Preprints
https://doi.org/10.5194/hess-2024-69
https://doi.org/10.5194/hess-2024-69
08 Apr 2024
 | 08 Apr 2024
Status: this preprint is currently under review for the journal HESS.

The Early Identification of Flash Flood Disasters: Mechanism, Model and Uncertainty

Zhengli Yang, Heng Lu, Kai Song, Zhijie Zhang, Chao Liu, Ruihua Nie, Lei Ma, Wanchang Zhang, Chen Chen, Min Zhang, and Gang Fan

Abstract. Flash flood disasters are one of the major natural disasters in the world, and rapid and accurate early identification of flash flood disasters is the key to preventing and controlling them. In recent years, computer and spatial information technology development has promoted the advancement of early identification technology for flash floods. However, previous research has mainly focused on the impact of "water" and neglected the impact of "sediment" deposition on the rise of water levels. To gain a more comprehensive understanding of flash floods and improve the accuracy of early identification, this article first uses bibliometric methods to review the spatiotemporal distribution, internal relationships, and research hotspots of literature in this field over the past 42 years. Then, the research practice of considering the impact of sediment on the early identification of flash floods was introduced from three aspects: mechanism, model, and uncertainty. Finally, the existing problems in current research were discussed, and future research directions were proposed. The research results have shown that the number of publications in this field has been increasing yearly and will continue to increase, but the cooperation between authors is not close. The coupling effect between sediment replenishment and floods cannot be ignored. Taking into account multiple uncertainties can greatly improve recognition accuracy. This study can provide a panoramic literature perspective and practical research experience for relevant researchers and decision-makers and support further improving flash flood prevention and control capabilities.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Zhengli Yang, Heng Lu, Kai Song, Zhijie Zhang, Chao Liu, Ruihua Nie, Lei Ma, Wanchang Zhang, Chen Chen, Min Zhang, and Gang Fan

Status: open (until 21 Jun 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Zhengli Yang, Heng Lu, Kai Song, Zhijie Zhang, Chao Liu, Ruihua Nie, Lei Ma, Wanchang Zhang, Chen Chen, Min Zhang, and Gang Fan
Zhengli Yang, Heng Lu, Kai Song, Zhijie Zhang, Chao Liu, Ruihua Nie, Lei Ma, Wanchang Zhang, Chen Chen, Min Zhang, and Gang Fan

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Short summary
1. Effective early identification is the key to predicting flash floods. 2. Considering the impact of local sediment deposition will improve the early identification ability . 3. Based on bibliometric analysis, a comprehensive knowledge system has been provided. 4. Conduct practical research focusing on mechanisms, models, and uncertainties. 5. Application of Expandable Knowledge Graph in Early Identification of Mountain Floods in the Future.