title: Urban flood risk warning under rapid urbanization.
abstract: In the past decades, China has observed rapid urbanization, the nation's urban population reached 50% in 2000, and is still in steady increase. Rapid urbanization in China has an adverse impact on urban hydrological processes, particularly in increasing the urban flood risks and causing serious urban flooding losses. Urban flooding also increases health risks such as causing epidemic disease break out, polluting drinking water and damaging the living environment. In the highly urbanized area, non-engineering measurement is the main way for managing urban flood risk, such as flood risk warning. There is no mature method and pilot study for urban flood risk warning, the purpose of this study is to propose the urban flood risk warning method for the rapidly urbanized Chinese cities. This paper first presented an urban flood forecasting model, which produces urban flood inundation index for urban flood risk warning. The model has 5 modules. The drainage system and grid dividing module divides the whole city terrain into drainage systems according to its first-order river system, and delineates the drainage system into grids based on the spatial structure with irregular gridding technique; the precipitation assimilation module assimilates precipitation for every grids which is used as the model input, which could either be the radar based precipitation estimation or interpolated one from rain gauges; runoff production module classifies the surface into pervious and impervious surface, and employs different methods to calculate the runoff respectively; surface runoff routing module routes the surface runoff and determines the inundation index. The routing on surface grid is calculated according to the two dimensional shallow water unsteady flow algorithm, the routing on land channel and special channel is calculated according to the one dimensional unsteady flow algorithm. This paper then proposed the urban flood risk warning method that is called DPSIR model based multiple index fuzzy evaluation warning method, and referred to as DMFEW method. DMFEW first selects 5 evaluation indexes based on the DPSIR model for flood risk warning evaluation, including driving force index, pressure index, state index, impact index and response index. Based on the values of all evaluation indexes, one evaluation index for the whole system evaluation result is determined by using the fuzzy comprehensive evaluation method. The flood risk level is divided into 4 levels, having Level 1 the most serious. Every evaluation index is also categorized as 4 levels, and a linear fuzzy subjection function is proposed to do the fuzzy comprehensive evaluation. Dongguan City is used as the study case to validate the proposed method. The urban flood forecasting model is set up with the topographic data, the city map, the underground pipelines and land cover types, and two flood events are simulated with observed precipitation, one is interpolated from the rain gauges data, and another is estimated by digital weather radar. The simulated results are compared with the investigated water depth, and the results show the model has very good performances. The results are further used for the flood risk warning simulation, and are very reasonable.
authors.affiliation: Laboratory of Water Disaster Management and Hydroinformatics, School of Geography and Planning, Sun Yat-sen University, 510275 Guangzhou, China. Electronic address: eescyb@mail.sysu.edu.cn.
authors.forename: Yangbo
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Laboratory of Water Disaster Management and Hydroinformatics, School of Geography and Planning, Sun Yat-sen University, 510275 Guangzhou, China.
authors.forename: Haolan
authors.initials: H
authors.lastname: Zhou
authors.affiliation: Laboratory of Water Disaster Management and Hydroinformatics, School of Geography and Planning, Sun Yat-sen University, 510275 Guangzhou, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Laboratory of Water Disaster Management and Hydroinformatics, School of Geography and Planning, Sun Yat-sen University, 510275 Guangzhou, China.
authors.forename: Guoming
authors.initials: G
authors.lastname: Du
authors.affiliation: Laboratory of Water Disaster Management and Hydroinformatics, School of Geography and Planning, Sun Yat-sen University, 510275 Guangzhou, China.
authors.forename: Jinhui
authors.initials: J
authors.lastname: Zhou
mesh_terms: D002681:China; D002959:Civil Defense; D004190:Disasters / Q000706:statistics & numerical data; D055868:Floods / Q000706:statistics & numerical data; D008962:Models, Theoretical; D011891:Rain; D018570:Risk Assessment; D012498:Sanitary Engineering; D014507:Urbanization / Q000639:trends*
keywords: DPSIR model; Fuzzy comprehensive evaluation; Fuzzy evaluation; Radar based precipitation estimation; Urban flood forecasting model; Urban risk warning