High Risk Flash Flood Rainstorm Area Mapping And Its Application in Jiangxi Province, China

Abstract

The leading hydrologists around the world have been working hard to develop some kind of preventive measures to reduce the disastrous consequences of a flash flood in advance. For this purpose, a flash flood early-warning and forecasting system that can accurately and timely forecast an coming flash flood has being the research focus in this field, despite its difficulties and complexities. An ideal to specify those areas that are subject at high risk to flash flood in terms of precipitation intensity in a relatively large region is proposed in this paper. It is accomplished through the design of the High Risk Flash Flood Rainstorm Area (HRFFRA) with a certain return period for a given duration based on the application of the end-to-end Regional L-moments Approach to precipitation frequency analysis. A HRFFRA is defined as the area potentially under hitting by higher intense-precipitation for a given duration with certain return period that may cause a flash flood disaster in the area. An example to develop the HRFFRA has been demonstrated in detail in this paper through the application of the Regional L-Moments Approach to precipitation frequency analysis in Jiangxi Province, South China Mainland. The high risk areas that will be hit by an forthcoming flash flood can be visually showed by the HRFFRA, with its help, hydrologists and governments can substantially reduce the disastrous outcome of a flash flood beforehand.

Regional Precipitation frequency analysis for 24-hour duration using L-moments approach in Shaoguan, South China

“…Later, by applying the concept of regional analysis, Lin et al separated a rainfall into common component and local component, in the practices of precipitation frequency analysis for the NOAA Atlas 14 in the U.S. (Lin et al 2006;Bonnin et al 2012) as well as for the Taihu Lake Basin in China Wu et al 2015). Other studies abroad have also been done using the regional L-moments approach which is combing the regional analysis with the L-moments for rainfall frequency analysis (e.g., United Kingdom (Fowler et al 2010), Italy (Norbiato et al 2007), Norway (Hailegeorgis et al 2013)) and many regions of China (e.g., Guangxi (Chen et al 2014), Yangtze River Delta region (Yin et al 2016), Huaihe River Basin (Shao et al 2016), Jiangxi (Ding et al 2018;Liu et al 2018), Sichuan (Li et al 2019) and Xiamen (Shang et al 2019)). The research results indicated that the regional L-moments method is able to solve the problems related to identification of homogeneous regions, testing and selection of the best fitting distribution, as well as estimations of parameters and quantiles at places of interest.…”

A New Look at Storm Separation Technique in Estimation of Probable Maximum Precipitation in Mountainous Areas

“…It is reported that L-moments have the theoretical advantages over conventional moments of being more robust to the presence of outliers in the data and being less subjective to biasness in estimation of parameters [10,13,15,17]. Other studies have also been done using the regional L-moments approach for rainfall frequency analysis globally (e.g., United Kingdom [18], Italy [19], Norway [20]) and many regions of China (e.g., Guangxi [21], Yangtze River Delta region [22], Huaihe River Basin [23], Jiangxi [24,25], and Sichuan [26]). The research results indicated that this method is at an advantage on estimation of extreme quantiles over the at-site analysis under the conventional moments.…”