Remote Sensing-Supported Flood Forecasting of Urbanized Watersheds—A Case Study in Southern China
Urbanization has significant impacts on watershed hydrology, but previous studies have been confirmatory and not comprehensive; in particular, few studies have addressed the impact of urbanization on flooding in highly urbanized watersheds. In this study, this effect is studied in Chebei Creek, a hi...
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MDPI AG
2022-12-01
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Online Access: | https://www.mdpi.com/2072-4292/14/23/6129 |
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author | Yu Gu Yangbo Chen Huaizhang Sun Jun Liu |
author_facet | Yu Gu Yangbo Chen Huaizhang Sun Jun Liu |
author_sort | Yu Gu |
collection | DOAJ |
description | Urbanization has significant impacts on watershed hydrology, but previous studies have been confirmatory and not comprehensive; in particular, few studies have addressed the impact of urbanization on flooding in highly urbanized watersheds. In this study, this effect is studied in Chebei Creek, a highly urbanized watershed in the Pearl River Delta, southern China. Landsat satellite images acquired in 2015 were used to estimate land use and cover changes using the Decision Tree (DT) C4.5 classification algorithm, while the Liuxihe model, a physically based distributed hydrological model (PBDHM), is employed to simulate watershed flooding and hydrological processes. For areas with high degrees of urbanization, the duration of the flood peak is only 1 h, and the flood water level shows steep rises and falls. These characteristics increase the difficulty of flood modeling and forecasting in urbanized areas. At present, hydrological research in urbanized watersheds generally focuses on the quantitative simulation of runoff from urban areas to the watershed, flood flows, peak flood flow, and runoff depth. Few studies have involved real-time flood forecasting in urbanized watersheds. To achieve real-time flood forecasting in urbanized watersheds, PBDHMs and refined underlying surface data based on remote sensing technology are necessary. The Liuxihe model is a PBDHM that can meet the accuracy requirements of inflow flood forecasting for reservoir flood control operations. The accuracies of the two flood forecasting methods used in this study were 83.95% and 97.06%, showing the excellent performance of the Liuxihe model for the real-time flood forecasting of urbanized rivers such as the Chebei Creek watershed. |
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issn | 2072-4292 |
language | English |
last_indexed | 2024-03-09T17:32:38Z |
publishDate | 2022-12-01 |
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spelling | doaj.art-363d3b81764e4db8ba2250573b2049102023-11-24T12:06:17ZengMDPI AGRemote Sensing2072-42922022-12-011423612910.3390/rs14236129Remote Sensing-Supported Flood Forecasting of Urbanized Watersheds—A Case Study in Southern ChinaYu Gu0Yangbo Chen1Huaizhang Sun2Jun Liu3School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, ChinaSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, ChinaSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, ChinaSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, ChinaUrbanization has significant impacts on watershed hydrology, but previous studies have been confirmatory and not comprehensive; in particular, few studies have addressed the impact of urbanization on flooding in highly urbanized watersheds. In this study, this effect is studied in Chebei Creek, a highly urbanized watershed in the Pearl River Delta, southern China. Landsat satellite images acquired in 2015 were used to estimate land use and cover changes using the Decision Tree (DT) C4.5 classification algorithm, while the Liuxihe model, a physically based distributed hydrological model (PBDHM), is employed to simulate watershed flooding and hydrological processes. For areas with high degrees of urbanization, the duration of the flood peak is only 1 h, and the flood water level shows steep rises and falls. These characteristics increase the difficulty of flood modeling and forecasting in urbanized areas. At present, hydrological research in urbanized watersheds generally focuses on the quantitative simulation of runoff from urban areas to the watershed, flood flows, peak flood flow, and runoff depth. Few studies have involved real-time flood forecasting in urbanized watersheds. To achieve real-time flood forecasting in urbanized watersheds, PBDHMs and refined underlying surface data based on remote sensing technology are necessary. The Liuxihe model is a PBDHM that can meet the accuracy requirements of inflow flood forecasting for reservoir flood control operations. The accuracies of the two flood forecasting methods used in this study were 83.95% and 97.06%, showing the excellent performance of the Liuxihe model for the real-time flood forecasting of urbanized rivers such as the Chebei Creek watershed.https://www.mdpi.com/2072-4292/14/23/6129urbanizationLiuxihe modelland use/cover changesflood forecastingremote sensing |
spellingShingle | Yu Gu Yangbo Chen Huaizhang Sun Jun Liu Remote Sensing-Supported Flood Forecasting of Urbanized Watersheds—A Case Study in Southern China Remote Sensing urbanization Liuxihe model land use/cover changes flood forecasting remote sensing |
title | Remote Sensing-Supported Flood Forecasting of Urbanized Watersheds—A Case Study in Southern China |
title_full | Remote Sensing-Supported Flood Forecasting of Urbanized Watersheds—A Case Study in Southern China |
title_fullStr | Remote Sensing-Supported Flood Forecasting of Urbanized Watersheds—A Case Study in Southern China |
title_full_unstemmed | Remote Sensing-Supported Flood Forecasting of Urbanized Watersheds—A Case Study in Southern China |
title_short | Remote Sensing-Supported Flood Forecasting of Urbanized Watersheds—A Case Study in Southern China |
title_sort | remote sensing supported flood forecasting of urbanized watersheds a case study in southern china |
topic | urbanization Liuxihe model land use/cover changes flood forecasting remote sensing |
url | https://www.mdpi.com/2072-4292/14/23/6129 |
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