Impact of downscaled rainfall biases on projected runoff changes

• Published in: Hydrology and earth system sciences Vol. 24; no. 6; pp. 2981 - 2997
• Main Authors: Charles, Stephen P, Chiew, Francis H. S, Potter, Nicholas J, Zheng, Hongxing, Fu, Guobin, Zhang, Lu
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 08.06.2020; Copernicus Publications
• Subjects: Bias; Catchment area; Catchment scale; Catchments; Climate change; Computer simulation; Daily precipitation; Environmental assessment; Environmental impact; Global temperature changes; Hydraulic flow; Hydrologic models; Hydrology; Mapping; Numerical weather prediction; Prejudice; Rain; Rainfall frequency; Rainfall runoff; Rainfall simulators; Rainfall-runoff modeling; Rainfall-runoff relationships; Regional climates; Runoff; Water supply; Australia
• ISSN: 1607-7938; 1027-5606; 1607-7938
• DOI: 10.5194/hess-24-2981-2020

Realistic projections of changes to daily rainfall frequency and magnitude, at catchment scales, are required to assess the potential impacts of climate change on regional water supply. We show that quantile–quantile mapping (QQM) bias-corrected daily rainfall from dynamically downscaled WRF simulations of current climate produce biased hydrological simulations, in a case study for the state of Victoria, Australia (237 629 km2). While the QQM bias correction can remove bias in daily rainfall distributions at each 10 km × 10 km grid point across Victoria, the GR4J rainfall–runoff model underestimates runoff when driven with QQM bias-corrected daily rainfall. We compare simulated runoff differences using bias-corrected and empirically scaled rainfall for several key water supply catchments across Victoria and discuss the implications for confidence in the magnitude of projected changes for mid-century. Our results highlight the imperative for methods that can correct for temporal and spatial biases in dynamically downscaled daily rainfall if they are to be suitable for hydrological projection.