Articles | Volume 18, issue 2
https://doi.org/10.5194/nhess-18-555-2018
© 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-18-555-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Feb 2018
Research article |
| 21 Feb 2018
| 21 Feb 2018
Debris flow run-out simulation and analysis using a dynamic model
Centre for Geographical Studies, Institute of Geography and Spatial Planning, Universidade de Lisboa, Edifício IGOT, Rua Branca Edmée Marques, 1600-276 Lisbon, Portugal
Theo van Asch
Faculty of Geosciences, Utrecht University, P.O. Box 80115, 3508 TC Utrecht, the Netherlands
José L. Zêzere
Centre for Geographical Studies, Institute of Geography and Spatial Planning, Universidade de Lisboa, Edifício IGOT, Rua Branca Edmée Marques, 1600-276 Lisbon, Portugal
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Cited
27 citations as recorded by crossref.
- Combining data-driven models to assess susceptibility of shallow slides failure and run-out R. Melo et al. 10.1007/s10346-019-01235-2
- Rainfall conditions leading to runoff-initiated post-fire debris flows in Campania, Southern Italy G. Esposito et al. 10.1016/j.geomorph.2022.108557
- Coupled empirical–mechanical modeling of debris flows occurred in small ungauged basins Y. Wu 10.1007/s12665-020-09318-3
- Hazard assessment of a catastrophic mine waste debris flow of Hou Gully, Shimian, China M. Chang et al. 10.1016/j.enggeo.2020.105733
- Multi‐Model Comparison of Computed Debris Flow Runout for the 9 January 2018 Montecito, California Post‐Wildfire Event K. Barnhart et al. 10.1029/2021JF006245
- Depth-averaged mixture model for development processes of debris flows over a steep unsaturated mobile bed S. Takayama et al. 10.1007/s10346-023-02202-8
- Applying a Series and Parallel Model and a Bayesian Networks Model to Produce Disaster Chain Susceptibility Maps in the Changbai Mountain area, China L. Han et al. 10.3390/w11102144
- Runout Number: A New Metric for Landslide Runout Characterization C. Wallace & P. Santi 10.2113/EEG-D-20-00144
- Defining evacuation travel times and safety areas in a debris flow hazard scenario R. Melo et al. 10.1016/j.scitotenv.2019.136452
- Synergistic analysis of satellite, unmanned aerial vehicle, terrestrial laser scanner data and process-based modelling for understanding the dynamics and morphological changes around the snout of Gangotri Glacier, India P. Dhote et al. 10.1016/j.geomorph.2021.108005
- A Framework for Studying Hydrology-Driven Landslide Hazards in Northwestern US Using Satellite InSAR, Precipitation and Soil Moisture Observations: Early Results and Future Directions Z. Lu & J. Kim 10.3390/geohazards2020002
- Post-wildfire slope stability effects and mitigation: a case study from hilly terrains with unmanaged forest L. Araújo Santos et al. 10.1007/s42452-020-03660-8
- Predictive simulation of concurrent debris flows: How slope failure locations affect predicted damage K. Yamanoi et al. 10.1111/jfr3.12776
- Physical process-based runout modeling and hazard assessment of catastrophic debris flow using SPH incorporated with ArcGIS: A case study of the Hongchun gully H. Cheng et al. 10.1016/j.catena.2022.106052
- Experimental and numerical study on the performance of novel RC frame structure encased with shaped steel under debris flow impact P. Li et al. 10.1016/j.engstruct.2020.110472
- Curvature derived from LiDAR digital elevation models as simple indicators of debris-flow susceptibility A. Nonomura et al. 10.1007/s11629-018-5098-8
- Rainfall-Induced Shallow Landslide Detachment, Transit and Runout Susceptibility Mapping by Integrating Machine Learning Techniques and GIS-Based Approaches M. Di Napoli et al. 10.3390/w13040488
- Fusion Analysis of Optical Satellite Images and Digital Elevation Model for Quantifying Volume in Debris Flow Disaster H. Miura 10.3390/rs11091096
- Estimating the debris-flow magnitude using landslide sediment connectivity, Qipan catchment, Wenchuan County, China X. Hu et al. 10.1016/j.catena.2022.106689
- Assessment of debris-flow potential dangers in the Jiuzhaigou Valley following the August 8, 2017, Jiuzhaigou earthquake, western China X. Hu et al. 10.1016/j.enggeo.2019.05.004
- 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
- Assessment of exposed elements in a changing built environment by using an integrated model of debris flow initiation and runout (Kalimpong region, Himalaya) S. Bera et al. 10.1007/s10064-021-02352-w
- Research Progress of Initial Mechanism on Debris Flow and Related Discrimination Methods: A Review J. Du et al. 10.3389/feart.2021.629567
- Modeling Shallow Landslide Runout Distance in Eocene Flysch Facies Using Empirical–Statistical Models (Western Black Sea Region of Türkiye) M. Komu et al. 10.3390/ijgi13030084
- Modelling the evolution of propagation and runout from a gravel–silty clay landslide to a debris flow in Shaziba, southwestern Hubei Province, China X. HU et al. 10.1007/s10346-022-01897-5
- Hydrologic-geotechnical modelling of shallow landslide and flood hazards caused by heavy rainfall N. Dolojan et al. 10.1016/j.enggeo.2023.107184
- Numerical simulation of the entrainment effect during mass movement in high-speed debris avalanches Y. Hu et al. 10.1007/s12517-018-4199-6
27 citations as recorded by crossref.
- Combining data-driven models to assess susceptibility of shallow slides failure and run-out R. Melo et al. 10.1007/s10346-019-01235-2
- Rainfall conditions leading to runoff-initiated post-fire debris flows in Campania, Southern Italy G. Esposito et al. 10.1016/j.geomorph.2022.108557
- Coupled empirical–mechanical modeling of debris flows occurred in small ungauged basins Y. Wu 10.1007/s12665-020-09318-3
- Hazard assessment of a catastrophic mine waste debris flow of Hou Gully, Shimian, China M. Chang et al. 10.1016/j.enggeo.2020.105733
- Multi‐Model Comparison of Computed Debris Flow Runout for the 9 January 2018 Montecito, California Post‐Wildfire Event K. Barnhart et al. 10.1029/2021JF006245
- Depth-averaged mixture model for development processes of debris flows over a steep unsaturated mobile bed S. Takayama et al. 10.1007/s10346-023-02202-8
- Applying a Series and Parallel Model and a Bayesian Networks Model to Produce Disaster Chain Susceptibility Maps in the Changbai Mountain area, China L. Han et al. 10.3390/w11102144
- Runout Number: A New Metric for Landslide Runout Characterization C. Wallace & P. Santi 10.2113/EEG-D-20-00144
- Defining evacuation travel times and safety areas in a debris flow hazard scenario R. Melo et al. 10.1016/j.scitotenv.2019.136452
- Synergistic analysis of satellite, unmanned aerial vehicle, terrestrial laser scanner data and process-based modelling for understanding the dynamics and morphological changes around the snout of Gangotri Glacier, India P. Dhote et al. 10.1016/j.geomorph.2021.108005
- A Framework for Studying Hydrology-Driven Landslide Hazards in Northwestern US Using Satellite InSAR, Precipitation and Soil Moisture Observations: Early Results and Future Directions Z. Lu & J. Kim 10.3390/geohazards2020002
- Post-wildfire slope stability effects and mitigation: a case study from hilly terrains with unmanaged forest L. Araújo Santos et al. 10.1007/s42452-020-03660-8
- Predictive simulation of concurrent debris flows: How slope failure locations affect predicted damage K. Yamanoi et al. 10.1111/jfr3.12776
- Physical process-based runout modeling and hazard assessment of catastrophic debris flow using SPH incorporated with ArcGIS: A case study of the Hongchun gully H. Cheng et al. 10.1016/j.catena.2022.106052
- Experimental and numerical study on the performance of novel RC frame structure encased with shaped steel under debris flow impact P. Li et al. 10.1016/j.engstruct.2020.110472
- Curvature derived from LiDAR digital elevation models as simple indicators of debris-flow susceptibility A. Nonomura et al. 10.1007/s11629-018-5098-8
- Rainfall-Induced Shallow Landslide Detachment, Transit and Runout Susceptibility Mapping by Integrating Machine Learning Techniques and GIS-Based Approaches M. Di Napoli et al. 10.3390/w13040488
- Fusion Analysis of Optical Satellite Images and Digital Elevation Model for Quantifying Volume in Debris Flow Disaster H. Miura 10.3390/rs11091096
- Estimating the debris-flow magnitude using landslide sediment connectivity, Qipan catchment, Wenchuan County, China X. Hu et al. 10.1016/j.catena.2022.106689
- Assessment of debris-flow potential dangers in the Jiuzhaigou Valley following the August 8, 2017, Jiuzhaigou earthquake, western China X. Hu et al. 10.1016/j.enggeo.2019.05.004
- 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
- Assessment of exposed elements in a changing built environment by using an integrated model of debris flow initiation and runout (Kalimpong region, Himalaya) S. Bera et al. 10.1007/s10064-021-02352-w
- Research Progress of Initial Mechanism on Debris Flow and Related Discrimination Methods: A Review J. Du et al. 10.3389/feart.2021.629567
- Modeling Shallow Landslide Runout Distance in Eocene Flysch Facies Using Empirical–Statistical Models (Western Black Sea Region of Türkiye) M. Komu et al. 10.3390/ijgi13030084
- Modelling the evolution of propagation and runout from a gravel–silty clay landslide to a debris flow in Shaziba, southwestern Hubei Province, China X. HU et al. 10.1007/s10346-022-01897-5
- Hydrologic-geotechnical modelling of shallow landslide and flood hazards caused by heavy rainfall N. Dolojan et al. 10.1016/j.enggeo.2023.107184
- Numerical simulation of the entrainment effect during mass movement in high-speed debris avalanches Y. Hu et al. 10.1007/s12517-018-4199-6
Latest update: 19 Apr 2024
Short summary
Only two months after a huge forest fire occurred in the upper part of a valley located in central Portugal, several debris flows were triggered by intense rainfall. This research aims to simulate the debris flow run-out for the entire basin, using a dynamic model. Three scenarios were developed and the results were confronted with the existing buildings exposed in the study area. The worst-case scenario showed a potential inundation that may affect 345 buildings.
Only two months after a huge forest fire occurred in the upper part of a valley located in...
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