Articles | Volume 21, issue 7
https://doi.org/10.5194/nhess-21-2109-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-21-2109-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jul 2021
Research article |
| 13 Jul 2021
| 13 Jul 2021
Spatiotemporal clustering of flash floods in a changing climate (China, 1950–2015)
Nan Wang
State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
University of Chinese Academy of Sciences, Beijing, 100049, China
Luigi Lombardo
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, Enschede, AE 7500, the Netherlands
Marj Tonini
Institute of Earth Surface Dynamics, Faculty of Geosciences and Environment, University of Lausanne, 1015 Lausanne, Switzerland
State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
University of Chinese Academy of Sciences, Beijing, 100049, China
Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing, 210023, China
Collaborative Innovation Center of South China Sea Studies, Nanjing, 210093, China
Liang Guo
Research Center on Flood and Drought Disaster Reduction of the MWR, Beijing, 100038, China
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Junnan Xiong
State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu, 610500, China
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Cited
12 citations as recorded by crossref.
- Susceptibility Assessment of Flash Floods: A Bibliometrics Analysis and Review L. Duan et al. 10.3390/rs14215432
- Impact-based probabilistic modeling of hydro-morphological processes in China (1985–2015) N. Wang et al. 10.1016/j.jenvman.2023.118463
- Floods and droughts: a multivariate perspective M. Brunner 10.5194/hess-27-2479-2023
- Landslide spatial prediction using cluster analysis Z. Zhao et al. 10.1016/j.gr.2024.02.006
- A systematic review with bibliometric analysis of different approaches and methodologies for undertaking flood vulnerability research T. Nguyen et al. 10.1007/s40899-023-00865-8
- Large-scale flash flood warning in China using deep learning G. Zhao et al. 10.1016/j.jhydrol.2021.127222
- Spatio-temporal clustering of extreme floods in Great Britain G. Formetta et al. 10.1080/02626667.2024.2367167
- Projecting dry-wet abrupt alternation across China from the perspective of soil moisture J. Qiu et al. 10.1038/s41612-024-00808-w
- Mapping homogeneous regions for flash floods using machine learning: A case study in Jiangxi province, China R. Zhang et al. 10.1016/j.jag.2022.102717
- Temporal hydrological drought clustering varies with climate and land-surface processes M. Brunner & K. Stahl 10.1088/1748-9326/acb8ca
- Decadal trends and climatic influences on flash droughts and flash floods in Indian cities T. Archana et al. 10.1016/j.uclim.2024.102143
- Spatiotemporal variation of flash floods in the Hengduan Mountains region affected by rainfall properties and land use X. Sun et al. 10.1007/s11069-021-05061-5
11 citations as recorded by crossref.
- Susceptibility Assessment of Flash Floods: A Bibliometrics Analysis and Review L. Duan et al. 10.3390/rs14215432
- Impact-based probabilistic modeling of hydro-morphological processes in China (1985–2015) N. Wang et al. 10.1016/j.jenvman.2023.118463
- Floods and droughts: a multivariate perspective M. Brunner 10.5194/hess-27-2479-2023
- Landslide spatial prediction using cluster analysis Z. Zhao et al. 10.1016/j.gr.2024.02.006
- A systematic review with bibliometric analysis of different approaches and methodologies for undertaking flood vulnerability research T. Nguyen et al. 10.1007/s40899-023-00865-8
- Large-scale flash flood warning in China using deep learning G. Zhao et al. 10.1016/j.jhydrol.2021.127222
- Spatio-temporal clustering of extreme floods in Great Britain G. Formetta et al. 10.1080/02626667.2024.2367167
- Projecting dry-wet abrupt alternation across China from the perspective of soil moisture J. Qiu et al. 10.1038/s41612-024-00808-w
- Mapping homogeneous regions for flash floods using machine learning: A case study in Jiangxi province, China R. Zhang et al. 10.1016/j.jag.2022.102717
- Temporal hydrological drought clustering varies with climate and land-surface processes M. Brunner & K. Stahl 10.1088/1748-9326/acb8ca
- Decadal trends and climatic influences on flash droughts and flash floods in Indian cities T. Archana et al. 10.1016/j.uclim.2024.102143
Latest update: 21 Nov 2024
Short summary
This study exploits 66 years of flash flood disasters across China.
The conclusions are as follows. The clustering procedure highlights distinct spatial and temporal patterns of flash flood disasters at different scales. There are distinguished seasonal, yearly and even long-term persistent flash flood behaviors of flash flood disasters. Finally, the decreased duration of clusters in the recent period indicates a possible activation induced by short-duration extreme rainfall events.
This study exploits 66 years of flash flood disasters across China.
The conclusions are as...
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