Articles | Volume 15, issue 4
https://doi.org/10.5194/nhess-15-817-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-15-817-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
10 Apr 2015
Research article |
| 10 Apr 2015
Analysis of changes in post-seismic landslide distribution and its effect on building reconstruction
W. T. Yang
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
Department of Earth System Analysis, Faculty of Geo-Information and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
School of Soil and Water Conservation, Beijing Forestry University, Beijing, China
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing, China
M. Wang
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing, China
N. Kerle
Department of Earth System Analysis, Faculty of Geo-Information and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
C. J. Van Westen
Department of Earth System Analysis, Faculty of Geo-Information and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
L. Y. Liu
Key Laboratory of Environmental Change and Natural Disaster, MOE, Beijing Normal University, Beijing, China
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing, China
P. J. Shi
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
Key Laboratory of Environmental Change and Natural Disaster, MOE, Beijing Normal University, Beijing, China
Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing, China
Related authors
X. L. Chen, H. L. Ran, and W. T. Yang
Nat. Hazards Earth Syst. Sci., 12, 3645–3657, https://doi.org/10.5194/nhess-12-3645-2012, https://doi.org/10.5194/nhess-12-3645-2012, 2012
Aulia Imania Sukma, Mila N. Koeva, Diana Reckien, Marija Bockarjova, Andre da Silva Mano, Giulia Canili, Giovanni Vicentini, and Norman Kerle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W11-2024, 129–136, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-129-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-129-2024, 2024
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
Short summary
Short summary
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.
Yuting Zhang, Kai Liu, Xiaoyong Ni, Ming Wang, Jianchun Zheng, Mengting Liu, and Dapeng Yu
Nat. Hazards Earth Syst. Sci., 24, 63–77, https://doi.org/10.5194/nhess-24-63-2024, https://doi.org/10.5194/nhess-24-63-2024, 2024
Short summary
Short summary
This article is aimed at developing a method to quantify the influence of inclement weather on the accessibility of emergency medical services (EMSs) in Beijing, China, and identifying the vulnerable areas that could not get timely EMSs under inclement weather. We found that inclement weather could reduce the accessibility of EMSs by up to 40%. Furthermore, towns with lower baseline EMSs accessibility are more vulnerable when inclement weather occurs.
Di Wang, Ming Wang, Kai Liu, and Jun Xie
Nat. Hazards Earth Syst. Sci., 23, 1409–1423, https://doi.org/10.5194/nhess-23-1409-2023, https://doi.org/10.5194/nhess-23-1409-2023, 2023
Short summary
Short summary
The short–medium-term intervention effect on the post-earthquake area was analysed by simulations in different scenarios. The sediment transport patterns varied in different sub-regions, and the relative effectiveness in different scenarios changed over time with a general downward trend, where the steady stage implicated the scenario with more facilities performing better in controlling sediment output. Therefore, the simulation methods could support optimal rehabilitation strategies.
Jianxin Zhang, Kai Liu, and Ming Wang
Earth Syst. Sci. Data, 15, 521–540, https://doi.org/10.5194/essd-15-521-2023, https://doi.org/10.5194/essd-15-521-2023, 2023
Short summary
Short summary
This study successfully extracted global flood days based on gravity satellite and precipitation data between 60° S and 60° N from 1 April 2002 to 31 August 2016. Our flood days data performed well compared with current available observations. This provides an important data foundation for analyzing the spatiotemporal distribution of large-scale floods and exploring the impact of ocean–atmosphere oscillations on floods in different regions.
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
Short summary
Short summary
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.
Qian He, Ming Wang, Kai Liu, Kaiwen Li, and Ziyu Jiang
Earth Syst. Sci. Data, 14, 3273–3292, https://doi.org/10.5194/essd-14-3273-2022, https://doi.org/10.5194/essd-14-3273-2022, 2022
Short summary
Short summary
We used three machine learning models and determined that Gaussian process regression (GPR) is best suited to the interpolation of air temperature data for China. The GPR-derived results were compared with that of traditional interpolation techniques and existing data sets and it was found that the accuracy of the GPR-derived data was better. Finally, we generated a gridded monthly air temperature data set with 1 km resolution and high accuracy for China (1951–2020) using the GPR model.
N. Zhang, F. Nex, G. Vosselman, and N. Kerle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1189–1196, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1189-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1189-2022, 2022
S. Karam, F. Nex, O. Karlsson, J. Rydell, E. Bilock, M. Tulldahl, M. Holmberg, and N. Kerle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2022, 203–210, https://doi.org/10.5194/isprs-annals-V-1-2022-203-2022, https://doi.org/10.5194/isprs-annals-V-1-2022-203-2022, 2022
Weihua Zhu, Kai Liu, Ming Wang, Philip J. Ward, and Elco E. Koks
Nat. Hazards Earth Syst. Sci., 22, 1519–1540, https://doi.org/10.5194/nhess-22-1519-2022, https://doi.org/10.5194/nhess-22-1519-2022, 2022
Short summary
Short summary
We present a simulation framework to analyse the system vulnerability and risk of the Chinese railway system to floods. To do so, we develop a method for generating flood events at both the national and river basin scale. Results show flood system vulnerability and risk of the railway system are spatially heterogeneous. The event-based approach shows how we can identify critical hotspots, taking the first steps in developing climate-resilient infrastructure.
Weihua Zhu, Kai Liu, Ming Wang, Sadhana Nirandjan, and Elco Koks
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-277, https://doi.org/10.5194/nhess-2021-277, 2021
Manuscript not accepted for further review
Short summary
Short summary
We use multi-source empirical damage data to generate vulnerability curves and assess the risk of transportation infrastructure to rainfall-induced hazards. The results show large variations in the shape of the vulnerability curves and risk of railway infrastructure in China across the different regions. The usage of multi-source empirical data offer opportunities to perform risk assessments that include spatial detail among regions.
Qian He, Ming Wang, Kai Liu, Kaiwen Li, and Ziyu Jiang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-267, https://doi.org/10.5194/essd-2021-267, 2021
Manuscript not accepted for further review
Short summary
Short summary
We used three machine learning models and determined that Gaussian process regression (GPR) is best suited to interpolation of air temperature data for China. The GPR-derived results were compared with that of traditional interpolation techniques and existing datasets and it was found that the accuracy of the GPR-derived data was better. Finally, we generated a gridded monthly air temperature dataset with 1 km resolution and high accuracy for China (1951–2020) using the GPR model.
N. Zhang, F. Nex, N. Kerle, and G. Vosselman
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 427–432, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-427-2021, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-427-2021, 2021
Seyedabdolhossein Mehvar, Kathelijne Wijnberg, Bas Borsje, Norman Kerle, Jan Maarten Schraagen, Joanne Vinke-de Kruijf, Karst Geurs, Andreas Hartmann, Rick Hogeboom, and Suzanne Hulscher
Nat. Hazards Earth Syst. Sci., 21, 1383–1407, https://doi.org/10.5194/nhess-21-1383-2021, https://doi.org/10.5194/nhess-21-1383-2021, 2021
Short summary
Short summary
This review synthesizes and complements existing knowledge in designing resilient vital infrastructure systems (VIS). Results from a systematic literature review indicate that (i) VIS are still being built without taking resilience explicitly into account and (ii) measures to enhance the resilience of VIS have not been widely applied in practice. The main pressing topic to address is the integration of the combined social, ecological, and technical resilience of these systems.
Bastian van den Bout, Theo van Asch, Wei Hu, Chenxiao X. Tang, Olga Mavrouli, Victor G. Jetten, and Cees J. van Westen
Geosci. Model Dev., 14, 1841–1864, https://doi.org/10.5194/gmd-14-1841-2021, https://doi.org/10.5194/gmd-14-1841-2021, 2021
Short summary
Short summary
Landslides, debris flows and other types of dense gravity-driven flows threaten livelihoods around the globe. Understanding the mechanics of these flows can be crucial for predicting their behaviour and reducing disaster risk. Numerical models assume that the solids and fluids of the flow are unstructured. The newly presented model captures the internal structure during movement. This important step can lead to more accurate predictions of landslide movement.
Wentao Yang, Lianyou Liu, and Peijun Shi
Nat. Hazards Earth Syst. Sci., 20, 3215–3224, https://doi.org/10.5194/nhess-20-3215-2020, https://doi.org/10.5194/nhess-20-3215-2020, 2020
Short summary
Short summary
We analysed deformation of a moving slope along the Jinsha River from November 2015 to November 2019. The slope is 80 km downstream from the famous Baige landslide, which caused two mega floods affecting downstream communities. This slope was relatively stable for the first 3 years (2015–2018) but moved significantly in the last year (2018–2019). The deformation is linked to seasonal precipitation. If this slope continues to slide downwards, it may have similar impacts to the Baige landslide.
Lina Hao, Rajaneesh A., Cees van Westen, Sajinkumar K. S., Tapas Ranjan Martha, Pankaj Jaiswal, and Brian G. McAdoo
Earth Syst. Sci. Data, 12, 2899–2918, https://doi.org/10.5194/essd-12-2899-2020, https://doi.org/10.5194/essd-12-2899-2020, 2020
Short summary
Short summary
Kerala in India was subjected to an extreme rainfall event in the monsoon season of 2018 which triggered extensive floods and landslides. In order to study whether the landslides were related to recent land use changes, we generated an accurate and almost complete landslide inventory based on two existing datasets and the detailed interpretation of images from the Google Earth platform. The final dataset contains 4728 landslides with attributes of land use in 2010 and land use in 2018.
S. M. Tilon, F. Nex, D. Duarte, N. Kerle, and G. Vosselman
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 573–582, https://doi.org/10.5194/isprs-annals-V-2-2020-573-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-573-2020, 2020
Siyuan Zhou, Jing Yang, Wei-Chyung Wang, Chuanfeng Zhao, Daoyi Gong, and Peijun Shi
Atmos. Chem. Phys., 20, 5211–5229, https://doi.org/10.5194/acp-20-5211-2020, https://doi.org/10.5194/acp-20-5211-2020, 2020
Short summary
Short summary
Aerosol–cloud–precipitation interaction is a challenging problem in regional climate. Our study contrasted the observed diurnal variation of heavy rainfall and associated clouds over Beijing–Tianjin–Hebei between clean and polluted days during the 2002–2012 summers. We found the heavy rainfall under pollution has earlier start time, earlier peak time and longer duration, and further found the absorbing aerosols and scattering aerosols play different roles in the heavy rainfall diurnal variation.
Chenxiao Tang, Xinlei Liu, Yinghua Cai, Cees Van Westen, Yu Yang, Hai Tang, Chengzhang Yang, and Chuan Tang
Nat. Hazards Earth Syst. Sci., 20, 1163–1186, https://doi.org/10.5194/nhess-20-1163-2020, https://doi.org/10.5194/nhess-20-1163-2020, 2020
Short summary
Short summary
Recovering from major earthquakes is a challenge due to a destablized environment. Over 11 years, we monitored a region hit by the Wenchuan earthquake, finding the loss caused by postseismic hazards was more than that caused by the earthquake. The main reason was a rush in reconstruction without proper hazard and risk assessment. It was concluded that postseismic recovery should consider not only spatial but also temporal dynamics of hazards as well as possible interaction among hazards.
N. Kerle, F. Nex, D. Duarte, and A. Vetrivel
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W8, 187–194, https://doi.org/10.5194/isprs-archives-XLII-3-W8-187-2019, https://doi.org/10.5194/isprs-archives-XLII-3-W8-187-2019, 2019
Jianqiang Zhang, Cees J. van Westen, Hakan Tanyas, Olga Mavrouli, Yonggang Ge, Samjwal Bajrachary, Deo Raj Gurung, Megh Raj Dhital, and Narendral Raj Khanal
Nat. Hazards Earth Syst. Sci., 19, 1789–1805, https://doi.org/10.5194/nhess-19-1789-2019, https://doi.org/10.5194/nhess-19-1789-2019, 2019
Short summary
Short summary
The aim of this study is to investigate the differences in the mappable characteristics of earthquake-triggered and rainfall triggered landslides in terms of their frequency–area relationships, spatial distributions and relation with causal factors, as well as to evaluate whether separate susceptibility maps generated for specific landslide size and triggering mechanism are better than a generic landslide susceptibility assessment including all landslide sizes and triggers.
S. Ghaffarian and N. Kerle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 297–302, https://doi.org/10.5194/isprs-archives-XLII-2-W13-297-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-297-2019, 2019
D. Duarte, F. Nex, N. Kerle, and G. Vosselman
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 29–36, https://doi.org/10.5194/isprs-annals-IV-2-W5-29-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-29-2019, 2019
Tao Ye, Weihang Liu, Jidong Wu, Yijia Li, Peijun Shi, and Qiang Zhang
Nat. Hazards Earth Syst. Sci., 19, 697–713, https://doi.org/10.5194/nhess-19-697-2019, https://doi.org/10.5194/nhess-19-697-2019, 2019
Short summary
Short summary
Livestock and their owners in the Qinghai–Tibetan Plateau has long suffered from snow disaster. In order to help the local herder community better prepare for potential loss, we developed a probabilistic disaster-event simulation approach, from which livestock loss induced by a snow disaster with specific intensity and local prevention capacity could be predicted. By using this method, we managed to estimate snow disaster duration, livestock loss rate, and number at different return periods.
Johnny Cusicanqui, Norman Kerle, and Francesco Nex
Nat. Hazards Earth Syst. Sci., 18, 1583–1598, https://doi.org/10.5194/nhess-18-1583-2018, https://doi.org/10.5194/nhess-18-1583-2018, 2018
Short summary
Short summary
Aerial multi-perspective images can be used for the effective assessment of post-disaster structural damage. Alternatively, rapidly available video data can be processed for the same purpose. However, video quality characteristics are different than those of images taken with still cameras. The use of video data in post-disaster damage assessment has not been demonstrated. Based on a comparative assessment, our findings support the application of video data in post-disaster damage assessment.
D. Duarte, F. Nex, N. Kerle, and G. Vosselman
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 89–96, https://doi.org/10.5194/isprs-annals-IV-2-89-2018, https://doi.org/10.5194/isprs-annals-IV-2-89-2018, 2018
Qiang Zhang, Xihui Gu, Vijay P. Singh, Peijun Shi, and Peng Sun
Hydrol. Earth Syst. Sci., 22, 2637–2653, https://doi.org/10.5194/hess-22-2637-2018, https://doi.org/10.5194/hess-22-2637-2018, 2018
D. Duarte, F. Nex, N. Kerle, and G. Vosselman
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 93–100, https://doi.org/10.5194/isprs-archives-XLII-2-W6-93-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-93-2017, 2017
Chenxiao Tang, Cees J. Van Westen, Hakan Tanyas, and Victor G. Jetten
Nat. Hazards Earth Syst. Sci., 16, 2641–2655, https://doi.org/10.5194/nhess-16-2641-2016, https://doi.org/10.5194/nhess-16-2641-2016, 2016
Short summary
Short summary
Post-seismic landslides highlighted the need for more research to provide critical information for reconstruction. By mapping detailed landslide inventories, our work shows that most of the landslide activities were concentrated within the first 3 years after the earthquake, and they are majorly determined by vegetation regrowth, available volumes of loose materials, and extreme rainfall events. The landslide activity will continue to decay, but it may be halted if extreme rainfall occurs.
W. Kim, N. Kerle, and M. Gerke
Nat. Hazards Earth Syst. Sci., 16, 287–298, https://doi.org/10.5194/nhess-16-287-2016, https://doi.org/10.5194/nhess-16-287-2016, 2016
Short summary
Short summary
This study assesses the value of a novel technology, mobile augmented reality, for rapid damage and safety assessment of the state of buildings in the aftermath of a disaster event. In this study, we propose and demonstrate conceptual frameworks and approaches for in situ ground-based assessment based on augmented reality using mobile devices such as smartphones and tablet PCs.
Z. C. Aye, M. Jaboyedoff, M. H. Derron, C. J. van Westen, H. Y. Hussin, R. L. Ciurean, S. Frigerio, and A. Pasuto
Nat. Hazards Earth Syst. Sci., 16, 85–101, https://doi.org/10.5194/nhess-16-85-2016, https://doi.org/10.5194/nhess-16-85-2016, 2016
Short summary
Short summary
This paper presents the development and application of a prototype web-GIS tool for risk analysis, in particular for floods and landslides, based on open-source software and web technologies. The aim is to assist experts (risk managers) in analysing the impacts and consequences of a certain hazard event in a considered region, contributing to open-source and research community in natural hazards and risk assessment. The tool is demonstrated using a regional data set of Fella River basin, Italy.
Y. Meng, S. Yang, P. Shi, and C. C. Jeager
Nat. Hazards Earth Syst. Sci., 15, 2273–2281, https://doi.org/10.5194/nhess-15-2273-2015, https://doi.org/10.5194/nhess-15-2273-2015, 2015
Short summary
Short summary
We propose a gravity model tailed to China’s national circumstances and taking into account the natural disaster impact. China’s natural disasters increase exports, but they have no significant impact on imports. Trading partner countries’ natural disasters reduce Chinese imports and exports. The impact of natural disasters on trade is asymmetric and significantly affected by other factors, like development level and land area.
J. Fernandez Galarreta, N. Kerle, and M. Gerke
Nat. Hazards Earth Syst. Sci., 15, 1087–1101, https://doi.org/10.5194/nhess-15-1087-2015, https://doi.org/10.5194/nhess-15-1087-2015, 2015
T. Turkington, J. Ettema, C. J. van Westen, and K. Breinl
Nat. Hazards Earth Syst. Sci., 14, 1517–1530, https://doi.org/10.5194/nhess-14-1517-2014, https://doi.org/10.5194/nhess-14-1517-2014, 2014
N. Kerle and R. R. Hoffman
Nat. Hazards Earth Syst. Sci., 13, 97–113, https://doi.org/10.5194/nhess-13-97-2013, https://doi.org/10.5194/nhess-13-97-2013, 2013
X. L. Chen, H. L. Ran, and W. T. Yang
Nat. Hazards Earth Syst. Sci., 12, 3645–3657, https://doi.org/10.5194/nhess-12-3645-2012, https://doi.org/10.5194/nhess-12-3645-2012, 2012
Related subject area
Landslides and Debris Flows Hazards
Topographic controls on landslide mobility: modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico
Characterizing the scale of regional landslide triggering from storm hydrometeorology
A participatory approach to determine the use of road cut slope design guidelines in Nepal to lessen landslides
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
Is higher resolution always better? Open-access DEM comparison for Slope Units delineation and regional landslide prediction
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
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
Comparative Analysis of μ (I) and Voellmy-Type Grain Flow Rheologies in Geophysical Mass Flows: Insights from Theoretical and Real Case Studies
From rockfall source areas identification to susceptibility zonation: a proposed workflow tested in El Hierro (Canary Islands, Spain)
Exploring implications of input parameter uncertainties on GLOF modelling results using the state-of-the-art modelling code, r.avaflow
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
Addressing class imbalance in soil movement predictions
Assessing the impact of climate change on landslides near Vejle, Denmark, using public data
A regional analysis of paraglacial landslide activation in southern coastal Alaska
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
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
Brief Communication: Weak correlation between building damage and loss of life from landslides
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
Dianne L. Brien, Mark E. Reid, Collin Cronkite-Ratcliff, and Jonathan P. Perkins
Nat. Hazards Earth Syst. Sci., 25, 1229–1253, https://doi.org/10.5194/nhess-25-1229-2025, https://doi.org/10.5194/nhess-25-1229-2025, 2025
Short summary
Short summary
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. Landslide runout may occur on hillslopes or in channels, requiring different modeling approaches. We develop methods to identify potential runout zones and apply these methods to identify susceptible areas for three municipalities in Puerto Rico.
Jonathan Perkins, Nina S. Oakley, Brian D. Collins, Skye C. Corbett, and W. Paul Burgess
Nat. Hazards Earth Syst. Sci., 25, 1037–1056, https://doi.org/10.5194/nhess-25-1037-2025, https://doi.org/10.5194/nhess-25-1037-2025, 2025
Short summary
Short summary
Rainfall-induced landslides result in deaths and economic losses annually across the globe. However, it is unclear how storm severity relates to landslide severity across large regions. Here we develop a method to dynamically map landslide-affected areas, and we compare this to meteorological estimates of storm severity. We find that preconditioning by earlier storms and the location of rainfall bursts, rather than atmospheric storm strength, dictate landslide magnitude and pattern.
Ellen B. Robson, Bhim Kumar Dahal, and David G. Toll
Nat. Hazards Earth Syst. Sci., 25, 949–973, https://doi.org/10.5194/nhess-25-949-2025, https://doi.org/10.5194/nhess-25-949-2025, 2025
Short summary
Short summary
Slopes excavated alongside roads in Nepal frequently fail (a landslide), resulting in substantial losses. Our participatory approach study with road engineers aimed to assess how road slope design guidelines in Nepal can be improved. Our study revealed inconsistent guideline adherence due to a lack of user-friendliness and inadequate training. We present general recommendations to enhance road slope management, as well as technical recommendations to improve the guidelines.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Mahnoor Ahmed, Giacomo Titti, Sebastiano Trevisani, Lisa Borgatti, and Mirko Francioni
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-211, https://doi.org/10.5194/nhess-2024-211, 2024
Preprint under review for NHESS
Short summary
Short summary
Elevation models are compared with a true dataset for terrain characteristics which selects a better ranking model to test with different parameters for partitioning the terrain. The partitioning of the terrain is measured by how well a partitioned unit can support the mapped landslide area and number of landslides. The effect of this relationship is reflected with different metrics in the susceptibility maps.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Yu Zhuang, Brian W. McArdell, and Perry Bartelt
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-87, https://doi.org/10.5194/nhess-2024-87, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study reformulates the μ(I) rheology into a Voellmy-type relationship to elucidate its physical implications. The μ(I) rheology, incorporating a dimensionless inertial number, mimics granular temperature effects, reflecting shear thinning behavior of mass flows. However, its constant Coulomb friction coefficient limits accuracy in modeling deposition. Comparing μ(I) with Voellmy-type rheologies reveals strengths and limitations, enhancing mass flow modeling and engineering applications.
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
Short summary
Short summary
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.
Sonam Rinzin, Stuart Dunning, Rachel Carr, Ashim Sattar, and Martin Mergili
EGUsphere, https://doi.org/10.5194/egusphere-2024-1819, https://doi.org/10.5194/egusphere-2024-1819, 2024
Short summary
Short summary
We evaluated the sensitivity of model outputs to input parameter uncertainties by performing multiple GLOF simulations using the r.avaflow model. We found out that GLOF modelling outputs are highly sensitive to six parameters: volume of mass movements entering lakes, DEM datasets, origin of mass movements, mesh size, basal frictional angle, and entrainment coefficient. Future modelling should carefully consider the output uncertainty from these sensitive parameters.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Jane Walden, Mylène Jacquemart, Bretwood Higman, Romain Hugonnet, Andrea Manconi, and Daniel Farinotti
EGUsphere, https://doi.org/10.5194/egusphere-2024-1086, https://doi.org/10.5194/egusphere-2024-1086, 2024
Short summary
Short summary
In a study of eight landslides adjacent to glaciers in Alaska, we found that landslide movement increased as the glacier retreated past the landslide at four sites. Movement at other sites coincided with heavy precipitation or increased glacier thinning, and two sites showed little-to-no motion. We suggest that landslides next to water-terminating glaciers may be especially vulnerable to acceleration, which we guess is due to faster retreat rates and water replacing ice at the landslide edge.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Maximillian Van Wyk de Vries, Alexandre Dunant, Amy L. Johnson, Erin L. Harvey, Sihan Li, Katherine Arrell, Jeevan Baniya, Dipak Basnet, Gopi K. Basyal, Nyima Dorjee Bhotia, Simon J. Dadson, Alexander L. Densmore, Tek Bahadur Dong, Mark E. Kincey, Katie Oven, Anuradha Puri, and Nick J. Rosser
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-40, https://doi.org/10.5194/nhess-2024-40, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Mapping exposure to landslides is necessary to mitigate risk and reduce vulnerability. In this study, we show that there is a poor correlation between building damage and deaths from landslides- such that the deadliest landslides do not always destroy the most buildings and vice versa. This has important implications for our management on landslide risk.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Atta-ur-Rahman, Khan, A. N., Collins, A. E., and Qazi, F.: Causes and extent of environmental impacts of landslide hazard in the Himalayan region: a case study of Murree, Pakistan, Nat. Hazards, 57, 413–434, https://doi.org/10.1007/s11069-010-9621-7, 2010.
Atta-ur-Rahman, Khan, A. N., and Collins, A. E.: Analysis of landslide causes and associated damages in the Kashmir Himalayas of Pakistan, Nat. Hazards, 71, 803–821, https://doi.org/10.1007/s11069-013-0918-1, 2013.
Chen, C.-Y.: Sedimentary impacts from landslides in the Tachia River Basin, Taiwan, Geomorphology, 105, 355–365, https://doi.org/10.1016/j.geomorph.2008.10.009, 2009.
Cheng, J. D., Huang, Y. C., Wu, H. L., Yeh, J. L., and Chang, C. H.: Hydrometeorological and landuse attributes of debris flows and debris floods during typhoon Toraji, 29–30 July 2001 in central Taiwan, J. Hydrol., 306, 161–173, https://doi.org/10.1016/j.jhydrol.2004.09.007, 2005.
Cui, P., Chen, X.-Q., Zhu, Y.-Y., Su, F.-H., Wei, F.-Q., Han, Y.-S., Liu, H.-J., and Zhuang, J.-Q.: The Wenchuan Earthquake (12 May 2008), Sichuan Province, China, and resulting geohazards, Nat. Hazards, 56, 19–36, https://doi.org/10.1007/s11069-009-9392-1, 2011.
Dadson, S. J., Hovius, N., Chen, H., Dade, W. B., Hsieh, M.-L., Willett, S. D., Hu, J.-C., Horng, M.-J., Chen, M.-C., and Stark, C. P.: Links between erosion, runoff variability and seismicity in the Taiwan orogen, Nature, 426, 648–651, 2003.
Dunford, M. and Li, L.: Earthquake reconstruction in Wenchuan: Assessing the state overall plan and addressing the "forgotten phase", Appl. Geogr., 31, 998–1009, https://doi.org/10.1016/j.apgeog.2011.01.001, 2011.
Fan, X., Tang, C. X., van Westen, C. J., and Alkema, D.: Simulating dam-breach flood scenarios of the Tangjiashan landslide dam induced by the Wenchuan Earthquake, Nat. Hazards Earth Syst. Sci., 12, 3031–3044, https://doi.org/10.5194/nhess-12-3031-2012, 2012a.
Fan, X., van Westen, C. J., Korup, O., Gorum, T., Xu, Q., Dai, F., Huang, R., and Wang, G.: Transient water and sediment storage of the decaying landslide dams induced by the 2008 Wenchuan earthquake, China, Geomorphology, 171, 58–68, 2012b.
Gorum, T., Fan, X., van Westen, C. J., Huang, R. Q., Xu, Q., Tang, C., and Wang, G.: Distribution pattern of earthquake-induced landslides triggered by the 12 May 2008 Wenchuan earthquake, Geomorphology, 133, 152–167, 2011.
Huang, R.: After effect of geohazards induced by the Wenchuan Earthquake, Journal of Engineering Geology, 19, 145–151, 2011.
Jha, A. K. and Duyne, J. E.: Safer homes, stronger communities: a handbook for reconstructing after natural disasters, World Bank Publications, Washington DC, 7–21, 2010.
Johnson, C.: Strategic planning for post-disaster temporary housing, Disasters, 31, 435–458, 2007.
Keefer, D. K.: The importance of earthquake-induced landslides to long-term slope erosion and slope-failure hazards in seismically active regions, Geomorphology, 10, 265–284, 1994.
Khan, S. F., Kamp, U., and Owen, L. A.: Documenting five years of landsliding after the 2005 Kashmir earthquake, using repeat photography, Geomorphology, 197, 45–55, https://doi.org/10.1016/j.geomorph.2013.04.033, 2013.
Khattak, G. A., Owen, L. A., Kamp, U., and Harp, E. L.: Evolution of earthquake-triggered landslides in the Kashmir Himalaya, northern Pakistan, Geomorphology, 115, 102–108, https://doi.org/10.1016/j.geomorph.2009.09.035, 2010.
Koi, T., Hotta, N., Ishigaki, I., Matuzaki, N., Uchiyama, Y., and Suzuki, M.: Prolonged impact of earthquake-induced landslides on sediment yield in a mountain watershed: The Tanzawa region, Japan, Geomorphology, 101, 692–702, https://doi.org/10.1016/j.geomorph.2008.03.007, 2008.
Kozin, F. and Zhou, H.: System study of urban response and reconstruction due to earthquake, J. Eng. Mech.-Asce., 116, 1959–1972, 1990.
Lin, C.-W., Liu, S.-H., Lee, S.-Y., and Liu, C.-C.: Impacts of the Chi-Chi earthquake on subsequent rainfall-induced landslides in central Taiwan, Eng. Geol., 86, 87–101, https://doi.org/10.1016/j.enggeo.2006.02.010, 2006.
Lin, W.-T., Chou, W.-C., and Lin, C.-Y.: Earthquake-induced landslide hazard and vegetation recovery assessment using remotely sensed data and a neural network-based classifier: a case study in central Taiwan, Nat. Hazards, 47, 331–347, https://doi.org/10.1007/s11069-008-9222-x, 2008.
Mao, H., Zhang, X., and Wang, Z.: Design tactics of post-disaster urban renaissance – take the reconstruction plan of Nanba town, Pingwu as an example, New Architecture, 104–107, 2009.
Quarantelli, E. L.: Sheltering and housing after major community disasters: case studies and general observations, Washington DC, 72–74, 1982.
Saba, S. B., van der Meijde, M., and van der Werff, H.: Spatiotemporal landslide detection for the 2005 Kashmir earthquake region, Geomorphology, 124, 17–25, https://doi.org/10.1016/j.geomorph.2010.07.026, 2010.
Schwendtner, B., Papathoma-Köhle, M., and Glade, T.: Risk evolution: how can changes in the built environment influence the potential loss of natural hazards?, Nat. Hazards Earth Syst. Sci., 13, 2195–2207, https://doi.org/10.5194/nhess-13-2195-2013, 2013.
Shi, P.: Theory and practice of disaster study, Journal of Natural Disasters, 5, 6–14, 1996.
Sudmeier-Rieux, K., Jaboyedoff, M., Breguet, A., and Dubois, J.: The 2005 Pakistan Earthquake Revisited: Methods for Integrated Landslide Assessment, Mt. Res. Dev., 31, 112–121, https://doi.org/10.1659/mrd-journal-d-10-00110.1, 2011.
Tang, C., Zhu, J., Qi, X., and Ding, J.: Landslides induced by the Wenchuan earthquake and the subsequent strong rainfall event: A case study in the Beichuan area of China, Eng. Geol., 122, 22–33, https://doi.org/10.1016/j.enggeo.2011.03.013, 2011.
UNDRO: Shelter after disaster: Guidelines for assistance, United Nations, 46–47, New York, 1982.
Wang, M., Yang, W., Shi, P., Xu, C., and Liu, L.: Diagnosis of Vegetation Recovery in Mountainous Regions After the Wenchuan Earthquake, IEEE J. Sel. Top. Appl., 7, 3029–3037, https://doi.org/10.1109/JSTARS.2014.2327794, 2014.
Wu, J. Y. and Lindell, M. K.: Housing Reconstruction After Two Major Earthquakes: The 1994 Northridge Earthquake in the United States and the 1999 Chi-Chi Earthquake Earthquake in Taiwan, Disasters, 28, 63–81, 2004.
Xin, H.: Slew of Landslides Unmask Hidden Geological Hazards, Science, 330, p. 744, 2010.
Xu, C., Xu, X., Yao, X., and Dai, F.: Three (nearly) complete inventories of landslides triggered by the 12 May 2008 Wenchuan Mw 7.9 earthquake of China and their spatial distribution statistical analysis, Landslides, 11, 441–461, 2014.
Xu, X. W., Wen, X. Z., Yu, G. H., Chen, G. H., Klinger, Y., Hubbard, J., and Shaw, J.: Coseismic reverse- and oblique-slip surface faulting generated by the 2008 Mw 7.9 Wenchuan earthquake, China , Geology, 37, 515–518, 2009.
Yin, Y.: Researches on the geo-hazards triggered by Wenchuan earthquake, Sichuan [J], J. Eng. Geol., 4, 7–12, 2008.
Zhao, J., Wu, J., Shi, L., and Liu, Y.: Distribution of Seismic Damaged Buildings along the Trace of Ground Surface Rupture Caused by the Ms 8.0 Wenchuan Earthquake, Advances in Geosciences (21633967), 2, 1–15, 2012.
Altmetrics
Final-revised paper
Preprint