Selecting Stochastic Climate Realizations to Efficiently Explore a Wide Range of Climate Risk to Water Resource Systems

Abstract

There are significant computational requirements for assessing climate change impacts on water resource system reliability and vulnerability, particularly when analyzing a wide range of plausible scenarios. These requirements often deter analysts from exhaustively identifying climate hazards. This technical note investigates two approaches for generating a subset of stochastic climate realizations that efficiently explore a range of risk to water supply systems. In both methods, a large ensemble of stochastic weather time series is generated to simulate the natural variability of the local climate system, and a selected subset of these sequences is used in the impacts assessment. Method 1 selects the subset by first passing the entire ensemble through a rainfall-runoff model and then screening the hydrologic sequences using the sequent peak algorithm. Method 2 selects a subset of climate sequences based on climate statistics alone, prior to hydrological modeling. Both methods provide insight for identifying the climate statistics that best relate to the vulnerability of the water system and can be used to reduce the computational burden of modeling climate variability and change impacts.