A High-Resolution DEM-Based Method for Tracking Urban Pluvial–Fluvial Floods

Flood models based on high-resolution digital elevation models (DEMs) are important for identifying urban land inundation during extreme rainfall events. Urban pluvial and fluvial floods are influenced by distinct processes that are interconnected; thus, they can transform into one another. Conventional flood models struggle to delineate inundation caused by drainage system overflow (urban pluvial flood) and that caused by rivers (urban fluvial flood). In this study, we proposed a novel method for identifying urban pluvial–fluvial floods using a high-resolution DEM. We developed a DEM-based surface pluvial and fluvial inundation tracking model (DEM-SPFITM) that incorporated flood development and mutual transformation processes. When combined with a surface flood control model (SFCM), this approach enabled tracking of the flow paths and exchanged water volume associated with both flood types. The case study results indicate that the proposed method effectively captures the interplay between pluvial and fluvial flooding, enabling the separate identification of flood extent, depth, and velocity under extreme rainfall conditions for both pluvial and fluvial flooding. Compared to the conventional approach, which independently simulates pluvial and fluvial flooding using the SFCM and subsequently overlays the results to estimate pluvial–fluvial flooding inundation, the proposed method demonstrates superior accuracy and computational efficiency. Simulations of three extreme rainstorms indicated that pluvial flooding primarily contributed to extensive land inundation, characterised by shallower depths and lower velocities, with a limited influence of flood depth on velocity. Meanwhile, fluvial flooding further exacerbated land inundation, leading to significant pluvial–fluvial coexistence. In areas adjacent to these flood zones, fluvial flooding predominated, resulting in greater inundation depths and a more pronounced effect of flood depth on velocity. As rainfall intensity and total rainfall increased, the area of fluvial inundation diminished significantly, whereas pluvial–fluvial coexistence intensified and was distributed in zones with relatively large inundation depths and higher flow velocities. This research presented a novel method for distinguishing between urban pluvial–fluvial floods, providing valuable insights for integrated urban flood management and joint flood risk zoning.

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Publication Details

Journal
Remote Sensing
Published
2025-03-30
DOI
https://doi.org/10.3390/rs17071225
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

A High-Resolution DEM-Based Method for Tracking Urban Pluvial–Fluvial Floods

Weihong Liao, Hao Wang, Yongshuai Liang
Remote Sensing
Flood Risk Assessment and Management
article

A High-Resolution DEM-Based Method for Tracking Urban Pluvial–Fluvial Floods

Weihong Liao, Hao Wang, Yongshuai Liang
article en

Abstract

Flood models based on high-resolution digital elevation models (DEMs) are important for identifying urban land inundation during extreme rainfall events. Urban pluvial and fluvial floods are influenced by distinct processes that are interconnected; thus, they can transform into one another. Conventional flood models struggle to delineate inundation caused by drainage system overflow (urban pluvial flood) and that caused by rivers (urban fluvial flood). In this study, we proposed a novel method for identifying urban pluvial–fluvial floods using a high-resolution DEM. We developed a DEM-based surface pluvial and fluvial inundation tracking model (DEM-SPFITM) that incorporated flood development and mutual transformation processes. When combined with a surface flood control model (SFCM), this approach enabled tracking of the flow paths and exchanged water volume associated with both flood types. The case study results indicate that the proposed method effectively captures the interplay between pluvial and fluvial flooding, enabling the separate identification of flood extent, depth, and velocity under extreme rainfall conditions for both pluvial and fluvial flooding. Compared to the conventional approach, which independently simulates pluvial and fluvial flooding using the SFCM and subsequently overlays the results to estimate pluvial–fluvial flooding inundation, the proposed method demonstrates superior accuracy and computational efficiency. Simulations of three extreme rainstorms indicated that pluvial flooding primarily contributed to extensive land inundation, characterised by shallower depths and lower velocities, with a limited influence of flood depth on velocity. Meanwhile, fluvial flooding further exacerbated land inundation, leading to significant pluvial–fluvial coexistence. In areas adjacent to these flood zones, fluvial flooding predominated, resulting in greater inundation depths and a more pronounced effect of flood depth on velocity. As rainfall intensity and total rainfall increased, the area of fluvial inundation diminished significantly, whereas pluvial–fluvial coexistence intensified and was distributed in zones with relatively large inundation depths and higher flow velocities. This research presented a novel method for distinguishing between urban pluvial–fluvial floods, providing valuable insights for integrated urban flood management and joint flood risk zoning.

Remote SensingVol. 17(7)
China Institute of Water Resources and Hydropower Research (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 93%
Flood Risk Assessment and Management
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