Causes and Reconstruction of Catastrophic Flash Flood Disasters: Investigation, Analysis, Modelling and Risk Management

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

Deadline for manuscript submissions: closed (20 May 2024) | Viewed by 5223

Special Issue Editors


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Guest Editor
State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, China
Interests: hydraulics and river dynamics; water–sediment disaster; flash flood; forecasting and early warning; hydrological–hydrodynamic modeling
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Guest Editor
Changjiang River Scientific Research Institute, Changjiang Water Resource Commission, Research Center on Mountain Torrent Geological Disaster Prevention of Ministry of Water Resources, Wuhan, China
Interests: soil erosion process; mechnaism of soil eroison ; watershed sediment connectivity; land use variation; landscape parameters
Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Interests: satellite remote sensing; infrared precipitation estimation; microwave precipitation retrieval; multi-precipitation merging; global change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, catastrophic flash flood events often occurred and gradually became an increased trend in the mountainous regions with the changing extreme climate, and resulted in devastating human deaths and economic losses. Notably, flash flood disasters induced by heavy rainfall are very common worldwide. Most research showed these main impacted factors include precipitation characteristics, underlying conditions and anthropogenetic activities. In order to better understand the causes of flash flood events and provide disasters control and mitigation ways for human health and economic development in mountainous regions, this Special Issue hopes that all the related researchers in the world could share the novel and interesting achievements such as field investigation, theroectial analysis, numerical simulation of catastrophic flash flood events around the world. On the basis of these historical disaster events, the reliable ways of flash flood risk managemnt could be founded and widely used in the future. On the other hand, the flash flood involved interdisciplinarities such as meteorology, hydrology, soil and water conservation, flow-sediment dynamics can be futher developed, of course, the mechanism of flash flood may be further elucidated and beneficial to impove these prevention techniques of flash flood disasters in mountain area.

Therefore, we kindly invite you to submit for this Special Issue your work results and contributions to causes and reconstruction of catastrophic flash flood disasters in the world: the potential contributions could include but are not limited to:

  • Catastrophic flash flood events in the world;
  • Precipitation estimation and forecasting in mountainous regions;
  • The changes of underly conditions and their impacts on flash floods;
  • Influences of Anthropogenetic activities on flash floods;
  • Hydrological and hydro-meteorological modeling for flash flood disaster analysis;
  • The studies of soil erosion, water-sediment process and mechanism of flash flood disaster;
  • Identification of areas prone to flash floods;
  • Risk management of flash floods.

Submissions of causes and reconstruction of catastrophic flash flood disasters as well as foundation of flash flood disasters database in different spatial and temporal scales are strongly encouraged.

Prof. Dr. Xiekang Wang
Prof. Dr. Wenfeng Ding
Dr. Ziqiang Ma
Guest Editors

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Keywords

  • Catastrophic flash flood, Climate changes, Extreme precipitation, Underly conditions, Human activities, Hydrological and hydro-meteorological modelling, Soil erosion, Water-sediment process, Mechanism of flash flood disaster, Risk assessment and management

Published Papers (4 papers)

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Research

17 pages, 4993 KiB  
Article
Correction of Fused Rainfall Data Based on Identification and Exclusion of Anomalous Rainfall Station Data
by Qingtai Qiu, Zheng Wang, Jiyang Tian, Yong Tu, Xidong Cui, Chunqi Hu and Yajing Kang
Water 2023, 15(14), 2541; https://doi.org/10.3390/w15142541 - 11 Jul 2023
Viewed by 1022
Abstract
High-quality rainfall data are crucial for accurately forecasting flash floods and runoff simulations. However, traditional correction methods often overlook errors in rainfall-monitoring data. We established a screening system to identify anomalous stations using the Hampel method, Grubbs criterion, analysis of surrounding measurement stations, [...] Read more.
High-quality rainfall data are crucial for accurately forecasting flash floods and runoff simulations. However, traditional correction methods often overlook errors in rainfall-monitoring data. We established a screening system to identify anomalous stations using the Hampel method, Grubbs criterion, analysis of surrounding measurement stations, and radar-assisted verification. Three rainfall data-fusion methods were used to fuse rainfall station data with radar quantitative precipitation estimation data; the accuracies of the fused data products with and without anomalous data identification were compared. Validation was performed using four 2012 rainfall events in Hebei Province. The 08:00–19:00 July 3 rainfall event had the highest number of anomalous stations (11.5% of the total), while the 01:00–17:00 August 9 event had the lowest number (7.8%). By comparing stations deemed to be anomalous with stations that were actually anomalous, we determined that the accuracy of reference station determination using Hampel’s method and Grubbs’ test was 94.2%. Radar-assisted validation improved the average accuracy of anomalous station identification during the four typical rainfall events from 89.7 to 93.7%. Excluding anomalous data also significantly impacted the efficacy of rainfall-data fusion, as it improved the quality of the rainfall station data. Among the performance indicators, 95% improved after the exclusion of anomalous data for all four rainfall events. Full article
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15 pages, 4553 KiB  
Article
A Snowfall Detection Algorithm for Fengyun-3D Microwave Sounders with Differentiated Atmospheric Temperature Conditions
by Qingwen Ji, Ziqiang Ma, Jintao Xu, Songkun Yan and Xiaoqing Li
Water 2023, 15(13), 2315; https://doi.org/10.3390/w15132315 - 21 Jun 2023
Viewed by 875
Abstract
Precipitation in different phases has varying effects on runoff. However, monitoring surface snowfall poses a significant challenge, highlighting the importance of developing a snowfall detection algorithm. The objective of this study is develop a snowfall detection algorithm for the Microwave Temperature Sounder-2 (MWTS-II) [...] Read more.
Precipitation in different phases has varying effects on runoff. However, monitoring surface snowfall poses a significant challenge, highlighting the importance of developing a snowfall detection algorithm. The objective of this study is develop a snowfall detection algorithm for the Microwave Temperature Sounder-2 (MWTS-II) and the Microwave Humidity Sounder-2 (MWHS-II) onboard the FY-3D satellite while considering the differentiated atmosphere temperature conditions. The results show that: (1) The brightness temperature (TB) of MWTS Channel 3 is well-suited for pre-classifying atmospheric temperatures, and significant differences in TB distribution exist between the two pre-classification subsets. (2) Among six machine classifiers examined, the random forest classifier exhibits favorable classification performance on both the validation set (accuracy: 0.76, recall: 0.76, F1 score: 0.75) and test set (accuracy: 0.80, recall: 0.44, F1 score: 0.44). (3) The application of the snowfall detection algorithm showcases a reasonable spatial distribution and outperforms the IMERG and ERA5 snowfall data. Full article
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16 pages, 6942 KiB  
Article
Application of Variational Optical Flow Forecasting Technique Based on Precipitation Spectral Decomposition to Three Case Studies of Heavy Precipitation Events during Rainy Season in Hebei Province
by Jiyang Tian, Qingtai Qiu, Xiaoqi Zhao, Wenbin Mu, Xidong Cui, Chunqi Hu, Yajing Kang and Yong Tu
Water 2023, 15(12), 2204; https://doi.org/10.3390/w15122204 - 12 Jun 2023
Viewed by 1172
Abstract
Short-term heavy precipitation is a crucial factor that triggers urban waterlogging and flash flood disasters, which impact human production and livelihood. Traditional short-term forecasting methods have time- and scale-based limitations. To achieve timely, location-specific, and quantitative precipitation forecasting, this study applies the precipitation [...] Read more.
Short-term heavy precipitation is a crucial factor that triggers urban waterlogging and flash flood disasters, which impact human production and livelihood. Traditional short-term forecasting methods have time- and scale-based limitations. To achieve timely, location-specific, and quantitative precipitation forecasting, this study applies the precipitation spectral decomposition algorithm, along with variational echo tracking and autoregressive AR2 extrapolation techniques, to forecast three cases of heavy precipitation events during the rainy season in Hebei Province. The variational optical flow extrapolation forecasting based on precipitation spectral decomposition has a forecasting lead time of up to 3 h. However, noticeable discrepancies in forecast accuracy can be observed around 2 h, and the forecasting skill gradually weakens with longer lead times. For 3 h lead time forecasts, substantial variability occurs among different performance metrics, lacking clear comparability. The effective forecast lead time for variational optical flow forecasting based on precipitation spectral decomposition is up to 1.6 h for severe convective weather systems and up to 2.2 h for stratiform cloud weather systems. Overall, the forecast effect of this method is good in the three rainfalls—the highest CSI is up to 0.74, the highest POD is up to 0.87, and the forecast accuracy and success rate are high. Full article
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21 pages, 6909 KiB  
Article
Study on Risk Assessment of Flash Floods in Hubei Province
by Yong Tu, Yanwei Zhao, Rui Dong, Han Wang, Qiang Ma, Bingshun He and Changjun Liu
Water 2023, 15(4), 617; https://doi.org/10.3390/w15040617 - 4 Feb 2023
Cited by 2 | Viewed by 1518
Abstract
Flash floods are typically associated with short, high-intensity and extreme rain-storms, and they are characterized by short response time and severely impact and damage communities in different areas in China. In order to scientifically assess the risks of flash floods, this paper takes [...] Read more.
Flash floods are typically associated with short, high-intensity and extreme rain-storms, and they are characterized by short response time and severely impact and damage communities in different areas in China. In order to scientifically assess the risks of flash floods, this paper takes Hubei Province as an example to carry out risk assessment. Based on Pearson correlation coefficient and principal component analysis methods, 14 factors were selected from 98 factors to establish a risk assessment model. The confidence coefficient model and multi-factor superposition method were used to determine the weight of each risk factor, and a risk map of Hubei Province was finally constructed. The results show that medium-high risk areas in Huanggang account for 47.00%, and high-risk areas account for 8.70%, with both areas adding up to more than 50%, followed by more than 40% in Shiyan, E’zhou and Xianning, and more than 30% in Huangshi, Yichang, Xiangyang, Jingmen and Suizhou. The risk level distribution is highly consistent with the location and frequency of flash flood disasters, shows high reliability, and can provide data support for flash flood disaster prevention and control. This study used a quantitative method to determine the key factors affecting flash flood disasters and provides a reference and basis for flash flood risk assessment in other provinces in China. Full article
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