Exploratory Modeling for Understanding Water Scarcity in Coupled Human-Natural Systems: From Vulnerability Assessment to Scenario Storyline Discovery

Traditional scenario-based approaches to water resources planning often miss consequential dynamics and diverse stakeholder vulnerabilities that emerge from complex interactions between climate, institutions, infrastructure, and human action. This presentation will demonstrate the use of bottom-up exploratory modeling frameworks in advancing our understanding of water scarcity in institutionally complex river basins by systematically exploring large ensembles of plausible futures. Working in the Upper Colorado River Basin—a system governed by prior appropriation water rights—we couple the State's water allocation model with exploratory modeling to simulate hundreds of thousands of plausible scenarios spanning diverse hydroclimatic conditions, demand changes, and other stressors. Paired with global sensitivity analysis and other diagnostics, we show how human institutions and system complexity fundamentally shape vulnerability: under identical scenarios, stakeholders experience vastly different impacts depending on their position within water rights and infrastructure networks. The analysis demonstrates several critical insights. First, dominant stressors controlling water shortages vary across users and across severity thresholds for individual users. Second, robustness assessments must account for multiple actors with distinct objectives, as no single metric captures all system responses to stress. Third, scenario storylines can be identified and used to describe consequential multi-actor dynamics and inform planning, despite these limitations. This framework is currently extended with new stochastic weather generation tools using multivariate copulas to explore deeply uncertain precipitation-temperature relationships and their compounding effects on water scarcity. This work demonstrates how exploratory modeling can transform traditional water resources planning from evaluating predetermined scenarios to systematically discovering consequential uncertainties and generating actionable storylines for decision-making under deep uncertainty.