Assessment of Future Floods in the Bagmati River Basin of Nepal Using Bias-Corrected Daily GCM Precipitation Data

Abstract

AbstractIn this paper, climate change impact on flood frequency has been investigated in Bagmati River Basin of Nepal using bias-corrected global climate model (GCM) precipitation output. The research reported in this paper employed a high-resolution (approximately 20-km) daily GCM precipitation and temperature output of Meteorological Research Institute (MRI), Japan. Comparison of observation and GCM data pointed out that the MRI-GCM precipitation consists of significant biases in frequency and intensity values. Quantile-quantile mapping method of GCM bias correction was applied for minimizing the biases in precipitation frequencies and intensities. Concept of homogeneous precipitation regions was introduced to link the uneven observation data stations and GCM grid cells. Analyses of return period curves, shape, and scale factors at different observation stations enabled delineation of three homogeneous precipitation regions. Accordingly, regional quantile-quantile bias-correction technique was developed...