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Flash-Flood Hazard Hydro-Geomorphic Characterization and Mapping: Latest Advances and Prospects

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (15 February 2024) | Viewed by 3910

Special Issue Editor


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Guest Editor
China Institute of Water Resources and Hydropower Research, Beijing, China
Interests: flash flood prevention and control; hydrology and hydraulic modeling; remote science; flood risk management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Adverse topographical and geological conditions are important factors contributing to the occurrence of mountain flood disasters. In-depth research on the hydrological and geomorphological characteristics of mountain flood disasters and surveying techniques has become a critical direction for current mountain flood disaster prevention and control. In terms of hydrological and geomorphological characteristics, the accurate description of the underlying surface characteristics of small watersheds and a clear understanding of production–conflux characteristics are crucial for simulating and analyzing the process and causes of mountain floods. With the development of measurement techniques, advanced surveying methods such as LIDAR, UAV aerial photography, and satellite remote sensing have been widely used in the real-time monitoring of terrain and flood dynamics in complex areas, providing more comprehensive and accurate data support for the monitoring, early warning and scientific research of mountain flood disasters. Exploring how to quickly obtain high-precision topographic data, vegetation cover information, and the basic attributes of small watersheds over a large-scale area, and strengthening basic data sharing, promoting the application of various advanced surveying technologies, and improving the scientific and intelligent level of mountain flood disaster prevention and control are the main directions for future research on mountain flood disaster prevention and control. The journal will play a critical role in mountain flood disaster monitoring, early warning and scientific research.

Prof. Dr. Changjun Liu
Guest Editor

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Keywords

  • flash floods
  • cause analysis
  • hydromorphology
  • hnderlying surface characteristics
  • mapping technique

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Published Papers (1 paper)

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Review

26 pages, 3243 KiB  
Review
Flash Flood Susceptibility Modelling Using Soft Computing-Based Approaches: From Bibliometric to Meta-Data Analysis and Future Research Directions
by Gilbert Hinge, Mohamed A. Hamouda and Mohamed M. Mohamed
Water 2024, 16(1), 173; https://doi.org/10.3390/w16010173 - 3 Jan 2024
Cited by 12 | Viewed by 3577
Abstract
In recent years, there has been a growing interest in flood susceptibility modeling. In this study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the nature and evolution of literature, intellectual structure networks, emerging themes, and knowledge gaps in [...] Read more.
In recent years, there has been a growing interest in flood susceptibility modeling. In this study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the nature and evolution of literature, intellectual structure networks, emerging themes, and knowledge gaps in flood susceptibility modeling. Relevant publications were retrieved from the Web of Science database to identify the leading authors, influential journals, and trending articles. The results of the meta-data analysis indicated that hybrid models were the most frequently used prediction models. Results of bibliometric analysis show that GIS, machine learning, statistical models, and the analytical hierarchy process were the central focuses of this research area. The analysis also revealed that slope, elevation, and distance from the river are the most commonly used factors in flood susceptibility modeling. The present study discussed the importance of the resolution of input data, the size and representation of the training sample, other lessons learned, and future research directions in this field. Full article
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