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.