Impacts of Climate Change on Urban Drainage Systems by Future Short-Duration Design Rainstorms

Han Zhang,Yanpeng Cai,Jing Qiu,Zhifeng Yang,Bensheng Huang

doi:10.3390/w13192718

Abstract

The adverse impacts of climate change and urbanization are converging to challenge the waterlogging control measures established in the Dong Hao Chong (DHC) Basin. Based on representative concentration pathway (RCP) scenarios, the future (2030–2050) waterlogging was assessed for the DHC basin and combined with future design rainfall. The delta change factors were projected using the regional climate model, RegCM4.6, and the annual maximum one-day rainstorm was modified to develop the annual maximum value method. By combining the delta change and annual maximum value methods, a future short-duration design rainstorm formula is developed in this study. The Chicago hyetograph shapes indicated that the peak rainfall intensity and amount both increase in the five return periods with two RCP scenarios. The InfoWorks ICM urban flood model is used to simulate the hydrological response. The results show that climate change will exacerbate urban waterlogging in DHC Basin. The maximum inundation volume and number of inundation nodes were expected to increase in the five return periods under the RCP4.5 and RCP8.5 scenarios, respectively. The submerged area is increasing due to climate change. This study highlights the link between climate change and urban drainage systems, and suggests that the effect of climate change in extreme rainfall should be considered in urban waterlogging management and drainage system design.

Highlights

IntroductionThe atmospheric concentrations of greenhouse gases have been increasing since industrialization due to human activity, and have led to significant climate change that intensifies the global hydrological cycle and influences climatology characteristics
The performance of regional climate model (RCM) downscaling outputs is evaluated by comparing with the observations of 15 meteorological stations, on the basis of the mean error (ME), root mean squared error (RMSE), temporal correlation coefficient (TCC) and spatial correlation coefficient (SCC)
The Rx1day, Rx5day and R25mm tend to be underestimated by 33%, 24%, and 12.74 days, respectively, which indicates an uncertainty involved in RCM for reproducing extreme precipitation events

Summary

Introduction

The atmospheric concentrations of greenhouse gases have been increasing since industrialization due to human activity, and have led to significant climate change that intensifies the global hydrological cycle and influences climatology characteristics. Rainfall will become more uneven and intense [1], and such variations in rainfall have had serious impacts on urban flooding in recent years [2]. General circulation models (GCMs) are a class of computer-driven models for understanding the historical climate and projecting future climate change, and are considered to be the most reliable resources that are currently available for investigating and predicting climate change [3,4,5]. The resolution of GCM outputs tends to be coarse and cannot be used directly in hydrological modeling for regional climate impact studies

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Discussion

Conclusion