Articles | Volume 19, issue 4
https://doi.org/10.5194/nhess-19-791-2019
© Author(s) 2019. 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-19-791-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Apr 2019
Research article |
| 17 Apr 2019
| 17 Apr 2019
Probabilistic forecasting of plausible debris flows from Nevado de Colima (Mexico) using data from the Atenquique debris flow, 1955
Andrea Bevilacqua
CORRESPONDING AUTHOR
Department of Earth Sciences, SUNY at Buffalo, Buffalo, NY, 14260, USA
Computational Data Science and Engineering programme, SUNY at Buffalo, Buffalo, NY, 14260, USA
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Pisa, 56126, Italy
Abani K. Patra
Department of Mechanical and Aerospace Engineering, SUNY at Buffalo, NY, 14260, USA
Computational Data Science and Engineering programme, SUNY at Buffalo, Buffalo, NY, 14260, USA
Marcus I. Bursik
Department of Earth Sciences, SUNY at Buffalo, Buffalo, NY, 14260, USA
E. Bruce Pitman
Department of Materials Design and Innovation, SUNY at Buffalo, Buffalo, NY, 14260, USA
José Luis Macías
Departamento de Vulcanología, Instituto de Geofísica, UNAM, Mexico City, DF, 04510, Mexico
Ricardo Saucedo
Instituto de Geología, Facultad de Ingeniería, UASLP, San Luis, SLP, 78240, Mexico
David Hyman
Department of Earth Sciences, SUNY at Buffalo, Buffalo, NY, 14260, USA
now at: Collaborative Institute for Meteorological Satellite Studies, UW, Madison, WI, 53706, USA
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We evaluate through first-order kinetic energy models, the minimum volume and mass of a pyroclastic density current generated at the Aso caldera that might affect any of five distal infrastructure sites. These target sites are all located 115–145 km from the caldera, but in well-separated directions. Our constraints of volume and mass are then compared with the scale of Aso-4, the largest caldera-forming eruption of Aso.
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In this paper we test a simplified numerical model for pyroclastic density currents or PDCs (mixtures of hot gas, lapilli and ash moving across the landscape under the effect of gravity). The aim is quantifying the differences between real and modelled deposits of some PDCs of the 79 CE eruption of Vesuvius, Italy. This step is important because in the paper it is demonstrated that this simplified model is useful for constraining input parameters for more computationally expensive models.
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In this work, we present new methods for calculating the mean, standard deviation, median, and modal locations of the boundaries of volcanic hazards. These calculations are based on a new, mathematically rigorous definition of probabilistic hazard maps – a way to map the probabilities of inundation by a given hazard. We apply this analysis to several models of volcanic flows: simple models of viscous flows, complex models of a tabletop granular flow, and a complex model of a volcanic mud flow.
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This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Fire in steep landscapes increases the potential for debris flows that can develop during intense rainstorms. To explore possible debris flow hazards, we utilize a computational model of the physical processes of debris flow initiation and runout. Such process-based models are computationally intensive and of limited use in rapid hazard assessments. Thus we build statistical surrogate of these physical models to examine how inundation footprints vary with rainfall intensity and time since fire.
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We evaluate through first-order kinetic energy models, the minimum volume and mass of a pyroclastic density current generated at the Aso caldera that might affect any of five distal infrastructure sites. These target sites are all located 115–145 km from the caldera, but in well-separated directions. Our constraints of volume and mass are then compared with the scale of Aso-4, the largest caldera-forming eruption of Aso.
Andrea Bevilacqua, Alvaro Aravena, Augusto Neri, Eduardo Gutiérrez, Demetrio Escobar, Melida Schliz, Alessandro Aiuppa, and Raffaello Cioni
Nat. Hazards Earth Syst. Sci., 21, 1639–1665, https://doi.org/10.5194/nhess-21-1639-2021, https://doi.org/10.5194/nhess-21-1639-2021, 2021
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We present novel probability maps for the opening position of new vents in the San Salvador (El Salvador) and Nejapa-Chiltepe (Nicaragua) volcanic complexes. In particular, we present thematic maps, i.e., we consider different hazardous phenomena separately. To illustrate the significant effects of considering the expected eruption style in the construction of vent opening maps, we focus on the analysis of small-scale pyroclastic density currents using an approach based on numerical modeling.
Alessandro Tadini, Andrea Bevilacqua, Augusto Neri, Raffaello Cioni, Giovanni Biagioli, Mattia de'Michieli Vitturi, and Tomaso Esposti Ongaro
Solid Earth, 12, 119–139, https://doi.org/10.5194/se-12-119-2021, https://doi.org/10.5194/se-12-119-2021, 2021
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In this paper we test a simplified numerical model for pyroclastic density currents or PDCs (mixtures of hot gas, lapilli and ash moving across the landscape under the effect of gravity). The aim is quantifying the differences between real and modelled deposits of some PDCs of the 79 CE eruption of Vesuvius, Italy. This step is important because in the paper it is demonstrated that this simplified model is useful for constraining input parameters for more computationally expensive models.
David M. Hyman, Andrea Bevilacqua, and Marcus I. Bursik
Nat. Hazards Earth Syst. Sci., 19, 1347–1363, https://doi.org/10.5194/nhess-19-1347-2019, https://doi.org/10.5194/nhess-19-1347-2019, 2019
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In this work, we present new methods for calculating the mean, standard deviation, median, and modal locations of the boundaries of volcanic hazards. These calculations are based on a new, mathematically rigorous definition of probabilistic hazard maps – a way to map the probabilities of inundation by a given hazard. We apply this analysis to several models of volcanic flows: simple models of viscous flows, complex models of a tabletop granular flow, and a complex model of a volcanic mud flow.
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G. Córdoba, M. F. Sheridan, and E. B. Pitman
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Manuscript not accepted for further review
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The program predictions fits within 10% of tested analytical and field data.
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Preprint under review for NHESS
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Elevation models are compared with a true dataset for terrain characteristics which selects a better ranking model to test with different parameters for partitioning the terrain. The partitioning of the terrain is measured by how well a partitioned unit can support the mapped landslide area and number of landslides. The effect of this relationship is reflected with different metrics in the susceptibility maps.
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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.
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.
Yu Zhuang, Brian W. McArdell, and Perry Bartelt
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-87, https://doi.org/10.5194/nhess-2024-87, 2024
Revised manuscript accepted for NHESS
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This study reformulates the μ(I) rheology into a Voellmy-type relationship to elucidate its physical implications. The μ(I) rheology, incorporating a dimensionless inertial number, mimics granular temperature effects, reflecting shear thinning behavior of mass flows. However, its constant Coulomb friction coefficient limits accuracy in modeling deposition. Comparing μ(I) with Voellmy-type rheologies reveals strengths and limitations, enhancing mass flow modeling and engineering applications.
Roberto Sarro, Mauro Rossi, Paola Reichenbach, and Rosa María Mateos
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-85, https://doi.org/10.5194/nhess-2024-85, 2024
Revised manuscript accepted for NHESS
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This study proposes a novel workflow to precisely model rockfalls. It compares three methods for defining source areas to enhance model accuracy. Identified areas are inputted into a runout model to identify vulnerable zones. A new approach generates probabilistic susceptibility maps using ECDFs. Validation strategies employing various inventory types are included. Comparing six susceptibility maps highlights the impact of source area definition on model precision.
Sonam Rinzin, Stuart Dunning, Rachel Carr, Ashim Sattar, and Martin Mergili
EGUsphere, https://doi.org/10.5194/egusphere-2024-1819, https://doi.org/10.5194/egusphere-2024-1819, 2024
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We evaluated the sensitivity of model outputs to input parameter uncertainties by performing multiple GLOF simulations using the r.avaflow model. We found out that GLOF modelling outputs are highly sensitive to six parameters: volume of mass movements entering lakes, DEM datasets, origin of mass movements, mesh size, basal frictional angle, and entrainment coefficient. Future modelling should carefully consider the output uncertainty from these sensitive parameters.
Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley
Nat. Hazards Earth Syst. Sci., 24, 2359–2374, https://doi.org/10.5194/nhess-24-2359-2024, https://doi.org/10.5194/nhess-24-2359-2024, 2024
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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.
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.
Jane Walden, Mylène Jacquemart, Bretwood Higman, Romain Hugonnet, Andrea Manconi, and Daniel Farinotti
EGUsphere, https://doi.org/10.5194/egusphere-2024-1086, https://doi.org/10.5194/egusphere-2024-1086, 2024
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In a study of eight landslides adjacent to glaciers in Alaska, we found that landslide movement increased as the glacier retreated past the landslide at four sites. Movement at other sites coincided with heavy precipitation or increased glacier thinning, and two sites showed little-to-no motion. We suggest that landslides next to water-terminating glaciers may be especially vulnerable to acceleration, which we guess is due to faster retreat rates and water replacing ice at the landslide edge.
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024, https://doi.org/10.5194/nhess-24-1741-2024, 2024
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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.
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.
Maximillian Van Wyk de Vries, Alexandre Dunant, Amy L. Johnson, Erin L. Harvey, Sihan Li, Katherine Arrell, Jeevan Baniya, Dipak Basnet, Gopi K. Basyal, Nyima Dorjee Bhotia, Simon J. Dadson, Alexander L. Densmore, Tek Bahadur Dong, Mark E. Kincey, Katie Oven, Anuradha Puri, and Nick J. Rosser
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-40, https://doi.org/10.5194/nhess-2024-40, 2024
Revised manuscript accepted for NHESS
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Mapping exposure to landslides is necessary to mitigate risk and reduce vulnerability. In this study, we show that there is a poor correlation between building damage and deaths from landslides- such that the deadliest landslides do not always destroy the most buildings and vice versa. This has important implications for our management on landslide risk.
Ashok Dahal, Hakan Tanyas, Cees van Westen, Mark van der Meijde, Paul Martin Mai, Raphaël Huser, and Luigi Lombardo
Nat. Hazards Earth Syst. Sci., 24, 823–845, https://doi.org/10.5194/nhess-24-823-2024, https://doi.org/10.5194/nhess-24-823-2024, 2024
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We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
Li-Ru Luo, Zhi-Xiang Yu, Li-Jun Zhang, Qi Wang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci., 24, 631–649, https://doi.org/10.5194/nhess-24-631-2024, https://doi.org/10.5194/nhess-24-631-2024, 2024
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We performed field investigations on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was obtained from an unmanned aerial vehicle survey. A finite element model was created to reproduce the damage evolution. We found that the impact kinetic energy was below the design protection energy. Improper member connections prevent the barrier from producing significant deformation to absorb energy. Damage is avoided by improving the ability of the nets and ropes to slide.
Sudhanshu Dixit, Srikrishnan Siva Subramanian, Piyush Srivastava, Ali P. Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci., 24, 465–480, https://doi.org/10.5194/nhess-24-465-2024, https://doi.org/10.5194/nhess-24-465-2024, 2024
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Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards. Large-scale sediment disasters like landslides, debris flows, and flash floods happen frequently in the Himalayas because of their propensity for intense precipitation events. We provide a new framework that combines the Weather Research and Forecasting (WRF) model with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, https://doi.org/10.5194/nhess-24-1-2024, 2024
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Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
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The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
Xushan Shi, Bo Chai, Juan Du, Wei Wang, and Bo Liu
Nat. Hazards Earth Syst. Sci., 23, 3425–3443, https://doi.org/10.5194/nhess-23-3425-2023, https://doi.org/10.5194/nhess-23-3425-2023, 2023
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A 3D stability analysis method is proposed for biased rockfall with external erosion. Four failure modes are considered according to rockfall evolution processes, including partial damage of underlying soft rock and overall failure of hard rock blocks. This method is validated with the biased rockfalls in the Sichuan Basin, China. The critical retreat ratio from low to moderate rockfall susceptibility is 0.33. This method could facilitate rockfall early identification and risk mitigation.
Marius Schneider, Nicolas Oestreicher, Thomas Ehrat, and Simon Loew
Nat. Hazards Earth Syst. Sci., 23, 3337–3354, https://doi.org/10.5194/nhess-23-3337-2023, https://doi.org/10.5194/nhess-23-3337-2023, 2023
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Rockfalls and their hazards are typically treated as statistical events based on rockfall catalogs, but only a few complete rockfall inventories are available today. Here, we present new results from a Doppler radar rockfall alarm system, which has operated since 2018 at a high frequency under all illumination and weather conditions at a site where frequent rockfall events threaten a village and road. The new data set is used to investigate rockfall triggers in an active rockslide complex.
Annette I. Patton, Lisa V. Luna, Joshua J. Roering, Aaron Jacobs, Oliver Korup, and Benjamin B. Mirus
Nat. Hazards Earth Syst. Sci., 23, 3261–3284, https://doi.org/10.5194/nhess-23-3261-2023, https://doi.org/10.5194/nhess-23-3261-2023, 2023
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Landslide warning systems often use statistical models to predict landslides based on rainfall. They are typically trained on large datasets with many landslide occurrences, but in rural areas large datasets may not exist. In this study, we evaluate which statistical model types are best suited to predicting landslides and demonstrate that even a small landslide inventory (five storms) can be used to train useful models for landslide early warning when non-landslide events are also included.
Sandra Melzner, Marco Conedera, Johannes Hübl, and Mauro Rossi
Nat. Hazards Earth Syst. Sci., 23, 3079–3093, https://doi.org/10.5194/nhess-23-3079-2023, https://doi.org/10.5194/nhess-23-3079-2023, 2023
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The estimation of the temporal frequency of the involved rockfall processes is an important part in hazard and risk assessments. Different methods can be used to collect and analyse rockfall data. From a statistical point of view, rockfall datasets are nearly always incomplete. Accurate data collection approaches and the application of statistical methods on existing rockfall data series as reported in this study should be better considered in rockfall hazard and risk assessments in the future.
Stefan Hergarten
Nat. Hazards Earth Syst. Sci., 23, 3051–3063, https://doi.org/10.5194/nhess-23-3051-2023, https://doi.org/10.5194/nhess-23-3051-2023, 2023
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Rockslides are a major hazard in mountainous regions. In formerly glaciated regions, the disposition mainly arises from oversteepened topography and decreases through time. However, little is known about this decrease and thus about the present-day hazard of huge, potentially catastrophic rockslides. This paper presents a new theoretical framework that explains the decrease in maximum rockslide size through time and predicts the present-day frequency of large rockslides for the European Alps.
Colin K. Bloom, Corinne Singeisen, Timothy Stahl, Andrew Howell, Chris Massey, and Dougal Mason
Nat. Hazards Earth Syst. Sci., 23, 2987–3013, https://doi.org/10.5194/nhess-23-2987-2023, https://doi.org/10.5194/nhess-23-2987-2023, 2023
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Landslides are often observed on coastlines following large earthquakes, but few studies have explored this occurrence. Here, statistical modelling of landslides triggered by the 2016 Kaikōura earthquake in New Zealand is used to investigate factors driving coastal earthquake-induced landslides. Geology, steep slopes, and shaking intensity are good predictors of landslides from the Kaikōura event. Steeper slopes close to the coast provide the best explanation for a high landslide density.
Cited articles
Aghakhani, H., Dalbey, K., Salac, D., and Patra, A. K.: Heuristic and Eulerian
interface capturing approaches for shallow water type flow and application to
granular flows, Comput. Meth. Appl. Mech. Eng., 304, 243–264, https://doi.org/10.1016/j.cma.2016.02.021, 2016. a
Ai, M., Kong, X., and Li, K.: A general theory for orthogonal array based latin
hypercube sampling, Statist. Sin., 26, 761–777, https://doi.org/10.5705/ss.202015.0029, 2016. a
Akhavan-Safaei, A.: Analysis and Implementation of Multiple Models and
Multi-Models for Shallow-Water Type Models of Large Mass Flows, MS thesis,
University at Buffalo, Buffalo, 2018. a
Allan, J.: Geology of the northern Colima and Zacoalco grabens, southwest Mexico:
Late Cenozoic rifting in the Mexican volcanic belt, Geol. Soc. Am. Bull., 97,
473–485, https://doi.org/10.1130/0016-7606(1986)97<473:GOTNCA>2.0.CO;2, 1986. a
Bartelt, P. and McArdell, B.: Granulometric investigations of snow avalanches,
J. Glaciol., 55, 829–833, 2009. a
Bartelt, P., Salm, B., and Gruber, U.: Calculating dense-snow avalanche runout
using a Voellmy-fluid model with active/passive longitudinal straining, J.
Glaciol., 45, 242–254, 1999. a
Bayarri, M. J., Berger, J. O., Calder, E. S., Dalbey, K., Lunagomez, S., Patra,
A. K., Pitman, E. B., Spiller, E. T., and Wolpert, R. L.: Using Statistical and
Computer Models to Quantify Volcanic Hazards, Technometrics, 51, 402–413,
https://doi.org/10.1198/TECH.2009.08018, 2009. a
Capra, L., Manea, V. C., Manea, M., and Norini, G.: The importance of digital
elevation model resolution on granular flow simulations: a test case for Colima
volcano using TITAN2D computational routine, Nat. Hazards, 59, 665–680,
https://doi.org/10.1007/s11069-011-9788-6, 2011. a
Charbonnier, S. J. and Gertisser, R.: Numerical simulations of block-and-ash
flows using the Titan2D flow model: examples from the 2006 eruption of Merapi
Volcano, Java, Indonesia, Bull. Volcanol., 71, 953–959, https://doi.org/10.1007/s00445-009-0299-1, 2009. a
Christen, M., Kowalski, J., and Bartelt, P.: RAMMS: Numerical simulation of
dense snow avalanches in three-dimensional terrain, Cold Reg. Sci. Technol.,
63, 1–14, https://doi.org/10.1016/j.coldregions.2010.04.005, 2010. a
Cortés, A., Garduño, V., Navarro, C., Komorowski, J., Saucedo, R.,
Macías, J., and Gavilanes, J.: Geología del Complejo Volcánico de
Colima, Series de Cartas y Mapas del Instituto de Geología, 10, 37, 2005. a
Cortés, A., Garduño, V., Navarro-Ochoa, C., Komorowski, J., Saucedo, R.,
Macías, J., and Gavilanes, J.: Geologic mapping of the Colima Volcanic
Complex (Mexico), and implications for hazard assessment, in: vol. Stratigraphy
and Geology of Volcanic Areas, chap. 12, Geological Society of America, Boulder,
Colorado, USA, 251–266, https://doi.org/10.1130/2010.2464(12), 2010. a
Dade, W. B. and Huppert, H. E.: Long-runout rockfalls, Geology, 26, 803–806,
https://doi.org/10.1130/0091-7613(1998)026<0803:LRR>2.3.CO;2, 1998. a
Dalbey, K. R.: Predictive Simulation and Model Based Hazard Maps, PhD thesis,
University at Buffalo, Buffalo, 2009. a
Dalbey, K. R., Patra, A. K., Pitman, E. B., Bursik, M. I., and Sheridan, M. F.:
Input uncertainty propagation methods and hazard mapping of geophysical mass
flows, J. Geophys. Res.-Solid, 113, 1–16, https://doi.org/10.1029/2006JB004471, 2008. a
Drucker, D. C. and Prager, W.: Soil mechanics and plastic analysis for limit
design, Q. Appl. Math., 10, 157–165, 1952. a
Farrell, K., Tinsley, J., and Faghihi, D.: A Bayesian framework for adaptive
selection, calibration, and validation of coarse-grained models of atomistic
systems, J. Comput. Phys., 295, 189–208, https://doi.org/10.1016/J.JCP.2015.03.071, 2015. a
Fischer, J., Kowalski, J., and Pudasaini, S. P.: Topographic curvature effects
in applied avalanche modeling, Cold Reg. Sci. Technol., 74–75, 21–30,
https://doi.org/10.1016/j.coldregions.2012.01.005, 2012. a, b
Forterre, Y. and Pouliquen, O.: Long-surface-wave instability in dense granular
flows, J. Fluid Mech., 486, 21–50, https://doi.org/10.1017/S0022112003004555, 2003. a, b, c, d
Ghosh, T. and Krishnamurti, T. N.: Improvements in Hurricane Intensity Forecasts
from a Multimodel Superensemble Utilizing a Generalized Neural Network Technique,
Weather Forecast., 33, 873–885, https://doi.org/10.1175/WAF-D-17-0006.1, 2018. a
Gilbert, S.: Model building and a definition of science, J. Res. Sci. Teach.,
28, 73–79, https://doi.org/10.1002/tea.3660280107, 1991. a
Gruber, U. and Bartelt, P.: Snow avalanche hazard modelling of large areas
using shallow water numerical models and GIS, Environ. Model. Softw., 22,
1472–1481, https://doi.org/10.1016/j.envsoft.2007.01.001, 2007. a
Iverson, R. M. and George, D. L.: A depth-averaged debris-flow model that
includes the effects of evolving dilatancy. I. Physical basis, P. Roy. Soc.
Lond. A, 470, 20130819, https://doi.org/10.1098/rspa.2013.0819, 2014. a
Kelfoun, K.: Suitability of simple rheological laws for the numerical simulation
of dense pyroclastic flows and long-runout volcanic avalanches, J. Geophysi.
Res., 116, B08209, https://doi.org/10.1029/2010JB007622, 2011. a
Kelfoun, K., Samaniego, P., Palacios, P., and Barba, D.: Testing the suitability
of frictional behaviour for pyroclastic flow simulation by comparison with a
well-constrained eruption at Tungurahua volcano (Ecuador), Bull. Volcanol., 71,
1057–1075, https://doi.org/10.1007/s00445-009-0286-6, 2009. a
Kern, M., Bartelt, P., Sovilla, B., and Buser, O.: Measured shear rates in large
dry and wet snow avalanches, J. Glaciol., 55, 327–338, 2009. a
Krishnamurti, T. N., Kumar, V., Simon, A., Bhardwaj, A., Ghosh, T., and Ross,
R.: A review of multimodel superensemble forecasting for weather, seasonal
climate, and hurricanes, Rev. Geophys., 54, 336–377, https://doi.org/10.1002/2015RG000513, 2016. a
Luhr, J. and Carmichael, J.: Geology of the Volán de Colima, Serie de
Divulgación, Universidad Nacional de México, Instituto de Geología, México, 1990. a
Macorps, E., Charbonnier, S. J., Varley, N. R., Capra, L., Atlas, Z., and
Cabré, J.: Stratigraphy, sedimentology and inferred flow dynamics from the
July 2015 block-and-ash flow deposits at Volcán de Colima, Mexico, J.
Volcanol. Geoth. Res., 349, 99–116, https://doi.org/10.1016/j.jvolgeores.2017.09.025, 2018. a
McKay, M. D., Beckman, R. J., and Conover, W. J.: A comparison of three methods
for selecting values of input variables in the analysis of output from a
computer code, Technometrics, 21, 239–245, 1979. a
Mooser, F.: Los volcanes de Colima, in: vol. 61, Universidad Nacional
Autónoma de México, Instituto de Geología, México, 49–71, 1961. a
Norini, G., De Beni, E., Andronico, D., Polacci, M., Burton, M., and Zucca, F.:
The 16 November 2006 flank collapse of the south-east crater at Mount Etna,
Italy: Study of the deposit and hazard assessment, J. Geophys. Res.-Solid Earth,
114, b02204, https://doi.org/10.1029/2008JB005779, 2009. a
Ogburn, S. E., Berger, J., Calder, E. S., Lopes, D., Patra, A., Pitman, E. B.,
Rutarindwa, R., Spiller, E., and Wolpert, R. L.: Pooling strength amongst
limited datasets using hierarchical Bayesian analysis, with application to
pyroclastic density current mobility metrics, Stat. Volcanol., 2, 1–26,
https://doi.org/10.5038/2163-338X.2.1, 2016. a
Owen, A. B.: Orthogonal arrays for computer experiments, integration and
visualization, Statist. Sin., 2, 439–452, 1992a. a
Owen, A. B.: A Central Limit Theorem for Latin Hypercube Sampling, J. Roy.
Stat. Soc., 54, 541–551, 1992b. a
Patra, A. K., Bauer, A. C., Nichita, C. C., Pitman, E. B., Sheridan, M. F.,
Bursik, M., Rupp, B., Webber, A., Stinton, A. J., Namikawa, L. M., and Renschler,
C. S.: Parallel adaptive numerical simulation of dry avalanches over natural
terrain, J. Volcanol. Geoth. Res., 139, 1–21, https://doi.org/10.1016/j.jvolgeores.2004.06.014, 2005. a, b
Patra, A. K., Nichita, C., Bauer, A., Pitman, E., Bursik, M., and Sheridan, M.:
Parallel adaptive discontinuous Galerkin approximation for thin layer avalanche
modeling, Comput. Geosci., 32, 912–926, https://doi.org/10.1016/j.cageo.2005.10.023, 2006. a
Patra, A. K., Bevilacqua, A., and Akhavan-Safaei, A.: Analyzing Complex Models
using Data and Statistics, in: vol. 10861 of ICCS, Lecture Notes in Computer
Science, chap. 57, Springer, Cham, iSBN 978-3-319-93701-4, 724–736, 2018a. a
Pitman, E. B. and Le, L.: A two-fluid model for avalanche and debris flows, P.
Roy. Soc. Lond. A, 363, 1573–601, https://doi.org/10.1098/rsta.2005.1596, 2005. a
Popper, K. R.: The Logic of Scientific Discovery, Routledge, London, New York,
https://doi.org/10.2307/2104331, 1959. a
Procter, J. N., Cronin, S. J., Platz, T., Patra, A., Dalbey, K., Sheridan, M.,
and Neall, V.: Mapping block-and-ash flow hazards based on Titan 2D simulations:
a case study from Mt. Taranaki, NZ, Nat. Hazards, 53, 483–501,
https://doi.org/10.1007/s11069-009-9440-x, 2010. a
Pudasaini, S. P. and Hutter, K.: Rapid shear flows of dry granular masses down
curved and twisted channels, J. Fluid Mech., 495, 193–208, 2003. a
Ranjan, P. and Spencer, N.: Space-filling Latin hypercube designs based on
randomization restrictions in factorial experiments, Stat. Probab. Lett., 94,
239–247, https://doi.org/10.1016/j.spl.2014.07.032, 2014. a
Rankine, W. J. M.: On the Stability of Loose Earth, Philos. T. Roy. Soc. Lond.,
147, 9–27, 1857. a
Robin, C., Mossand, P., Camus, G., Cantagrel, J., Gourgaud, A., and Vincent,
P.: Eruptive history of the Colima volcanic complex (Mexico), J. Volcanol.
Geoth. Res., 31, 99–113, https://doi.org/10.1016/0377-0273(87)90008-4, 1987. a
Rupp, B., Bursik, M., Namikawa, L., Webb, A., Patra, A. K., Saucedo, R.,
Macías, J. L., and Renschler, C.: Computational modeling of the 1991 block
and ash fows at Colima Volcano, Mèxico, Geol. Soc. Am. Spec. Pap., 402,
223–237, https://doi.org/10.1130/2006.2402(11), 2006. a
Salm, B.: Flow, flow transition and runout distances of flowing avalanches,
Ann. Glaciol., 18, 221–226, 1993. a
Saucedo, R.: The 1955 debris flow generated by intense rain fall at Atenquique,
Jalisco, Mexico, in: Regional Geomorphology Conference, Mexico City, Mexico, 2003. a
Saucedo, R., Macías, J., Gavilanes, J., Arce, J., Komorowski, J., Gardner,
J., and Valdez-Moreno, G.: Eyewitness, stratigraphy, chemistry, and eruptive
dynamics of the 1913 Plinian eruption of Volcán de Colima, México, J.
Volcanol. Geoth. Res., 191, 149–166, https://doi.org/10.1016/j.jvolgeores.2010.01.011, 2010. a
Savage, S. B. and Hutter, K.: The motion of a finite mass of granular material
down a rough incline, J. Fluid Mech., 199, 177–215, https://doi.org/10.1017/S0022112089000340, 1989. a, b, c
Sheridan, M. F., Stinton, A., Patra, A., Pitman, E., Bauer, A., and Nichita, C.:
Evaluating Titan2D mass-flow model using the 1963 Little Tahoma Peak avalanches,
Mount Rainier, Washington, J. Volcanol. Geoth. Res., 139, 89–102,
https://doi.org/10.1016/j.jvolgeores.2004.06.011, 2005. a
Sheridan, M. F., Patra, A. K., Dalbey, K., and Hubbard, B.: Probabilistic
digital hazard maps for avalanches and massive pyroclastic flows using TITAN2D,
in: vol. Stratigraphy and geology of volcanic areas, chap. 14, Geological
Society of America, Boulder, Colorado, USA, 281–291, https://doi.org/10.1130/2010.2464(14), 2010. a
Spiller, E. T., Bayarri, M. J., Berger, J. O., Calder, E. S., Patra, A. K.,
Pitman, E. B., and Wolpert, R. L.: Automating Emulator Construction for
Geophysical Hazard Maps, SIAM/ASA J. Uncertain. Quant., 2, 126–152,
https://doi.org/10.1137/120899285, 2014.
a
Stefanescu, E. R., Bursik, M., Cordoba, G., Dalbey, K., Jones, M. D., Patra, A.
K., Pieri, D. C., Pitman, E. B., and Sheridan, M. F.: Digital elevation model
uncertainty and hazard analysis using a geophysical flow model, P. Roy. Soc.
Lond. A, 468, 1543–1563, https://doi.org/10.1098/rspa.2011.0711, 2012a. a
Stefanescu, E. R., Bursik, M., and Patra, A. K.: Effect of digital elevation
model on Mohr–Coulomb geophysical flow model output, Nat. Hazards, 62, 635–656,
https://doi.org/10.1007/s11069-012-0103-y, 2012b. a
Stein, M.: Large Sample Properties of Simulations Using Latin Hypercube Sampling,
Technometrics, 29, 143–151, 1987. a
Sulpizio, R., Capra, L., Sarocchi, D., Saucedo, R., Gavilanes-Ruiz, J., and
Varley, N.: Predicting the block-and-ash flow inundation areas at Volcán
de Colima (Colima, Mexico) based on the present day (February 2010) status,
J. Volcanol. Geoth. Res., 193, 49–66, https://doi.org/10.1016/j.jvolgeores.2010.03.007, 2010. a
Tang, B.: Orthogonal Array-Based Latin Hypercubes, J. Am. Stat. Assoc., 88,
1392–1397, 1993. a
Tarantola, A.: Inverse Problem Theory: Methods for Data Fitting and Model
Parameter Estimation, Elsevier, Amsterdam, New York, 1987. a
Tarantola, A. and Valette, B.: Inverse Problems = Quest for Information,
J. Geophys., 50, 159–170, 1982. a
VHUB: Titan2D Mass-Flow Simulation Tool, v 4.0.0, available at:
https://vhub.org/resources/titan2d, last access: 23 June 2016. a
Yu, B., Dalbey, K., Webb, A., Bursik, M., Patra, A. K., Pitman, E. B., and
Nichita, C.: Numerical issues in computing inundation areas over natural
terrains using Savage-Hutter theory, Nat. Hazards, 50, 249–267, https://doi.org/10.1007/s11069-008-9336-1, 2009. a
Zobin, V., Arámbula, R., Bretón, M., Reyes, G., Plascencia, I., Navarro,
C., Téllez, A., Campos, A., González, M., León, Z., Martínez,
A., and Ramírez, C.: Dynamics of the January 2013–June 2014 explosive-effusive
episode in the eruption of Volcán de Colima, México: insights from
seismic and video monitoring, Bull. Volcanol., 77, 31, https://doi.org/10.1007/s00445-015-0917-z, 2015. a
Short summary
We introduce a new prediction-oriented method for hazard assessment of volcaniclastic debris flows, based on multiple models. We apply our procedure to a case study of the 1955 Atenquique flow, using three widely used depth-averaged models. Depending on how it is looked at, the exercise provides useful information in either model selection or data inversion. Connecting inverse problems and model uncertainty represents a fundamental challenge in the future development of
multi-model solvers.
We introduce a new prediction-oriented method for hazard assessment of volcaniclastic debris...
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