A dynamic impact assessment method for rainstorm waterlogging using land-use data

Abstract

As a result of rapid urbanization and climate change, many largeand medium-sized cities in China frequently undergo urban disasters with severe impacts that result in many casualties, induce significant economic losses, and restrict sustainable social and economic development. Providing timely and accurate early warnings is the most effective measure for disaster prevention and mitigation before such disasters can impose severe impacts. In this study, we propose a dynamic impact assessment method for rainstorm waterlogging using land-use data. First, based on a detailed collection of disaster prevention and mitigation data, we construct an impact assessment index based on the assessment objects of this study. Then, a waterlogging simulation is performed, and the simulation results are found to meet the assessment requirements. Finally, we conduct an impact assessment every half hour during a heavy rainfall event and evaluate the performance of the proposed method by assessing the socioeconomic impact, object impact, industry impact, regional impact, and comprehensive impact of the event. These assessments produce valuable information for providing diverse and timely services in the event of urban waterlogging. ARTICLE HISTORY

Assessment of flash flood risk based on improved analytic hierarchy process method and integrated maximum likelihood clustering algorithm

“…In the future, this problem can be improved by acquiring more detailed data and increasing relative risk indices. Moreover, more detailed work would focus on waterlogging disasters in these urban cities in the future (Yang et al, 2019;Zhu et al, 2019).…”

Construction and verification of a rainstorm death risk index based on grid data fusion: a case study of the Beijing rainstorm on July 21, 2012

“…Many other scholars set indexes on disaster-inducing factors, hazard-inducing environment and exposure degree, and constructed corresponding risk assessment models for flood disasters (such as Cao and Li 2015;Jiang et al 2013;Wan et al 2017;Jiang et al 2009;Ma et al 2016). Based on the land-use data, Zhu et al (2019) proposed a dynamic impact assessment method to provide timely rainstorm disaster early warning for decision-makers. Using meteorological and socioeconomic statistical data of the Nanjing area, Chen et al (2020) selected 10 indicators and evaluated urban rainstorm disaster risk in Nanjing city by principal component analysis.…”

Investigation of the drainage loss effects with a street view based drainage calculation method in hydrodynamic modelling of pluvial floods in urbanized area

“…The threat of flooding, particularly in metropolitan areas, has severe societal and economical consequences (Hallegatte et al, 2013;Komolafe et al, 2018;Mustafa et al, 2018;Tanaka et al, 2020) and the associate scientific issues attract both industrial and academic interests. With its effectiveness in simulating flood inundation, numerical modelling has become an indispensable tool in flood risk assessment and management (Rangari et al, 2021;Yin et al, 2016;Zhu et al, 2019). For urbanized environments, as opposed to rural floodplains or natural catchments, flood modelling should accurately simulate the propagation of floods in complex topography that includes flow paths between densely populated areas (Cea and Bladé, 2015;Glenis et al, 2018;Schubert and Sanders, 2012;Xia et al, 2017).…”