Integrating an hourly weather generator with an hourly rainfall SWAT model for climate change impact assessment in the Ru River Basin, China

Abstract

The Ru River Basin is facing severe water security challenges such as frequent occurrence of extreme events and serious nutrient enrichment of its water bodies. In simulating daily streamflow, monthly total nitrogen (TN) loads, and monthly total phosphorous (TP) loads of the basin, the SWAT (Soil and Water Assessment Tool) model utilizing hourly rainfall inputs was found to perform considerably better than the model utilizing daily rainfall inputs. For climate change impact assessment, the hourly weather generator AWE-GEN was calibrated based on historical hourly rainfall records from 1970 to 1999 in the basin. Evaluation of its performance have indicated that the AWE-GEN could reasonably characterize the main features of monthly, daily, and hourly rainfall in the basin. The outputs of eight GCMs under a total of four climate change scenarios were then downscaled with the AWE-GEN to produce synthetic future hourly rainfall series to drive the hourly rainfall SWAT model for climate change impact assessment. The ensemble of SWAT simulation results have suggested that future streamflow, TN loads and TP loads were all likely to increase in the flood season in the Ru River Basin. Since the Ru River has already been afflicted with nutrient enrichment issues, the projected increase in nutrient loads due to climate change necessitates the enforcement of additional nutrient abatement measures to offset the adverse impacts imposed by climate change.