Abstract

Projecting future changes in extreme flood is critical for risk management. This paper presented an analysis of the implications of the Fifth Coupled Model Intercomparison Project Phase (CMIP5) climate models on the future flood in the Jinsha River Basin (JRB) in Southwest China, using the Xinanjiang (XAJ) hydrologic model. The bias-corrected and resampled results of the multimodel dataset came from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Relatively optimal general circulation models (GCMs) were selected with probability density functions (PDFs)-based assessment. These GCMs were coupled with the XAJ model to evaluate the impact of climate change on future extreme flood changes in the JRB. Two scenarios were chosen, namely: a midrange mitigation scenario (Representative Concentration Pathway 4.5, RCP4.5) and a high scenario (RCP8.5). Results show that: (1) The XAJ model performed well in simulating daily discharge and was suitable for the study area, with ENS and R2 higher than 0.8; (2) IPSL-CM5A-LR and MIROC-ESM-CHEM showed considerable skill in representing the observed PDFs of extreme precipitation. The average skill scores across the total area of the JRB were 0.41 to 0.66 and 0.53 to 0.67, respectively. Therefore, these two GCMs can be chosen to analyze the changes in extreme precipitation and flood in the future; (3) The average extreme precipitation under 20- and 50-year return period across the JRB were projected to increase by 1.0–33.7% under RCP4.5 and RCP8.5 during 2020 to 2050. The Upper basin is projected to experience the largest increase in extreme precipitation indices, possibly caused by a warmer climate. The extreme flood under 20- and 50-year return period will change by 0.8 to 23.8% and −6.2 to 28.2%, respectively, over this same future period. Most of scenarios projected an increase during the near future periods, implying the JRB would be likely to undergo more flooding in the future.

Highlights

  • The recorded data series was divided into calibration driving data of the XAJ model were generated

  • The recorded data series was divided into calibration period validation period period

  • This research studied the projected extreme precipitation and flood variation of the Jinsha River Basin (JRB) in RCP4.5 and RCP8.5 scenarios based on five CMIP5 general circulation models (GCMs)

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Summary

Introduction

Between 1980 and 2013, economic losses caused by floods have exceeded $1 trillion (2013 values). Over this same period, more than 220,000 people have lost their lives [1]. Global climate change has already begun to affect the earth’s hydrologic cycle. Warmer climate will bring about high atmospheric moisture content, which will further lead to the increase of extreme precipitation events [2,3,4]. As flood is influenced greatly by precipitation, the risk of this kind of extreme hydrologic event is likely to grow. Investigating flood changes in the context of climate change is imperative for risk management

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