Impacts of Climate Change on Urban Extreme Rainfall and Drainage Infrastructure Performance: A Case Study in Wuhan City, China

Abstract

The design of stormwater drainage infrastructure in urban areas in China is based on the statistical stationary assumption of probability distribution of extreme rainfall, which is being increasingly challenged by climate change. However, quantitative assessment of the performance of urban drainage systems in response to climate change with the latest emission scenarios of the Coupled Model Intercomparison Project Phase 5 in China is quite limited. This study aims to investigate potential changes of extreme rainfall and their influence on drainage infrastructure in a representative urban area in Wuhan city, China. The Storm Water Management Model is established to investigate the response of drainage infrastructure to future design rainfall. It is found that the probability distribution of extreme rainfall for two historical sub‐periods (1961–1985 and 1986–2005) has changed, especially in the head and tail of the frequency curves. Furthermore, the design rainfall with return periods of 2, 3, 4 and 5 years increases more significantly than those of 10 and 20 years. Consequently, the incapability of the current drainage infrastructure in the study area is aggravated. Moreover, the results of SWMM modelling provide detailed information about the performance of current drainage infrastructure, which can provide technical support for future modifications of the current drainage infrastructure of the study area. © 2018 John Wiley & Sons, Ltd.

On the Applicability of the Expected Waiting Time Method in Nonstationary Flood Design

“…A typical assumption in TFFA is stationarity, i.e., the statistical characteristics (e.g., mean and standard deviation) in flood sample series collected during a historical period are identical in the future. However, hydrological systems throughout the world have undergone substantial alterations caused by natural and anthropogenic changes, and the stationary assumption is untenable and questionable (Su and Chen 2019;Xiong et al 2019;Li et al 2018;Serago and Vogel 2018;Wang et al 2018;Xie et al 2018;Zhang et al 2018a, b). Thus, TFFA should be revised and accommodated to take into account nonstationarity in flooding design, in particular a system vulnerable to changing environment.…”

Design flood estimation with varying record lengths in Norway under stationarity and nonstationarity scenarios

“…However, it should be mentioned that the ST assumption is quite rigorous because of the dynamic nature of flood events caused by climate change and human activities (Vogel et al 2011;Luke et al 2017;Serago & Vogel 2018;Zhang et al 2019). Thus, the ST assumption has been questioned by many researchers under changing environment (Milly et al 2008;Villarini et al 2009;Montanari et al 2013;Milly et al 2015;Yan et al 2017a;Xu et al 2018;Xiong et al 2019;Yan et al 2019b).…”

Calculation Method of Short Duration Rainstorm Intensity Formula Considering Non-Stationarity of Rainfall Series: Impacts on Simulation of Urban Drainage System

“…In recent years, many researchers have analyzed the impact of environmental change on extreme rainstorm and urban drainage system (Denault et al, 2006;Arnbjerg-Nielsen et al, 2013;Huong and Pathirana, 2013;Zhang et al, 2019;Xiong et al, 2019;Andimuthu et al, 2019;Yang et al, 2020).It is found that under the non-stationary conditions and future environment, the risk of damage to the existing drainage system infrastructure will increase. The change of short duration rainstorm will have a significant impact on the outflow, overload and overflow of urban drainage system.…”