Articles | Volume 19, issue 11
https://doi.org/10.5194/nhess-19-2477-2019
© Author(s) 2019. 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-19-2477-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Nov 2019
Research article |
| 12 Nov 2019
| 12 Nov 2019
A new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA
Ronda Strauch
CORRESPONDING AUTHOR
Seattle City Light, Seattle, WA, USA
Civil & Environmental Engineering, College of Engineering, University of Washington, Seattle, WA, USA
Erkan Istanbulluoglu
Civil & Environmental Engineering, College of Engineering, University of Washington, Seattle, WA, USA
Jon Riedel
National Park Service, US Department of the Interior, Sedro-Woolley, WA, USA
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Total article views: 3,804 (including HTML, PDF, and XML)
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Cited
19 citations as recorded by crossref.
- Multi-Temporal Landslide Inventory-Based Statistical Susceptibility Modeling Associated With the 2017 Mw 6.5 Jiuzhaigou Earthquake, Sichuan, China L. Luo et al. 10.3389/fenvs.2022.858635
- Landslide Susceptibility Mapping and Assessment Using Geospatial Platforms and Weights of Evidence (WoE) Method in the Indian Himalayan Region: Recent Developments, Gaps, and Future Directions A. Batar & T. Watanabe 10.3390/ijgi10030114
- Improving Spatial Landslide Prediction with 3D Slope Stability Analysis and Genetic Algorithm Optimization: Application to the Oltrepò Pavese N. Palazzolo et al. 10.3390/w13060801
- Modelling landslides in the Lesser Himalaya region using geospatial and numerical simulation techniques M. Islam & S. Chattoraj 10.1007/s12517-023-11541-8
- Evaluation and prediction of compound geohazards in highly urbanized regions across China's Greater Bay Area K. He et al. 10.1016/j.jclepro.2024.141641
- Evaluating thresholds: the impact of terrain modifications on landslide susceptibility in a mountainous city S. Heo et al. 10.1080/19475705.2025.2493211
- Quantitative spatial distribution model of site-specific loess landslides on the Heifangtai terrace, China Q. Zhou et al. 10.1007/s10346-020-01551-y
- Comparison of hybrid data-driven and physical models for landslide susceptibility mapping at regional scales X. Wei et al. 10.1007/s11440-023-01841-4
- Integrating Physical and Machine Learning Models for Enhanced Landslide Prediction in Data-Scarce Environments H. Al-Najjar et al. 10.1007/s41748-024-00508-8
- Integrated analysis of landslide susceptibility: geotechnical insights, frequency ratio method, and hazard mitigation strategies in a volcanic terrain B. Momene Tuwa et al. 10.1007/s12517-025-12221-5
- Hybrid method for rainfall-induced regional landslide susceptibility mapping S. Wu et al. 10.1007/s00477-024-02753-9
- FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides Z. Guo et al. 10.1016/j.envsoft.2022.105354
- Invited perspectives: Views of 350 natural hazard community members on key challenges in natural hazards research and the Sustainable Development Goals R. Šakić Trogrlić et al. 10.5194/nhess-22-2771-2022
- Automatic Identification Model for Landslide Disaster Using Remote Sensing Images Based on Improved Multiresunet Z. Zhao et al. 10.1109/ACCESS.2024.3525067
- GIS-Based Data Integration Approach for Rainfall-Induced Slope Failure Susceptibility Mapping in Clayey Soils A. Baral et al. 10.1061/(ASCE)NH.1527-6996.0000478
- Assessing probability of failure of urban landslides through rapid characterization of soil properties and vegetation distribution S. Fiolleau et al. 10.1016/j.geomorph.2022.108560
- Debris flow magnitude, frequency, and precipitation threshold in the eastern North Cascades, Washington, USA J. Riedel & S. Sarrantonio 10.1007/s11069-021-04553-8
- Improving pixel-based regional landslide susceptibility mapping X. Wei et al. 10.1016/j.gsf.2024.101782
- Exploring the role of social determinants in the risk reduction of landslide-prone settlements: a case study of Giripurno Village in Central Java, Indonesia S. Purwitaningsih et al. 10.1186/s40677-023-00261-6
19 citations as recorded by crossref.
- Multi-Temporal Landslide Inventory-Based Statistical Susceptibility Modeling Associated With the 2017 Mw 6.5 Jiuzhaigou Earthquake, Sichuan, China L. Luo et al. 10.3389/fenvs.2022.858635
- Landslide Susceptibility Mapping and Assessment Using Geospatial Platforms and Weights of Evidence (WoE) Method in the Indian Himalayan Region: Recent Developments, Gaps, and Future Directions A. Batar & T. Watanabe 10.3390/ijgi10030114
- Improving Spatial Landslide Prediction with 3D Slope Stability Analysis and Genetic Algorithm Optimization: Application to the Oltrepò Pavese N. Palazzolo et al. 10.3390/w13060801
- Modelling landslides in the Lesser Himalaya region using geospatial and numerical simulation techniques M. Islam & S. Chattoraj 10.1007/s12517-023-11541-8
- Evaluation and prediction of compound geohazards in highly urbanized regions across China's Greater Bay Area K. He et al. 10.1016/j.jclepro.2024.141641
- Evaluating thresholds: the impact of terrain modifications on landslide susceptibility in a mountainous city S. Heo et al. 10.1080/19475705.2025.2493211
- Quantitative spatial distribution model of site-specific loess landslides on the Heifangtai terrace, China Q. Zhou et al. 10.1007/s10346-020-01551-y
- Comparison of hybrid data-driven and physical models for landslide susceptibility mapping at regional scales X. Wei et al. 10.1007/s11440-023-01841-4
- Integrating Physical and Machine Learning Models for Enhanced Landslide Prediction in Data-Scarce Environments H. Al-Najjar et al. 10.1007/s41748-024-00508-8
- Integrated analysis of landslide susceptibility: geotechnical insights, frequency ratio method, and hazard mitigation strategies in a volcanic terrain B. Momene Tuwa et al. 10.1007/s12517-025-12221-5
- Hybrid method for rainfall-induced regional landslide susceptibility mapping S. Wu et al. 10.1007/s00477-024-02753-9
- FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides Z. Guo et al. 10.1016/j.envsoft.2022.105354
- Invited perspectives: Views of 350 natural hazard community members on key challenges in natural hazards research and the Sustainable Development Goals R. Šakić Trogrlić et al. 10.5194/nhess-22-2771-2022
- Automatic Identification Model for Landslide Disaster Using Remote Sensing Images Based on Improved Multiresunet Z. Zhao et al. 10.1109/ACCESS.2024.3525067
- GIS-Based Data Integration Approach for Rainfall-Induced Slope Failure Susceptibility Mapping in Clayey Soils A. Baral et al. 10.1061/(ASCE)NH.1527-6996.0000478
- Assessing probability of failure of urban landslides through rapid characterization of soil properties and vegetation distribution S. Fiolleau et al. 10.1016/j.geomorph.2022.108560
- Debris flow magnitude, frequency, and precipitation threshold in the eastern North Cascades, Washington, USA J. Riedel & S. Sarrantonio 10.1007/s11069-021-04553-8
- Improving pixel-based regional landslide susceptibility mapping X. Wei et al. 10.1016/j.gsf.2024.101782
- Exploring the role of social determinants in the risk reduction of landslide-prone settlements: a case study of Giripurno Village in Central Java, Indonesia S. Purwitaningsih et al. 10.1186/s40677-023-00261-6
Latest update: 29 Oct 2025
Short summary
Identifying landslide hazards is challenging but important for understanding risks to people and both built and natural resources. We use models to identify landslide hazards based on observed landslides and local site traits such as slope and on physical mechanisms such as soil moisture. Integrating both approaches improves hazard detection by accounting for processes not captured in the physically based model. Hazard maps are made for the North Cascades National Park Complex (Washington, USA).
Identifying landslide hazards is challenging but important for understanding risks to people and...
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