can trigger nonlinear water allocation changes in the Decision Support Systems (DSS); which can be further aggravated by the nonlinear adaptive responses of irrigators to water shortages. For example, while some irrigators barely experience economic losses (average profit and employment fall by <0.5 %) under mild water allocation reductions of 5 % or lower, profit and employment fall up to 12 % (~24x more) where water allocation is reduced by 10 % or less (~2x more). This substantiates the relevance of informing on the potential natural and socioeconomic impacts of adaptation strategies, and related uncertainties, towards identifying robust decisions.