Articles | Volume 11, issue 7
https://doi.org/10.5194/gmd-11-2841-2018
© 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/gmd-11-2841-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
13 Jul 2018
Development and technical paper |
| 13 Jul 2018
| 13 Jul 2018
EDDA 2.0: integrated simulation of debris flow initiation and dynamics considering two initiation mechanisms
Ping Shen
Department of Civil and Environmental Engineering, The Hong Kong
University of Science and Technology, Clear Water Bay, Hong Kong
Department of Civil and Environmental Engineering, The Hong Kong
University of Science and Technology, Clear Water Bay, Hong Kong
Hongxin Chen
Key Laboratory of Geotechnical and Underground Engineering of
Ministry of Education, Department of Geotechnical Engineering, Tongji
University, China
Ruilin Fan
Department of Civil and Environmental Engineering, The Hong Kong
University of Science and Technology, Clear Water Bay, Hong Kong
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Cited
48 citations as recorded by crossref.
- Sensitivity Analysis of Debris Flow Simulations Using Kanako-2D M. PAIXÃO et al. 10.13101/ijece.14.1
- High-Precision Debris Flow Scale Prediction Model Based on CIHHO Algorithm Combined With Multilayer Perceptron Neural Network Y. Qiang et al. 10.1109/ACCESS.2024.3471795
- AscDAMs: advanced SLAM-based channel detection and mapping system T. Wang et al. 10.5194/nhess-24-3075-2024
- Data-driven landslide forecasting: Methods, data completeness, and real-time warning T. Xiao & L. Zhang 10.1016/j.enggeo.2023.107068
- Impact of Debris and Non-Debris Flow in Flood Damage at River Confluence, Case Study of Miu-Tuva River Confluence M. Sinema Telaumbanua et al. 10.1051/e3sconf/202451903013
- Contributions of Particle–Fluid, Collisional, and Colloidal Interactions to Rheological Behavior of Soil–Water Mixtures M. Kamali Zarch et al. 10.1061/(ASCE)GT.1943-5606.0002837
- A modified leading-edge runout model incorporating the flow regimes of debris flows X. Gong et al. 10.1007/s10346-023-02055-1
- Experimental Study on the Clogging Performance of Waste Slag S. Li et al. 10.3390/w16101390
- INTEGRATED SIMULATION OF LANDSLIDE AND SEDIMENT RUNOFF EMPLOYING STREAM-TUBE BASED TERRAIN MODEL K. YAMANOI et al. 10.2208/jscejhe.76.2_I_889
- Dynamic Risk Assessment of Landslide Hazard for Large-Scale Photovoltaic Power Plants under Extreme Rainfall Conditions R. Li et al. 10.3390/w15152832
- Time capsule for landslide risk assessment Y. Lei et al. 10.1080/17499518.2023.2164899
- Assessment of Physical Vulnerability and Uncertainties for Debris Flow Hazard: A Review concerning Climate Change M. Khan et al. 10.3390/land11122240
- Predicting debris-flow clusters under extreme rainstorms: a case study on Hong Kong Island S. Zhou et al. 10.1007/s10064-019-01504-3
- Debris flow enlargement from entrainment: A case study for comparison of three entrainment models P. Shen et al. 10.1016/j.enggeo.2020.105581
- Simulation of runout behavior of submarine debris flows over regional natural terrain considering material softening Y. Chen et al. 10.1080/1064119X.2021.2020942
- Soft matter physics of the ground beneath our feet A. Voigtländer et al. 10.1039/D4SM00391H
- Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility J. Sun et al. 10.1007/s11069-020-04498-4
- Numerical modeling of interactions between a flow slide and buildings considering the destruction process S. Feng et al. 10.1007/s10346-019-01220-9
- Rheology of debris flow materials is controlled by the distance from jamming R. Kostynick et al. 10.1073/pnas.2209109119
- A Physically Based Model for the Sequential Evolution Analysis of Rainfall‐Induced Shallow Landslides in a Catchment Y. Jiang et al. 10.1029/2022WR032716
- Formation mechanism and quantitative risk analysis of the landslide-induced hazard chain by an integrated approach for emergency management: A case study in the Bailong River basin, China Y. Chong et al. 10.1016/j.catena.2023.107522
- Hypermobility of a Catastrophic Earthquake-Induced Loess Landslide S. Xiao et al. 10.1016/j.enggeo.2024.107777
- Activity evolution of landslides and debris flows after the Wenchuan earthquake in the Qipan catchment, Southwest China Q. Shi et al. 10.1007/s11629-020-6494-4
- Numerical simulation of rainfall-induced debris flow in the Hongchun gully based on the coupling of the LHT model and the Pudasaini model H. Yin et al. 10.1007/s11069-023-05956-5
- Evaluating effectiveness of mitigation measures for large debris flows in Wenchuan, China J. He et al. 10.1007/s10346-021-01809-z
- Landslide susceptibility mapping of mountain roads based on machine learning combined model H. Dou et al. 10.1007/s11629-022-7657-2
- Predicting peakflows in mountain river basins and data-scarce areas: a case study in northeastern Italy E. Arnone et al. 10.1080/02626667.2022.2162408
- Spatial-temporal rain field generation for the Guangdong-Hong Kong-Macau Greater Bay Area considering climate change Y. Qiang et al. 10.1016/j.jhydrol.2020.124584
- Debris Flow Susceptibility Evaluation—A Review A. Kumar & R. Sarkar 10.1007/s40996-022-01000-x
- Machine learning approaches to debris flow susceptibility analyses in the Yunnan section of the Nujiang River Basin J. Zhou et al. 10.7717/peerj.17352
- X-SLIP: A SLIP-based multi-approach algorithm to predict the spatial–temporal triggering of rainfall-induced shallow landslides over large areas M. Placido Antonio Gatto & L. Montrasio 10.1016/j.compgeo.2022.105175
- Initiation mechanisms and dynamics of a debris flow originated from debris-ice mixture slope failure in southeast Tibet, China D. Peng et al. 10.1016/j.enggeo.2022.106783
- An overview of debris-flow mathematical modelling M. Trujillo-Vela et al. 10.1016/j.earscirev.2022.104135
- Modelling rainfall-induced landslides from initiation of instability to post-failure X. Chen et al. 10.1016/j.compgeo.2020.103877
- Deep learning enables super-resolution hydrodynamic flooding process modeling under spatiotemporally varying rainstorms J. He et al. 10.1016/j.watres.2023.120057
- Predicting landslide runout paths using terrain matching-targeted machine learning L. Ju et al. 10.1016/j.enggeo.2022.106902
- A framework for understanding water-related multi-hazards in a sustainable development context J. Docherty et al. 10.1177/0309133319900926
- Evaluating volume of coseismic landslide clusters by flow direction-based partitioning R. Fan et al. 10.1016/j.enggeo.2019.105238
- Comprehensive analysis and numerical simulation of a large debris flow in the Meilong catchment, China H. An et al. 10.1016/j.enggeo.2022.106546
- Designing conduit sabo dam series as a debris flow protection structure D. Anggun Lestari et al. 10.1051/e3sconf/202133108001
- Characteristics of debris flow dynamics and prediction of the hazardous area in Bangou Village, Yanqing District, Beijing, China S. Wang et al. 10.1515/geo-2022-0655
- Prompt Quantitative Risk Assessment for Rain-Induced Landslides J. He et al. 10.1061/JGGEFK.GTENG-10980
- Hazard assessment of a catastrophic mine waste debris flow of Hou Gully, Shimian, China M. Chang et al. 10.1016/j.enggeo.2020.105733
- Hazard assessment of debris flow by using FLO-2D and hazard matrix: a case study of Qingshui Gully in the southern Gansu Province, China P. Zhang et al. 10.5004/dwt.2023.30108
- The mechanisms of high mobility of a glacial debris flow using the Pudasaini-Mergili multi-phase modeling T. Wang et al. 10.1016/j.enggeo.2023.107186
- Declining geohazard activity with vegetation recovery during first ten years after the 2008 Wenchuan earthquake P. Shen et al. 10.1016/j.geomorph.2019.106989
- Predicting spatio-temporal man-made slope failures induced by rainfall in Hong Kong using machine learning techniques T. Xiao et al. 10.1680/jgeot.21.00160
- A hybrid framework integrating physical model and convolutional neural network for regional landslide susceptibility mapping X. Wei et al. 10.1007/s11069-021-04844-0
47 citations as recorded by crossref.
- Sensitivity Analysis of Debris Flow Simulations Using Kanako-2D M. PAIXÃO et al. 10.13101/ijece.14.1
- High-Precision Debris Flow Scale Prediction Model Based on CIHHO Algorithm Combined With Multilayer Perceptron Neural Network Y. Qiang et al. 10.1109/ACCESS.2024.3471795
- AscDAMs: advanced SLAM-based channel detection and mapping system T. Wang et al. 10.5194/nhess-24-3075-2024
- Data-driven landslide forecasting: Methods, data completeness, and real-time warning T. Xiao & L. Zhang 10.1016/j.enggeo.2023.107068
- Impact of Debris and Non-Debris Flow in Flood Damage at River Confluence, Case Study of Miu-Tuva River Confluence M. Sinema Telaumbanua et al. 10.1051/e3sconf/202451903013
- Contributions of Particle–Fluid, Collisional, and Colloidal Interactions to Rheological Behavior of Soil–Water Mixtures M. Kamali Zarch et al. 10.1061/(ASCE)GT.1943-5606.0002837
- A modified leading-edge runout model incorporating the flow regimes of debris flows X. Gong et al. 10.1007/s10346-023-02055-1
- Experimental Study on the Clogging Performance of Waste Slag S. Li et al. 10.3390/w16101390
- INTEGRATED SIMULATION OF LANDSLIDE AND SEDIMENT RUNOFF EMPLOYING STREAM-TUBE BASED TERRAIN MODEL K. YAMANOI et al. 10.2208/jscejhe.76.2_I_889
- Dynamic Risk Assessment of Landslide Hazard for Large-Scale Photovoltaic Power Plants under Extreme Rainfall Conditions R. Li et al. 10.3390/w15152832
- Time capsule for landslide risk assessment Y. Lei et al. 10.1080/17499518.2023.2164899
- Assessment of Physical Vulnerability and Uncertainties for Debris Flow Hazard: A Review concerning Climate Change M. Khan et al. 10.3390/land11122240
- Predicting debris-flow clusters under extreme rainstorms: a case study on Hong Kong Island S. Zhou et al. 10.1007/s10064-019-01504-3
- Debris flow enlargement from entrainment: A case study for comparison of three entrainment models P. Shen et al. 10.1016/j.enggeo.2020.105581
- Simulation of runout behavior of submarine debris flows over regional natural terrain considering material softening Y. Chen et al. 10.1080/1064119X.2021.2020942
- Soft matter physics of the ground beneath our feet A. Voigtländer et al. 10.1039/D4SM00391H
- Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility J. Sun et al. 10.1007/s11069-020-04498-4
- Numerical modeling of interactions between a flow slide and buildings considering the destruction process S. Feng et al. 10.1007/s10346-019-01220-9
- Rheology of debris flow materials is controlled by the distance from jamming R. Kostynick et al. 10.1073/pnas.2209109119
- A Physically Based Model for the Sequential Evolution Analysis of Rainfall‐Induced Shallow Landslides in a Catchment Y. Jiang et al. 10.1029/2022WR032716
- Formation mechanism and quantitative risk analysis of the landslide-induced hazard chain by an integrated approach for emergency management: A case study in the Bailong River basin, China Y. Chong et al. 10.1016/j.catena.2023.107522
- Hypermobility of a Catastrophic Earthquake-Induced Loess Landslide S. Xiao et al. 10.1016/j.enggeo.2024.107777
- Activity evolution of landslides and debris flows after the Wenchuan earthquake in the Qipan catchment, Southwest China Q. Shi et al. 10.1007/s11629-020-6494-4
- Numerical simulation of rainfall-induced debris flow in the Hongchun gully based on the coupling of the LHT model and the Pudasaini model H. Yin et al. 10.1007/s11069-023-05956-5
- Evaluating effectiveness of mitigation measures for large debris flows in Wenchuan, China J. He et al. 10.1007/s10346-021-01809-z
- Landslide susceptibility mapping of mountain roads based on machine learning combined model H. Dou et al. 10.1007/s11629-022-7657-2
- Predicting peakflows in mountain river basins and data-scarce areas: a case study in northeastern Italy E. Arnone et al. 10.1080/02626667.2022.2162408
- Spatial-temporal rain field generation for the Guangdong-Hong Kong-Macau Greater Bay Area considering climate change Y. Qiang et al. 10.1016/j.jhydrol.2020.124584
- Debris Flow Susceptibility Evaluation—A Review A. Kumar & R. Sarkar 10.1007/s40996-022-01000-x
- Machine learning approaches to debris flow susceptibility analyses in the Yunnan section of the Nujiang River Basin J. Zhou et al. 10.7717/peerj.17352
- X-SLIP: A SLIP-based multi-approach algorithm to predict the spatial–temporal triggering of rainfall-induced shallow landslides over large areas M. Placido Antonio Gatto & L. Montrasio 10.1016/j.compgeo.2022.105175
- Initiation mechanisms and dynamics of a debris flow originated from debris-ice mixture slope failure in southeast Tibet, China D. Peng et al. 10.1016/j.enggeo.2022.106783
- An overview of debris-flow mathematical modelling M. Trujillo-Vela et al. 10.1016/j.earscirev.2022.104135
- Modelling rainfall-induced landslides from initiation of instability to post-failure X. Chen et al. 10.1016/j.compgeo.2020.103877
- Deep learning enables super-resolution hydrodynamic flooding process modeling under spatiotemporally varying rainstorms J. He et al. 10.1016/j.watres.2023.120057
- Predicting landslide runout paths using terrain matching-targeted machine learning L. Ju et al. 10.1016/j.enggeo.2022.106902
- A framework for understanding water-related multi-hazards in a sustainable development context J. Docherty et al. 10.1177/0309133319900926
- Evaluating volume of coseismic landslide clusters by flow direction-based partitioning R. Fan et al. 10.1016/j.enggeo.2019.105238
- Comprehensive analysis and numerical simulation of a large debris flow in the Meilong catchment, China H. An et al. 10.1016/j.enggeo.2022.106546
- Designing conduit sabo dam series as a debris flow protection structure D. Anggun Lestari et al. 10.1051/e3sconf/202133108001
- Characteristics of debris flow dynamics and prediction of the hazardous area in Bangou Village, Yanqing District, Beijing, China S. Wang et al. 10.1515/geo-2022-0655
- Prompt Quantitative Risk Assessment for Rain-Induced Landslides J. He et al. 10.1061/JGGEFK.GTENG-10980
- Hazard assessment of a catastrophic mine waste debris flow of Hou Gully, Shimian, China M. Chang et al. 10.1016/j.enggeo.2020.105733
- Hazard assessment of debris flow by using FLO-2D and hazard matrix: a case study of Qingshui Gully in the southern Gansu Province, China P. Zhang et al. 10.5004/dwt.2023.30108
- The mechanisms of high mobility of a glacial debris flow using the Pudasaini-Mergili multi-phase modeling T. Wang et al. 10.1016/j.enggeo.2023.107186
- Declining geohazard activity with vegetation recovery during first ten years after the 2008 Wenchuan earthquake P. Shen et al. 10.1016/j.geomorph.2019.106989
- Predicting spatio-temporal man-made slope failures induced by rainfall in Hong Kong using machine learning techniques T. Xiao et al. 10.1680/jgeot.21.00160
Latest update: 24 Dec 2024
Short summary
A rainstorm can trigger numerous debris flows. A difficult task in debris flow risk assessment is to identify debris flow initiation locations and volumes. This paper presents a new model to solve this problem by physically simulating the initiation of debris flows by hillslope bed erosion and transformation from slope failures. The sediment from these two initiation mechanisms joins the flow mixture, and the volume of the flow mixture increases along the flow path due to additional bed erosion.
A rainstorm can trigger numerous debris flows. A difficult task in debris flow risk assessment...
