Articles | Volume 22, issue 7
https://doi.org/10.5194/nhess-22-2239-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-22-2239-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Jul 2022
Research article |
| 11 Jul 2022
| 11 Jul 2022
Geographic information system models with fuzzy logic for susceptibility maps of debris flow using multiple types of parameters: a case study in Pinggu District of Beijing, China
Yiwei Zhang
College of Construction Engineering, Jilin University, Changchun, Jilin 130026, China
Jianping Chen
CORRESPONDING AUTHOR
College of Construction Engineering, Jilin University, Changchun, Jilin 130026, China
Qing Wang
College of Construction Engineering, Jilin University, Changchun, Jilin 130026, China
Chun Tan
China Water Northeastern Investigation, Design and Research Co., Ltd, Changchun, Jilin 130026, China
North China Power Engineering Co., Ltd. of China Power Engineering
Consulting Group, Changchun, Jilin 130000, China
Yongchao Li
Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and
Geophysics, University of Chinese Academy of Sciences, Beijing 100029, China
University of Chinese Academy of Sciences, Beijing 100029, China
Innovation Academy for Earth Science, Chinese Academy of Sciences, Beijing 100029, China
Xiaohui Sun
Department of Earth Sciences and Engineering, Taiyuan University of
Technology, Taiyuan, Shanxi 030024, China
Yang Li
Beijing institute of geological and prospecting engineering, Beijing, Beijing 100020, China
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Qing-bo Yu, Qing Wang, Xue-xin Yan, Tian-liang Yang, Jian-ping Chen, Meng Yao, Kai Zhou, and Xin-lei Huang
Proc. IAHS, 382, 381–386, https://doi.org/10.5194/piahs-382-381-2020, https://doi.org/10.5194/piahs-382-381-2020, 2020
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The ground deformation of a typical reclamation area in Chongming East Shoal, Shanghai was monitored by the SBAS method. Moreover, corresponding the monitoring results to the soil properties with field investigation and laboratory tests. The soil properties including physical and chemical properties, compressibility, micropore distribution and microstructure characteristics, are studied, and then the monitoring results are reasonably interpreted, providing a reference for future construction.
Related subject area
Landslides and Debris Flows Hazards
Lessons learnt from a rockfall time series analysis: data collection, statistical analysis, and applications
The concept of event-size-dependent exhaustion and its application to paraglacial rockslides
Coastal earthquake-induced landslide susceptibility during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand
Characteristics of debris flows recorded in the Shenmu area of central Taiwan between 2004 and 2021
Semi-automatic mapping of shallow landslides using free Sentinel-2 images and Google Earth Engine
The role of thermokarst evolution in debris flow initiation (Hüttekar Rock Glacier, Austrian Alps)
Accounting for the effect of forest and fragmentation in probabilistic rockfall hazard
Comprehensive landslide susceptibility map of Central Asia
The influence of large woody debris on post-wildfire debris flow sediment storage
Statistical modeling of sediment supply in torrent catchments of the northern French Alps
A data-driven evaluation of post-fire landslide susceptibility
Deciphering seasonal effects of triggering and preparatory precipitation for improved shallow landslide prediction using generalized additive mixed models
Rockfall monitoring with a Doppler radar on an active rock slide complex in Brienz/Brinzauls (Switzerland)
Brief communication: The northwest Himalaya towns slipping towards potential disaster
Dynamic response and breakage of trees subject to a landslide-induced air blast
Debris-flow surges of a very active alpine torrent: a field database
Rainfall thresholds estimation for shallow landslides in Peru from gridded daily data
Instantaneous limit equilibrium back analyses of major rockslides triggered during the 2016–2017 central Italy seismic sequence
Deadly disasters in southeastern South America: flash floods and landslides of February 2022 in Petrópolis, Rio de Janeiro
Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines
Antecedent rainfall as a critical factor for the triggering of debris flows in arid regions
Landslide initiation thresholds in data sparse regions: Application to landslide early warning criteria in Sitka, Alaska, USA
Sensitivity analysis of a built environment exposed to the synthetic monophasic viscous debris flow impacts with 3-D numerical simulations
Simulation analysis of 3D stability of a landslide with a locking segment: A case study of Tizicao landslide in Maoxian County, Southwest China
Characteristics and causes of natural and human-induced landslides in a tropical mountainous region: the rift flank west of Lake Kivu (Democratic Republic of the Congo)
Spatio-temporal analysis of slope-type debris flow activity in Horlachtal, Austria, based on orthophotos and lidar data since 1947
Assessing the relationship between weather conditions and rockfall using terrestrial laser scanning to improve risk management
Using principal component analysis to incorporate multi-layer soil moisture information in hydrometeorological thresholds for landslide prediction: an investigation based on ERA5-Land reanalysis data
Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria)
Brief communication: An autonomous UAV for catchment-wide monitoring of a debris flow torrent
How volcanic stratigraphy constrains headscarp collapse scenarios: the Samperre cliff case study (Martinique island, Lesser Antilles)
Landslide susceptibility assessment in the rocky coast subsystem of Essaouira, Morocco
Landsifier v1.0: a Python library to estimate likely triggers of mapped landslides
Timing landslide and flash flood events from SAR satellite: a regionally applicable methodology illustrated in African cloud-covered tropical environments
Potential of satellite-derived hydro-meteorological information for landslide initiation thresholds in Rwanda
Earthquake-induced landslides in Haiti: analysis of seismotectonic and possible climatic influences
Pre-collapse motion of the February 2021 Chamoli rock–ice avalanche, Indian Himalaya
Physically based modeling of co-seismic landslide, debris flow, and flood cascade
Finite-hillslope analysis of landslides triggered by excess pore water pressure: the roles of atmospheric pressure and rainfall infiltration during typhoons
Estimating global landslide susceptibility and its uncertainty through ensemble modeling
Terrain visibility impact on the preparation of landslide inventories: a practical example in Darjeeling district (India)
Using Sentinel-1 radar amplitude time series to constrain the timings of individual landslides: a step towards understanding the controls on monsoon-triggered landsliding
Introducing SlideforMAP: a probabilistic finite slope approach for modelling shallow-landslide probability in forested situations
Augmentation of WRF-Hydro to simulate overland-flow- and streamflow-generated debris flow susceptibility in burn scars
A new analytical method for stability analysis of rock blocks with cavity in sub-horizontal strata by considering eccentric effect
What drives landslide risk? Disaggregating risk analyses, an example from the Franz Josef Glacier and Fox Glacier valleys, New Zealand
Spatial assessment of probable recharge areas – investigating the hydrogeological controls of an active deep-seated gravitational slope deformation
Rainfall-induced landslide early warning system based on corrected mesoscale numerical models: an application for the southern Andes
Quantification of meteorological conditions for rockfall triggers in Germany
Debris flow velocity and volume estimations based on seismic data
Sandra Melzner, Marco Conedera, Johannes Hübl, and Mauro Rossi
Nat. Hazards Earth Syst. Sci., 23, 3079–3093, https://doi.org/10.5194/nhess-23-3079-2023, https://doi.org/10.5194/nhess-23-3079-2023, 2023
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The estimation of the temporal frequency of the involved rockfall processes is an important part in hazard and risk assessments. Different methods can be used to collect and analyse rockfall data. From a statistical point of view, rockfall datasets are nearly always incomplete. Accurate data collection approaches and the application of statistical methods on existing rockfall data series as reported in this study should be better considered in rockfall hazard and risk assessments in the future.
Stefan Hergarten
Nat. Hazards Earth Syst. Sci., 23, 3051–3063, https://doi.org/10.5194/nhess-23-3051-2023, https://doi.org/10.5194/nhess-23-3051-2023, 2023
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Rockslides are a major hazard in mountainous regions. In formerly glaciated regions, the disposition mainly arises from oversteepened topography and decreases through time. However, little is known about this decrease and thus about the present-day hazard of huge, potentially catastrophic rockslides. This paper presents a new theoretical framework that explains the decrease in maximum rockslide size through time and predicts the present-day frequency of large rockslides for the European Alps.
Colin K. Bloom, Corinne Singeisen, Timothy Stahl, Andrew Howell, Chris Massey, and Dougal Mason
Nat. Hazards Earth Syst. Sci., 23, 2987–3013, https://doi.org/10.5194/nhess-23-2987-2023, https://doi.org/10.5194/nhess-23-2987-2023, 2023
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Landslides are often observed on coastlines following large earthquakes, but few studies have explored this occurrence. Here, statistical modelling of landslides triggered by the 2016 Kaikōura earthquake in New Zealand is used to investigate factors driving coastal earthquake-induced landslides. Geology, steep slopes, and shaking intensity are good predictors of landslides from the Kaikōura event. Steeper slopes close to the coast provide the best explanation for a high landslide density.
Yi-Min Huang
Nat. Hazards Earth Syst. Sci., 23, 2649–2662, https://doi.org/10.5194/nhess-23-2649-2023, https://doi.org/10.5194/nhess-23-2649-2023, 2023
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Debris flows are common hazards in Taiwan, and debris-flow early warning is important for disaster responses. The rainfall thresholds of debris flows are analyzed and determined in terms of rainfall intensity, accumulated rainfall, and rainfall duration, based on case histories in Taiwan. These thresholds are useful for disaster management, and the cases in Taiwan are useful for global debris-flow databases.
Davide Notti, Martina Cignetti, Danilo Godone, and Daniele Giordan
Nat. Hazards Earth Syst. Sci., 23, 2625–2648, https://doi.org/10.5194/nhess-23-2625-2023, https://doi.org/10.5194/nhess-23-2625-2023, 2023
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We developed a cost-effective and user-friendly approach to map shallow landslides using free satellite data. Our methodology involves analysing the pre- and post-event NDVI variation to semi-automatically detect areas potentially affected by shallow landslides (PLs). Additionally, we have created Google Earth Engine scripts to rapidly compute NDVI differences and time series of affected areas. Datasets and codes are stored in an open data repository for improvement by the scientific community.
Simon Seelig, Thomas Wagner, Karl Krainer, Michael Avian, Marc Olefs, Klaus Haslinger, and Gerfried Winkler
Nat. Hazards Earth Syst. Sci., 23, 2547–2568, https://doi.org/10.5194/nhess-23-2547-2023, https://doi.org/10.5194/nhess-23-2547-2023, 2023
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A rapid sequence of cascading events involving thermokarst lake outburst, rock glacier front failure, debris flow development, and river blockage hit an alpine valley in Austria during summer 2019. We analyze the environmental conditions initiating the process chain and identify the rapid evolution of a thermokarst channel network as the main driver. Our results highlight the need to account for permafrost degradation in debris flow hazard assessment studies.
Camilla Lanfranconi, Paolo Frattini, Gianluca Sala, Giuseppe Dattola, Davide Bertolo, Juanjuan Sun, and Giovanni Battista Crosta
Nat. Hazards Earth Syst. Sci., 23, 2349–2363, https://doi.org/10.5194/nhess-23-2349-2023, https://doi.org/10.5194/nhess-23-2349-2023, 2023
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This paper presents a study on rockfall dynamics and hazard, examining the impact of the presence of trees along slope and block fragmentation. We compared rockfall simulations that explicitly model the presence of trees and fragmentation with a classical approach that accounts for these phenomena in model parameters (both the hazard and the kinetic energy change). We also used a non-parametric probabilistic rockfall hazard analysis method for hazard mapping.
Ascanio Rosi, William Frodella, Nicola Nocentini, Francesco Caleca, Hans Balder Havenith, Alexander Strom, Mirzo Saidov, Gany Amirgalievich Bimurzaev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 23, 2229–2250, https://doi.org/10.5194/nhess-23-2229-2023, https://doi.org/10.5194/nhess-23-2229-2023, 2023
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This work was carried out within the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project and is focused on the first landslide susceptibility analysis at a regional scale for Central Asia. The most detailed available landslide inventories were implemented in a random forest model. The final aim was to provide a useful tool for reduction strategies to landslide scientists, practitioners, and administrators.
Francis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann M. Youberg, Daniel Cadol, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 23, 2075–2088, https://doi.org/10.5194/nhess-23-2075-2023, https://doi.org/10.5194/nhess-23-2075-2023, 2023
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Debris flows often occur after wildfires. These debris flows move water, sediment, and wood. The wood can get stuck in channels, creating a dam that holds boulders, cobbles, sand, and muddy material. We investigated how the channel width and wood length influenced how much sediment is stored. We also used a series of equations to back calculate the debris flow speed using the breaking threshold of wood. These data will help improve models and provide insight into future field investigations.
Maxime Morel, Guillaume Piton, Damien Kuss, Guillaume Evin, and Caroline Le Bouteiller
Nat. Hazards Earth Syst. Sci., 23, 1769–1787, https://doi.org/10.5194/nhess-23-1769-2023, https://doi.org/10.5194/nhess-23-1769-2023, 2023
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In mountain catchments, damage during floods is generally primarily driven by the supply of a massive amount of sediment. Predicting how much sediment can be delivered by frequent and infrequent events is thus important in hazard studies. This paper uses data gathered during the maintenance operation of about 100 debris retention basins to build simple equations aiming at predicting sediment supply from simple parameters describing the upstream catchment.
Elsa S. Culler, Ben Livneh, Balaji Rajagopalan, and Kristy F. Tiampo
Nat. Hazards Earth Syst. Sci., 23, 1631–1652, https://doi.org/10.5194/nhess-23-1631-2023, https://doi.org/10.5194/nhess-23-1631-2023, 2023
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Landslides have often been observed in the aftermath of wildfires. This study explores regional patterns in the rainfall that caused landslides both after fires and in unburned locations. In general, landslides that occur after fires are triggered by less rainfall, confirming that fire helps to set the stage for landslides. However, there are regional differences in the ways in which fire impacts landslides, such as the size and direction of shifts in the seasonality of landslides after fires.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
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We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Marius Schneider, Nicolas Oestreicher, and Simon Loew
EGUsphere, https://doi.org/10.5194/egusphere-2023-555, https://doi.org/10.5194/egusphere-2023-555, 2023
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Rockfalls and their hazards are typically treated as statistical events based on rockfall catalogs, but only a few complete rockfall inventories are available today. Here we present new results from a Doppler radar rockfall alarm system, which operates since 2018 at high frequency under all illumination and weather conditions, at a site where frequent rockfall events threaten a village and a road. The new data set is used to investigate rockfall triggers and in an active rockslide complex.
Yaspal Sundriyal, Vipin Kumar, Neha Chauhan, Sameeksha Kaushik, Rahul Ranjan, and Mohit Kumar Punia
Nat. Hazards Earth Syst. Sci., 23, 1425–1431, https://doi.org/10.5194/nhess-23-1425-2023, https://doi.org/10.5194/nhess-23-1425-2023, 2023
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The NW Himalaya has been one of the most affected terrains of the Himalaya, subject to disastrous landslides. This article focuses on two towns (Joshimath and Bhatwari) of the NW Himalaya, which have been witnessing subsidence for decades. We used a slope stability simulation to determine the response of the hillslopes accommodating these towns under various loading conditions. We found that the maximum displacement in these hillslopes might reach up to 20–25 m.
Yu Zhuang, Aiguo Xing, Perry Bartelt, Muhammad Bilal, and Zhaowei Ding
Nat. Hazards Earth Syst. Sci., 23, 1257–1266, https://doi.org/10.5194/nhess-23-1257-2023, https://doi.org/10.5194/nhess-23-1257-2023, 2023
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Tree destruction is often used to back calculate the air blast impact region and to estimate the air blast power. Here we established a novel model to assess air blast power using tree destruction information. We find that the dynamic magnification effect makes the trees easier to damage by a landslide-induced air blast, but the large tree deformation would weaken the effect. Bending and overturning are two likely failure modes, which depend heavily on the properties of trees.
Suzanne Lapillonne, Firmin Fontaine, Frédéric Liebault, Vincent Richefeu, and Guillaume Piton
Nat. Hazards Earth Syst. Sci., 23, 1241–1256, https://doi.org/10.5194/nhess-23-1241-2023, https://doi.org/10.5194/nhess-23-1241-2023, 2023
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Debris flows are fast flows most often found in torrential watersheds. They are composed of two phases: a liquid phase which can be mud-like and a granular phase, including large boulders, transported along with the flow. Due to their destructive nature, accessing features of the flow, such as velocity and flow height, is difficult. We present a protocol to analyse debris flow data and results of the Réal torrent in France. These results will help experts in designing models.
Carlos Millán-Arancibia and Waldo Lavado-Casimiro
Nat. Hazards Earth Syst. Sci., 23, 1191–1206, https://doi.org/10.5194/nhess-23-1191-2023, https://doi.org/10.5194/nhess-23-1191-2023, 2023
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This study is the first approximation of regional rainfall thresholds for shallow landslide occurrence in Peru. This research was generated from a gridded precipitation data and landslide inventory. The analysis showed that the threshold based on the combination of mean daily intensity–duration variables gives the best results for separating rainfall events that generate landslides. Through this work the potential of thresholds for landslide monitoring at the regional scale is demonstrated.
Luca Verrucci, Giovanni Forte, Melania De Falco, Paolo Tommasi, Giuseppe Lanzo, Kevin W. Franke, and Antonio Santo
Nat. Hazards Earth Syst. Sci., 23, 1177–1190, https://doi.org/10.5194/nhess-23-1177-2023, https://doi.org/10.5194/nhess-23-1177-2023, 2023
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Stability analyses in static and seismic conditions were performed on four rockslides that occurred during the main shocks of the 2016–2017 central Italy seismic sequence. These results also indicate that specific structural features of the slope must carefully be accounted for in evaluating potential hazards on transportation infrastructures in mountainous regions.
Enner Alcântara, José A. Marengo, José Mantovani, Luciana R. Londe, Rachel Lau Yu San, Edward Park, Yunung Nina Lin, Jingyu Wang, Tatiana Mendes, Ana Paula Cunha, Luana Pampuch, Marcelo Seluchi, Silvio Simões, Luz Adriana Cuartas, Demerval Goncalves, Klécia Massi, Regina Alvalá, Osvaldo Moraes, Carlos Souza Filho, Rodolfo Mendes, and Carlos Nobre
Nat. Hazards Earth Syst. Sci., 23, 1157–1175, https://doi.org/10.5194/nhess-23-1157-2023, https://doi.org/10.5194/nhess-23-1157-2023, 2023
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The municipality of Petrópolis (approximately 305 687 inhabitants) is nestled in the mountains 68 km outside the city of Rio de Janeiro. On 15 February 2022, the city of Petrópolis in Rio de Janeiro, Brazil, received an unusually high volume of rain within 3 h (258 mm). This resulted in flash floods and subsequent landslides that caused 231 fatalities, the deadliest landslide disaster recorded in Petrópolis. This work shows how the disaster was triggered.
Joshua N. Jones, Georgina L. Bennett, Claudia Abancó, Mark A. M. Matera, and Fibor J. Tan
Nat. Hazards Earth Syst. Sci., 23, 1095–1115, https://doi.org/10.5194/nhess-23-1095-2023, https://doi.org/10.5194/nhess-23-1095-2023, 2023
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We modelled where landslides occur in the Philippines using landslide data from three typhoon events in 2009, 2018, and 2019. These models show where landslides occurred within the landscape. By comparing the different models, we found that the 2019 landslides were occurring all across the landscape, whereas the 2009 and 2018 landslides were mostly occurring at specific slope angles and aspects. This shows that landslide susceptibility must be considered variable through space and time.
Shalev Siman-Tov and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1079–1093, https://doi.org/10.5194/nhess-23-1079-2023, https://doi.org/10.5194/nhess-23-1079-2023, 2023
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Debris flows represent a threat to infrastructure and the population. In arid areas, they are observed when heavy rainfall hits steep slopes with sediments. Here, we use digital surface models and radar rainfall data to detect and characterize the triggering and non-triggering rainfall conditions. We find that rainfall intensity alone is insufficient to explain the triggering. We suggest that antecedent rainfall could represent a critical factor for debris flow triggering in arid regions.
Annette I. Patton, Lisa V. Luna, Joshua J. Roering, Aaron Jacobs, Oliver Korup, and Benjamin B. Mirus
EGUsphere, https://doi.org/10.5194/egusphere-2023-25, https://doi.org/10.5194/egusphere-2023-25, 2023
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Landslide warning systems often use statistical models to predict landslides based on rainfall. They are typically trained on large datasets with many landslide occurrences, but in rural areas large datasets may not exist. In this study, we evaluate which statistical model types are best suited for predicting landslides and demonstrate that even a small landslide inventory (5 storms) can be used to train useful models for landslide early warning when non-landslide events are also included.
Xun Huang, Zhijian Zhang, and Guoping Xiang
Nat. Hazards Earth Syst. Sci., 23, 871–889, https://doi.org/10.5194/nhess-23-871-2023, https://doi.org/10.5194/nhess-23-871-2023, 2023
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A sensitivity analysis on the building impact force resulting from the representative built environment parameters is executed through the FLOW-3D model. The surrounding buildings' properties, especially the azimuthal angle, have been confirmed to play significant roles in determining the peak impact forces. The single and combined effects of built environments are analyzed in detail. This will improve understanding of vulnerability assessment and migration design against debris flow hazards.
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
EGUsphere, https://doi.org/10.5194/egusphere-2023-28, https://doi.org/10.5194/egusphere-2023-28, 2023
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We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide. We found that the CSM-HSP combines the advantages of the IRMM model in simulating the actual deformation of slopes with rock bridges and the modeling advantage of the JM model. The research results are helpful to choose an appropriate rock bridge model to simulate the 3D landslide stability and to reveal the influence laws of rock bridges on the 3D stability of landslides.
Jean-Claude Maki Mateso, Charles L. Bielders, Elise Monsieurs, Arthur Depicker, Benoît Smets, Théophile Tambala, Luc Bagalwa Mateso, and Olivier Dewitte
Nat. Hazards Earth Syst. Sci., 23, 643–666, https://doi.org/10.5194/nhess-23-643-2023, https://doi.org/10.5194/nhess-23-643-2023, 2023
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This research highlights the importance of human activities on the occurrence of landslides and the need to consider this context when studying hillslope instability patterns in regions under anthropogenic pressure. Also, this study highlights the importance of considering the timing of landslides and hence the added value of using historical information for compiling an inventory.
Jakob Rom, Florian Haas, Tobias Heckmann, Moritz Altmann, Fabian Fleischer, Camillo Ressl, Sarah Betz-Nutz, and Michael Becht
Nat. Hazards Earth Syst. Sci., 23, 601–622, https://doi.org/10.5194/nhess-23-601-2023, https://doi.org/10.5194/nhess-23-601-2023, 2023
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In this study, an area-wide slope-type debris flow record has been established for Horlachtal, Austria, since 1947 based on historical and recent remote sensing data. Spatial and temporal analyses show variations in debris flow activity in space and time in a high-alpine region. The results can contribute to a better understanding of past slope-type debris flow dynamics in the context of extreme precipitation events and their possible future development.
Tom Birien and Francis Gauthier
Nat. Hazards Earth Syst. Sci., 23, 343–360, https://doi.org/10.5194/nhess-23-343-2023, https://doi.org/10.5194/nhess-23-343-2023, 2023
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On highly fractured rockwalls such as those found in northern Gaspésie, most rockfalls are triggered by weather conditions. This study highlights that in winter, rockfall frequency is 12 times higher during a superficial thaw than during a cold period in which temperature remains below 0 °C. In summer, rockfall frequency is 22 times higher during a heavy rainfall event than during a mainly dry period. This knowledge could be used to implement a risk management strategy.
Nunziarita Palazzolo, David J. Peres, Enrico Creaco, and Antonino Cancelliere
Nat. Hazards Earth Syst. Sci., 23, 279–291, https://doi.org/10.5194/nhess-23-279-2023, https://doi.org/10.5194/nhess-23-279-2023, 2023
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We propose an approach exploiting PCA to derive hydrometeorological landslide-triggering thresholds using multi-layered soil moisture data from ERA5-Land reanalysis. Comparison of thresholds based on single- and multi-layered soil moisture information provides a means to identify the significance of multi-layered data for landslide triggering in a region. In Sicily, the proposed approach yields thresholds with a higher performance than traditional precipitation-based ones (TSS = 0.71 vs. 0.50).
Raphael Knevels, Helene Petschko, Herwig Proske, Philip Leopold, Aditya N. Mishra, Douglas Maraun, and Alexander Brenning
Nat. Hazards Earth Syst. Sci., 23, 205–229, https://doi.org/10.5194/nhess-23-205-2023, https://doi.org/10.5194/nhess-23-205-2023, 2023
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In summer 2009 and 2014, rainfall events occurred in the Styrian Basin (Austria), triggering thousands of landslides. Landslide storylines help to show potential future changes under changing environmental conditions. The often neglected uncertainty quantification was the aim of this study. We found uncertainty arising from the landslide model to be of the same order as climate scenario uncertainty. Understanding the dimensions of uncertainty is crucial for allowing informed decision-making.
Fabian Walter, Elias Hodel, Erik S. Mannerfelt, Kristen Cook, Michael Dietze, Livia Estermann, Michaela Wenner, Daniel Farinotti, Martin Fengler, Lukas Hammerschmidt, Flavia Hänsli, Jacob Hirschberg, Brian McArdell, and Peter Molnar
Nat. Hazards Earth Syst. Sci., 22, 4011–4018, https://doi.org/10.5194/nhess-22-4011-2022, https://doi.org/10.5194/nhess-22-4011-2022, 2022
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Debris flows are dangerous sediment–water mixtures in steep terrain. Their formation takes place in poorly accessible terrain where instrumentation cannot be installed. Here we propose to monitor such source terrain with an autonomous drone for mapping sediments which were left behind by debris flows or may contribute to future events. Short flight intervals elucidate changes of such sediments, providing important information for landscape evolution and the likelihood of future debris flows.
Marc Peruzzetto, Yoann Legendre, Aude Nachbaur, Thomas J. B. Dewez, Yannick Thiery, Clara Levy, and Benoit Vittecoq
Nat. Hazards Earth Syst. Sci., 22, 3973–3992, https://doi.org/10.5194/nhess-22-3973-2022, https://doi.org/10.5194/nhess-22-3973-2022, 2022
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Volcanic edifices result from successive construction and dismantling phases. Thus, the geological units forming volcanoes display complex geometries. We show that such geometries can be reconstructed thanks to aerial views, topographic surveys and photogrammetric models. In our case study of the Samperre cliff (Martinique, Lesser Antilles), it allows us to link destabilizations from a rocky cliff to the existence of a filled paleo-valley and estimate a potentially unstable volume.
Abdellah Khouz, Jorge Trindade, Sérgio C. Oliveira, Fatima El Bchari, Blaid Bougadir, Ricardo A. C. Garcia, and Mourad Jadoud
Nat. Hazards Earth Syst. Sci., 22, 3793–3814, https://doi.org/10.5194/nhess-22-3793-2022, https://doi.org/10.5194/nhess-22-3793-2022, 2022
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The aim of this study was to assess the landslide susceptibility of the rocky coast of Essaouira using the information value model. The resulting susceptibility maps could be used for both environmental protection and general planning of future development activities.
Kamal Rana, Nishant Malik, and Ugur Ozturk
Nat. Hazards Earth Syst. Sci., 22, 3751–3764, https://doi.org/10.5194/nhess-22-3751-2022, https://doi.org/10.5194/nhess-22-3751-2022, 2022
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The landslide hazard models assist in mitigating losses due to landslides. However, these models depend on landslide databases, which often have missing triggering information, rendering these databases unusable for landslide hazard models. In this work, we developed a Python library, Landsifier, consisting of three different methods to identify the triggers of landslides. These methods can classify landslide triggers with high accuracy using only a landslide polygon shapefile as an input.
Axel A. J. Deijns, Olivier Dewitte, Wim Thiery, Nicolas d'Oreye, Jean-Philippe Malet, and François Kervyn
Nat. Hazards Earth Syst. Sci., 22, 3679–3700, https://doi.org/10.5194/nhess-22-3679-2022, https://doi.org/10.5194/nhess-22-3679-2022, 2022
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Landslides and flash floods are rainfall-induced processes that often co-occur and interact, generally very quickly. In mountainous cloud-covered environments, determining when these processes occur remains challenging. We propose a regional methodology using open-access satellite radar images that allow for the timing of landslide and flash floods events, in the contrasting landscapes of tropical Africa, with an accuracy of up to a few days. The methodology shows potential for transferability.
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661, https://doi.org/10.5194/nhess-22-3641-2022, https://doi.org/10.5194/nhess-22-3641-2022, 2022
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This study compared gauge-based and satellite-based precipitation products. Similarly, satellite- and hydrological model-derived soil moisture was compared to in situ soil moisture and used in landslide hazard assessment and warning. The results reveal the cumulative 3 d rainfall from the NASA-GPM to be the most effective landslide trigger. The modelled antecedent soil moisture in the root zone was the most informative hydrological variable for landslide hazard assessment and warning in Rwanda.
Hans-Balder Havenith, Kelly Guerrier, Romy Schlögel, Anika Braun, Sophia Ulysse, Anne-Sophie Mreyen, Karl-Henry Victor, Newdeskarl Saint-Fleur, Léna Cauchie, Dominique Boisson, and Claude Prépetit
Nat. Hazards Earth Syst. Sci., 22, 3361–3384, https://doi.org/10.5194/nhess-22-3361-2022, https://doi.org/10.5194/nhess-22-3361-2022, 2022
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We present a new landslide inventory for the 2021, M 7.2, Haiti, earthquake. We compare characteristics of this inventory with those of the 2010 seismically induced landslides, highlighting the much larger total area of 2021 landslides. This fact could be related to the larger earthquake magnitude in 2021, to the more central location of the fault segment ruptured in 2021 with respect to coastal zones, and/or to possible climatic preconditioning of slope failures in the 2021 affected area.
Maximillian Van Wyk de Vries, Shashank Bhushan, Mylène Jacquemart, César Deschamps-Berger, Etienne Berthier, Simon Gascoin, David E. Shean, Dan H. Shugar, and Andreas Kääb
Nat. Hazards Earth Syst. Sci., 22, 3309–3327, https://doi.org/10.5194/nhess-22-3309-2022, https://doi.org/10.5194/nhess-22-3309-2022, 2022
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On 7 February 2021, a large rock–ice avalanche occurred in Chamoli, Indian Himalaya. The resulting debris flow swept down the nearby valley, leaving over 200 people dead or missing. We use a range of satellite datasets to investigate how the collapse area changed prior to collapse. We show that signs of instability were visible as early 5 years prior to collapse. However, it would likely not have been possible to predict the timing of the event from current satellite datasets.
Bastian van den Bout, Chenxiao Tang, Cees van Westen, and Victor Jetten
Nat. Hazards Earth Syst. Sci., 22, 3183–3209, https://doi.org/10.5194/nhess-22-3183-2022, https://doi.org/10.5194/nhess-22-3183-2022, 2022
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Natural hazards such as earthquakes, landslides, and flooding do not always occur as stand-alone events. After the 2008 Wenchuan earthquake, a co-seismic landslide blocked a stream in Hongchun. Two years later, a debris flow breached the material, blocked the Min River, and resulted in flooding of a small town. We developed a multi-process model that captures the full cascade. Despite input and process uncertainties, probability of flooding was high due to topography and trigger intensities.
Lucas Pelascini, Philippe Steer, Maxime Mouyen, and Laurent Longuevergne
Nat. Hazards Earth Syst. Sci., 22, 3125–3141, https://doi.org/10.5194/nhess-22-3125-2022, https://doi.org/10.5194/nhess-22-3125-2022, 2022
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Landslides represent a major natural hazard and are often triggered by typhoons. We present a new 2D model computing the respective role of rainfall infiltration, atmospheric depression and groundwater in slope stability during typhoons. The results show rainfall is the strongest factor of destabilisation. However, if the slope is fully saturated, near the toe of the slope or during the wet season, rainfall infiltration is limited and atmospheric pressure change can become the dominant factor.
Anne Felsberg, Jean Poesen, Michel Bechtold, Matthias Vanmaercke, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 22, 3063–3082, https://doi.org/10.5194/nhess-22-3063-2022, https://doi.org/10.5194/nhess-22-3063-2022, 2022
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In this study we assessed global landslide susceptibility at the coarse 36 km spatial resolution of global satellite soil moisture observations to prepare for a subsequent combination of the two. Specifically, we focus therefore on the susceptibility of hydrologically triggered landslides. We introduce ensemble techniques, common in, for example, meteorology but not yet in the landslide community, to retrieve reliable estimates of the total prediction uncertainty.
Txomin Bornaetxea, Ivan Marchesini, Sumit Kumar, Rabisankar Karmakar, and Alessandro Mondini
Nat. Hazards Earth Syst. Sci., 22, 2929–2941, https://doi.org/10.5194/nhess-22-2929-2022, https://doi.org/10.5194/nhess-22-2929-2022, 2022
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One cannot know if there is a landslide or not in an area that one has not observed. This is an obvious statement, but when landslide inventories are obtained by field observation, this fact is seldom taken into account. Since fieldwork campaigns are often done following the roads, we present a methodology to estimate the visibility of the terrain from the roads, and we demonstrate that fieldwork-based inventories are underestimating landslide density in less visible areas.
Katy Burrows, Odin Marc, and Dominique Remy
Nat. Hazards Earth Syst. Sci., 22, 2637–2653, https://doi.org/10.5194/nhess-22-2637-2022, https://doi.org/10.5194/nhess-22-2637-2022, 2022
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The locations of triggered landslides following a rainfall event can be identified in optical satellite images. However cloud cover associated with the rainfall means that these images cannot be used to identify landslide timing. Timings of landslides triggered during long rainfall events are often unknown. Here we present methods of using Sentinel-1 satellite radar data, acquired every 12 d globally in all weather conditions, to better constrain the timings of rainfall-triggered landslides.
Feiko Bernard van Zadelhoff, Adel Albaba, Denis Cohen, Chris Phillips, Bettina Schaefli, Luuk Dorren, and Massimiliano Schwarz
Nat. Hazards Earth Syst. Sci., 22, 2611–2635, https://doi.org/10.5194/nhess-22-2611-2022, https://doi.org/10.5194/nhess-22-2611-2022, 2022
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Shallow landslides pose a risk to people, property and infrastructure. Assessment of this hazard and the impact of protective measures can reduce losses. We developed a model (SlideforMAP) that can assess the shallow-landslide risk on a regional scale for specific rainfall events. Trees are an effective and cheap protective measure on a regional scale. Our model can assess their hazard reduction down to the individual tree level.
Chuxuan Li, Alexander L. Handwerger, Jiali Wang, Wei Yu, Xiang Li, Noah J. Finnegan, Yingying Xie, Giuseppe Buscarnera, and Daniel E. Horton
Nat. Hazards Earth Syst. Sci., 22, 2317–2345, https://doi.org/10.5194/nhess-22-2317-2022, https://doi.org/10.5194/nhess-22-2317-2022, 2022
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In January 2021 a storm triggered numerous debris flows in a wildfire burn scar in California. We use a hydrologic model to assess debris flow susceptibility in pre-fire and postfire scenarios. Compared to pre-fire conditions, postfire conditions yield dramatic increases in peak water discharge, substantially increasing debris flow susceptibility. Our work highlights the hydrologic model's utility in investigating and potentially forecasting postfire debris flows at regional scales.
Xushan Shi, Bo Chai, Juan Du, Wei Wang, and Bo Liu
EGUsphere, https://doi.org/10.5194/egusphere-2022-658, https://doi.org/10.5194/egusphere-2022-658, 2022
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A three-dimensional stability analysis method is proposed for biased rockfall with basal cavity. Four failure modes are considered according to rockfall evolution process, including partial damage of underlying soft rock and overall failure of hard rock block. This method is validated with the biased rockfalls in Sichuan basin, China. Critical cavity retreat ratio from low to moderate rockfall susceptibility is 0.33. This method could facilitate rockfall early identification and risk mitigation.
Saskia de Vilder, Chris Massey, Biljana Lukovic, Tony Taig, and Regine Morgenstern
Nat. Hazards Earth Syst. Sci., 22, 2289–2316, https://doi.org/10.5194/nhess-22-2289-2022, https://doi.org/10.5194/nhess-22-2289-2022, 2022
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This study calculates the fatality risk posed by landslides while visiting Franz Josef Glacier and Fox Glacier valleys, New Zealand, for nine different scenarios, where the variables of the risk equation were adjusted to determine the range in risk values and associated uncertainty. The results show that it is important to consider variable inputs that change through time, such as the increasing probability of an earthquake and the impact of climate change on landslide characteristics.
Jan Pfeiffer, Thomas Zieher, Jan Schmieder, Thom Bogaard, Martin Rutzinger, and Christoph Spötl
Nat. Hazards Earth Syst. Sci., 22, 2219–2237, https://doi.org/10.5194/nhess-22-2219-2022, https://doi.org/10.5194/nhess-22-2219-2022, 2022
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The activity of slow-moving deep-seated landslides is commonly governed by pore pressure variations within the shear zone. Groundwater recharge as a consequence of precipitation therefore is a process regulating the activity of landslides. In this context, we present a highly automated geo-statistical approach to spatially assess groundwater recharge controlling the velocity of a deep-seated landslide in Tyrol, Austria.
Ivo Fustos-Toribio, Nataly Manque-Roa, Daniel Vásquez Antipan, Mauricio Hermosilla Sotomayor, and Viviana Letelier Gonzalez
Nat. Hazards Earth Syst. Sci., 22, 2169–2183, https://doi.org/10.5194/nhess-22-2169-2022, https://doi.org/10.5194/nhess-22-2169-2022, 2022
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We develop for the first time a rainfall-induced landslide early warning system for the south of Chile. We used forecast precipitation values at different scales using mesoscale models to evaluate the probability of landslides using statistical models. We showed the feasibility of implementing these models in future, supporting stakeholders and decision-makers.
Katrin M. Nissen, Stefan Rupp, Thomas M. Kreuzer, Björn Guse, Bodo Damm, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 22, 2117–2130, https://doi.org/10.5194/nhess-22-2117-2022, https://doi.org/10.5194/nhess-22-2117-2022, 2022
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A statistical model is introduced which quantifies the influence of individual potential triggering factors and their interactions on rockfall probability in central Europe. The most important factor is daily precipitation, which is most effective if sub-surface moisture levels are high. Freeze–thaw cycles in the preceding days can further increase the rockfall hazard. The model can be applied to climate simulations in order to investigate the effect of climate change on rockfall probability.
Andreas Schimmel, Velio Coviello, and Francesco Comiti
Nat. Hazards Earth Syst. Sci., 22, 1955–1968, https://doi.org/10.5194/nhess-22-1955-2022, https://doi.org/10.5194/nhess-22-1955-2022, 2022
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The estimation of debris flow velocity and volume is a fundamental task for the development of early warning systems and other mitigation measures. This work provides a first approach for estimating the velocity and the total volume of debris flows based on the seismic signal detected with simple, low-cost geophones installed along the debris flow channel. The developed method was applied to seismic data collected at three test sites in the Alps: Gadria and Cancia (IT) and Lattenbach (AT).
Cited articles
Akbar, T. A. and Ha, S. R.: Landslide hazard zoning along Himalayan Kaghan
Valley of Pakistan – by integration of GPS, GIS, and remote sensing
technology, Landslides, 8, 527–540, https://doi.org/10.1007/s10346-011-0260-1, 2011.
Beijing Municipal Commission of Planning and Natural Resources: The distribution map of potential geological hazard points and
susceptibility map in pinggu district, http://ghzrzyw.beijing.gov.cn/zhengwuxinxi/zxzt/dzzhfzzt/zzzhdcpg/202008/t20200807_1976436.html, last access: 25 June 2022.
Benda, L. E. and Dunne, T.: Sediment routing by debris flow, in: Erosion and
sedimentation in the Pacific Rim, edited by: Beschta, R. L., Blinn, T.,
Grant, G. E., Swanson, F. J., and Ice, G. G., IAHS P., 213–223,
https://doi.org/10.1111/j.1753-4887.1977.tb06503.x, 1987.
Borrelli, L., Cofone, G., Coscarelli, R., and Gullà, G.: Shallow
landslides triggered by consecutive rainfall events at Catanzaro strait
(Calabria–Southern Italy), J. Maps, 11, 730–744, https://doi.org/10.1080/17445647.2014.943814, 2014.
Bovis, M. and Dagg, B.: Debris flow triggering by impulsive loading -
mechanical modeling and case-studies, Can. Geotech. J., 29,
345–352, https://doi.org/10.1139/t92-040, 1992.
Cao, C., Xu, P., Chen, J., Zheng, L., and Niu, C.: Hazard assessment of
debris-flow along the baicha river in heshigten banner, inner mongolia,
china, Int. J. Environ. Res. Pu., 14, 1–19, https://doi.org/10.3390/ijerph14010030,
2016.
Chang, T. C. and Chien, Y. H.: The application of genetic algorithm in
debris flows prediction, Environ. Geol., 53, 339–347, https://doi.org/10.1007/s00254-007-0649-2, 2007.
Chiou, I. J., Chen, C. H., Liu, W. L., Huang, S. M., and Chang, Y. M.:
Methodology of disaster risk assessment for debris flows in a river basin,
Stoch. Env. Res. Risk. A, 29, 775–792, https://doi.org/10.1007/s00477-014-0932-1, 2015.
Chung, C.-J. F. and Fabbri, A. G.: Probabilistic prediction models for
landslide hazard mapping, Photogramm. Eng. Rem. S.,
65, 1389–1399, https://doi.org/10.1016/S0924-2716(99)00030-1, 1999.
Chung, C. J. F., Fabbri, A., and Westen, C. J. v.: Multivariate regression
analysis for landslide hazard zonation, Adb, Nat. Technol. Haz., 5, 107–133, 1995.
Conoscenti, C., Ciaccio, M., Caraballo-Arias, N. A.,
Gómez-Gutiérrez, Á., Rotigliano, E., and Agnesi, V.: Assessment
of susceptibility to earth-flow landslide using logistic regression and
multivariate adaptive regression splines: A case of the Belice River basin
(western Sicily, Italy), Geomorphology, 242, 49–64, https://doi.org/10.1016/j.geomorph.2014.09.020, 2015.
Crozier, M. J., Vaughan, E. E., and Tippett, J. M.: Relative instability of
colluvium-filled bedrock depressions, Earth Surf. Proc. Land.,
15, 329–339, https://doi.org/10.1002/esp.3290150404, 1990.
Dai, F. C. and Lee, C. F.: Landslide characteristics and slope instability
modeling using GIS, Lantau Island, Hong Kong, Geomorphology, 42, 213–228, https://doi.org/10.1016/S0169-555X(01)00087-3, 2002.
Dai, F. C., Lee, C. F., Li, H.-Z., and Xu, C.: Assessment of landslide
susceptibility on the natural terrain of Lantau Island, Hong Kong,
Environ. Geol., 40, 381–391, https://doi.org/10.1007/s002540000163, 2001.
Deng, J. L.: Control problems of grey systems, Syst. Control Lett.,
1, 288–294, https://doi.org/10.1016/S0167-6911(82)80025-X, 1982.
Deng, J. L.: Grey prediction and decision, Huazhong University of Science
and Technology Press, Wuhan, ISBN 7-5609-0269-3, 1988.
Di, B., Zhang, H., Liu, Y., Li, J., Chen, N., Stamatopoulos, C. A., Luo, Y.,
and Zhan, Y.: Assessing susceptibility of debris flow in southwest china
using gradient boosting machine, Sci. Rep.-UK, 9, 12532, https://doi.org/10.1038/s41598-019-48986-5, 2019.
Dietrich, W. E., Wilson, C. J., and Reneau, S. L.: Hollows, colluvium, and
landslides in soil-mantled landscapes, in: Hillslope Processes, edited by:
Abrahams, A. D., Allen & Unwin, Boston, 1986.
Di Napoli, M., Carotenuto, F., Cevasco, A., Confuorto, P., Di Martire, D.,
Firpo, M., Pepe, G., Raso, E., and Calcaterra, D.: Machine learning ensemble
modelling as a tool to improve landslide susceptibility mapping reliability,
Landslides, 17, 1897–1914, https://doi.org/10.1007/s10346-020-01392-9, 2020.
Donati, L. and Turrini, M. C.: An objective method to rank the importance of
the factors predisposing to landslides with the GIS methodology: application
to an area of the Apennines (Valnerina; Perugia, Italy), Eng.
Geol., 63, 277–289, https://doi.org/10.1016/S0013-7952(01)00087-4, 2002.
Dong, J.-J., Lee, C.-T., Tung, Y.-H., Liu, C.-N., Lin, K.-P., and Lee,
J.-F.: The role of the sediment budget in understanding debris flow
susceptibility, Earth Surf. Proc. Land., 34, 1612–1624, https://doi.org/10.1002/esp.1850, 2009.
Dramis, F. and Sorriso-Valvo, M.: Deep-seated gravitational slope
deformations, relatedlandslides and tectonics, Eng. Geol., 38,
231–243, https://doi.org/10.1016/0013-7952(94)90040-X, 1994.
Ercanoglu, M. and Gokceoglu, C.: Use of fuzzy relations to produce landslide
susceptibility map of a landslide prone area (West Black Sea Region,
Turkey), Eng. Geol., 75, 229–250, https://doi.org/10.1016/j.enggeo.2004.06.001,
2004.
Ercanoglu, M. and Temiz, F. A.: Application of logistic regression and fuzzy
operators to landslide susceptibility assessment in Azdavay (Kastamonu,
Turkey), Environ. Earth Sci., 64, 949–964, https://doi.org/10.1007/s12665-011-0912-4, 2011.
Fairchild, L. H.: The importance of lahar initiation processes, Rev.
Eng. Geol., 7, 51–62, https://doi.org/10.1130/REG7-p51, 1987.
Fang, Z., Wang, Y., Peng, L., and Hong, H.: A comparative study of
heterogeneous ensemble-learning techniques for landslide susceptibility
mapping, Int. J. Geogr. Inf. Sci., 35,
321–347, https://doi.org/10.1080/13658816.2020.1808897, 2020.
Frattini, P., Crosta, G., and Carrara, A.: Techniques for evaluating the
performance of landslide susceptibility models, Eng. Geol., 111,
62–72, https://doi.org/10.1016/j.enggeo.2009.12.004, 2010.
Gómez, H. and Kavzoglu, T.: Assessment of shallow landslide
susceptibility using artificial neural networks in Jabonosa River Basin,
Venezuela, Eng. Geol., 78, 11–27, https://doi.org/10.1016/j.enggeo.2004.10.004,
2005.
Guzzetti, F., Carrara, A., Cardinali, M., and Reichenbach, P.: Landslide
hazard evaluation: a review of current techniques and their application in a
multi-scale study, Central Italy, Geomorphology, 31, 181–216, https://doi.org/10.1016/s0169-555x(99)00078-1, 1999.
He, Y. and Beighley, R. E.: GIS-based regional landslide susceptibility
mapping: a case study in southern California, Earth Surf. Proc.
Land., 33, 380–393, https://doi.org/10.1002/esp.1562, 2008.
Hu, K., Wei, F., and Li, Y.: Real-time measurement and preliminary analysis
of debris-flow impact force at Jiangjia Ravine, China, Earth Surf.
Proc. Land., 36, 1268–1278, https://doi.org/10.1002/esp.2155, 2011.
Hungr, O., McDougall, S., and Bovis, M.: Entrainment of material by debris
flows, in: Debris-flow Hazards and Related Phenomena, edited by: Jakob, M.
and Hungr, O., Springer, Berlin, Heidelberg, 135–158, ISBN 978-3-540-20726-9, 2005.
Iverson, R. M.: The physics of debris flows, Rev. Geophys., 35,
245–296, https://doi.org/10.1029/97RG00426, 1997.
Iverson, R. M., Reid, M. E., and LaHusen, R. G.: Debris-flow mobilization
from landslides, Annual Rev. Earth Pl. Sc., 25, 85–138, https://doi.org/10.1146/annurev.earth.25.1.85, 1997.
Kanungo, D. P., Arora, M. K., Sarkar, S., and Gupta, R. P.: A comparative
study of conventional, ANN black box, fuzzy and combined neural and fuzzy
weighting procedures for landslide susceptibility zonation in Darjeeling
Himalayas, Eng. Geol., 85, 347–366, https://doi.org/10.1016/j.enggeo.2006.03.004,
2006.
Kanungo, D. P., Arora, M., Sarkar, S., and Gupta, R.: A fuzzy set based
approach for integration of thematic maps for landslide susceptibility
zonation, Georisk, 3, 30–43, https://doi.org/10.1080/17499510802541417, 2009.
Kellogg, K. S.: Tectonic controls on a large landslide complex: Williams
Fork Mountains near Dillon, Colorado, Geomorphology, 41, 355–368, https://doi.org/10.1016/S0169-555X(01)00067-8, 2001.
Khan, U., Tuteja, N. K., and Sharma, A.: Delineating hydrologic response
units in large upland catchments and its evaluation using soil moisture
simulations, Environ. Modell. Softw., 46, 142–154, https://doi.org/10.1016/j.envsoft.2013.03.005, 2013.
Khan, U., Tuteja, N. K., Sharma, A., Lucas, S., Murphy, B., and Jenkins, B.:
Applicability of Hydrologic Response Units in low topographic relief
catchments and evaluation using high resolution aerial photograph analysis,
Environ. Modell. Softw., 81, 56–71, https://doi.org/10.1016/j.envsoft.2016.03.010, 2016.
Korup, O.: Geomorphic implications of fault zone weakening Slope instability
along the Alpine Fault South Westland to Fiordland, New Zeal. J.
Geol. Geop., 47, 257–267, https://doi.org/10.1080/00288306.2004.9515052, 2004.
Kritikos, T. and Davies, T.: Assessment of rainfall-generated shallow
landslide/debris-flow susceptibility and runout using a GIS-based approach:
application to western Southern Alps of New Zealand, Landslides, 12,
1051–1075, https://doi.org/10.1007/s10346-014-0533-6, 2015.
Kuo, Y., Yang, T., and Huang, G.-W.: The use of grey relational analysis in
solving multiple attribute decision-making problems, Comput.
Ind. Eng., 55, 80–93, https://doi.org/10.1016/j.cie.2007.12.002, 2008.
Lee, S.: Application and verification of fuzzy algebraic operators to
landslide susceptibility mapping, Environ. Geol., 52, 615–623, https://doi.org/10.1007/s00254-006-0491-y, 2006.
Lee, S. and Choi, J.: Landslide susceptibility mapping using GIS and the
weight-of-evidence model, Int. J. Geogr. Inf.
Sci., 18, 789–814, https://doi.org/10.1080/13658810410001702003, 2004.
Lee, S. and Sambath, T.: Landslide susceptibility mapping in the Damrei
Romel area, Cambodia using frequency ratio and logistic regression models,
Environ. Geol., 50, 847–855, https://doi.org/10.1007/s00254-006-0256-7, 2006.
Lee, S. and Talib, J. A.: Probabilistic landslide susceptibility and factor
effect analysis, Environ. Geol., 47, 982–990, https://doi.org/10.1007/s00254-005-1228-z, 2005.
Lee, S., Ryu, J.-H., Min, K., and Won, J.-S.: Landslide susceptibility
analysis using GIS and artificial neural network, Earth Surf. Proc.
Land., 28, 1361–1376, https://doi.org/10.1002/esp.593, 2003.
Li, Y., Chen, J., Zhang, Y., Song, S., Han, X., and Ammar, M.: Debris flow
susceptibility assessment and runout prediction: A case study in shiyang
gully, beijing, china, Int. J. Environ. Res., 14,
365–383, https://doi.org/10.1007/s41742-020-00263-4, 2020a.
Li, Y., Chen, J., Tan, C., Li, Y., Gu, F., Zhang, Y., and Mehmood, Q.:
Application of the borderline-SMOTE method in susceptibility assessments of
debris flows in Pinggu District, Beijing, China, Nat. Hazards, 105,
2499–2522, https://doi.org/10.1007/s11069-020-04409-7, 2020b.
Li, Y., Chen, J., Li, Z., Han, X., Zhai, S., Li, Y., and Zhang, Y.: A case
study of debris flow risk assessment and hazard range prediction based on a
neural network algorithm and finite volume shallow water flow model,
Environ. Earth Sci., 80, 275, https://doi.org/10.1007/s12665-021-09580-z, 2021.
Li, Z., Chen, J., Tan, C., Zhou, X., Li, Y., and Han, M.: Debris flow
susceptibility assessment based on topo-hydrological factors at different
unit scales: a case study of Mentougou district, Beijing, Environ.
Earth Sci., 80, 365, https://doi.org/10.1007/s12665-021-09665-9, 2021.
Liang, W.-J., Zhuang, D.-F., Jiang, D., Pan, J.-J., and Ren, H.-Y.:
Assessment of debris flow hazards using a Bayesian Network, Geomorphology,
171–172, 94–100, https://doi.org/10.1016/j.geomorph.2012.05.008, 2012.
Lin, C. L. and Lin, C. L.: The use of the orthogonal array with grey
relational analysis to optimize the electrical discharge machining process
with multiple performance characteristics, Int. J. Mach.
Tools Manu., 42, 237–244, https://doi.org/10.1016/S0890-6955(01)00107-9, 2002.
Liu, L. and Wang, S.: Fuzzy comprehensive evaluation on landslide and debris
flow risk degree in Zaotong, Yunnan, Mountain Research, 13, 261–266, 1995 (in Chinese).
Liu, S., Dang, Y., and Fang, Z.: Grey system theory and its applications,
Science Press, Beijing, ISBN 7-03-013351-X, 2004.
Liu, Y., Guo, H. C., Zou, R., and Wang, L. J.: Neural network modeling for
regional hazard assessment of debris flow in Lake Qionghai Watershed, China,
Environ. Geol., 49, 968–976, https://doi.org/10.1007/s00254-005-0135-7, 2005.
Lü, J., Wang, C., Liu, H., and Zhang, X.: Division of beijing geological
environment system, Urban Geol., 12, 19–25, https://doi.org/10.3969/j.issn.1007-1903.2017.03.004, 2017.
Luo, X. and Dimitrakopoulos, R.: Data-driven fuzzy analysis in quantitative
mineral resource assessment, Comput. Geosci., 29, 3–13, https://doi.org/10.1016/s0098-3004(02)00078-x, 2003.
Marjanović, M., Kovačević, M., Bajat, B., and
Voženílek, V.: Landslide susceptibility assessment using SVM
machine learning algorithm, Eng. Geol., 123, 225–234, https://doi.org/10.1016/j.enggeo.2011.09.006, 2011.
Melo, R., Vieira, G., Caselli, A., and Ramos, M.: Susceptibility modelling
of hummocky terrain distribution using the information value method
(Deception Island, Antarctic Peninsula), Geomorphology, 155–156, 88–95, https://doi.org/10.1016/j.geomorph.2011.12.027, 2012.
Meyer, N. K., Schwanghart, W., Korup, O., Romstad, B., and Etzelmüller,
B.: Estimating the topographic predictability of debris flows,
Geomorphology, 207, 114–125, https://doi.org/10.1016/j.geomorph.2013.10.030, 2014.
Ministry of Natural Resources of the People’s Republic of China: Specification of geological investigation for debris
flow stabilization (DZ/T0220-2006), Standards Press of China, https://www.docin.com/p-971592722.html (last access: 29 June 2022), ISBN 02202006, 2006.
Ohlmacher, G. C.: Plan curvature and landslide probability in regions
dominated by earth flows and earth slides, Eng. Geol., 91, 117–134, https://doi.org/10.1016/j.enggeo.2007.01.005, 2007.
Pierson, T. C., Janda, R. J., Thouret, J.-C., and Borrero, C. A.:
Perturbation and melting of snow and ice by the 13 November 1985 eruption of
Nevado del Ruiz, Colombia, and consequent mobilization, flow and deposition
of lahars, J. Volcanol. Geoth. Res., 41, 17–66, https://doi.org/10.1016/0377-0273(90)90082-q, 1990.
Porwal, A., Carranza, E. J. M., and Hale, M.: A Hybrid Fuzzy
Weights-of-Evidence Model for Mineral Potential Mapping, Natural Resources
Research, 15, 1–14, https://doi.org/10.1007/s11053-006-9012-7, 2006.
Pourghasemi, H. R., Yousefi, S., Kornejady, A., and Cerda, A.: Performance
assessment of individual and ensemble data-mining techniques for gully
erosion modeling, Sci. Total Environ., 609, 764–775, https://doi.org/10.1016/j.scitotenv.2017.07.198, 2017.
Pradhan, B.: Landslide susceptibility mapping of a catchment area using
frequency ratio, fuzzy logic and multivariate logistic regression
approaches, J. Indian Soc. Remote, 38, 301–320, https://doi.org/10.1007/s12524-010-0020-z, 2010.
Pradhan, B.: Manifestation of an advanced fuzzy logic model coupled with
Geo-information techniques to landslide susceptibility mapping and their
comparison with logistic regression modelling, Environ. Ecol.
Stat., 18, 471–493, https://doi.org/10.1007/s10651-010-0147-7, 2011a.
Pradhan, B.: Use of GIS-based fuzzy logic relations and its cross
application to produce landslide susceptibility maps in three test areas in
Malaysia, Environ. Earth Sci., 63, 329–349, https://doi.org/10.1007/s12665-010-0705-1, 2011b.
Regmi, N. R., Giardino, J. R., McDonald, E. V., and Vitek, J. D.: A
comparison of logistic regression-based models of susceptibility to
landslides in western Colorado, USA, Landslides, 11, 247–262, https://doi.org/10.1007/s10346-012-0380-2, 2013.
Remondo, J., González, A., Terán, J. R. D. D., Cendrero, A., Fabbri,
A., and Chung, C.-J. F.: Validation of landslide susceptibility maps;
examples and applications from a case study in northern spain, Nat.
Hazards, 30, 437–449, https://doi.org/10.1023/B:NHAZ.0000007201.80743.fc, 2003.
Roeloffs, E.: Poroelastic techniques in the study of earthquake-related
hydrologic phenomena, Adv. Geophys., 38, 135–195, https://doi.org/10.1016/S0065-2687(08)60270-8, 1996.
Ross, T. J.: Fuzzy logic with engineering applications, McGraw-Hill, New
York, ISBN 0-07-053917-0, 1995.
Selby, M. J.: Hillslope materials and processes, Oxford University Press,
Oxford, ISBN 0198741278, 1982.
Sun, X., Chen, J., Bao, Y., Han, X., Zhan, J., and Peng, W.: Landslide
Susceptibility Mapping Using Logistic Regression Analysis along the Jinsha
River and Its Tributaries Close to Derong and Deqin County, Southwestern
China, ISPRS Int. J. Geo-Inf., 7, 438, https://doi.org/10.3390/ijgi7110438, 2018.
Takahashi, T.: Debris flow mechanics,prediction and countermeasures, second,
Taylor & Francis/Balkema, the Netherlands, ISBN 9781138000070, 2014.
Tien Bui, D., Pradhan, B., Lofman, O., Revhaug, I., and Dick, O. B.:
Landslide susceptibility assessment in the Hoa Binh province of Vietnam: A
comparison of the Levenberg–Marquardt and Bayesian regularized neural
networks, Geomorphology, 171–172, 12–29, https://doi.org/10.1016/j.geomorph.2012.04.023,
2012.
Tsangaratos, P. and Ilia, I.: Landslide susceptibility mapping using a
modified decision tree classifier in the Xanthi Perfection, Greece,
Landslides, 13, 305–320, https://doi.org/10.1007/s10346-015-0565-6, 2015.
Tsukamoto, Y., Ohta, T., and Noguchi, H.: Hydrological and geomorphological
studies of debris slides on forested hillslopes in japan, Journal des
Sciences Hydrologiques, 27, 234, 1982.
Vallance, J. W. and Scott, K. M.: The Osceola mudflow from mount rainier:
Sedimentology and hazard implications of a huge clay-rich debris flow,
Geol. Soc. Am. Bull., 109, 143–163, https://doi.org/10.1130/0016-7606(1997)109<0143:TOMFMR>2.3.CO;2, 1997.
van Westen, C. J., Rengers, N., and Soeters, R.: Use of geomorphological
information in indirect landslide susceptibility assessment, Nat.
Hazards, 30, 399–419, https://doi.org/10.1023/B:NHAZ.0000007097.42735.9e, 2003.
Wang, J., Yu, Y., Yang, S., Lu, G.-H., and Ou, G.-Q.: A modified certainty
coefficient method (M-CF) for debris flow susceptibility assessment: A case
study for the Wenchuan earthquake meizoseismal areas, J. Mt.
Sci., 11, 1286–1297, https://doi.org/10.1007/s11629-013-2781-7, 2014.
Wei, Z., Shang, Y., Zhao, Y., Pan, P., and Jiang, Y.: Rainfall threshold for
initiation of channelized debris flows in a small catchment based on in-site
measurement, Eng. Geol., 217, 23–34, https://doi.org/10.1016/j.enggeo.2016.12.003,
2017.
Wu, S., Chen, J., Zhou, W., Iqbal, J., and Yao, L.: A modified Logit model
for assessment and validation of debris-flow susceptibility, B.
Eng. Geol. Environ., 78, 4421–4438, https://doi.org/10.1007/s10064-018-1412-5, 2019.
Wu, Y., Li, W., Liu, P., Bai, H., Wang, Q., He, J., Liu, Y., and Sun, S.:
Application of analytic hierarchy process model for landslide susceptibility
mapping in the Gangu County, Gansu Province, China, Environ. Earth
Sci., 75, 422, https://doi.org/10.1007/s12665-015-5194-9, 2016.
Xie, H., Zhong, D., Wei, F., and Wang, S.: Classification of debris flow in
the mountains of beijing, J. Mt. Sci., 22, 212–219, https://doi.org/10.16089/j.cnki.1008-2786.2004.02.013, 2004.
Zadeh, L. A.: Fuzzy sets, Information & Control, 8, 338–353, https://doi.org/10.1016/S0019-9958(65)90241-X, 1965.
Zhang, W., Li, H. Z., Chen, J. P., Zhang, C., Xu, L. M., and Sang, W. F.:
Comprehensive hazard assessment and protection of debris flows along Jinsha
River close to the Wudongde dam site in China, Nat. Hazards, 58, 459–477, https://doi.org/10.1007/s11069-010-9680-9, 2011.
Zhang, W., Chen, J.-P., Wang, Q., An, Y., Qian, X., Xiang, L., and He, L.:
Susceptibility analysis of large-scale debris flows based on combination
weighting and extension methods, Nat. Hazards, 66, 1073–1100, https://doi.org/10.1007/s11069-012-0539-0, 2013.
Zhang, Y., Chen, J., Tan, C., Bao, Y., Han, X., Yan, J., and Mehmood, Q.: A
novel approach to simulating debris flow runout via a three-dimensional CFD
code: a case study of Xiaojia Gully, B. Eng. Geol.
Environ., 80, 5293–5313, https://doi.org/10.1007/s10064-021-02270-x, 2021.
Zhong, D., Xie, H., Wang, S., Wei, F., and Jin, H.: Debris flow in Beijing
mountain, Commercial Press, Beijing, ISBN 7-100-04069-8,
2004.
Zou, Q., Cui, P., He, J., Lei, Y., and Li, S.: Regional risk assessment of
debris flows in China – An HRU-based approach, Geomorphology, 340, 84–102, https://doi.org/10.1016/j.geomorph.2019.04.027, 2019.
Short summary
The disaster prevention and mitigation of debris flow is a very important scientific problem. Our model is based on geographic information system (GIS), combined with grey relational, data-driven and fuzzy logic methods. Through our results, we believe that the streamlining of factors and scientific classification should attract attention from other researchers to optimize a model. We also propose a good perspective to make better use of the watershed feature parameters.
The disaster prevention and mitigation of debris flow is a very important scientific problem....
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