Articles | Volume 18, issue 5
https://doi.org/10.5194/nhess-18-1395-2018
© Author(s) 2018. 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-18-1395-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 May 2018
Research article |
| 17 May 2018
| 17 May 2018
Rainfall threshold calculation for debris flow early warning in areas with scarcity of data
Hua-Li Pan
Key Laboratory of Mountain Hazards and Earth Surface Process, Chinese
Academy of Sciences, Chengdu 610041, China
Institute of Mountain Hazards and Environment, Chinese Academy of
Sciences, Chengdu 610041, China
Yuan-Jun Jiang
CORRESPONDING AUTHOR
Key Laboratory of Mountain Hazards and Earth Surface Process, Chinese
Academy of Sciences, Chengdu 610041, China
Institute of Mountain Hazards and Environment, Chinese Academy of
Sciences, Chengdu 610041, China
Jun Wang
Guangzhou Institute of Geography, Guangzhou 510070, China
Guo-Qiang Ou
Key Laboratory of Mountain Hazards and Earth Surface Process, Chinese
Academy of Sciences, Chengdu 610041, China
Institute of Mountain Hazards and Environment, Chinese Academy of
Sciences, Chengdu 610041, China
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Cited
32 citations as recorded by crossref.
- Constructing rainfall thresholds for debris flow initiation based on critical discharge and S-hydrograph Y. Li et al. 10.1016/j.enggeo.2020.105962
- Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment S. Dixit et al. 10.5194/nhess-24-465-2024
- Deep learning prediction of rainfall-driven debris flows considering the similar critical thresholds within comparable background conditions H. Jiang et al. 10.1016/j.envsoft.2024.106130
- Variability in the characteristics of extreme rainfall events triggering debris flows: a case study in the Chenyulan watershed, Taiwan J. Chen et al. 10.1007/s11069-020-03938-5
- Uncertainty analysis of a rainfall threshold estimate for stony debris flow based on the backward dynamical approach M. Martinengo et al. 10.5194/nhess-21-1769-2021
- A systematic review on rainfall thresholds for landslides occurrence F. Gonzalez et al. 10.1016/j.heliyon.2023.e23247
- The twin catastrophic flows occurred in 2014 at Ambato Range (28°09′–28°20′S), Catamarca Province, Northwest Argentina D. Fernández et al. 10.1016/j.jsames.2020.103086
- Preface: Landslide early warning systems: monitoring systems, rainfall thresholds, warning models, performance evaluation and risk perception S. Segoni et al. 10.5194/nhess-18-3179-2018
- Influence of the mapping unit for regional landslide early warning systems: comparison between pixels and polygons in Catalonia (NE Spain) R. Palau et al. 10.1007/s10346-020-01425-3
- Using Tabu Search Adjusted with Urban Sewer Flood Simulation to Improve Pluvial Flood Warning via Rainfall Thresholds H. Liao et al. 10.3390/w11020348
- Urban pluvial flooding prediction by machine learning approaches – a case study of Shenzhen city, China Q. Ke et al. 10.1016/j.advwatres.2020.103719
- Definition of Rainfall Thresholds for Landslides Using Unbalanced Datasets: Two Case Studies in Shaanxi Province, China S. Zhang et al. 10.3390/w15061058
- Rainfall Warning Model for Rainfall-Triggered Channelized Debris Flow Based on Physical Model Test—A Case Study of Laomao Mountain Debris Flow in Dalian City Y. Wang et al. 10.3390/w13081083
- Research Progress of Initial Mechanism on Debris Flow and Related Discrimination Methods: A Review J. Du et al. 10.3389/feart.2021.629567
- Evaluation of Rainfall-Triggered Debris Flows under the Impact of Extreme Events: A Chenyulan Watershed Case Study, Taiwan J. Chen & W. Huang 10.3390/w13162201
- A review of recent earthquake-induced landslides on the Tibetan Plateau B. Zhao et al. 10.1016/j.earscirev.2023.104534
- Early warning of debris flow using optimized self-organizing feature mapping network X. Wang et al. 10.2166/ws.2020.142
- Validation and potential forecast use of a debris-flow rainfall threshold calibrated with the Backward Dynamical Approach M. Martinengo et al. 10.1016/j.geomorph.2022.108519
- Torrential Hazard Prevention in Alpine Small Basin through Historical, Empirical and Geomorphological Cross Analysis in NW Italy L. Turconi et al. 10.3390/land11050699
- Modelamiento numérico de un flujo de escombros asociado a una rotura de presa en la subcuenca Quillcay, Áncash, Perú A. Díaz-Salas et al. 10.54139/revinguc.v28i1.4
- Frequent dry-wet cycles promote debris flow occurrence: Insights from 40 years of data in subtropical monsoon region of Sichuan, China J. Li et al. 10.1016/j.catena.2024.107888
- Quantitative assessment of the complexity of talus slope morphodynamics using multi-temporal data from terrestrial laser scanning (Tatra Mts., Poland) Z. Rączkowska & J. Cebulski 10.1016/j.catena.2021.105792
- Quantifying Debris Flood Deposits in an Alaskan Fjord Using Multitemporal Digital Elevation Models M. Balazs et al. 10.3390/s21061966
- Evaluating the thresholds for predicting post-earthquake debris flows: Comparison of meteorological, hydro-meteorological and critical discharge approaches Z. Wei et al. 10.1016/j.enggeo.2024.107773
- Development of Nomogram for Debris Flow Forecasting Based on Critical Accumulated Rainfall in South Korea D. Nam et al. 10.3390/w11102181
- Experimental study on debris flow initiation X. Liu et al. 10.1007/s10064-019-01618-8
- Information Entropy Embedded Back Propagation Neural Network Approach for Debris Flows Hazard Assessment Y. Yu & J. Wang 10.1088/1755-1315/453/1/012015
- Debris Flow Risk Assessment Based on a Water–Soil Process Model at the Watershed Scale Under Climate Change: A Case Study in a Debris-Flow-Prone Area of Southwest China Q. Li et al. 10.3390/su11113199
- Application of a fuzzy verification framework for the evaluation of a regional-scale landslide early warning system during the January 2020 Gloria storm in Catalonia (NE Spain) R. Palau et al. 10.1007/s10346-022-01854-2
- A Regional-Scale Landslide Warning System Based on 20 Years of Operational Experience S. Segoni et al. 10.3390/w10101297
- Parameter Sensitivity Analysis of a Korean Debris Flow-Induced Rainfall Threshold Estimation Algorithm K. Choo et al. 10.3390/w16060828
- Temporal changes in the debris flow threshold under the effects of ground freezing and sediment storage on Mt. Fuji F. Imaizumi et al. 10.5194/esurf-9-1381-2021
32 citations as recorded by crossref.
- Constructing rainfall thresholds for debris flow initiation based on critical discharge and S-hydrograph Y. Li et al. 10.1016/j.enggeo.2020.105962
- Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment S. Dixit et al. 10.5194/nhess-24-465-2024
- Deep learning prediction of rainfall-driven debris flows considering the similar critical thresholds within comparable background conditions H. Jiang et al. 10.1016/j.envsoft.2024.106130
- Variability in the characteristics of extreme rainfall events triggering debris flows: a case study in the Chenyulan watershed, Taiwan J. Chen et al. 10.1007/s11069-020-03938-5
- Uncertainty analysis of a rainfall threshold estimate for stony debris flow based on the backward dynamical approach M. Martinengo et al. 10.5194/nhess-21-1769-2021
- A systematic review on rainfall thresholds for landslides occurrence F. Gonzalez et al. 10.1016/j.heliyon.2023.e23247
- The twin catastrophic flows occurred in 2014 at Ambato Range (28°09′–28°20′S), Catamarca Province, Northwest Argentina D. Fernández et al. 10.1016/j.jsames.2020.103086
- Preface: Landslide early warning systems: monitoring systems, rainfall thresholds, warning models, performance evaluation and risk perception S. Segoni et al. 10.5194/nhess-18-3179-2018
- Influence of the mapping unit for regional landslide early warning systems: comparison between pixels and polygons in Catalonia (NE Spain) R. Palau et al. 10.1007/s10346-020-01425-3
- Using Tabu Search Adjusted with Urban Sewer Flood Simulation to Improve Pluvial Flood Warning via Rainfall Thresholds H. Liao et al. 10.3390/w11020348
- Urban pluvial flooding prediction by machine learning approaches – a case study of Shenzhen city, China Q. Ke et al. 10.1016/j.advwatres.2020.103719
- Definition of Rainfall Thresholds for Landslides Using Unbalanced Datasets: Two Case Studies in Shaanxi Province, China S. Zhang et al. 10.3390/w15061058
- Rainfall Warning Model for Rainfall-Triggered Channelized Debris Flow Based on Physical Model Test—A Case Study of Laomao Mountain Debris Flow in Dalian City Y. Wang et al. 10.3390/w13081083
- Research Progress of Initial Mechanism on Debris Flow and Related Discrimination Methods: A Review J. Du et al. 10.3389/feart.2021.629567
- Evaluation of Rainfall-Triggered Debris Flows under the Impact of Extreme Events: A Chenyulan Watershed Case Study, Taiwan J. Chen & W. Huang 10.3390/w13162201
- A review of recent earthquake-induced landslides on the Tibetan Plateau B. Zhao et al. 10.1016/j.earscirev.2023.104534
- Early warning of debris flow using optimized self-organizing feature mapping network X. Wang et al. 10.2166/ws.2020.142
- Validation and potential forecast use of a debris-flow rainfall threshold calibrated with the Backward Dynamical Approach M. Martinengo et al. 10.1016/j.geomorph.2022.108519
- Torrential Hazard Prevention in Alpine Small Basin through Historical, Empirical and Geomorphological Cross Analysis in NW Italy L. Turconi et al. 10.3390/land11050699
- Modelamiento numérico de un flujo de escombros asociado a una rotura de presa en la subcuenca Quillcay, Áncash, Perú A. Díaz-Salas et al. 10.54139/revinguc.v28i1.4
- Frequent dry-wet cycles promote debris flow occurrence: Insights from 40 years of data in subtropical monsoon region of Sichuan, China J. Li et al. 10.1016/j.catena.2024.107888
- Quantitative assessment of the complexity of talus slope morphodynamics using multi-temporal data from terrestrial laser scanning (Tatra Mts., Poland) Z. Rączkowska & J. Cebulski 10.1016/j.catena.2021.105792
- Quantifying Debris Flood Deposits in an Alaskan Fjord Using Multitemporal Digital Elevation Models M. Balazs et al. 10.3390/s21061966
- Evaluating the thresholds for predicting post-earthquake debris flows: Comparison of meteorological, hydro-meteorological and critical discharge approaches Z. Wei et al. 10.1016/j.enggeo.2024.107773
- Development of Nomogram for Debris Flow Forecasting Based on Critical Accumulated Rainfall in South Korea D. Nam et al. 10.3390/w11102181
- Experimental study on debris flow initiation X. Liu et al. 10.1007/s10064-019-01618-8
- Information Entropy Embedded Back Propagation Neural Network Approach for Debris Flows Hazard Assessment Y. Yu & J. Wang 10.1088/1755-1315/453/1/012015
- Debris Flow Risk Assessment Based on a Water–Soil Process Model at the Watershed Scale Under Climate Change: A Case Study in a Debris-Flow-Prone Area of Southwest China Q. Li et al. 10.3390/su11113199
- Application of a fuzzy verification framework for the evaluation of a regional-scale landslide early warning system during the January 2020 Gloria storm in Catalonia (NE Spain) R. Palau et al. 10.1007/s10346-022-01854-2
- A Regional-Scale Landslide Warning System Based on 20 Years of Operational Experience S. Segoni et al. 10.3390/w10101297
- Parameter Sensitivity Analysis of a Korean Debris Flow-Induced Rainfall Threshold Estimation Algorithm K. Choo et al. 10.3390/w16060828
- Temporal changes in the debris flow threshold under the effects of ground freezing and sediment storage on Mt. Fuji F. Imaizumi et al. 10.5194/esurf-9-1381-2021
Latest update: 05 Nov 2024
Short summary
Debris flow early warning has always been based on well-calibrated rainfall thresholds. For areas where historical data are insufficient, to determine a rainfall threshold, it is necessary to develop a method to obtain the threshold by using limited data. A quantitative method, a new way to calculate the rainfall threshold, is developed in this study, which combines the initiation mechanism of hydraulic-driven debris flow with the runoff yield and concentration laws of the watershed.
Debris flow early warning has always been based on well-calibrated rainfall thresholds. For...
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