Articles | Volume 17, issue 12
https://doi.org/10.5194/nhess-17-2213-2017
© Author(s) 2017. 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-17-2213-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Dec 2017
Research article |
| 08 Dec 2017
| 08 Dec 2017
Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides
Roberto Greco
Dipartimento di Ingegneria Civile Design Edilizia e Ambiente,
Universitá degli Studi della Campania “Luigi Vanvitelli”, Via Roma 9, 81031 Aversa (CE), Italy
Dipartimento di Ingegneria Civile Edile e Ambientale, Universitá
degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli, Italy
Related authors
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.
Daniel Camilo Roman Quintero, Pasquale Marino, Abdullah Abdullah, Giovanni Francesco Santonastaso, and Roberto Greco
EGUsphere, https://doi.org/10.5194/egusphere-2024-2329, https://doi.org/10.5194/egusphere-2024-2329, 2024
Short summary
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Local thresholds for landslide forecasting, combining hydrologic predisposing factors and rainfall features, are developed from a physically based model of a slope. To extend their application to a wide area, uncertainty due to spatial variability of geomorphological and hydrologic variables is introduced. The obtained hydrometeorological thresholds, integrating root zone soil moisture and aquifer water level with rainfall depth, outperform thresholds based on rain intensity and duration.
Daniel Camilo Roman Quintero, Pasquale Marino, Giovanni Francesco Santonastaso, and Roberto Greco
Hydrol. Earth Syst. Sci., 27, 4151–4172, https://doi.org/10.5194/hess-27-4151-2023, https://doi.org/10.5194/hess-27-4151-2023, 2023
Short summary
Short summary
This study shows a methodological approach using machine learning techniques to disentangle the relationships among the variables in a synthetic dataset to identify suitable variables that control the hydrologic response of the slopes. It has been found that not only is the rainfall responsible for the water accumulation in the slope; the ground conditions (soil water content and aquifer water level) also indicate the activation of natural slope drainage mechanisms.
Yi Luo, Jiaming Zhang, Zhi Zhou, Juan P. Aguilar-Lopez, Roberto Greco, and Thom Bogaard
Hydrol. Earth Syst. Sci., 27, 783–808, https://doi.org/10.5194/hess-27-783-2023, https://doi.org/10.5194/hess-27-783-2023, 2023
Short summary
Short summary
This paper describes an experiment and modeling of the hydrological response of desiccation cracks under long-term wetting–drying cycles. We developed a new dynamic dual-permeability model to quantify the dynamic evolution of desiccation cracks and associated preferential flow and moisture distribution. Compared to other models, the dynamic dual-permeability model could describe the experimental data much better, but it also provided an improved description of the underlying physics.
Luca Comegna, Emilia Damiano, Roberto Greco, Lucio Olivares, and Luciano Picarelli
Earth Syst. Sci. Data, 13, 2541–2553, https://doi.org/10.5194/essd-13-2541-2021, https://doi.org/10.5194/essd-13-2541-2021, 2021
Short summary
Short summary
The set-up of an automatic field station allowed for the monitoring of the annual cyclic hydrological response of a deposit in pyroclastic air-fall soils covering a steep mountainous area in Campania region (Italy), which in 1999 was involved in a rainfall-induced flowslide. Data highlight the influence of the initial conditions, governed by the antecedent wetting/drying history, on the weather-induced hydraulic paths, allowing us to estimate their influence on the local stability conditions.
David J. Peres, Antonino Cancelliere, Roberto Greco, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 18, 633–646, https://doi.org/10.5194/nhess-18-633-2018, https://doi.org/10.5194/nhess-18-633-2018, 2018
Short summary
Short summary
We investigate the influence of imprecise identification of triggering instants on landslide early warning thresholds by perturbing an error-free synthetic dataset. Combined impacts of uncertainty with respect to temporal discretization of data and criteria for singling out rainfall events are assessed as well. Results show that thresholds can be significantly affected by these uncertainty sources.
Thom Bogaard and Roberto Greco
Nat. Hazards Earth Syst. Sci., 18, 31–39, https://doi.org/10.5194/nhess-18-31-2018, https://doi.org/10.5194/nhess-18-31-2018, 2018
Short summary
Short summary
The vast majority of shallow landslides and debris flows are precipitation initiated and predicted using historical landslides plotted versus observed precipitation information. However, this approach has severe limitations. This is partly due to the fact that it is not precipitation that initiates a landslide or debris flow but rather the hydrological dynamics in the soil and slope. We propose to include hydrological information in the regional hydro-meteorological hazard assessment.
W. Shao, T. A. Bogaard, M. Bakker, and R. Greco
Hydrol. Earth Syst. Sci., 19, 2197–2212, https://doi.org/10.5194/hess-19-2197-2015, https://doi.org/10.5194/hess-19-2197-2015, 2015
Short summary
Short summary
The effect of preferential flow on the stability of landslides is studied through numerical simulation of two types of rainfall events on a hypothetical hillslope. A model is developed that consists of two parts. The first part is a model for combined saturated/unsaturated subsurface flow and is used to compute the spatial and temporal water pressure response to rainfall. Preferential flow is simulated with a dual-permeability continuum model consisting of a matrix/preferential flow domain.
R. Greco, L. Comegna, E. Damiano, A. Guida, L. Olivares, and L. Picarelli
Hydrol. Earth Syst. Sci., 17, 4001–4013, https://doi.org/10.5194/hess-17-4001-2013, https://doi.org/10.5194/hess-17-4001-2013, 2013
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.
Daniel Camilo Roman Quintero, Pasquale Marino, Abdullah Abdullah, Giovanni Francesco Santonastaso, and Roberto Greco
EGUsphere, https://doi.org/10.5194/egusphere-2024-2329, https://doi.org/10.5194/egusphere-2024-2329, 2024
Short summary
Short summary
Local thresholds for landslide forecasting, combining hydrologic predisposing factors and rainfall features, are developed from a physically based model of a slope. To extend their application to a wide area, uncertainty due to spatial variability of geomorphological and hydrologic variables is introduced. The obtained hydrometeorological thresholds, integrating root zone soil moisture and aquifer water level with rainfall depth, outperform thresholds based on rain intensity and duration.
Daniel Camilo Roman Quintero, Pasquale Marino, Giovanni Francesco Santonastaso, and Roberto Greco
Hydrol. Earth Syst. Sci., 27, 4151–4172, https://doi.org/10.5194/hess-27-4151-2023, https://doi.org/10.5194/hess-27-4151-2023, 2023
Short summary
Short summary
This study shows a methodological approach using machine learning techniques to disentangle the relationships among the variables in a synthetic dataset to identify suitable variables that control the hydrologic response of the slopes. It has been found that not only is the rainfall responsible for the water accumulation in the slope; the ground conditions (soil water content and aquifer water level) also indicate the activation of natural slope drainage mechanisms.
Yi Luo, Jiaming Zhang, Zhi Zhou, Juan P. Aguilar-Lopez, Roberto Greco, and Thom Bogaard
Hydrol. Earth Syst. Sci., 27, 783–808, https://doi.org/10.5194/hess-27-783-2023, https://doi.org/10.5194/hess-27-783-2023, 2023
Short summary
Short summary
This paper describes an experiment and modeling of the hydrological response of desiccation cracks under long-term wetting–drying cycles. We developed a new dynamic dual-permeability model to quantify the dynamic evolution of desiccation cracks and associated preferential flow and moisture distribution. Compared to other models, the dynamic dual-permeability model could describe the experimental data much better, but it also provided an improved description of the underlying physics.
Luca Comegna, Emilia Damiano, Roberto Greco, Lucio Olivares, and Luciano Picarelli
Earth Syst. Sci. Data, 13, 2541–2553, https://doi.org/10.5194/essd-13-2541-2021, https://doi.org/10.5194/essd-13-2541-2021, 2021
Short summary
Short summary
The set-up of an automatic field station allowed for the monitoring of the annual cyclic hydrological response of a deposit in pyroclastic air-fall soils covering a steep mountainous area in Campania region (Italy), which in 1999 was involved in a rainfall-induced flowslide. Data highlight the influence of the initial conditions, governed by the antecedent wetting/drying history, on the weather-induced hydraulic paths, allowing us to estimate their influence on the local stability conditions.
David J. Peres, Antonino Cancelliere, Roberto Greco, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 18, 633–646, https://doi.org/10.5194/nhess-18-633-2018, https://doi.org/10.5194/nhess-18-633-2018, 2018
Short summary
Short summary
We investigate the influence of imprecise identification of triggering instants on landslide early warning thresholds by perturbing an error-free synthetic dataset. Combined impacts of uncertainty with respect to temporal discretization of data and criteria for singling out rainfall events are assessed as well. Results show that thresholds can be significantly affected by these uncertainty sources.
Alfredo Reder, Guido Rianna, and Luca Pagano
Nat. Hazards Earth Syst. Sci., 18, 613–631, https://doi.org/10.5194/nhess-18-613-2018, https://doi.org/10.5194/nhess-18-613-2018, 2018
Short summary
Short summary
Recently, landslides affecting pyroclastic covers of Campania Region caused many deaths and huge costs. The development of early warning systems represents a key issue for the area. However, the features of such soils make the development of reliable predictive tools challenging. The relevance of accounting for evaporative losses in slope hydrological balance regulating safety conditions is here discussed. To that end, the 2005 landslide in Nocera Inferiore is used as test case.
Thom Bogaard and Roberto Greco
Nat. Hazards Earth Syst. Sci., 18, 31–39, https://doi.org/10.5194/nhess-18-31-2018, https://doi.org/10.5194/nhess-18-31-2018, 2018
Short summary
Short summary
The vast majority of shallow landslides and debris flows are precipitation initiated and predicted using historical landslides plotted versus observed precipitation information. However, this approach has severe limitations. This is partly due to the fact that it is not precipitation that initiates a landslide or debris flow but rather the hydrological dynamics in the soil and slope. We propose to include hydrological information in the regional hydro-meteorological hazard assessment.
W. Shao, T. A. Bogaard, M. Bakker, and R. Greco
Hydrol. Earth Syst. Sci., 19, 2197–2212, https://doi.org/10.5194/hess-19-2197-2015, https://doi.org/10.5194/hess-19-2197-2015, 2015
Short summary
Short summary
The effect of preferential flow on the stability of landslides is studied through numerical simulation of two types of rainfall events on a hypothetical hillslope. A model is developed that consists of two parts. The first part is a model for combined saturated/unsaturated subsurface flow and is used to compute the spatial and temporal water pressure response to rainfall. Preferential flow is simulated with a dual-permeability continuum model consisting of a matrix/preferential flow domain.
R. Greco, L. Comegna, E. Damiano, A. Guida, L. Olivares, and L. Picarelli
Hydrol. Earth Syst. Sci., 17, 4001–4013, https://doi.org/10.5194/hess-17-4001-2013, https://doi.org/10.5194/hess-17-4001-2013, 2013
Related subject area
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Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer
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Size scaling of large landslides from incomplete inventories
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Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA
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Assessing the impact of climate change on landslides near Vejle, Denmark, using public data
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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
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Exploratory analysis of the annual risk to life from debris flows
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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.
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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 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.
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Catalogues of mapped landslides are useful for learning and forecasting how frequently they occur in relation to their size. Yet, rare and large landslides remain mostly uncertain in statistical summaries of these catalogues. We propose a single, consistent method of comparing across different data sources and find that landslide statistics disclose more about subjective mapping choices than trigger types or environmental settings.
Rachael Lau, Carolina Seguí, Tyler Waterman, Nathaniel Chaney, and Manolis Veveakis
Nat. Hazards Earth Syst. Sci., 24, 3651–3661, https://doi.org/10.5194/nhess-24-3651-2024, https://doi.org/10.5194/nhess-24-3651-2024, 2024
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This work examines the use of interferometric synthetic-aperture radar (InSAR) alongside in situ borehole measurements to assess the stability of deep-seated landslides for the case study of El Forn (Andorra). Comparing InSAR with borehole data suggests a key trade-off between accuracy and precision for various InSAR resolutions. Spatial interpolation with InSAR informed how many remote observations are necessary to lower error in a remote sensing re-creation of ground motion over the landslide.
Zhen Lei Wei, Yue Quan Shang, Qiu Hua Liang, and Xi Lin Xia
Nat. Hazards Earth Syst. Sci., 24, 3357–3379, https://doi.org/10.5194/nhess-24-3357-2024, https://doi.org/10.5194/nhess-24-3357-2024, 2024
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The initiation of debris flows is significantly influenced by rainfall-induced hydrological processes. We propose a novel framework based on an integrated hydrological and hydrodynamic model and aimed at estimating intensity–duration (ID) rainfall thresholds responsible for triggering debris flows. In comparison to traditional statistical approaches, this physically based framework is particularly suitable for application in ungauged catchments where historical debris flow data are scarce.
Dianne L. Brien, Mark E. Reid, Collin Cronkite-Ratcliff, and Jonathan P. Perkins
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-141, https://doi.org/10.5194/nhess-2024-141, 2024
Revised manuscript accepted for NHESS
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Landslide runout zones are the areas downslope or downstream of landslide initiation. People often live and work in these areas, leading to property damage and deaths. We develop methods to identify potential runout zones from landslides. We apply our methods to create susceptibility maps for three study areas in Puerto Rico and assess the success of our methods based on mapped landslides from Hurricane Maria.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024, https://doi.org/10.5194/nhess-24-3207-2024, 2024
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The Himalayan road network links remote areas, but fragile terrain and poor construction lead to frequent landslides. This study on the NH-7 in India's Uttarakhand region analyzed 300 landslides after heavy rainfall in 2022 . Factors like slope, rainfall, rock type and road work influence landslides. The study's model predicts landslide locations for better road maintenance planning, highlighting the risk from climate change and increased road use.
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.
Praveen Kumar, Priyanka Priyanka, Kala Venkata Uday, and Varun Dutt
Nat. Hazards Earth Syst. Sci., 24, 1913–1928, https://doi.org/10.5194/nhess-24-1913-2024, https://doi.org/10.5194/nhess-24-1913-2024, 2024
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Our study focuses on predicting soil movement to mitigate landslide risks. We develop machine learning models with oversampling techniques to address the class imbalance in monitoring data. The dynamic ensemble model with K-means SMOTE (synthetic minority oversampling technique) achieves high precision, high recall, and a high F1 score. Our findings highlight the potential of these models with oversampling techniques to improve soil movement predictions in landslide-prone areas.
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci., 24, 1897–1911, https://doi.org/10.5194/nhess-24-1897-2024, https://doi.org/10.5194/nhess-24-1897-2024, 2024
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In our study, we analysed publicly available data in order to investigate the impact of climate change on landslides in Denmark. Our research indicates that the rising groundwater table due to climate change will result in an increase in landslide activity. Previous incidents of extremely wet winters have caused damage to infrastructure and buildings due to landslides. This study is the first of its kind to exclusively rely on public data and examine landslides in Denmark.
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024, https://doi.org/10.5194/nhess-24-1741-2024, 2024
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With a simplified formula linking rainfall and groundwater level, the rise of the phreatic surface within the slope can be obtained. Then, a global analysis method that considers both seepage and seismic forces is proposed to determine the safety factor of slopes subjected to the combined effect of rainfall and earthquakes. By taking a slope in the Three Gorges Reservoir area as an example, the safety evolution of the slope combined with both rainfall and earthquake is also examined.
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024, https://doi.org/10.5194/nhess-24-1697-2024, 2024
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Central Asia regions are marked by active tectonics, high mountains with glaciers, and strong rainfall. These predisposing factors make large landslides a serious threat in the area and a source of possible damming scenarios, which endanger the population. To prevent this, a semi-automated geographic information system (GIS-)based mapping method, centered on a bivariate correlation of morphometric parameters, was applied to give preliminary information on damming susceptibility in Central Asia.
Rex L. Baum, Dianne L. Brien, Mark E. Reid, William H. Schulz, and Matthew J. Tello
Nat. Hazards Earth Syst. Sci., 24, 1579–1605, https://doi.org/10.5194/nhess-24-1579-2024, https://doi.org/10.5194/nhess-24-1579-2024, 2024
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We mapped potential for heavy rainfall to cause landslides in part of the central mountains of Puerto Rico using new tools for estimating soil depth and quasi-3D slope stability. Potential ground-failure locations correlate well with the spatial density of landslides from Hurricane Maria. The smooth boundaries of the very high and high ground-failure susceptibility zones enclose 75 % and 90 %, respectively, of observed landslides. The maps can help mitigate ground-failure hazards.
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 24, 1459–1483, https://doi.org/10.5194/nhess-24-1459-2024, https://doi.org/10.5194/nhess-24-1459-2024, 2024
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Debris flows are a type of fast-moving landslide that start from shallow landslides or during intense rain. Infrastructure located downstream of watersheds susceptible to debris flows may be damaged should a debris flow reach them. We present and evaluate an approach to forecast building damage caused by debris flows. We test three alternative models for simulating the motion of debris flows and find that only one can forecast the correct number and spatial pattern of damaged buildings.
Luke A. McGuire, Francis K. Rengers, Ann M. Youberg, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Ryan Porter
Nat. Hazards Earth Syst. Sci., 24, 1357–1379, https://doi.org/10.5194/nhess-24-1357-2024, https://doi.org/10.5194/nhess-24-1357-2024, 2024
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Runoff and erosion increase after fire, leading to a greater likelihood of floods and debris flows. We monitored debris flow activity following a fire in western New Mexico, USA, and observed 16 debris flows over a <2-year monitoring period. Rainstorms with recurrence intervals of approximately 1 year were sufficient to initiate debris flows. All debris flows initiated during the first several months following the fire, indicating a rapid decrease in debris flow susceptibility over time.
Ken'ichi Koshimizu, Satoshi Ishimaru, Fumitoshi Imaizumi, and Gentaro Kawakami
Nat. Hazards Earth Syst. Sci., 24, 1287–1301, https://doi.org/10.5194/nhess-24-1287-2024, https://doi.org/10.5194/nhess-24-1287-2024, 2024
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Morphological conditions of drainage basins that classify the presence or absence of debris flow fans were analyzed in areas with different rock strength using decision tree analysis. The relief ratio is the most important morphological factor regardless of the geology. However, the thresholds of morphological parameters needed for forming debris flow fans differ depending on the geology. Decision tree analysis is an effective tool for evaluating the debris flow risk for each geology.
Jonathan P. Perkins, Nina S. Oakley, Brian D. Collins, Skye C. Corbett, and W. Paul Burgess
EGUsphere, https://doi.org/10.5194/egusphere-2024-873, https://doi.org/10.5194/egusphere-2024-873, 2024
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Landslides are a global issue that results in deaths and economic losses annually. However, it is not clear how storm severity relates to landslide severity across large regions. Here we develop a method to estimate the footprint of landslide area and compare this to meteorologic estimates of storm severity. We find that total storm strength does not clearly relate to landslide area. Rather, landslide area depends on soil wetness and smaller storm structures that can produce intense rainfall.
Daniel Bolliger, Fritz Schlunegger, and Brian W. McArdell
Nat. Hazards Earth Syst. Sci., 24, 1035–1049, https://doi.org/10.5194/nhess-24-1035-2024, https://doi.org/10.5194/nhess-24-1035-2024, 2024
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We analysed data from the Illgraben debris flow monitoring station, Switzerland, and we modelled these flows with a debris flow runout model. We found that no correlation exists between the grain size distribution, the mineralogical composition of the matrix, and the debris flow properties. The flow properties rather appear to be determined by the flow volume, from which most other parameters can be derived.
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
Nat. Hazards Earth Syst. Sci., 24, 891–906, https://doi.org/10.5194/nhess-24-891-2024, https://doi.org/10.5194/nhess-24-891-2024, 2024
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We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide and found that the contact surface model with high strength parameters combines advantages of the intact rock mass model in simulating the deformation of slopes with rock bridges and the modeling advantage of the Jennings model. The results help in choosing a rock bridge model to simulate landslide stability and reveal the influence laws of rock bridges on the stability of landslides.
Ashok Dahal, Hakan Tanyas, Cees van Westen, Mark van der Meijde, Paul Martin Mai, Raphaël Huser, and Luigi Lombardo
Nat. Hazards Earth Syst. Sci., 24, 823–845, https://doi.org/10.5194/nhess-24-823-2024, https://doi.org/10.5194/nhess-24-823-2024, 2024
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We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
Li-Ru Luo, Zhi-Xiang Yu, Li-Jun Zhang, Qi Wang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci., 24, 631–649, https://doi.org/10.5194/nhess-24-631-2024, https://doi.org/10.5194/nhess-24-631-2024, 2024
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We performed field investigations on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was obtained from an unmanned aerial vehicle survey. A finite element model was created to reproduce the damage evolution. We found that the impact kinetic energy was below the design protection energy. Improper member connections prevent the barrier from producing significant deformation to absorb energy. Damage is avoided by improving the ability of the nets and ropes to slide.
Sudhanshu Dixit, Srikrishnan Siva Subramanian, Piyush Srivastava, Ali P. Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci., 24, 465–480, https://doi.org/10.5194/nhess-24-465-2024, https://doi.org/10.5194/nhess-24-465-2024, 2024
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Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards. Large-scale sediment disasters like landslides, debris flows, and flash floods happen frequently in the Himalayas because of their propensity for intense precipitation events. We provide a new framework that combines the Weather Research and Forecasting (WRF) model with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, https://doi.org/10.5194/nhess-24-1-2024, 2024
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Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
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The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
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.
Cited articles
Alfieri, L., Salamon, P., Pappenberger, F., Wetterhall, F., and Thielen, J.: Operational early warning systems for water-related hazards in Europe, Environ. Sci. Policy, 21, 35–49, https://doi.org/10.1016/j.envsci.2012.01.008, 2012.
Alfieri, L. and Thielen, J.: A European precipitation index for extreme rain-storm and flash flood early warning, Meteorol. Appl., 22, 3–13, https://doi.org/10.1002/met.1328, 2015.
Arnone, E., Noto, L. V., Lepore, C., and Bras, R. L.: Physically-based and distributed approach to analyze rainfall-triggered landslides at watershed scale, Geomorphology, 133, 121–131, https://doi.org/10.1016/j.geomorph.2011.03.019, 2011.
Bakkehoi, S.: Snow avalanche prediction using a probabilistic method, Avalanche Formation, Movement and Effects, Proceedings of the Davos Symposium, September 1986, IAHS Publ., 162, 1986.
Basher, R.: Global early warning systems for natural hazards: systematic and people centred, Philos. T. R. Soc. A, 364, 2167–2182, https://doi.org/10.1098/rsta.2006.1819, 2006.
Baum, R. L. and Godt, J. W.: Early warning of rainfall-induced shallow landslides and debris flows in the USA, Landslides, 7, 259–272, https://doi.org/10.1007/s10346-009-0177-0, 2010.
Bogaard, T. A. and Greco, R.: Landslide hydrology: from hydrology to pore pressure, WIREs Water, 3, 439–459, https://doi.org/10.1002/wat2.1126, 2015.
Calcaterra, D., De Riso, R., Evangelista, A., Nicotera, M. V., Santo, A., and Scotto di Santolo, A.: Slope instabilities in the pyroclastic deposits of the Phlegraean district and the carbonate Apennine (Campania, Italy), Proceedings of an International Workshop on Occurrence and Mechanisms of Flows in Natural Slopes and Earthfills held in Sorrento, Italy, 14–16 May 2003, 61–75, 2004.
Calvello, M. and Piciullo, L.: Assessing the performance of regional landslide early warning models: the EDuMaP method, Nat. Hazards Earth Syst. Sci., 16, 103–122, https://doi.org/10.5194/nhess-16-103-2016, 2016.
Capparelli, G., Giorgio, M., and Greco, R.: Shallow Landslides Risk Mitigation by Early Warning: The Sarno Case, in: Landslide Science and Practice, edited by: Margottini, C., Canuti, P., and Sassa, K., Springer-Verlag, Berlin, 6, 767–772, https://doi.org/10.1007/978-3-642-31319-6_98, 2013.
Capparelli, G. and Tiranti, D.: Application of the MoniFLaIR early warning system for rainfall-induced landslides in Piedmont region (Italy), Landslides, 7, 401–410, https://doi.org/10.1007/s10346-009-0189-9, 2010.
Capparelli, G. and Versace, P.: FLaIR and SUSHI: two mathematical models for early warning of landslides induced by rainfall, Landslides, 8, 67–79, https://doi.org/10.1007/s10346-010-0228-6, 2011.
Cascini, L. and Ferlisi, S.: Occurrence and consequences of flowslides: a case study, Proceedings of an International Conference on Fast Slope Movements – Prediction and Prevention for Risk Mitigation held in Napoli, 11–13 May 2003, 1, 85–92, 2003.
Chleborad, A. F., Baum, R. L., and Godt, J. W.: A prototype system for forecasting landslides in the Seattle, Washington, area, in: Engineering geology and landslides of the Seattle, Washington, area, edited by: Baum, R. L., Godt, J. W., and Highland, L. M., Geological Society of America Reviews in Engineering Geology, Geological Society of America, Boulder, XX, 103–120, https://doi.org/10.1130/2008.4020(06), 2008.
Cranston, M. D. and Tavendale, A. C. W.: Advances in operational flood forecasting in Scotland, P. I. Civil Eng.-Wat. M., 165, 69–87, https://doi.org/10.1680/wama.2012.165.2.79, 2012.
de Riso, R., Budetta, P., Calcaterra, D., and Santo, A.: Riflessioni sul comportamento delle colate rapide non incanalate della Campania, alla luce delle conoscenze pregresse, Proc. National Conf. on La Mitigazione del Rischio da Colate di Fango, Napoli, May, 2–3, 2005, 81–92, 2007.
de Saint-Aubin, C., Garandeau, L., Janet, B., and Javelle, P.: A new French flash flood warning service, in: E3S Web of Conferences, edited by: Samuels, P., Klijn, F., and Lang, M., 3rd European Conference on Flood Risk Management, FLOODrisk 2016, Lyon, France, 17–21 October 2016, EDP Sciences, Les Ulis, 7, 18–24, https://doi.org/10.1051/e3sconf/20160718024, 2016.
Eichenberger, J., Ferrari, A., and Laloui, L.: Early warning thresholds for partially saturated slopes in volcanic ashes, Comput. Geotech., 49, 79–89, https://doi.org/10.1016/j.compgeo.2012.11.002, 2013.
GEO-SLOPE: SEEP/W for finite element seepage analysis,GEO-SLOPE International, Calgary, 2004.
Giorgio, M. and Greco, R.: Rainfall height stochastic modelling as a support tool for floods and flowslides early warning, Water Engineering for a Sustainable Environment, Proceedings of XXXIII IAHR Congress, Vancouver, International Association of Hydraulic Engineering & Research, August 2009, 6812–6819, 2009.
Greco, R. and Bogaard, T. A.: The influence of non-linear hydraulic behavior of slope soil covers on rainfall intensity-duration thresholds, in: Landslides and Engineered Slopes. Experience, Theory and Practice, edited by: Aversa, S., Cascini, L., Picarelli, L., and Scavia, C., 2, 1021–1025, Taylor and Francis, 2016.
Greco, R., Giorgio, M., Capparelli, G., and Versace, P.: Early warning of rainfall-induced landslides based on empirical mobility function predictor, Eng. Geol., 153, 68–79, https://doi.org/10.1016/j.enggeo.2012.11.009, 2013.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol. Atmos. Phys., 98, 239–267, https://doi.org/10.1007/s00703-007-0262-7, 2007.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: The rainfall intensity-duration control of shallow landslides and debris flows: an update, Landslides, 5, 3–17, https://doi.org/10.1007/s10346-007-0112-1, 2008.
Heneker, T. M., Lambert, M. F., and Kuczera, G.: A point rainfall model for risk-based design, J. Hydrol., 247, 54–71, https://doi.org/10.1016/S0022-1694(01)00361-4, 2001.
Iadanza, C., Trigila, A., and Napolitano, F.: Identification and characterization of rainfall events responsible for triggering of debris flows and shallow landslides, J. Hydrol., 541, 230–245, https://doi.org/10.1016/j.jhydrol.2016.01.018, 2016.
Iiritano, G., Versace, P., and Sirangelo, B.: Real-time estimation of hazard for landslides triggered by rainfall, Environ. Geol., 35, 175–183, https://doi.org/10.1007/s002540050303, 1998.
Intrieri, E., Gigli, G., Mugnai, F., Fanti, R., and Casagli, N.: Design and implementation of a landslide early warning system, Eng. Geol., 147–148, https://doi.org/10.1016/j.enggeo.2012.07.017, 2012.
Intrieri, E., Gigli, G., Casagli, N., and Nadim, F.: Brief communication “Landslide Early Warning System: toolbox and general concepts”, Nat. Hazards Earth Syst. Sci., 13, 85–90, https://doi.org/10.5194/nhess-13-85-2013, 2013.
Jakob, M., Owen, T., and Simpson, T.: A regional real-time debris-flow warning system for the District of North Vancouver, Canada, Landslides, 9, 165–178, https://doi.org/10.1007/s10346-011-0282-8, 2012.
Keefer, D. K., Wilson, R. C., Mark, R. K., Brabb, E. E., Brown, W. M., Ellen, S. D., Harp, E. L., Wieczorek, G. F., Alger, C. S., and Zatkin, R. S.: Real-time landslide warning during heavy rainfall, Science, 238, 921–925, https://doi.org/10.1126/science.238.4829.921, 1987.
Liu, X., Liu, Y., Li, L., and Ren, Y.: Disaster monitoring and early-warning system for snow avalanche along Tianshan highway, IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009, Cape Town, South Africa, 12–17 July 2009, IEEE Geoscience and Remote Sensing Society, 2, 11634–11637, https://doi.org/10.1109/IGARSS.2009.5418166, 2009.
Ma, H. and Chi, F.: Major Technologies for Safe Construction of High Earth-Rockfill Dams, Engineering, 2, 498–509, https://doi.org/10.1016/J.ENG.2016.04.001, 2016.
Manconi, A. and Giordan, D.: Landslide failure forecast in near-real-time, Geomatics, Natural Hazards and Risk, 7, 639–648, https://doi.org/10.1080/19475705.2014.942388, 2016.
Mannara, G., Sarnataro, A., Sposito, P., Piccolo, G., Ciancia, N., and Infante, S.: Rete di sensori accelerometrici MEMS per il monitoraggio in continuo di rilievi franosi in ambito ferroviario, SEF09 Sicurezza ed Esercizio Ferroviario I Convegno Nazionale, Roma 20 marzo 2009, 2009.
Martelloni, G., Segoni, S., Fanti, R., and Catani, F.: Rainfall thresholds for the forecasting of landslide occurrence at regional scale, Landslides, 9, 485–495, https://doi.org/10.1007/s10346-011-0308-2, 2012.
Maugeri, M. and Motta, E.: Slope Failure. Effects of Heavy Rainfalls on Slope Behavior: The October 1, 2009 Disaster of Messina (Italy), in: Geotechnics and Earthquake Geotechnics Towards Global Sustainability, Geotechnical, Geological, and Earthquake Engineering, edited by: Iai, S., Springer, Dordrecht, 15, 2011.
Michoud, C., Bazin, S., Blikra, L. H., Derron, M.-H., and Jaboyedoff, M.: Experiences from site-specific landslide early warning systems, Nat. Hazards Earth Syst. Sci., 13, 2659–2673, https://doi.org/10.5194/nhess-13-2659-2013, 2013.
Nicotera, M. and Papa, R.: Comportamento idraulico e meccanico della serie piroclastica di Monteforte Irpino, Progetto PETIT-OSA Monitoraggio Frane: Contributo alle Conoscenze sulla Franosità in Campania, 272–280, ARACNE, 2007.
Ortigao, B. and Justi, M. G.: Rio-Watch: the Rio de Janeiro landslide alarm system, Geotechnical News, 22, 28–31, 2004.
Ozturk, U., Tarakegn, Y. A., Longoni, L., Brambilla, D., Papini, M., and Jensen, J.: A simplified early-warning system for imminent landslide prediction based on failure index fragility curves developed through numerical analysis, Geomatics, Natural Hazards and Risk, 7, 1406–1425, https://doi.org/10.1080/19475705.2015.1058863, 2016.
Pagano, L. and Sica, S.: Earthquake Early Warning for Earth Dams: Concepts and Objectives, Nat. Hazards, 66, 303–318, https://doi.org/10.1007/s11069-012-0486-9, 2013.
Pagano, L., Zingariello, M. C., and Vinale, F.: A large physical model to simulate flowslides in pyroclastic soils, Proc. First European Conf. on Unsaturated Soils: Advances in Geo-Engineering, Durham, 205–213, 2008.
Pagano, L., Picarelli, L., Rianna, G., and Urciuoli, G.: A simple numerical procedure for timely prediction of precipitation-induced landslides in unsaturated pyroclastic soils, Landslides, 7, 273–289, https://doi.org/10.1007/s10346-010-0216-x, 2010.
Papa, M. N., Medina, V., Ciervo, F., and Bateman, A.: Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems, Hydrol. Earth Syst. Sci., 17, 4095–4107, https://doi.org/10.5194/hess-17-4095-2013, 2013.
Peres, D. J. and Cancelliere, A.: Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach, Hydrol. Earth Syst. Sci., 18, 4913–4931, https://doi.org/10.5194/hess-18-4913-2014, 2014.
Piciullo, L., Gariano, S. L., Melillo, M., Brunetti, M. T., Peruccacci, S., Guzzetti, F., and Calvello, M.: Definition and performance of a threshold-based regional early warning model for rainfall-induced landslides, Landslides, 14, 995–1008, https://doi.org/10.1007/s10346-016-0750-2, 2017.
Ponziani, F., Pandolfo, C., Stelluti, M., Berni, N., Brocca, L., and Moramarco, T.: Assessment of rainfall thresholds and soil moisture modeling for operational hydrogeological risk prevention in the Umbria region (central Italy), Landslides, 9, 229–237, https://doi.org/10.1007/s10346-011-0287-3, 2012.
Posner, A. J. and Georgakakos, K. P.: Soil moisture and precipitation thresholds for real-time landslide prediction in El Salvador, Landslides, 12, 1179–1196, https://doi.org/10.1007/s10346-015-0618-x, 2015.
Pumo, D., Francipane, A., Lo Conti, F., Arnone, E., Bitonto, P., Viola, F., La Loggia, G., and Noto, L. V.: The SESAMO early warning system for rainfall-triggered landslides, J. Hydroinform., 18, 256–276, https://doi.org/10.2166/hydro.2015.060, 2016.
Rabuffetti, D. and Barbero, S.: Operational hydro-meteorological warning and real-time flood forecasting: the Piemonte Region case study, Hydrol. Earth Syst. Sci., 9, 457–466, https://doi.org/10.5194/hess-9-457-2005, 2005.
Reder, A., Pagano, L., Picarelli, L., and Rianna, G.: The role of the lowermost boundary conditions in the hydrological response of shallow sloping covers, Landslides 14, 3, 861–873, https://doi.org/10.1007/s10346-016-0753-z, 2017.
Rianna, G., Pagano, L., and Urciuoli, G.: Rainfall patterns triggering shallow flowslides in pyroclastic soils, Eng. Geol., 174, 22–35, https://doi.org/10.1016/j.enggeo.2014.03.004, 2014a.
Rianna, G., Pagano, L., and Urciuoli, G.: Investigation of soil-atmosphere interaction in pyroclastic soils, J. Hydrol., 510, 480–492, https://doi.org/10.1016/j.jhydrol.2013.12.042, 2014b.
Ruiz-Villanueva, V., Bodoque, J. M., Díez-Herrero, A., and Calvo, C.: Triggering threshold precipitation and soil hydrological characteristics of shallow landslides in granitic landscapes, Geomorphology, 133, 178–189, https://doi.org/10.1016/j.geomorph.2011.05.018, 2011.
Santo, A., Di Crescenzo, G., Del Prete, S., and Di Iorio, L.: The Ischia island flash flood of November 2009 (Italy): Phenomenon analysis and flood hazard, Phys. Chem. Earth, 49, 3–17, https://doi.org/10.1016/j.pce.2011.12.004, 2012.
Schmidt, J., Turek, G., Clark, M. P., Uddstrom, M., and Dymond, J. R.: Probabilistic forecasting of shallow, rainfall-triggered landslides using real-time numerical weather predictions, Nat. Hazards Earth Syst. Sci., 8, 349–357, https://doi.org/10.5194/nhess-8-349-2008, 2008.
Segoni, S., Battistini, A., Rossi, G., Rosi, A., Lagomarsino, D., Catani, F., Moretti, S., and Casagli, N.: Technical Note: An operational landslide early warning system at regional scale based on space–time–variable rainfall thresholds, Nat. Hazards Earth Syst. Sci., 15, 853–861, https://doi.org/10.5194/nhess-15-853-2015, 2015.
Segoni, S., Rossi, G., Rosi, A., and Catani, F.: Landslides triggered by rainfall: a semiautomated procedure to define consistent intensity-duration thresholds, Comput. Geosci., 63, 123–131, https://doi.org/10.1016/j.cageo.2013.10.009, 2014.
Sirangelo, B. and Braca, G.: Identification of hazard conditions for mudflow occurrence by hydrological model. Application of FLaIR model to Sarno warning system, Eng. Geol., 73, 267–276, https://doi.org/10.1016/j.enggeo.2004.01.008, 2004.
Sirangelo, B. and Versace, P.: A real time forecasting model for landslides triggered by rainfall, Meccanica, 31, 73–85, https://doi.org/10.1007/BF00444156, 1996.
Sirangelo, B., Versace, P., and Capparelli, G.: Forwarning model for landslides triggered by rainfall based on the analysis of historical data file, in: Hydrology of the Mediterranean and Semiarid Regions, edited by: Servat, E., Najem, W., Leduc, C., and Shakeel, A., IAHS Publ., 278, 298–304, 2003.
Tarolli, P., Borga, M., Chang, K. T., and Chiang, S. H.: Modeling shallow landsliding susceptibility by incorporating heavy rainfall statistical properties, Geomorphology, 133, 199–211, https://doi.org/10.1016/j.geomorph.2011.02.033, 2011.
Terlien, M. T. J.: The determination of statistical and deterministic hydrological landslide-triggering thresholds, Environ. Geol., 35, 124–130, https://doi.org/10.1007/s002540050299, 1998.
Terranova, O. G., Gariano, S. L., Iaquinta, P., and Iovine, G. G. R.: GASAKe: forecasting landslide activations by a genetic-algorithms-based hydrological model, Geosci. Model Dev., 8, 1955–1978, https://doi.org/10.5194/gmd-8-1955-2015, 2015.
Tiranti, D., Cremonini, R., Marco, F., Gaeta, A. R., and Barbero, S.: The DEFENSE (Debris Flows triggered by storms-Nowcasting SystEm): an early warning system for torrential processes by radar storm tracking using a Geographic Information System (GIS), Comput. Geosci., 70, 96–109, https://doi.org/10.1016/j.cageo.2014.05.004, 2014.
Tiranti, D. and Rabuffetti, D.: Estimation of rainfall thresholds triggering shallow landslides for an operational warning system implementation, Landslides, 7, 471–481, https://doi.org/10.1007/s10346-010-0198-8, 2010.
UN-ISDR (United Nations Inter-Agency Secretariat of theInternational Strategy for Disaster Reduction): Hyogo framework for action 2005–2015: building the resilience of nations and communities to disasters, World Conference on Disaster Reduction, Kobe, Japan, January 2005, available at: https://www.unisdr.org/2005/wcdr/intergover/official-doc/L-docs/Hyogo-framework-for-action-english.pdf (last access: 6 December 2017), 2005.
UN-ISDR (United Nations Inter-Agency Secretariat of the International Strategy for Disaster Reduction): Global Survey of Early Warning Systems: an assessment of capacities, gaps and opportunities towards building a comprehensive global early warning system for all natural hazards available at: http://www.unisdr.org/2006/ppew/info-resources/ewc3/Global-Survey-of-Early-Warning-Systems.pdf (last access: 6 December 2017), 2006.
Varnes, D. J.: Slope movement types and processes, in: Special Report 176, edited by: Schuster, R. L. and Krizek, R. J., Landslides, Analysis and Control, Transportation and Road Research Board, National Academy of Science, Washington DC, 11–33, 1978.
Short summary
The paper focuses on the main features characterizing predictive models working in early warning systems (EWS), by discussing their aims, the evolution stage of the phenomenon where they should be incardinated, and their architecture, regardless of the specific application field. With reference to flow-like landslide and earth flows, some alternative approaches to the development of the predictive tool and to its implementation in an EWS are described.
The paper focuses on the main features characterizing predictive models working in early warning...
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