Articles | Volume 21, issue 4
Nat. Hazards Earth Syst. Sci., 21, 1247–1262, 2021
https://doi.org/10.5194/nhess-21-1247-2021

Special issue: Resilience to risks in built environments

Nat. Hazards Earth Syst. Sci., 21, 1247–1262, 2021
https://doi.org/10.5194/nhess-21-1247-2021

Research article 21 Apr 2021

Research article | 21 Apr 2021

Exploring the potential relationship between the occurrence of debris flow and landslides

Zhu Liang et al.

Related authors

Classification and susceptibility assessment of debris flow based on a semi-quantitative method combination of the fuzzy C-means algorithm, factor analysis and efficacy coefficient
Zhu Liang, Changming Wang, Songling Han, Kaleem Ullah Jan Khan, and Yiao Liu
Nat. Hazards Earth Syst. Sci., 20, 1287–1304, https://doi.org/10.5194/nhess-20-1287-2020,https://doi.org/10.5194/nhess-20-1287-2020, 2020
Short summary
Exploring the potential relationship between the occurrence of landslides and debris flows: A new approach
Zhu Liang, Changming Wang, and Kaleem Ullah Jan Khan
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-127,https://doi.org/10.5194/nhess-2020-127, 2020
Revised manuscript not accepted
Short summary

Related subject area

Landslides and Debris Flows Hazards
Cascade effect of rock bridge failure in planar rock slides: numerical test with a distinct element code
Adeline Delonca, Yann Gunzburger, and Thierry Verdel
Nat. Hazards Earth Syst. Sci., 21, 1263–1278, https://doi.org/10.5194/nhess-21-1263-2021,https://doi.org/10.5194/nhess-21-1263-2021, 2021
Short summary
DebrisFlow Predictor: an agent-based runout program for shallow landslides
Richard Guthrie and Andrew Befus
Nat. Hazards Earth Syst. Sci., 21, 1029–1049, https://doi.org/10.5194/nhess-21-1029-2021,https://doi.org/10.5194/nhess-21-1029-2021, 2021
Short summary
Leveraging time series analysis of radar coherence and normalized difference vegetation index ratios to characterize pre-failure activity of the Mud Creek landslide, California
Mylène Jacquemart and Kristy Tiampo
Nat. Hazards Earth Syst. Sci., 21, 629–642, https://doi.org/10.5194/nhess-21-629-2021,https://doi.org/10.5194/nhess-21-629-2021, 2021
Short summary
Invited perspectives: Landslide populations – can they be predicted?
Fausto Guzzetti
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-39,https://doi.org/10.5194/nhess-2021-39, 2021
Revised manuscript accepted for NHESS
Short summary
A model for interpreting the deformation mechanism of reservoir landslides in the Three Gorges Reservoir area, China
Zongxing Zou, Huiming Tang, Robert E. Criss, Xinli Hu, Chengren Xiong, Qiong Wu, and Yi Yuan
Nat. Hazards Earth Syst. Sci., 21, 517–532, https://doi.org/10.5194/nhess-21-517-2021,https://doi.org/10.5194/nhess-21-517-2021, 2021
Short summary

Cited articles

Abdelaziz, M., Ali, P. Y., Jie, D., Jim, W., Binh, T., Dieu, T. B., Ram, A., and Boumezbeur, A. : Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance, Earth-Sci. Rev., 207, https://doi.org/10.1016/j.earscirev.2020.103225, 2020. 
Ahmed, M. Y., Hamid, R. P., Zohre, S. P., and Mohamed, A. K.: Erratum to: Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia, Landslides, 13, 1315–1318, 2016. 
Aleotti, P. and Chowdhury, R.: Landslide hazard assessment: summary review and new perspectives, Bull. Eng. Geol. Environ., 58, 21–44, 1999. 
Alessandro, T., Carla, I., Carlo, E., and Gabriele, S. M.: Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy), Geomorphology, 249, 119–136, 2015. 
Blais-Stevens, A. and Behnia, P.: Debris flow susceptibility mapping using a qualitative heuristic method and Flow-R along the Yukon Alaska Highway Corridor, Canada, Nat. Hazards Earth Syst. Sci., 16, 449–462, https://doi.org/10.5194/nhess-16-449-2016, 2016. 
Download
Short summary
In previous studies of landslide susceptibility mapping, one inventory is for one kind of landslide. However, this causes some problems for prevention and management. This study aims to map two kinds of landslides and use the results on the same map to explore the potential relationship. Through superimposition of two zoning maps, this provides a new way to evaluate the disaster chain and provides a valuable reference for land use planners.
Altmetrics
Final-revised paper
Preprint