Articles | Volume 21, issue 5
https://doi.org/10.5194/nhess-21-1531-2021
© Author(s) 2021. 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-21-1531-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The role of geomorphology, rainfall and soil moisture in the occurrence of landslides triggered by 2018 Typhoon Mangkhut in the Philippines
College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4RJ, United Kingdom
Georgina L. Bennett
College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4RJ, United Kingdom
Adrian J. Matthews
Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences and School of Mathematics, University of East Anglia, Norwich, NR4 7TJ, United Kingdom
Mark Anthony M. Matera
School of Civil, Environmental and Geological Engineering, Mapúa University, Manila, Philippines
Fibor J. Tan
School of Civil, Environmental and Geological Engineering, Mapúa University, Manila, Philippines
Related authors
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.
C. Abancó, M. Hürlimann, and J. Moya
Nat. Hazards Earth Syst. Sci., 14, 929–943, https://doi.org/10.5194/nhess-14-929-2014, https://doi.org/10.5194/nhess-14-929-2014, 2014
Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024, https://doi.org/10.5194/hess-28-3099-2024, 2024
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This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
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This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Alessandro Sgarabotto, Irene Manzella, Kyle Roskilly, Miles J. Clark, Georgie L. Bennett, Chunbo Luo, and Aldina M. A. Franco
EGUsphere, https://doi.org/10.5194/egusphere-2023-2596, https://doi.org/10.5194/egusphere-2023-2596, 2023
Preprint archived
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Smart sensors have been installed in boulders embedded in landslides to monitor the movements and characterise their hazards. Here, we present laboratory experiments to investigate how to use smart sensors to describe the movements of a cobble down an inclined plane and transmit the recorded motion data via a wireless network. This study contributes to understanding how to make the best use of smart sensors to describe boulder motion and assess the practicalities of their use in field settings.
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.
Jack Giddings, Karen J. Heywood, Adrian J. Matthews, Manoj M. Joshi, Benjamin G. M. Webber, Alejandra Sanchez-Franks, Brian A. King, and Puthenveettil N. Vinayachandran
Ocean Sci., 17, 871–890, https://doi.org/10.5194/os-17-871-2021, https://doi.org/10.5194/os-17-871-2021, 2021
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Little is known about the impact of chlorophyll on SST in the Bay of Bengal (BoB). Solar irradiance measured by an ocean glider and three Argo floats is used to determine the effect of chlorophyll on BoB SST during the 2016 summer monsoon. The Southwest Monsoon Current has high chlorophyll concentrations (∼0.5 mg m−3) and shallow solar penetration depths (∼14 m). Ocean mixed layer model simulations show that SST increases by 0.35°C per month, with the potential to influence monsoon rainfall.
Benedetta Dini, Georgina L. Bennett, Aldina M. A. Franco, Michael R. Z. Whitworth, Kristen L. Cook, Andreas Senn, and John M. Reynolds
Earth Surf. Dynam., 9, 295–315, https://doi.org/10.5194/esurf-9-295-2021, https://doi.org/10.5194/esurf-9-295-2021, 2021
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We use long-range smart sensors connected to a network based on the Internet of Things to explore the possibility of detecting hazardous boulder movements in real time. Prior to the 2019 monsoon season we inserted the devices in 23 boulders spread over debris flow channels and a landslide in northeastern Nepal. The data obtained in this pilot study show the potential of this technology to be used in remote hazard-prone areas in future early warning systems.
Jack Giddings, Adrian J. Matthews, Nicholas P. Klingaman, Karen J. Heywood, Manoj Joshi, and Benjamin G. M. Webber
Weather Clim. Dynam., 1, 635–655, https://doi.org/10.5194/wcd-1-635-2020, https://doi.org/10.5194/wcd-1-635-2020, 2020
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The impact of chlorophyll on the southwest monsoon is unknown. Here, seasonally varying chlorophyll in the Bay of Bengal was imposed in a general circulation model coupled to an ocean mixed layer model. The SST increases by 0.5 °C in response to chlorophyll forcing and shallow mixed layer depths in coastal regions during the inter-monsoon. Precipitation increases significantly to 3 mm d-1 across Myanmar during June and over northeast India and Bangladesh during October, decreasing model bias.
Noah J. Finnegan, Kiara N. Broudy, Alexander L. Nereson, Joshua J. Roering, Alexander L. Handwerger, and Georgina Bennett
Earth Surf. Dynam., 7, 879–894, https://doi.org/10.5194/esurf-7-879-2019, https://doi.org/10.5194/esurf-7-879-2019, 2019
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In some settings, landslides trigger valley blockages that impound huge volumes of sediment, often drastically changing river habitat and habitability. In other settings, landslides appear to have little effect on rivers. In this study, we explore what governs the different sensitivity of rivers to blocking from landslide debris. We accomplish this by comparing two sites in California with dramatic differences in blocking from otherwise similar slow-moving landslides.
Venugopal Thushara, Puthenveettil Narayana Menon Vinayachandran, Adrian J. Matthews, Benjamin G. M. Webber, and Bastien Y. Queste
Biogeosciences, 16, 1447–1468, https://doi.org/10.5194/bg-16-1447-2019, https://doi.org/10.5194/bg-16-1447-2019, 2019
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Chlorophyll distribution in the ocean remains to be explored in detail, despite its climatic significance. Here, we document the vertical structure of chlorophyll in the Bay of Bengal using observations and a model. The shape of chlorophyll profiles, characterized by prominent deep chlorophyll maxima, varies in dynamically different regions, controlled by the monsoonal forcings. The present study provides new insights into the vertical distribution of chlorophyll, rarely observed by satellites.
C. Abancó, M. Hürlimann, and J. Moya
Nat. Hazards Earth Syst. Sci., 14, 929–943, https://doi.org/10.5194/nhess-14-929-2014, https://doi.org/10.5194/nhess-14-929-2014, 2014
Related subject area
Landslides and Debris Flows Hazards
An integrated method for assessing vulnerability of buildings caused by debris flows in mountainous areas
Identifying unrecognised risks to life from debris flows
Predicting the thickness of shallow landslides in Switzerland using machine learning
Unraveling landslide failure mechanisms with seismic signal analysis for enhanced pre-survey understanding
Comparison of conditioning factor classification criteria in large-scale statistically based landslide susceptibility models
Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems
Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer
Limit analysis of earthquake-induced landslides considering two strength envelopes
Brief communication: Visualizing uncertainties in landslide susceptibility modeling using bivariate mapping
The vulnerability of buildings to a large-scale debris flow and outburst flood hazard cascade that occurred on 30 August 2020 in Ganluo, southwest China
Optimizing rainfall-triggered landslide thresholds for daily landslide hazard warning in the Three Gorges Reservoir area
Brief communication: Monitoring impending slope failure with very high-resolution spaceborne synthetic aperture radar
Size scaling of large landslides from incomplete inventories
InSAR-informed in situ monitoring for deep-seated landslides: insights from El Forn (Andorra)
A coupled hydrological and hydrodynamic modeling approach for estimating rainfall thresholds of debris-flow occurrence
Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico
More than one landslide per road kilometer – surveying and modeling mass movements along the Rishikesh–Joshimath (NH-7) highway, Uttarakhand, India
Temporal clustering of precipitation for detection of potential landslides
Shallow-landslide stability evaluation in loess areas according to the Revised Infinite Slope Model: a case study of the 7.25 Tianshui sliding-flow landslide events of 2013 in the southwest of the Loess Plateau, China
From rockfall source areas identification to susceptibility zonation: a proposed workflow tested in El Hierro (Canary Islands, Spain)
Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall
Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA
A participatory approach to determine the use of road cut slope design guidelines in Nepal to lessen landslides
Addressing class imbalance in soil movement predictions
Assessing the impact of climate change on landslides near Vejle, Denmark, using public data
Analysis of three-dimensional slope stability combined with rainfall and earthquake
Assessing landslide damming susceptibility in Central Asia
Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico
Evaluation of debris-flow building damage forecasts
Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA
Morphological characteristics and conditions of drainage basins contributing to the formation of debris flow fans: an examination of regions with different rock strength using decision tree analysis
Characterizing the scale of regional landslide triggering from storm hydrometeorology
Comparison of debris flow observations, including fine-sediment grain size and composition and runout model results, at Illgraben, Swiss Alps
Simulation analysis of 3D stability of a landslide with a locking segment: a case study of the Tizicao landslide in Maoxian County, southwest China
Space–time landslide hazard modeling via Ensemble Neural Networks
Optimization strategy for flexible barrier structures: investigation and back analysis of a rockfall disaster case in southwestern China
Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment
Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
A new analytical method for stability analysis of rock blocks with basal erosion in sub-horizontal strata by considering the eccentricity effect
Rockfall monitoring with a Doppler radar on an active rockslide complex in Brienz/Brinzauls (Switzerland)
Landslide initiation thresholds in data-sparse regions: application to landslide early warning criteria in Sitka, Alaska, USA
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
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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
Chenchen Qiu and Xueyu Geng
Nat. Hazards Earth Syst. Sci., 25, 709–726, https://doi.org/10.5194/nhess-25-709-2025, https://doi.org/10.5194/nhess-25-709-2025, 2025
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We propose an integrated method using a combination of a physical vulnerability matrix and a machine learning model to estimate the potential physical damage and associated economic loss caused by future debris flows based on collected historical data on the Qinghai–Tibet Plateau region.
Mark Bloomberg, Tim Davies, Elena Moltchanova, Tom Robinson, and David Palmer
Nat. Hazards Earth Syst. Sci., 25, 647–656, https://doi.org/10.5194/nhess-25-647-2025, https://doi.org/10.5194/nhess-25-647-2025, 2025
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Debris flows occur infrequently, with average recurrence intervals (ARIs) ranging from decades to millennia. Consequently, they pose an underappreciated hazard. We describe how to make a preliminary identification of debris-flow-susceptible catchments, estimate threshold ARIs for debris flows that pose an unacceptable risk to life, and identify the “window of non-recognition” where debris flows are infrequent enough that their hazard is unrecognised yet frequent enough to pose a risk to life.
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci., 25, 467–491, https://doi.org/10.5194/nhess-25-467-2025, https://doi.org/10.5194/nhess-25-467-2025, 2025
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We developed a machine-learning-based approach to predict the potential thickness of shallow landslides to generate improved inputs for slope stability models. We selected 21 explanatory variables, including metrics on terrain, geomorphology, vegetation height, and lithology, and used data from two Swiss field inventories to calibrate and test the models. The best-performing machine learning model consistently reduced the mean average error by at least 20 % compared to previous models.
Jui-Ming Chang, Che-Ming Yang, Wei-An Chao, Chin-Shang Ku, Ming-Wan Huang, Tung-Chou Hsieh, and Chi-Yao Hung
Nat. Hazards Earth Syst. Sci., 25, 451–466, https://doi.org/10.5194/nhess-25-451-2025, https://doi.org/10.5194/nhess-25-451-2025, 2025
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The study on the Cilan landslide (CL) demonstrates the utilization of seismic analysis results as preliminary data for geologists during field surveys. Spectrograms revealed that the first event of CL consisted of four sliding failures accompanied by a gradual reduction in landslide volume. The second and third events were minor toppling and rockfalls. Then combining the seismological-based knowledge and field survey results, the spatiotemporal variation in landslide evolution is proposed.
Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, and Snježana Mihalić Arbanas
Nat. Hazards Earth Syst. Sci., 25, 183–206, https://doi.org/10.5194/nhess-25-183-2025, https://doi.org/10.5194/nhess-25-183-2025, 2025
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The paper focuses on classifying continuous landslide conditioning factors for susceptibility modelling, which resulted in 54 landslide susceptibility models that tested 11 classification criteria in combination with 5 statistical methods. The novelty of the research is that using stretched landslide conditioning factor values results in models with higher accuracy and that certain statistical methods are more sensitive to the landslide conditioning factor classification criteria than others.
Benjamin B. Mirus, Thom Bogaard, Roberto Greco, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 25, 169–182, https://doi.org/10.5194/nhess-25-169-2025, https://doi.org/10.5194/nhess-25-169-2025, 2025
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Early warning of increased landslide potential provides situational awareness to reduce landslide-related losses from major storm events. For decades, landslide forecasts relied on rainfall data alone, but recent research points to the value of hydrologic information for improving predictions. In this paper, we provide our perspectives on the value and limitations of integrating subsurface hillslope hydrologic monitoring data and mathematical modeling for more accurate landslide forecasts.
Jui-Sheng Chou, Hoang-Minh Nguyen, Huy-Phuong Phan, and Kuo-Lung Wang
Nat. Hazards Earth Syst. Sci., 25, 119–146, https://doi.org/10.5194/nhess-25-119-2025, https://doi.org/10.5194/nhess-25-119-2025, 2025
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This study enhances landslide prediction using advanced machine learning, including new algorithms inspired by historical explorations. The research accurately forecasts landslide movements by analyzing 8 years of data from Taiwan's Lushan, improving early warning and potentially saving lives and infrastructure. This integration marks a significant advancement in environmental risk management.
Di Wu, Yuke Wang, and Xin Chen
Nat. Hazards Earth Syst. Sci., 24, 4617–4630, https://doi.org/10.5194/nhess-24-4617-2024, https://doi.org/10.5194/nhess-24-4617-2024, 2024
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This paper proposes a 3D limit analysis for seismic stability of soil slopes to address the influence of earthquakes on slope stabilities with nonlinear and linear criteria. Comparison results illustrate that the use of a linear envelope leads to the non-negligible overestimation of steep-slope stability, and this overestimation will be significant with increasing earthquakes. Earthquakes have a smaller influence on slope slip surfaces with a nonlinear envelope than those with a linear envelope.
Matthias Schlögl, Anita Graser, Raphael Spiekermann, Jasmin Lampert, and Stefan Steger
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-213, https://doi.org/10.5194/nhess-2024-213, 2024
Revised manuscript accepted for NHESS
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Communicating uncertainties is a crucial yet challenging aspect of spatial modelling – especially in applied research, where results inform decisions. In disaster risk reduction, susceptibility maps for natural hazards guide planning and risk assessment, yet their uncertainties are often overlooked. We present a new type of landslide susceptibility map that visualizes both susceptibility and associated uncertainty, alongside guidelines for creating such maps using free and open-source software.
Li Wei, Kaiheng Hu, Shuang Liu, Lan Ning, Xiaopeng Zhang, Qiyuan Zhang, and Md. Abdur Rahim
Nat. Hazards Earth Syst. Sci., 24, 4179–4197, https://doi.org/10.5194/nhess-24-4179-2024, https://doi.org/10.5194/nhess-24-4179-2024, 2024
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The damage patterns of the buildings were classified into three types: (I) buried by primary debris flow, (II) inundated by secondary dam-burst flood, and (III) sequentially buried by debris flow and inundated by dam-burst flood. The threshold of the impact pressures in Zones (II) and (III) where vulnerability is equal to 1 is 84 kPa and 116 kPa, respectively. Heavy damage occurs at an impact pressure greater than 50 kPa, while slight damage occurs below 30 kPa.
Bo Peng and Xueling Wu
Nat. Hazards Earth Syst. Sci., 24, 3991–4013, https://doi.org/10.5194/nhess-24-3991-2024, https://doi.org/10.5194/nhess-24-3991-2024, 2024
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Our research enhances landslide prevention using advanced machine learning to forecast heavy-rainfall-triggered landslides. By analyzing regions and employing various models, we identified optimal ways to predict high-risk rainfall events. Integrating multiple factors and models, including a neural network, significantly improves landslide predictions. Real data validation confirms our approach's reliability, aiding communities in mitigating landslide impacts and safeguarding lives and property.
Andrea Manconi, Yves Bühler, Andreas Stoffel, Johan Gaume, Qiaoping Zhang, and Valentyn Tolpekin
Nat. Hazards Earth Syst. Sci., 24, 3833–3839, https://doi.org/10.5194/nhess-24-3833-2024, https://doi.org/10.5194/nhess-24-3833-2024, 2024
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Our research reveals the power of high-resolution satellite synthetic-aperture radar (SAR) imagery for slope deformation monitoring. Using ICEYE data over the Brienz/Brinzauls instability, we measured surface velocity and mapped the landslide event with unprecedented precision. This underscores the potential of satellite SAR for timely hazard assessment in remote regions and aiding disaster mitigation efforts effectively.
Oliver Korup, Lisa V. Luna, and Joaquin V. Ferrer
Nat. Hazards Earth Syst. Sci., 24, 3815–3832, https://doi.org/10.5194/nhess-24-3815-2024, https://doi.org/10.5194/nhess-24-3815-2024, 2024
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Catalogues of mapped landslides are useful for learning and forecasting how frequently they occur in relation to their size. Yet, rare and large landslides remain mostly uncertain in statistical summaries of these catalogues. We propose a single, consistent method of comparing across different data sources and find that landslide statistics disclose more about subjective mapping choices than trigger types or environmental settings.
Rachael Lau, Carolina Seguí, Tyler Waterman, Nathaniel Chaney, and Manolis Veveakis
Nat. Hazards Earth Syst. Sci., 24, 3651–3661, https://doi.org/10.5194/nhess-24-3651-2024, https://doi.org/10.5194/nhess-24-3651-2024, 2024
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This work examines the use of interferometric synthetic-aperture radar (InSAR) alongside in situ borehole measurements to assess the stability of deep-seated landslides for the case study of El Forn (Andorra). Comparing InSAR with borehole data suggests a key trade-off between accuracy and precision for various InSAR resolutions. Spatial interpolation with InSAR informed how many remote observations are necessary to lower error in a remote sensing re-creation of ground motion over the landslide.
Zhen Lei Wei, Yue Quan Shang, Qiu Hua Liang, and Xi Lin Xia
Nat. Hazards Earth Syst. Sci., 24, 3357–3379, https://doi.org/10.5194/nhess-24-3357-2024, https://doi.org/10.5194/nhess-24-3357-2024, 2024
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The initiation of debris flows is significantly influenced by rainfall-induced hydrological processes. We propose a novel framework based on an integrated hydrological and hydrodynamic model and aimed at estimating intensity–duration (ID) rainfall thresholds responsible for triggering debris flows. In comparison to traditional statistical approaches, this physically based framework is particularly suitable for application in ungauged catchments where historical debris flow data are scarce.
Dianne L. Brien, Mark E. Reid, Collin Cronkite-Ratcliff, and Jonathan P. Perkins
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-141, https://doi.org/10.5194/nhess-2024-141, 2024
Revised manuscript accepted for NHESS
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Landslide runout zones are the areas downslope or downstream of landslide initiation. People often live and work in these areas, leading to property damage and deaths. We develop methods to identify potential runout zones from landslides. We apply our methods to create susceptibility maps for three study areas in Puerto Rico and assess the success of our methods based on mapped landslides from Hurricane Maria.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024, https://doi.org/10.5194/nhess-24-3207-2024, 2024
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The Himalayan road network links remote areas, but fragile terrain and poor construction lead to frequent landslides. This study on the NH-7 in India's Uttarakhand region analyzed 300 landslides after heavy rainfall in 2022 . Factors like slope, rainfall, rock type and road work influence landslides. The study's model predicts landslide locations for better road maintenance planning, highlighting the risk from climate change and increased road use.
Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 24, 2689–2704, https://doi.org/10.5194/nhess-24-2689-2024, https://doi.org/10.5194/nhess-24-2689-2024, 2024
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Landslides are complex phenomena causing important impacts in vulnerable areas, and they are often triggered by rainfall. Here, we develop a new approach that uses information on the temporal clustering of rainfall, i.e. multiple events close in time, to detect landslide events and compare it with the use of classical empirical rainfall thresholds, considering as a case study the region of Lisbon, Portugal. The results could help to improve the prediction of rainfall-triggered landslides.
Jianqi Zhuang, Jianbing Peng, Chenhui Du, Yi Zhu, and Jiaxu Kong
Nat. Hazards Earth Syst. Sci., 24, 2615–2631, https://doi.org/10.5194/nhess-24-2615-2024, https://doi.org/10.5194/nhess-24-2615-2024, 2024
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The Revised Infinite Slope Model (RISM) is proposed using the equal differential unit method and correcting the deficiency of the safety factor increasing with the slope increasing when the slope is larger than 40°, as calculated using the Taylor slope infinite model. The intensity–duration (I–D) prediction curve of the rainfall-induced shallow loess landslides with different slopes was constructed and can be used in forecasting regional shallow loess landslides.
Roberto Sarro, Mauro Rossi, Paola Reichenbach, and Rosa María Mateos
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-85, https://doi.org/10.5194/nhess-2024-85, 2024
Revised manuscript accepted for NHESS
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This study proposes a novel workflow to precisely model rockfalls. It compares three methods for defining source areas to enhance model accuracy. Identified areas are inputted into a runout model to identify vulnerable zones. A new approach generates probabilistic susceptibility maps using ECDFs. Validation strategies employing various inventory types are included. Comparing six susceptibility maps highlights the impact of source area definition on model precision.
Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley
Nat. Hazards Earth Syst. Sci., 24, 2359–2374, https://doi.org/10.5194/nhess-24-2359-2024, https://doi.org/10.5194/nhess-24-2359-2024, 2024
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Fire can dramatically increase the risk of debris flows to downstream communities with little warning, but hazard assessments have not traditionally included estimates of inundation. We unify models developed by the scientific community to create probabilistic estimates of inundation area in response to rainfall at forecast lead times (≥ 24 h) needed for decision-making. This work takes an initial step toward a near-real-time postfire debris-flow inundation hazard assessment product.
Francis K. Rengers, Samuel Bower, Andrew Knapp, Jason W. Kean, Danielle W. vonLembke, Matthew A. Thomas, Jaime Kostelnik, Katherine R. Barnhart, Matthew Bethel, Joseph E. Gartner, Madeline Hille, Dennis M. Staley, Justin K. Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgway, and Brendan P. Murphy
Nat. Hazards Earth Syst. Sci., 24, 2093–2114, https://doi.org/10.5194/nhess-24-2093-2024, https://doi.org/10.5194/nhess-24-2093-2024, 2024
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Every year the U.S. Geological Survey produces 50–100 postfire debris-flow hazard assessments using models for debris-flow likelihood and volume. To refine these models they must be tested with datasets that clearly document rainfall, debris-flow response, and debris-flow volume. These datasets are difficult to obtain, but this study developed and analyzed a postfire dataset with more than 100 postfire storm responses over a 2-year period. We also proposed ways to improve these models.
Ellen B. Robson, Bhim Kumar Dahal, and David G. Toll
EGUsphere, https://doi.org/10.5194/egusphere-2024-1300, https://doi.org/10.5194/egusphere-2024-1300, 2024
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Slopes excavated alongside roads in Nepal frequently fail (a landslide), resulting in substantial losses. Our participatory approach study involving road engineers aimed to assess the efficacy of the current slope design guidelines in Nepal. Our study revealed inconsistent guideline adherence due to their lack of user-friendliness and inadequate training. We recommend developing simpler, context-specific guidelines and comprehensive training to enhance resilience in Nepal's road network.
Praveen Kumar, Priyanka Priyanka, Kala Venkata Uday, and Varun Dutt
Nat. Hazards Earth Syst. Sci., 24, 1913–1928, https://doi.org/10.5194/nhess-24-1913-2024, https://doi.org/10.5194/nhess-24-1913-2024, 2024
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Our study focuses on predicting soil movement to mitigate landslide risks. We develop machine learning models with oversampling techniques to address the class imbalance in monitoring data. The dynamic ensemble model with K-means SMOTE (synthetic minority oversampling technique) achieves high precision, high recall, and a high F1 score. Our findings highlight the potential of these models with oversampling techniques to improve soil movement predictions in landslide-prone areas.
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci., 24, 1897–1911, https://doi.org/10.5194/nhess-24-1897-2024, https://doi.org/10.5194/nhess-24-1897-2024, 2024
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In our study, we analysed publicly available data in order to investigate the impact of climate change on landslides in Denmark. Our research indicates that the rising groundwater table due to climate change will result in an increase in landslide activity. Previous incidents of extremely wet winters have caused damage to infrastructure and buildings due to landslides. This study is the first of its kind to exclusively rely on public data and examine landslides in Denmark.
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024, https://doi.org/10.5194/nhess-24-1741-2024, 2024
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With a simplified formula linking rainfall and groundwater level, the rise of the phreatic surface within the slope can be obtained. Then, a global analysis method that considers both seepage and seismic forces is proposed to determine the safety factor of slopes subjected to the combined effect of rainfall and earthquakes. By taking a slope in the Three Gorges Reservoir area as an example, the safety evolution of the slope combined with both rainfall and earthquake is also examined.
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024, https://doi.org/10.5194/nhess-24-1697-2024, 2024
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Central Asia regions are marked by active tectonics, high mountains with glaciers, and strong rainfall. These predisposing factors make large landslides a serious threat in the area and a source of possible damming scenarios, which endanger the population. To prevent this, a semi-automated geographic information system (GIS-)based mapping method, centered on a bivariate correlation of morphometric parameters, was applied to give preliminary information on damming susceptibility in Central Asia.
Rex L. Baum, Dianne L. Brien, Mark E. Reid, William H. Schulz, and Matthew J. Tello
Nat. Hazards Earth Syst. Sci., 24, 1579–1605, https://doi.org/10.5194/nhess-24-1579-2024, https://doi.org/10.5194/nhess-24-1579-2024, 2024
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We mapped potential for heavy rainfall to cause landslides in part of the central mountains of Puerto Rico using new tools for estimating soil depth and quasi-3D slope stability. Potential ground-failure locations correlate well with the spatial density of landslides from Hurricane Maria. The smooth boundaries of the very high and high ground-failure susceptibility zones enclose 75 % and 90 %, respectively, of observed landslides. The maps can help mitigate ground-failure hazards.
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 24, 1459–1483, https://doi.org/10.5194/nhess-24-1459-2024, https://doi.org/10.5194/nhess-24-1459-2024, 2024
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Debris flows are a type of fast-moving landslide that start from shallow landslides or during intense rain. Infrastructure located downstream of watersheds susceptible to debris flows may be damaged should a debris flow reach them. We present and evaluate an approach to forecast building damage caused by debris flows. We test three alternative models for simulating the motion of debris flows and find that only one can forecast the correct number and spatial pattern of damaged buildings.
Luke A. McGuire, Francis K. Rengers, Ann M. Youberg, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Ryan Porter
Nat. Hazards Earth Syst. Sci., 24, 1357–1379, https://doi.org/10.5194/nhess-24-1357-2024, https://doi.org/10.5194/nhess-24-1357-2024, 2024
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Runoff and erosion increase after fire, leading to a greater likelihood of floods and debris flows. We monitored debris flow activity following a fire in western New Mexico, USA, and observed 16 debris flows over a <2-year monitoring period. Rainstorms with recurrence intervals of approximately 1 year were sufficient to initiate debris flows. All debris flows initiated during the first several months following the fire, indicating a rapid decrease in debris flow susceptibility over time.
Ken'ichi Koshimizu, Satoshi Ishimaru, Fumitoshi Imaizumi, and Gentaro Kawakami
Nat. Hazards Earth Syst. Sci., 24, 1287–1301, https://doi.org/10.5194/nhess-24-1287-2024, https://doi.org/10.5194/nhess-24-1287-2024, 2024
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Morphological conditions of drainage basins that classify the presence or absence of debris flow fans were analyzed in areas with different rock strength using decision tree analysis. The relief ratio is the most important morphological factor regardless of the geology. However, the thresholds of morphological parameters needed for forming debris flow fans differ depending on the geology. Decision tree analysis is an effective tool for evaluating the debris flow risk for each geology.
Jonathan P. Perkins, Nina S. Oakley, Brian D. Collins, Skye C. Corbett, and W. Paul Burgess
EGUsphere, https://doi.org/10.5194/egusphere-2024-873, https://doi.org/10.5194/egusphere-2024-873, 2024
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Landslides are a global issue that results in deaths and economic losses annually. However, it is not clear how storm severity relates to landslide severity across large regions. Here we develop a method to estimate the footprint of landslide area and compare this to meteorologic estimates of storm severity. We find that total storm strength does not clearly relate to landslide area. Rather, landslide area depends on soil wetness and smaller storm structures that can produce intense rainfall.
Daniel Bolliger, Fritz Schlunegger, and Brian W. McArdell
Nat. Hazards Earth Syst. Sci., 24, 1035–1049, https://doi.org/10.5194/nhess-24-1035-2024, https://doi.org/10.5194/nhess-24-1035-2024, 2024
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We analysed data from the Illgraben debris flow monitoring station, Switzerland, and we modelled these flows with a debris flow runout model. We found that no correlation exists between the grain size distribution, the mineralogical composition of the matrix, and the debris flow properties. The flow properties rather appear to be determined by the flow volume, from which most other parameters can be derived.
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
Nat. Hazards Earth Syst. Sci., 24, 891–906, https://doi.org/10.5194/nhess-24-891-2024, https://doi.org/10.5194/nhess-24-891-2024, 2024
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We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide and found that the contact surface model with high strength parameters combines advantages of the intact rock mass model in simulating the deformation of slopes with rock bridges and the modeling advantage of the Jennings model. The results help in choosing a rock bridge model to simulate landslide stability and reveal the influence laws of rock bridges on the stability of landslides.
Ashok Dahal, Hakan Tanyas, Cees van Westen, Mark van der Meijde, Paul Martin Mai, Raphaël Huser, and Luigi Lombardo
Nat. Hazards Earth Syst. Sci., 24, 823–845, https://doi.org/10.5194/nhess-24-823-2024, https://doi.org/10.5194/nhess-24-823-2024, 2024
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We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
Li-Ru Luo, Zhi-Xiang Yu, Li-Jun Zhang, Qi Wang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci., 24, 631–649, https://doi.org/10.5194/nhess-24-631-2024, https://doi.org/10.5194/nhess-24-631-2024, 2024
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We performed field investigations on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was obtained from an unmanned aerial vehicle survey. A finite element model was created to reproduce the damage evolution. We found that the impact kinetic energy was below the design protection energy. Improper member connections prevent the barrier from producing significant deformation to absorb energy. Damage is avoided by improving the ability of the nets and ropes to slide.
Sudhanshu Dixit, Srikrishnan Siva Subramanian, Piyush Srivastava, Ali P. Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci., 24, 465–480, https://doi.org/10.5194/nhess-24-465-2024, https://doi.org/10.5194/nhess-24-465-2024, 2024
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Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards. Large-scale sediment disasters like landslides, debris flows, and flash floods happen frequently in the Himalayas because of their propensity for intense precipitation events. We provide a new framework that combines the Weather Research and Forecasting (WRF) model with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, https://doi.org/10.5194/nhess-24-1-2024, 2024
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Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
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The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
Xushan Shi, Bo Chai, Juan Du, Wei Wang, and Bo Liu
Nat. Hazards Earth Syst. Sci., 23, 3425–3443, https://doi.org/10.5194/nhess-23-3425-2023, https://doi.org/10.5194/nhess-23-3425-2023, 2023
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A 3D stability analysis method is proposed for biased rockfall with external erosion. Four failure modes are considered according to rockfall evolution processes, including partial damage of underlying soft rock and overall failure of hard rock blocks. This method is validated with the biased rockfalls in the Sichuan Basin, China. The critical retreat ratio from low to moderate rockfall susceptibility is 0.33. This method could facilitate rockfall early identification and risk mitigation.
Marius Schneider, Nicolas Oestreicher, Thomas Ehrat, and Simon Loew
Nat. Hazards Earth Syst. Sci., 23, 3337–3354, https://doi.org/10.5194/nhess-23-3337-2023, https://doi.org/10.5194/nhess-23-3337-2023, 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 has operated since 2018 at a high frequency under all illumination and weather conditions at a site where frequent rockfall events threaten a village and road. The new data set is used to investigate rockfall triggers in an active rockslide complex.
Annette I. Patton, Lisa V. Luna, Joshua J. Roering, Aaron Jacobs, Oliver Korup, and Benjamin B. Mirus
Nat. Hazards Earth Syst. Sci., 23, 3261–3284, https://doi.org/10.5194/nhess-23-3261-2023, https://doi.org/10.5194/nhess-23-3261-2023, 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 to predicting landslides and demonstrate that even a small landslide inventory (five storms) can be used to train useful models for landslide early warning when non-landslide events are also included.
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.
Cited articles
Abancó, C., Hürlimann, M., Moya, J., and Berenguer, M.: Critical rainfall conditions for the initiation of torrential flows. Results from the Rebaixader catchment (Central Pyrenees), J. Hydrol., 541, 218–229, https://doi.org/10.1016/j.jhydrol.2016.01.019, 2016.
Abancó, C., Bennett, G., Briant, J., and Battiston, S.: Towards an automatic landslide mapping tool based on satellite imagery and geomorphological parameters. A study of the Itogon area (Philippines) after Typhoon Mangkhut, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17940, https://doi.org/10.5194/egusphere-egu2020-17940, 2020.
Aleotti, P. and Chowdhury, R.: Landslide hazard assessment: summary review and new perspectives, B. Eng. Geol. Environ., 58, 21–44, https://doi.org/10.1007/s100640050066, 1999.
Alvioli, M. ,Mondini, A. C. , Fiorucci, F. , Cardinali, M., Marchesini, I.: Topography-driven satellite imagery analysis for landslide mapping, Geomatics, Natural Hazards and Risk, 9, 544–567, https://doi.org/10.1080/19475705.2018.1458050, 2018a.
Alvioli, M., Melillo, M., Guzzetti, F., Rossi, M., Palazzi, E., von Hardenberg, J., Brunetti, M. T., and Peruccacci, S.: Implications of climate change on landslide hazard in Central Italy, Sci. Total Environ., 630, 1528–1543, https://doi.org/10.1016/j.scitotenv.2018.02.315, 2018b.
Arboleda, R., Martinez, M., Newhall, C., and Punongbayan, R.: 1992 lahars in the Pasig-Potrero river system, in: Fire and mud: eruptions and lahars of Mount Pinatubo, edited by: Newhall, C. G. and Punongbayan, R. S.,
Philippine Institute of Volcanology and Seismology, University of Washington Press, Seattle and London, 1996.
Bellon, H. and Yumul, G. P.: Mio-Pliocene magmatism in the Baguio mining district (Luzon, Philippines): Age clues to its geodynamic setting, CR Acad. Sci. II A, 331, 295–302, https://doi.org/10.1016/S1251-8050(00)01415-4, 2000.
Bennett, G. L., Molnar, P., Eisenbeiss, H., and McArdell, B. W.: Erosional power in the Swiss Alps: characterization of slope failure in the Illgraben, Earth Surf. Processes, 37, 1627–1640, https://doi.org/10.1002/esp.3263, 2012.
Bogaard, T. A. and van Asch, T. W. J.: The role of the soil moisture balance in the unsaturated zone on movement and stability of the Beline landslide, France, Earth Surf. Processes, 27, 1177–1188, https://doi.org/10.1002/esp.419, 2002.
Borghuis, A. M., Chang, K., and Lee, H. Y.: Comparison between automated and manual mapping of typhoon-triggered landslides from SPOT-5 imagery, Int. J. Remote Sens., 28, 1843–1856, https://doi.org/10.1080/01431160600935638, 2007.
Brunetti, M. T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., and Guzzetti, F.: Rainfall thresholds for the possible occurrence of landslides in Italy, Nat. Hazards Earth Syst. Sci., 10, 447–458, https://doi.org/10.5194/nhess-10-447-2010, 2010.
Brunetti, M. T., Melillo, M., Peruccacci, S., Ciabatta, L., and Brocca, L.: How far are we from the use of satellite rainfall products in landslide forecasting?, Remote Sens. Environ., 210, 65–75, https://doi.org/10.1016/j.rse.2018.03.016, 2018.
Bureau of Soils and Water Management, Soil Type Map, available at: https://www.geoportal.gov.ph/ (last acces: 15 April 2020), 2012.
Caine, N.: The Rainfall Intensity: Duration Control of Shallow Landslides and Debris Flows, Geogr. Ann. A, 62, 23–27, http://www.jstor.org/stable/520449 (last access: 15 July 2020), 1980.
Carating, R. B., Galanta, R. G., and Bacatio, C. D.: The Soils of the Philippines, Springer Netherlands, Dordrecht, 2014.
Cawis, R. M. M.: Itogon to commemorate “Ompong” tragedy anniversary with rituals, available at: https://pia.gov.ph/news/articles/1027251 (last access: 24 June 2020), 2019.
Chen, Y. C., Chang, K. T., Chiu, Y. J., Lau, S. M., and Lee, H. Y.: Quantifying rainfall controls on catchment-scale landslide erosion in Taiwan, Earth Surf. Processes, 38, 372–382, https://doi.org/10.1002/esp.3284, 2013.
Chen, Y. C., Chang, K. T., Wang, S. F., Huang, J. C., Yu, C. K., Tu, J. Y., Chu, H. J., and Liu, C. C.: Controls of preferential orientation of earthquake- and rainfall-triggered landslides in Taiwan's orogenic mountain belt, Earth Surf. Processes, 44, 1661–1674, https://doi.org/10.1002/esp.4601, 2019.
Chien-Yuan, C., Fan-Chieh, Y., Sheng-Chi, L., and Kei-Wai, C.: Discussion of landslide self-organized criticality and the initiation of debris flow, Earth Surf. Processes, 32, 197–209, 2006.
Clauset, A., Shalizi, C. R., and Newman, M. E. J.: Power-law distributions in empirical data, SIAM Rev., 51, 661–703, https://doi.org/10.1137/070710111, 2009.
Corominas, J., van Westen, C., Frattini, P., Cascini, L., Malet, J.-P., Fotopoulou, S., Catani, F., Van Den Eeckhaut, M., Mavrouli, O., Agliardi, F., Pitilakis, K., Winter, M. G., Pastor, M., Ferlisi, S., Tofani, V., Hervás, J., and Smith, J. T.: Recommendations for the quantitative analysis of landslide risk, B. Eng. Geol. Environ., 73, 209–263, https://doi.org/10.1007/s10064-013-0538-8, 2014.
Crosta, G. B. and Dal Negro, P.: Observations and modelling of soil slip-debris flow initiation processes in pyroclastic deposits: the Sarno 1998 event, Nat. Hazards Earth Syst. Sci., 3, 53–69, https://doi.org/10.5194/nhess-3-53-2003, 2003.
Crozier, M. J.: Multiple-occurrence regional landslide events in New Zealand: hazard management issues, Landslides, 2, 247–256, https://doi.org/10.1007/s10346-005-0019-7, 2005.
Crozier, M. J.: A proposed cell model for multiple-occurrence regional landslide events: Implications for landslide susceptibility mapping, Geomorphology, 295, 480–488, https://doi.org/10.1016/j.geomorph.2017.07.032, 2017.
de Lima, J. L. M. P.: The effect of oblique rain on inclined surfaces: A nomograph for the rain-gauge correction factor, J. Hydrol., 115, 407–412, https://doi.org/10.1016/0022-1694(90)90218-M, 1990.
Department of Environment and Natural Resources-Mines and Geosciences Bureau (DENR-MGB): Geological Map of Baguio City Quadrangle (1:50 000), Sheet 3169 III, Quezon City, Philippines, 1995.
Department of Environment and Natural Resources-National Mapping and Resource Information Authority (DENR-NAMRIA): Land Cover Map, Taguig City, Philippines, 2010.
Department of Environment and Natural Resources-National Mapping and Resource Information Authority (DENR-NAMRIA): Interferometric Synthetic Aperture Radar-Digital Elevation Models (IfSAR-DEMs), Taguig City, Philippines, 2013.
Department of Science and Technology-Philippine Atmospheric, Geophysical and Astronomical Services Administration (DOST-PAGASA): Climate Map of the
Philippines (1951–2010), Quezon City, Philippines, 2014.
De Vita, P., Reichenbach, P., Bathurst, J. C., Borga, M., Crosta, G., Crozier, M. J., Glade, T., Guzzetti, F., Hansen, A., and Wasowski, J.: Rainfall-triggered landslides: a reference list, Environ. Geol., 35, 219–233, 1998.
Del Ventisette, C., Righini, G., Moretti, S., and Casagli, N.: Multitemporal landslides inventory map updating using spaceborne SAR analysis, Int. J. Appl. Earth Obs., 30, 238–246, https://doi.org/10.1016/j.jag.2014.02.008, 2014.
Environmental Information Data Centre: https://eidc.ac.uk/, last access: 12 May 2021.
ESRI: ArcGIS Desktop version 10.6.1 user guide, Redlands, CA, Environmental Systems Research Institute, 2018.
Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., and Savage, W. Z. (on behalf of the JTC-1 Joint Technical Committee on Landslides): Guidelines for landslide susceptibility, hazard and risk zoning for land use planning, Eng. Geol., 102, 99–111, 2008.
Godt, J. W., Baum, R. L., Savage, W. Z., Salciarini, D., Schulz, W. H., and Harp, E. L.: Transient deterministic shallow landslide modeling: Requirements for susceptibility and hazard assessments in a GIS framework, Eng. Geol., 102, 214–226, 2008.
Gorum, T., van Westen, C. J., Korup, O., van der Meijde, M., Fan, X., and van der Meer, F. D.: Complex rupture mechanism and topography control symmetry of mass-wasting pattern, 2010 Haiti earthquake, Geomorphology, 184, 127–138, https://doi.org/10.1016/j.geomorph.2012.11.027, 2013.
Guzzetti, F., Reichenbach, P., Cardinali, M., Galli, M., and Ardizzone, F.: Probabilistic landslide hazard assessment at the basin scale, Geomorphology, 72, 272–299, 2005.
Guzzetti, F., Galli, M., Reichenbach, P., Ardizzone, F., and Cardinali, M.: Landslide hazard assessment in the Collazzone area, Umbria, Central Italy, Nat. Hazards Earth Syst. Sci., 6, 115–131, https://doi.org/10.5194/nhess-6-115-2006, 2006.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol. Atmos. Phys., 98, 239–267, https://doi.org/10.1007/s00703-007-0262-7, 2007.
Guzzetti, F., Mondini, A. C., Cardinali, M., Fiorucci, F., Santangelo, M., and Chang, K. T.: Landslide inventory maps: New tools for an old problem, Earth-Sci. Rev., 112, 42–66, https://doi.org/10.1016/j.earscirev.2012.02.001, 2012.
Guzzetti, F., Gariano, S. L., Peruccacci, S., Brunetti, M. T., Marchesini, I., Rossi, M., and Melillo, M.: Geographical landslide early warning systems, Earth-Sci. Rev., 200, 102973, https://doi.org/10.1016/j.earscirev.2019.102973, 2020.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hidayat, R., Sutanto, S. J., Hidayah, A., Ridwan, B., and Mulyana, A.: Development of a landslide early warning system in Indonesia, Geosciences, 9, 1–17, https://doi.org/10.3390/geosciences9100451, 2019.
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., and Jarvis, A.: Very high resolution interpolated climate surfaces for global land areas, Int. J. Climatol., 25, 1965–1978, https://doi.org/10.1002/joc.1276, 2005.
Hough, B. K.: Basic soils engineering, Ronald Press Co., New York, 1969.
Huffman, G. J., Stocker, E. F., Bolvin, D. T., Nelkin, E. J., and Tan, J.: GPM IMERG final precipitation L3 half hourly 0.1 degree × 0.1 degree V06. Goddard Earth Sciences Data and Information Services Center, https://doi.org/10.5067/GPM/IMERG/3B-HH/06, 2019.
Khan, M. A., Hossain, M. S., Khan, M. S., Samir, S., and Aramoon, A.: Impact of wet-dry cycles on the shear strength of high plastic clay based on direct shear testing, Geotechnical Frontiers, 280, 615–622, https://doi.org/10.1061/9780784480472.065, 2017.
Khan, S., Ivoke, J., and Nobahar, M.: Coupled effect of wet-dry cycles and rainfall on highway slope made of yazoo clay, Geosciences, 9, 341, https://doi.org/10.3390/geosciences9080341, 2019.
Kirschbaum, D. and Stanley, T.: Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness, Earth's Future, 6, 505–523, https://doi.org/10.1002/2017EF000715, 2018.
Kirschbaum, D., Stanley, T., and Zhou, Y.: Spatial and temporal analysis of a global landslide catalog, Geomorphology, 249, 4–15, https://doi.org/10.1016/j.geomorph.2015.03.016, 2015.
Krøgli, I. K., Devoli, G., Colleuille, H., Boje, S., Sund, M., and Engen, I. K.: The Norwegian forecasting and warning service for rainfall- and snowmelt-induced landslides, Nat. Hazards Earth Syst. Sci., 18, 1427–1450, https://doi.org/10.5194/nhess-18-1427-2018, 2018.
Lagmay, A. M. F., Racoma, B. A., Aracan, K. A., Alconis-Ayco, J., and Saddi, I. L.: Disseminating near-real-time hazards information and flood maps in the Philippines through Web-GIS, J. Environ. Sci., 59, 13–23, https://doi.org/10.1016/j.jes.2017.03.014, 2017.
Leonarduzzi, E. and Molnar, P.: Deriving rainfall thresholds for landsliding at the regional scale: daily and hourly resolutions, normalisation, and antecedent rainfall, Nat. Hazards Earth Syst. Sci., 20, 2905–2919, https://doi.org/10.5194/nhess-20-2905-2020, 2020.
Li, W. le, Huang, R. qiu, Xu, Q., and Tang, C.: Rapid susceptibility mapping of co-seismic landslides triggered by the 2013 Lushan Earthquake using the regression model developed for the 2008 Wenchuan Earthquake, J. Mt. Sci., 10, 699–715, https://doi.org/10.1007/s11629-013-2786-2, 2013.
Liao, Z., Hong, Y., Wang, J., Fukuoka, H., Sassa, K., Karnawati, D., and Fathani, F.: Prototyping an experimental early warning system for rainfall-induced landslides in Indonesia using satellite remote sensing and geospatial datasets, Landslides, 7, 317–324, https://doi.org/10.1007/s10346-010-0219-7, 2010.
Lin, G. W. and Chen, H.: The relationship of rainfall energy with landslides and sediment delivery, Eng. Geol., 125, 108–118, https://doi.org/10.1016/j.enggeo.2011.11.010, 2012.
Liu, J. K. and Shih, P. T. Y.: Topographic correction of Wind-Driven rainfall for landslide analysis in central Taiwan with validation from Aerial and satellite optical images, Remote Sens., 5, 2571–2589, https://doi.org/10.3390/rs5062571, 2013.
Luigi, S., Massimo, G., Silvia, M., and Brunetti, M. T.: How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering?, Nat. Hazards, 100, 655–670, https://doi.org/10.1007/s11069-019-03830-x, 2020.
Malamud, B. D., Turcotte, D. L., Guzzetti, F., and Reichenbach, P.: Landslide inventories and their statistical properties, Earth Surf. Processes, 29, 687–711, https://doi.org/10.1002/esp.1064, 2004.
Marino, P., Peres, D. J., Cancelliere, A., Greco, R., and Bogaard, T. A.: Soil moisture information can improve shallow landslide forecasting using the hydrometeorological threshold approach, Landslides, 17, 2041–2054, https://doi.org/10.1007/s10346-020-01420-8, 2020.
Martinis, S.: EO Tools and Products – Specifications (HEIMDALL project Deliverable 5.1), available at: https://heimdall-h2020.eu/public-deliverables/
(last access: 15 July 2020), 2018.
Martino, S., Antonielli, B., Bozzano, F., Caprari, P., Discenza, M. E., Esposito, C., Fiorucci, M., Iannucci, R., Marmoni, G. M., and Schilirò, L.: Landslides triggered after the 16 August 2018 Mw 5.1 Molise earthquake (Italy) by a combination of intense rainfalls and seismic shaking, Landslides, 17, 1177–1190, https://doi.org/10.1007/s10346-020-01359-w, 2020.
Mazzoglio, P., Laio, F., Balbo, S., Boccardo, P., and Disabato, F.: Improving an Extreme Rainfall Detection System with GPM IMERG data, Remote Sens., 11, 677, https://doi.org/10.3390/rs11060677, 2019.
Melillo, M., Brunetti, M. T., Peruccacci, S., Gariano, S. L., and Guzzetti, F.: An algorithm for the objective reconstruction of rainfall events responsible for landslides, Landslides, 12, 311–320, https://doi.org/10.1007/s10346-014-0471-3, 2014.
Mines and Geosciences Bureau: Report on the Result of the Geohazard Assessments in the Small Scale Mining Areas in the Municipality of Itogon, Benguet Province Re: Rain-Induced Landslide Incidents due to Typhoon Ompong., Quezon City, Philippines, 170 pp., 2018.
Mirus, B. B., Becker, R. E., Baum, R. L., and Smith, J. B.: Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning, Landslides, 15, 1909–1919, https://doi.org/10.1007/s10346-018-0995-z, 2018.
Mondini, A. C.: Measures of spatial autocorrelation changes in multitemporal SAR images for event landslides detection, Remote Sens., 9, 554, https://doi.org/10.3390/rs9060554, 2017.
Nikolopoulos, E., Borga, M., Creutin, J. and Marra, F.: Estimation of debris flow triggering rainfall: Influence of rain gauge density and interpolation methods, Geomorphology, 243, 40–50, 2015.
Nolasco-Javier, D. and Kumar, L.: Deriving the rainfall threshold for shallow landslide early warning during tropical cyclones: a case study in northern Philippines, Nat. Hazards, 90, 921–941, https://doi.org/10.1007/s11069-017-3081-2, 2018.
Nolasco-Javier, D. and Kumar, L.: Frequency ratio landslide susceptibility estimation in a tropical mountain region, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W8, 173–179, https://doi.org/10.5194/isprs-archives-XLII-3-W8-173-2019, 2019.
Nolasco-Javier, D., Kumar, L., and Tengonciang, A. M. P.: Rapid appraisal of rainfall threshold and selected landslides in Baguio, Philippines, Nat. Hazards, 78, 1587–1607, https://doi.org/10.1007/s11069-015-1790-y, 2015.
Oorthuis, R., Hürlimann, M., Abancó, C, Moya, J., and Carleo, L.: Monitoring of Rainfall and Soil Moisture at the Rebaixader Catchment (Central Pyrenees), Environmental and Engineering Geoscience 2021, https://doi.org/10.2113/EEG-D-20-00012, 2021.
Palangdan, V. T.: Save, recovery and development of Itogon. A Rehabilitation and recovery plan of the municipality of Itogon, Benguet (2019–2028), Itogon Local Government Unit, Itogon, Philippines,
54 pp., 2018.
Papa, M. N., Medina, V., Ciervo, F., and Bateman, A.: Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems, Hydrol. Earth Syst. Sci., 17, 4095–4107, https://doi.org/10.5194/hess-17-4095-2013, 2013.
Paringit, M. C. R., Cutora, M. D. L., Santiago, E. H., and Adajar, M. A. Q.: Assessment of Landslide Susceptibility: a Case Study of Carabao Mountain in Baguio City, International Journal of GEOMATE, 19, 166–173, https://doi.org/10.21660/2020.71.9261, 2020.
Pelascini, L., Steer, P., Longuevergne, L., and Lague, D.: The impact of atmospheric pressure change and rainfall for triggering landslides during weather events, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5423, https://doi.org/10.5194/egusphere-egu2020-5423, 2020
Peres, D. J., Cancelliere, A., Greco, R., and Bogaard, T. A.: Influence of uncertain identification of triggering rainfall on the assessment of landslide early warning thresholds, Nat. Hazards Earth Syst. Sci., 18, 633–646, https://doi.org/10.5194/nhess-18-633-2018, 2018.
Petley, D.: Global patterns of loss of life from landslides, Geology, 40, 927–930, 2012.
Prakash, N., Manconi, A., and Loew, S.: Mapping landslides on EO data: Performance of deep learning models vs. Traditional machine learning models, Remote Sens., 12, 346, https://doi.org/10.3390/rs12030346, 2020.
Rahardjo, H., Leong, E. C., and Rezaur, R. B.: Effect of antecedent rainfall on pore-water pressure distribution characteristics in residual soil slopes under tropical rainfall, Hydrol. Process., 22, 506–523, https://doi.org/10.1002/hyp.6880, 2008.
Reichle, R., De Lannoy, G., Koster, R. D., Crow, W. T., and Kimball, J. S.: SMAP L4 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data, Version 3, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/B59DT1D5UMB4, 2017.
Rengers, F. K., McGuire, L. A., Coe, J. A., Kean, J. W., Baum, R. L., Staley, D. M., and Godt, J. W.: The influence of vegetation on debris-flow initiation during extreme rainfall in the northern Colorado Front Range, Geology, 44, 823–826, https://doi.org/10.1130/G38096.1, 2016.
Scheip, C. M. and Wegmann, K. W.: HazMapper: A global open-source natural hazard mapping application in Google Earth Engine, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2020-108, in review, 2020.
Segoni, S., Piciullo, L., and Gariano, S. L.: A review of the recent literature on rainfall thresholds for landslide occurrence, Landslides, 15, 1483–1501, https://doi.org/10.1007/s10346-018-0966-4, 2018.
Shu, H., Hürlimann, M., Molowny-Horas, R., González, M., Pinyol, J., Abancó, C., and Ma, J.: Relation between land cover and landslide susceptibility in Val d'Aran, Pyrenees (Spain): Historical aspects, present situation and forward prediction, Sci. Total Environ., 693, 133557, https://doi.org/10.1016/j.scitotenv.2019.07.363, 2019.
Su, S. S.: Seismic hazard analysis for the Philippines, Nat. Hazards, 1, 27–44, https://doi.org/10.1007/BF00168220, 1988.
Tanyaş, H., van Westen, C. J., Allstadt, K. E., and Jibson, R. W.: Factors controlling landslide frequency–area distributions, Earth Surf. Processes, 44, 900–917, https://doi.org/10.1002/esp.4543, 2019.
Tseng, C. M., Lin, C. W., Dalla Fontana, G., and Tarolli, P.: The topographic signature of a major typhoon, Earth Surf. Processes, 40, 1129–1136, https://doi.org/10.1002/esp.3708, 2015.
Van Den Eeckhaut, M., Poesen, J., Govers, G., Verstraeten, G., and Demoulin, A.: Characteristics of the size distribution of recent and historical landslides in a populated hilly region, Earth Planet. Sci. Lett., 256, 588–603, https://doi.org/10.1016/j.epsl.2007.01.040, 2007.
Varnes, D. J.: Slope movements types and processes. Landslides analysis and control transportation research board, Natl. Acad. Sci. Spec. Rep., 176, 11–33, 1978.
von Ruette, J., Lehmann, P., and Or, D.: Effects of rainfall spatial variability and intermittency onshallow landslide triggering patterns at a catchment scale, Water Resour. Res., 50, 7780–7799, https://doi.org/10.1002/2013WR015122, 2014.
Weather Division PAGASA: Summary Report Typhoon Ompong (Mangkhut/1822), available at: https://pubfiles.pagasa.dost.gov.ph/pagasaweb/files/tamss/weather/tcsummary/TY_Ompong_Mangkhut.pdf (last access: 15 June 2020), 2018.
Yumul, G. P., Cruz, N. A., Servando, N. T., and Dimalanta, C. B.: Extreme weather events and related disasters in the Philippines, 2004–08: A sign of what climate change will mean?, Disasters, 35, 362–382, https://doi.org/10.1111/j.1467-7717.2010.01216.x, 2011.
Short summary
In 2018 Typhoon Mangkhut triggered thousands of landslides in the Itogon region (Philippines). An inventory of 1101 landslides revealed that landslides mostly occurred in slopes covered by wooded grassland in clayey materials, predominantly facing E-SE. Satellite rainfall and soil moisture data associated with Typhoon Mangkhut and the previous months in 2018 were analyzed. Results showed that landslides occurred during high-intensity rainfall that coincided with the highest soil moisture values.
In 2018 Typhoon Mangkhut triggered thousands of landslides in the Itogon region (Philippines)....
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