The Importance of Digital Elevation Model Selection in Flood Simulation and a Proposed Method to Reduce DEM Errors: A Case Study in Shanghai

Chengbo Wu,Kepeng Xu,Qinke Sun,Min Liu,Yongqiang Fang,Jiayi Fang

doi:10.1007/s13753-021-00377-z

Chengbo Wu, Kepeng Xu + Show 4 more

Open Access

https://doi.org/10.1007/s13753-021-00377-z

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Abstract

Digital Elevation Models (DEMs) play a critical role in hydrologic and hydraulic modeling. Flood inundation mapping is highly dependent on the accuracy of DEMs. Various vertical differences exist among open access DEMs as they use various observation satellites and algorithms. The problem is particularly acute in small, flat coastal cities. Thus, it is necessary to assess the differences of the input of DEMs in flood simulation and to reduce anomalous errors of DEMs. In this study, we first conducted urban flood simulation in the Huangpu River Basin in Shanghai by using the LISFLOOD-FP hydrodynamic model and six open-access DEMs (SRTM, MERIT, CoastalDEM, GDEM, NASADEM, and AW3D30), and analyzed the differences in the results of the flood inundation simulations. Then, we processed the DEMs by using two statistically based methods and compared the results with those using the original DEMs. The results show that: (1) the flood inundation mappings using the six original DEMs are significantly different under the same simulation conditions—this indicates that only using a single DEM dataset may lead to bias of flood mapping and is not adequate for high confidence analysis of exposure and flood management; and (2) the accuracy of a DEM corrected by the Dixon criterion for predicting inundation extent is improved, in addition to reducing errors in extreme water depths—this indicates that the corrected datasets have some performance improvement in the accuracy of flood simulation. A freely available, accurate, high-resolution DEM is needed to support robust flood mapping. Flood-related researchers, practitioners, and other stakeholders should pay attention to the uncertainty caused by DEM quality.

Highlights

Flooding has caused tremendous economic losses and fatalities around the world (Najibi and Devineni 2018), and coastal cities are areas that are at significant risk from flooding (Aerts et al 2014)
The results show that: (1) the flood inundation mappings using the six original Digital Elevation Models (DEMs) are significantly different under the same simulation conditions—this indicates that only using a single DEM dataset may lead to bias of flood mapping and is not adequate for high confidence analysis of exposure and flood & Jiayi Fang jyfang@geo.ecnu.edu.cn & Min Liu mliu@geo.ecnu.edu.cn
We focused on comparing the inundation simulation results of six open access DEMs and proposed a new method to eliminate DEM errors in the study area of Shanghai

Summary

Introduction

Flooding has caused tremendous economic losses and fatalities around the world (Najibi and Devineni 2018), and coastal cities are areas that are at significant risk from flooding (Aerts et al 2014). In recent decades there has been a massive migration of people towards the coastal regions of China (Niu and Zhao 2018), which has led to a large concentration of wealth and population in these areas (Dovern et al 2014). This change increases coastal cities’ exposure to risks (Surjan et al 2016), especially flood risk. An accurate assessment of flood inundation in urban areas in coastal cities is vital to understanding flood risks and providing precise disaster forecasting and emergency response (Yang et al 2020; Yin et al 2020)

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