PNNL

Abstract

There is significant uncertainty in how global water supply will evolve in the future, due to unknown climate, socioeconomic, and land use change drivers as well as the internal variability of hydrologic processes. It is critical to characterize the potential impacts of uncertainty in future water supply given its importance to the production of food and energy. We address the challenge of characterizing future water supply uncertainty and its multisector impacts through a novel integration of stochastic watershed and multisector dynamics models. We demonstrate that our stochastic watershed model can efficiently and effectively generate a large ensemble of scenarios of basin-scale runoff with global coverage that preserves mean, variance, and spatial correlation of a historical benchmark. We apply our stochastic model to a deterministic projection of future runoff that we run through a multisector dynamics model to explore the impacts of runoff variability on the energy, water, and agricultural sectors across spatial scales. We find that the impacts of future hydrologic variability vary across sector and region and are felt most strongly in the water and agricultural sectors for basins that are expected to have unsustainable water use in the future. Using the Indus River basin as a case study, we also show how our stochastic ensemble can be leveraged to explore the global multisector consequences of local extreme runoff conditions. This work introduces a novel technique to explore the propagation of future hydrologic variability across natural systems and spatial scales.