Identifying key water resource vulnerabilities in data‐scarce transboundary river basins

This paper presents a two‐step framework to identify key water resource vulnerabilities in transboundary river basins where data availability on both hydrological fluxes and the operation of man‐made facilities is either limited or nonexistent. In a first step, it combines two state‐of‐the‐art modeling tools to overcome data limitations and build a model that provides a lower bound on risks estimated in that basin. Land data assimilation (process‐based hydrological modeling taking remote‐sensed products as inputs) is needed to evaluate hydrological fluxes, that is, streamflow data and consumptive use in irrigated agriculture—a lower‐end estimate of demand. Hydroeconomic modeling provides cooperative water allocation policies that reflect the best‐case management of storage capacity under hydrological uncertainty at a monthly time step for competing uses—hydropower, irrigation. In a second step, the framework uses additional scenarios to proceed with the in‐depth analysis of the vulnerabilities identified despite the use of what is by definition a best‐case model. We implement this approach to the Tigris‐Euphrates river basin, a politically unstable region where water scarcity has been hypothesized to serve as a trigger for the Syrian revolution and ensuing war. Results suggest that even under the framework's best‐case assumptions, the Euphrates part of the basin is close to a threshold where it becomes reliant on transfers of saline water from other parts of the basin to ensure irrigation demands are met. This Tigris‐Euphrates river basin application demonstrates how the proposed framework quantifies vulnerabilities that have been hitherto discussed in a mostly qualitative, speculative way.