An improved interior-outer-set model framework for flood hazard analysis
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ORIGINAL PAPER
An improved interior-outer-set model framework for flood hazard analysis Yanhui Zheng1,2 • Yanhu He1 • Yanpeng Cai1 • Peng Wang3
Ó Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Flood disasters are one of the most destructive hazards faced across the globe, and thus flood hazard analysis is an essential factor for flood management. Due to the randomness and fuzziness of flood hazard, a series of possibilities is required for a certain flood level rather than just one exact probability. As a method for fuzzy hazard analysis derived from the information diffusion theory, the Interior-Outer-Set Model (IOSM) has the potential to reflect the randomness and fuzziness of flood hazard, however, the controlling intervals might have no sample points particularly when there are extraordinarily large flood peak flows or the flood samples concentrate. Based on this, the current study proposes a new framework for flood hazard analysis. First, flood samples are extracted from daily observed peak flow data. Second, the traditional IOSM is improved using design peak flows from flood frequency analysis (FFA) as the controlling points. From this, probability and floods hazard values are estimated via the FFA based IOSM (FFA-IOSM).The proposed framework is applied using data from the Dongjiang River, South China. Results demonstrate that the estimated flood probability was able to more effectively reflect the randomness and fuzziness of flood hazard compared to the traditional IOSM. This study provides a basis for reasonable flood engineering practices and supports the government with effective guidance on flood risk management, particularly under the increasing frequencies of the extreme precipitation events. Keywords Flood frequency analysis Interior-outer-set model Controlling point Possibility–probability distribution Flood hazard estimation
1 Introduction Flood disasters are common disasters that severely affect many countries across the globe (Stefanidis and Stathis 2013; Koks 2018). Over the past several decades, statistics indicate that flooding has caused a great deal of economic
& Yanhu He [email protected] 1
Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, Institute of Environmental and Ecological Engineering, Guangdong University of Technology, Guangzhou 510006, China
2
Franzero Water Technology (Guangzhou) CO., LTD, Guangzhou 510663, China
3
School of Environmental Science and Engineering, Guangdong University of Technology, Panyu District, Guangzhou 510006, China
damage and loss of human lives (Gaume et al. 2009; Gao et al. 2019). From 1900 to 2013, flooding caused more than US $600 billion in losses and approximately 7 million deaths worldwide (Disaster Profiles 2013). For example, more than half of the populations live below the mean sea level in Netherlands, while approximately 10% of the population live in flood risk areas in the UK (Samuels 2006); in the United States, coastal and riverine inundations a
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