Articles | Volume 23, issue 3
https://doi.org/10.5194/nhess-23-1157-2023
© Author(s) 2023. 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-23-1157-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Mar 2023
Research article |
| 21 Mar 2023
| 21 Mar 2023
Deadly disasters in southeastern South America: flash floods and landslides of February 2022 in Petrópolis, Rio de Janeiro
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
José A. Marengo
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
José Mantovani
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Luciana R. Londe
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Rachel Lau Yu San
National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University (NTU), Singapore
Edward Park
National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University (NTU), Singapore
Yunung Nina Lin
Institute of Earth Sciences, Academia Sinica, Taipei, Taiwan
Jingyu Wang
National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University (NTU), Singapore
Tatiana Mendes
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Department of Environmental Engineering, Institute of Science and Technology, São Paulo State University (Unesp), São José dos Campos, Brazil
Ana Paula Cunha
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Luana Pampuch
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Department of Environmental Engineering, Institute of Science and Technology, São Paulo State University (Unesp), São José dos Campos, Brazil
Marcelo Seluchi
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Silvio Simões
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Luz Adriana Cuartas
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Demerval Goncalves
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Klécia Massi
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Department of Environmental Engineering, Institute of Science and Technology, São Paulo State University (Unesp), São José dos Campos, Brazil
Regina Alvalá
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Osvaldo Moraes
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Carlos Souza Filho
Institute of Geosciences (IG/Unicamp), University of Campinas, Campinas, Brazil
Rodolfo Mendes
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Carlos Nobre
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Institute of Advanced Studies, University of São Paulo (IEA/USP), São Paulo, Brazil
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Revised manuscript not accepted
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Kaniska Mallick, Ivonne Trebs, Eva Boegh, Laura Giustarini, Martin Schlerf, Darren T. Drewry, Lucien Hoffmann, Celso von Randow, Bart Kruijt, Alessandro Araùjo, Scott Saleska, James R. Ehleringer, Tomas F. Domingues, Jean Pierre H. B. Ometto, Antonio D. Nobre, Osvaldo Luiz Leal de Moraes, Matthew Hayek, J. William Munger, and Steven C. Wofsy
Hydrol. Earth Syst. Sci., 20, 4237–4264, https://doi.org/10.5194/hess-20-4237-2016, https://doi.org/10.5194/hess-20-4237-2016, 2016
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R. M. S. P. Vieira, J. Tomasella, R. C. S. Alvalá, M. F. Sestini, A. G. Affonso, D. A. Rodriguez, A. A. Barbosa, A. P. M. A. Cunha, G. F. Valles, E. Crepani, S. B. P. de Oliveira, M. S. B. de Souza, P. M. Calil, M. A. de Carvalho, D. M. Valeriano, F. C. B. Campello, and M. O. Santana
Solid Earth, 6, 347–360, https://doi.org/10.5194/se-6-347-2015, https://doi.org/10.5194/se-6-347-2015, 2015
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P. I. M. Camarinha, V. Canavesi, and R. C. S. Alvalá
Nat. Hazards Earth Syst. Sci., 14, 2449–2468, https://doi.org/10.5194/nhess-14-2449-2014, https://doi.org/10.5194/nhess-14-2449-2014, 2014
A. Drumond, J. Marengo, T. Ambrizzi, R. Nieto, L. Moreira, and L. Gimeno
Hydrol. Earth Syst. Sci., 18, 2577–2598, https://doi.org/10.5194/hess-18-2577-2014, https://doi.org/10.5194/hess-18-2577-2014, 2014
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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.
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.
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.
Chenchen Qiu and Xueyu Geng
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-156, https://doi.org/10.5194/nhess-2024-156, 2024
Revised manuscript accepted for NHESS
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We proposed an interated method with the combination of a physical vulnerability matric and a machine learning model to estimate the potential physical damage and associated economic loss caused by future debris flows based on the collected historical data on the Qinghai-Tibet Plateau regions.
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.
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.
Jui-Ming Chang, Che-Ming Yang, Wei-An Chao, Chin-Shang Ku, Ming-Wan Huang, Tung-Chou Hsieh, and Chi-Yao Hung
EGUsphere, https://doi.org/10.5194/egusphere-2024-1267, https://doi.org/10.5194/egusphere-2024-1267, 2024
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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 1st event of CL consisted of 4 sliding failures, accompanied by a gradual reduction in landslide volume. The 2nd and 3rd events were minor topplings and rockfalls. Then combining the seismological-based knowledge and field survey results, the temporal-spatial variation of landslide evolution is proposed.
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.
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-76, https://doi.org/10.5194/nhess-2024-76, 2024
Revised manuscript accepted for NHESS
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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 least 17 % compared to previously existing models.
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.
Mark Bloomberg, Tim Davies, Elena Moltchanova, Tom Robinson, and David Palmer
EGUsphere, https://doi.org/10.5194/egusphere-2023-2695, https://doi.org/10.5194/egusphere-2023-2695, 2023
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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 which 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.
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.
Francis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann M. Youberg, Daniel Cadol, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 23, 2075–2088, https://doi.org/10.5194/nhess-23-2075-2023, https://doi.org/10.5194/nhess-23-2075-2023, 2023
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Debris flows often occur after wildfires. These debris flows move water, sediment, and wood. The wood can get stuck in channels, creating a dam that holds boulders, cobbles, sand, and muddy material. We investigated how the channel width and wood length influenced how much sediment is stored. We also used a series of equations to back calculate the debris flow speed using the breaking threshold of wood. These data will help improve models and provide insight into future field investigations.
Maxime Morel, Guillaume Piton, Damien Kuss, Guillaume Evin, and Caroline Le Bouteiller
Nat. Hazards Earth Syst. Sci., 23, 1769–1787, https://doi.org/10.5194/nhess-23-1769-2023, https://doi.org/10.5194/nhess-23-1769-2023, 2023
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In mountain catchments, damage during floods is generally primarily driven by the supply of a massive amount of sediment. Predicting how much sediment can be delivered by frequent and infrequent events is thus important in hazard studies. This paper uses data gathered during the maintenance operation of about 100 debris retention basins to build simple equations aiming at predicting sediment supply from simple parameters describing the upstream catchment.
Elsa S. Culler, Ben Livneh, Balaji Rajagopalan, and Kristy F. Tiampo
Nat. Hazards Earth Syst. Sci., 23, 1631–1652, https://doi.org/10.5194/nhess-23-1631-2023, https://doi.org/10.5194/nhess-23-1631-2023, 2023
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Landslides have often been observed in the aftermath of wildfires. This study explores regional patterns in the rainfall that caused landslides both after fires and in unburned locations. In general, landslides that occur after fires are triggered by less rainfall, confirming that fire helps to set the stage for landslides. However, there are regional differences in the ways in which fire impacts landslides, such as the size and direction of shifts in the seasonality of landslides after fires.
Cited articles
Albuquerque, J. P. D., Herfort, B., and Eckle, M.: The Tasks of the Crowd: A Typology of Tasks in Geographic Information Crowdsourcing and a Case Study in Humanitarian Mapping, Remote Sens., 8, 1–22, https://doi.org/10.3390/rs8100859, 2016.
Ansari, H., Zan, F. D., and Bamler, R.: Efficient Phase Estimation for Interferogram Stacks, IEEE T. Geosci. Remote, 56, 4109–4125, 10.1109/TGRS.2018.2826045. 2018.
Avelar, A. S., Netto, A. L. C., Lacerda, W. A, Becker, L. B., and Mendonça, M. B.: Mechanisms of the recent catastrophic landslides in the mountainous range of Rio de Janeiro, Brazil, in: Landslide science and practice. Springer, Berlin Heidelberg, 265–270, ISBN 978-3-642-31337-0-34, 2013.
Ávila, F. F., Alvalá, R. C., Mendes, R. M., and Amore, D. J.: The influence of land use/land cover variability and rainfall intensity in triggering landslides: a back-analysis study via physically based models, Nat. Hazards, 105, 1139–1161, https://doi.org/10.1007/s11069-020-04324-x, 2021.
Brasil: Lei no 12.651, de 25 de maio de 2012, https://www.planalto.gov.br/ccivil_03/_ato2011-2014/2012/lei/l12651.htm (last access: 1 May 2022), 2012.
Carvalho-Filho, A., Lumbreras, J. F., and Santos, R. D.: Os Solos do Estado do Rio de Janeiro, CPRM, Brasília, Brazil, 36 pp., https://www.embrapa.br/busca-de-publicacoes/-/publicacao/1090208/os-solos-do-estado-do-rio-de-janeiro (last access: 6 May 2022), 2000.
Catani, F., Lagomarsino, D., Segoni, S., and Tofani, V.: Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues, Nat. Hazards Earth Syst. Sci., 13, 2815–2831, https://doi.org/10.5194/nhess-13-2815-2013, 2013.
Chau, K. T. and Chan, J. E.: Regional bias of landslide data in generating susceptibility maps using logistic regression: Case of Hong Kong Island, Landslides, 2, 280–290, https://doi.org/10.1007/s10346-005-0024-x, 2005.
Chen, C. W. and Zebker, H. A.: Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization, J. Opt. Soc. Am. A, 18, 338–351, https://doi.org/10.1364/JOSAA.18.000338, 2001.
Chen, W., Xie, X., Wang, J., Pradhan, B., Hong, H., Bui, D. T., Duan, Z., and Ma, J.: A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility, Catena, 151, 147–160, https://doi.org/10.1016/j.catena.2016.11.032, 2017.
Costanzo, D., Rotigliano, E., Irigaray, C., Jiménez-Perálvarez, J. D., and Chacón, J.: Factors selection in landslide susceptibility modelling on large scale following the gis matrix method: application to the river Beiro basin (Spain), Nat. Hazards Earth Syst. Sci., 12, 327–340, https://doi.org/10.5194/nhess-12-327-2012, 2012.
CPRM (Geological Survey of Brazil): Avaliação técnica pós-desastre, Petropolis, RJ 2022, Ministry of Mines and Energy MME, 9 pp., https://rigeo.cprm.gov.br, last access: 1 May 2022.
Dai, F. C. and Lee, C. F.: Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong, Geomorphology, 42, 213–228, https://doi.org/10.1016/s0169-555x(01)00087-3, 2002.
Dean, W.: A ferro e fogo: a história e a devastação da Mata Atlântica brasileira, Companhia das Letras, São Paulo, ISBN 9788571645905, 1996.
Dembélé, M. and Zwart, S. J.: Evaluation and Comparison of Satellite-Based Rainfall Products in Burkina Faso, West Africa, Int. J. Remote Sens., 37, 3995–4014, https://doi.org/10.1080/01431161.2016.1207258, 2016.
Dias, H. C., Hölbling, D., and Grohmann, C. H.: Landslide Susceptibility Mapping in Brazil: A Review, Geosciences, 11, 1–15, https://doi.org/10.3390/geosciences11100425, 2021.
Dias, M. C. A., Saito, S. M., Alvalá, R. C., Stenner, C., Pinho, G., Nobre, C. A., Fonseca, M. R. S., Santos, C., Amadeu, P., Silva, D., Lima, C. O., Ribeiro, J., Nascimento, F., and Corrêa, C. O.: Estimation of exposed population to landslides and floods risk areas in Brazil, on intra-urban scale, Int. J. Disast. Risk Re., 31, 449–459, https://doi.org/10.1016/j.ijdrr.2018.06.002, 2018.
Dourado, F., Arraes, T. C., and Silva, M. F.: The “Megadesastre” in the Mountain Region of Rio de Janeiro State – Causes, Mechanisms of Mass Movements and Spatial Allocation of Investments for Reconstruction Post Disaster, Anuário do Instituto de Geeociências, 35, 43–54, https://doi.org/10.11137/2012_2_43_54, 2012.
Fattahi, H., Agram, P. S., Tymofyeyeva, E., and Bekaert, D. P.: FRInGE; Full-Resolution InSAR time series using Generalized Eigenvectors, American Geophysical Union, Fall Meeting 2019, 9–13 December 2019, San Francisco, CA, USA, abstract #G11B-0514, https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/497561 (last access: 6 May 2022), 2019.
FIRJAN: Firjan estima perda de R$ 665 milhões no PIB de Petrópolis após a forte chuva da última semana, FIRJAN, https://firjan.com.br/noticias/firjan-estima-perda-de-r-665-milhoes-no-pib-de-petropolis-apos-a-forte-chuva-da-ultima-semana-1.htm, last access: 20 March 2022.
Fonseca, M. J. G., Derze, G. R., Barreto, A. M., and Williams, G. H.: Mapa Geológico do Estado do Rio de Janeiro, Technical report, Departamento Nacional de Produção Mineral (DPMN), Rio de Janeiro, Brazil, 141 pp., http://www.cprm.gov.br/publique/Gestao-Territorial/Geologia%2C-Meio-Ambiente-e-Saude/Projeto-Rio-de-Janeiro-3498.html (last access: 6 May 2022), 1998.
Fundação SOS Mata Atlântica: Atlas dos Remanescentes Florestais da Mata Atlântica período 2016–2017, Technical report, Fundação SOS Mata Atlântica, Instituto Nacional de Pesquisas Espaciais, São Paulo, https://cms.sosma.org.br/wp-content/uploads/2021/05/SOSMA_Atlas-da-Mata-Atlantica_2019-2020.pdf(last access: 6 May 2022), 2018.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The climate hazards infrared precipitation with stations – a new environmental record for monitoring extremes, Sci. Data, 2, 150066, https://doi.org/10.1038/sdata.2015.66, 2015.
Galarneau, T. J. and Bosart, L. F.: Ridge Rollers: Mesoscale disturbances on the periphery of cutoff anticyclones, 21st Conf. on Weather Analysis and Forecasting/17th Conf. on Numerical Weather Prediction, 28 July–5 August 2005, Atlanta, GA, USA, Amer. Meteor. Soc., 3.2, https://ams.confex.com/ams/WAFNWP34BC/techprogram/paper_94414.htm (last access: 2 May 2022), 2006.
Goldblatt, R., Jones, N., and Mannix, J.: Assessing OpenStreetMap Completeness for Management of Natural Disaster by Means of Remote Sensing: A Case Study of Three Small Island States (Haiti, Dominica and St. Lucia), Remote Sens., 12, 1–25, https://doi.org/10.3390/rs12010118, 2020.
Gonçalves, L. F. H.: Avaliação e Diagnóstico da Distribuição Espacial e Temporal dos Movimentos de Massa com a Expansão da Área Urbana em Petrópolis-RJ, PhD Thesis, Universidade Federal do Rio de Janeiro-UFRJ, Rio de Janeiro, Brazil, 1998.
Guerra, A.: Catastrophic events in Petrópolis city (Rio de Janeiro state), between 1940 and 1990, GeoJournal, 37, 349–354, https://doi.org/10.1007/BF00814015, 1995.
Guzzetti, F., Carrara, A., Cardinali, M., and Reichenbach, P.: Landslide hazard evaluation: A review of current techniques and their application in a multi-scale study, Central Italy, Geomorphology, 31, 181–216, https://doi.org/10.1016/s0169-555x(99)00078-1, 1999.
Hermance, J. F. and Sulieman, H. M.: Adequacy of the daily TMPA 3B42 high-resolution satellite precipitation product for monitoring hydrometeorological hazards in the Southeast Sahel of Africa, Int. J. Remote Sens., 39, 2579–2596, https://doi.org/10.1080/01431161.2018.1430405, 2018.
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., 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., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, 2020.
Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K.-L., Joyce, R. J., Kidd, C., Nelkin, E. J., Sorooshian, S., Stocker, E. F., Tan, J., Wolff, D. B., and Xie, P.: Satellite Precipitation Measurement: Volume 1, edited by: Levizzani, V., Kidd, C., Kirschbaum, D. B., Kummerow, C. D., Nakamura, K., and Turk, F. J., 343–353, Springer Cham, ISBN 978-3030245672, 2020.
IBGE: Cidades, Instituto Brasileiro de Geografia e Estatística, https://cidades.ibge.gov.br/brasil/retropolisis/panorama, last access: 25 September 2018.
Janowiak, J., Joyce, B., and Xie, P.: NCEP/CPC L3 Half Hourly 4km Global (60S – 60N) Merged IR V1, edited by: Savtchenko, A., Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/P4HZB9N27EKU, 2017.
Jiang, L. and Bauer-Gottwein, P.: How do GPM IMERG precipitation estimates perform as hydrological model forcing? Evaluation for 300 catchments across Mainland China, J. Hydrol., 572, 486–500, https://doi.org/10.1016/j.jhydrol.2019.03.042, 2019.
Jolivet, R., Agram, Piyush, S., Lin, Y. N., Simons, M., Doin, M.-P., Peltzer, G., and Li, Z.: Improving InSAR geodesy using Global Atmospheric Models, J. Geophys. Res.-Sol. Ea., 119, 2324–2341, https://doi.org/10.1002/2013JB010588, 2014.
Kanwal, S., Atif, S., and Shafiq, M.: GIS based landslide susceptibility mapping of northern areas of Pakistan, a case study of Shigar and Shyok Basins, Geomat. Nat. Hazards Risk, 8, 348–366, https://doi.org/10.1080/19475705.2016.1220023, 2017.
Lambin, E. F. and Ehrlich, D.: The surface temperature-vegetation index space for land cover and land-cover change analysis, Int. J. Remote Sens., 17, 463–487, https://doi.org/10.1080/01431169608949021, 1996.
Li, H., Herfort, B., Huang, W., Zia, M., and Zipf, A.: Exploration of OpenStreetMap missing built-up areas using twitter hierarchical clustering and deep learning in Mozambique, ISPRS J. Photogramm., 166, 41–51, https://doi.org/10.1016/j.isprsjprs.2020.05.007, 2020.
Maddox, R. A., Hoxit, L. R., Chappell, C. F., and Caracena, F.: Comparison of meteorological aspects of the Big Thompson and Rapid City flash floods, Mon. Weather Rev., 106, 375–389, 1978.
Marchezini, V. and Wisner, B.: Challenges for vulnerability reduction in Brazil: Insights from the PAR framework, in: Reduction of vulnerability to disasters: From knowledge to action, edited by: Marchzini, V., Wisner, B., Londe, L., RIMA, ISBN 978-85-7656-050-0, 2017.
Marengo, J. A. and Alves, L. M.: The 2011 intense rainfall and floods in Rio de Janeiro, B. Am. Meteorol. Soc., 93, S176, https://doi.org/10.1175/2012BAMSStateoftheClimate.1, 2012.
Martinotti, M. E., Pisano, L., Marchesini, I., Rossi, M., Peruccacci, S., Brunetti, M. T., Melillo, M., Amoruso, G., Loiacono, P., Vennari, C., Vessia, G., Trabace, M., Parise, M., and Guzzetti, F.: Landslides, floods and sinkholes in a karst environment: the 1–6 September 2014 Gargano event, southern Italy, Nat. Hazards Earth Syst. Sci., 17, 467–480, https://doi.org/10.5194/nhess-17-467-2017, 2017.
Mendes, R. M., Andrade, M. R. M., Graminha, C. A., Prieto, C., Ávila, F. F., Camarinha, P. I.: Stability Analysis on Urban Slopes: Case Study of an Anthropogenic-Induced Landslide in São José dos Campos, Brazil, Geotech. Geol. Eng., 36, 599–610, https://doi.org/10.1007/s10706-017-0303-z, 2018a.
Mendes, R. M., de Andrade, M. R. M., Tomasella, J., de Moraes, M. A. E., and Scofield, G. B.: Understanding shallow landslides in Campos do Jordão municipality – Brazil: disentangling the anthropic effects from natural causes in the disaster of 2000, Nat. Hazards Earth Syst. Sci., 18, 15–30, https://doi.org/10.5194/nhess-18-15-2018, 2018b.
Minghini, M. and Frassinelli, F.: OpenStreetMap history for intrinsic quality assessment: Is OSM up-to-date?, Open Geospatial Data Softw. Stand., 4, 1–17, https://doi.org/10.1186/s40965-019-0067-x, 2019.
Mitchell, M. J., Arritt, R. W., and Labas, K.: A climatology of the warm season Great Plains low-level jet using wind profiler observations, Weather Forecast., 10, 576–591, https://doi.org/10.1175/1520-0434(1995)010<0576:ACOTWS>2.0.CO;2, 1995.
Myers, N., Mittermeier, R. A., Mittermeier, C. G., Fonseca, G. A. B., and Kent, J.: Biodiversity hotspots for conservation priorities, Nature, 403, 853–858, https://doi.org/10.1038/35002501, 2000.
Nehren, U., Schlüter, S., Raeding, C., Sattler, D., and Hissa, H. (Eds.): Strategies and Tools for a Sustainable Rural Rio de Janeiro, Springer Series on Environmental Management, https://doi.org/10.1007/978-3-319-89644-1_20, 2018.
Ohlmacher, G. C.: Plan curvature and landslide probability in regions dominated by Earth flows and Earth Slides, Eng. Geol., 91, 117–134, https://doi.org/10.1016/j.enggeo.2007.01.005, 2007.
Parida, B. R., Collado, W. B., Borah, R., Hazarika, M. K., and Samarakook, L.: Detecting drought-prone areas of rice agriculture using a MODIS-derivd soil moisture index, GIScience and Remote Sensing, 45, 109–129, 2008.
Penha, M. M., Ferrari, A. L., Junho, M. C. B., Souza, S. L. A., and Brennes, T. L.: Projeto Carta Geológica do Estado do Rio de Janeiro: Folha Itaipava, Technical report, vol. 1, Convênio DRM/IG-UFRJ, Rio de Janeiro, Brazil, http://www.cprm.gov.br/publique/Gestao-Territorial/Geologia%2C-Meio-Ambiente-e-Saude/Projeto-Rio-de-Janeiro-3498.html (last access: 3 May 2022), 1981.
Pisano, L., Zumpano, V., Malek, Z., Rosskopf, C. M., and Parise, M.: Variations in the susceptibility to landslides, as a consequence of land cover changes: a look to the past, and another towards the future, Sci. Total Environ., 601–602, 1147–1159, 2017.
Reichenbach, P., Rossi, M., Malamud, B., Mihir, M., and Guzzetti, F.: A review of statistically-based landslide susceptibility models, Earth-Sci. Rev., 180, 60–91, https://doi.org/10.1016/j.earscirev.2018.03.001, 2018.
Reis, A. A., Fernandes, W. S., and Ramos, M.-H.: Assessing two precipitation data sources at basins of special interest to hydropower production in Brazil, Brazilian Journal of Water Resources, 25, 1–16, https://doi.org/10.1590/2318-0331.252020190068, 2020.
Rosi, A., Canavesi, V., Segoni, S., Nery, T. D., Catani, F., and Casagli, N.: Landslides in the Mountain Region of Rio de Janeiro: A Proposal for the Semi-Automated Definition of Multiple Rainfall Thresholds, Geosciences, 9, 1–15, https://doi.org/10.3390/geosciences9050203, 2019.
Schlossmacher, E. J.: An Iterative Technique for Absolute Deviations Curve Fitting, J. Am. Stat. Assoc., 68, 857–859, https://doi.org/10.2307/2284512, 1973.
Silva, R. F. B., Batistella, M., Moran, E. F., and Liu, D.: Land changes fostering Atlantic Forest transition in Brazil: Evidence from the Paraíba Valley, Prof. Geogr., 69, 80–93, https://doi.org/10.1080/00330124.2016.1178151, 2017.
Souza Jr., C. M., Shimbo, J. Z., Rosa, M. R., Parente, L. L., Alencar, A. A., Rudorff, B. F. T., Hasenack, H., Matsumoto, M., Ferreira, L. G., Souza-Filho, P. W. M., de Oliveira, S. W., Rocha, W. F., Fonseca, A. V., Marques, C. B., Diniz, C.,G., Costa, D., Monteiro, D., Rosa, E. R., Vélez-Martin, E., Weber, E. J., Lenti, F. E. B., Paternost, F. F., Pareyn, F.,G.,C., Siqueira, J. V., Viera, J. L., Neto, L. C. F., Saraiva, M. M., Sales, M. H., Salgado, M. P. G., Vasconcelos, R., Galano, S., Mesquita, V. V., and Azevedo, T.: Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine, Remote Sens., 12, 1–17, https://doi.org/10.3390/rs12172735, 2020.
Wang, J., Dong, X., Kennedy, A., Hagenhoff, B., and Xi, B.: A regime-based evaluation of southern and northern great plains warm-season precipitation events in WRF, Weather Forecast., 34, 805–831, 2019.
Zhan, Z., Qin, Q., and Wang, X.: The Application of LST/NDVI Index for Monitoring Land Surface Moisture in Semiarid Area, Geoscience and Remote Sensing, IGARSS 2004, 2004 IEEE International Geoscience and Remote Sensing Symposium, 20–24 September 2004, Anchorage, AK, USA, IEEE, 3, 1551–1555, https://doi.org/10.1109/IGARSS.2004.1370609, 2004.
Short summary
The municipality of Petrópolis (approximately 305 687 inhabitants) is nestled in the mountains 68 km outside the city of Rio de Janeiro. On 15 February 2022, the city of Petrópolis in Rio de Janeiro, Brazil, received an unusually high volume of rain within 3 h (258 mm). This resulted in flash floods and subsequent landslides that caused 231 fatalities, the deadliest landslide disaster recorded in Petrópolis. This work shows how the disaster was triggered.
The municipality of Petrópolis (approximately 305 687 inhabitants) is nestled in the mountains...
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