摘要

In 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 for minimizing biases in MRI-GCM precipitation output. A distributed rainfall-runoff model enabled generation of streamflow series using bias-corrected GCM output for 1979-2003 and 2075-2099 periods, as current and future scenarios, respectively. Finally, comparative flood frequency analyses were carried out for the simulated annual daily maximum streamflow series of current and future climates. The analyses revealed that the climate change will result more extreme precipitation events in monsoon months and less precipitation in other months. The analyses also revealed that flood events will be significantly increased in future. The range of change in 2-100 year return period floods was from 24-40%.

  • 出版日期2015-8