Articles | Volume 22, issue 4
04 Apr 2022
Brief communication | 04 Apr 2022
Brief communication: Introducing rainfall thresholds for landslide triggering based on artificial neural networks
Pierpaolo Distefano et al.
No articles found.
Nunziarita Palazzolo, David Johnny Peres, Enrico Creaco, and Antonino Cancelliere
Nat. Hazards Earth Syst. Sci. Discuss.,
Preprint under review for NHESSShort summary
We explore the development of regional hydro-meteorological landslide triggering thresholds combining rainfall and soil moisture information at different depths. We apply PCA to condense multi-dimensional information in a simple 2D threshold. Based on ERA5-Land reanalysis soil moisture and observed precipitation we find that hydro-meteorological thresholds may significantly enhance landslide prediction (TSS = 0.71) compared to power-law rainfall intensity-duration thresholds (TSS = 0.50).
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 985–993,Short summary
To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.
David J. Peres, Alfonso Senatore, Paola Nanni, Antonino Cancelliere, Giuseppe Mendicino, and Brunella Bonaccorso
Nat. Hazards Earth Syst. Sci., 20, 3057–3082,Short summary
Regional climate models (RCMs) are commonly used for high-resolution assessment of climate change impacts. This research assesses the reliability of several RCMs in a Mediterranean area (southern Italy), comparing historic climate and drought characteristics with high-density and high-quality ground-based observational datasets. We propose a general methodology and identify the more skilful models able to reproduce precipitation and temperature variability as well as drought characteristics.
David J. Peres, Antonino Cancelliere, Roberto Greco, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 18, 633–646,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.
D. J. Peres and A. Cancelliere
Hydrol. Earth Syst. Sci., 18, 4913–4931,Short summary
A Monte Carlo approach, combining rainfall-stochastic models and hydrological and slope stability physically based models, is used to derive rainfall thresholds of landslide triggering. The uncertainty in threshold assessment related to variability of rainfall intensity within events and to past rainfall (antecedent rainfall) is analyzed and measured via ROC-based indexes, with a specific focus dedicated to the widely used power-law rainfall intensity-duration (I-D) thresholds.
Related subject area
Landslides and Debris Flows HazardsLandslide susceptibility assessment in the rocky coast subsystem of Essaouira, MoroccoLandsifier v1.0: a Python library to estimate likely triggers of mapped landslidesTiming landslide and flash flood events from SAR satellite: a regionally applicable methodology illustrated in African cloud-covered tropical environmentsPotential of satellite-derived hydro-meteorological information for landslide initiation thresholds in RwandaEarthquake-induced landslides in Haiti: analysis of seismotectonic and possible climatic influencesPre-collapse motion of the February 2021 Chamoli rock–ice avalanche, Indian HimalayaPhysically based modeling of co-seismic landslide, debris flow, and flood cascadeFinite-hillslope analysis of landslides triggered by excess pore water pressure: the roles of atmospheric pressure and rainfall infiltration during typhoonsEstimating global landslide susceptibility and its uncertainty through ensemble modelingTerrain visibility impact on the preparation of landslide inventories: a practical example in Darjeeling district (India)Using Sentinel-1 radar amplitude time series to constrain the timings of individual landslides: a step towards understanding the controls on monsoon-triggered landslidingIntroducing SlideforMAP: a probabilistic finite slope approach for modelling shallow-landslide probability in forested situationsAugmentation of WRF-Hydro to simulate overland-flow- and streamflow-generated debris flow susceptibility in burn scarsWhat drives landslide risk? Disaggregating risk analyses, an example from the Franz Josef Glacier and Fox Glacier valleys, New ZealandGeographic information system models with fuzzy logic for susceptibility maps of debris flow using multiple types of parameters: a case study in Pinggu District of Beijing, ChinaSpatial assessment of probable recharge areas – investigating the hydrogeological controls of an active deep-seated gravitational slope deformationRainfall-induced landslide early warning system based on corrected mesoscale numerical models: an application for the southern AndesQuantification of meteorological conditions for rockfall triggers in GermanyDebris flow velocity and volume estimations based on seismic dataIntegration of observed and model-derived groundwater levels in landslide threshold models in RwandaLandslides caught on seismic networks and satellite radarsVariable hydrograph inputs for a numerical debris-flow runout modelAssessing the relationship between weather conditions and rockfall using terrestrial laser scanner to improve risk managementHow 3d volcanic stratigraphy constrains headscarp collapse scenarios: the Samperre Cliff case study (Martinique Island, Lesser Antilles)Brief Communication: An Autonomous UAV for Catchment-Wide Monitoring of a Debris Flow TorrentAssessing the importance of conditioning factor selection in landslide susceptibility for the province of Belluno (region of Veneto, northeastern Italy)Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventoriesGenerating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth EngineMultiscale effects caused by the fracturing and fragmentation of rock blocks during rock mass movement: implications for rock avalanche propagationRapid assessment of abrupt urban mega-gully and landslide events with structure-from-motion photogrammetric techniques validates link to water resources infrastructure failures in an urban peripheryAutomated determination of landslide locations after large trigger events: advantages and disadvantages compared to manual mappingEvaluation of filtering methods for use on high-frequency measurements of landslide displacementsA modeling methodology to study the tributary-junction alluvial fan connectivity during a debris flow eventBrief communication: The role of geophysical imaging in local landslide early warning systemsEvaluating landslide response in a seismic and rainfall regime: a case study from the SE Carpathians, RomaniaMain Ethiopian Rift landslides formed in contrasting geological settings and climatic conditionsInvestigating causal factors of shallow landslides in grassland regions of SwitzerlandDebris flow event on Osorno volcano, Chile, during summer 2017: new interpretations for chain processes in the southern AndesIntegrating empirical models and satellite radar can improve landslide detection for emergency responseEvaluating methods for debris-flow prediction based on rainfall in an Alpine catchmentOptimizing and validating the Gravitational Process Path model for regional debris-flow runout modellingGeographic-information-system-based topographic reconstruction and geomechanical modelling of the Köfels rockslideSpatiotemporal clustering of flash floods in a changing climate (China, 1950–2015)Atmospheric triggering conditions and climatic disposition of landslides in Kyrgyzstan and Tajikistan at the beginning of the 21st centuryAnalysis of meteorological parameters triggering rainfall-induced landslide: a review of 70 years in ValtellinaLandslide risk management analysis on expansive residential areas – case study of La Marina (Alicante, Spain)Uncertainty analysis of a rainfall threshold estimate for stony debris flow based on the backward dynamical approachControls on the formation and size of potential landslide dams and dammed lakes in the Austrian AlpsThe role of geomorphology, rainfall and soil moisture in the occurrence of landslides triggered by 2018 Typhoon Mangkhut in the PhilippinesInvited perspectives: Landslide populations – can they be predicted?
Abdellah Khouz, Jorge Trindade, Sérgio C. Oliveira, Fatima El Bchari, Blaid Bougadir, Ricardo A. C. Garcia, and Mourad Jadoud
Nat. Hazards Earth Syst. Sci., 22, 3793–3814,Short summary
The aim of this study was to assess the landslide susceptibility of the rocky coast of Essaouira using the information value model. The resulting susceptibility maps could be used for both environmental protection and general planning of future development activities.
Kamal Rana, Nishant Malik, and Ugur Ozturk
Nat. Hazards Earth Syst. Sci., 22, 3751–3764,Short summary
The landslide hazard models assist in mitigating losses due to landslides. However, these models depend on landslide databases, which often have missing triggering information, rendering these databases unusable for landslide hazard models. In this work, we developed a Python library, Landsifier, consisting of three different methods to identify the triggers of landslides. These methods can classify landslide triggers with high accuracy using only a landslide polygon shapefile as an input.
Axel A. J. Deijns, Olivier Dewitte, Wim Thiery, Nicolas d'Oreye, Jean-Philippe Malet, and François Kervyn
Nat. Hazards Earth Syst. Sci., 22, 3679–3700,Short summary
Landslides and flash floods are rainfall-induced processes that often co-occur and interact, generally very quickly. In mountainous cloud-covered environments, determining when these processes occur remains challenging. We propose a regional methodology using open-access satellite radar images that allow for the timing of landslide and flash floods events, in the contrasting landscapes of tropical Africa, with an accuracy of up to a few days. The methodology shows potential for transferability.
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661,Short summary
This study compared gauge-based and satellite-based precipitation products. Similarly, satellite- and hydrological model-derived soil moisture was compared to in situ soil moisture and used in landslide hazard assessment and warning. The results reveal the cumulative 3 d rainfall from the NASA-GPM to be the most effective landslide trigger. The modelled antecedent soil moisture in the root zone was the most informative hydrological variable for landslide hazard assessment and warning in Rwanda.
Hans-Balder Havenith, Kelly Guerrier, Romy Schlögel, Anika Braun, Sophia Ulysse, Anne-Sophie Mreyen, Karl-Henry Victor, Newdeskarl Saint-Fleur, Léna Cauchie, Dominique Boisson, and Claude Prépetit
Nat. Hazards Earth Syst. Sci., 22, 3361–3384,Short summary
We present a new landslide inventory for the 2021, M 7.2, Haiti, earthquake. We compare characteristics of this inventory with those of the 2010 seismically induced landslides, highlighting the much larger total area of 2021 landslides. This fact could be related to the larger earthquake magnitude in 2021, to the more central location of the fault segment ruptured in 2021 with respect to coastal zones, and/or to possible climatic preconditioning of slope failures in the 2021 affected area.
Maximillian Van Wyk de Vries, Shashank Bhushan, Mylène Jacquemart, César Deschamps-Berger, Etienne Berthier, Simon Gascoin, David E. Shean, Dan H. Shugar, and Andreas Kääb
Nat. Hazards Earth Syst. Sci., 22, 3309–3327,Short summary
On 7 February 2021, a large rock–ice avalanche occurred in Chamoli, Indian Himalaya. The resulting debris flow swept down the nearby valley, leaving over 200 people dead or missing. We use a range of satellite datasets to investigate how the collapse area changed prior to collapse. We show that signs of instability were visible as early 5 years prior to collapse. However, it would likely not have been possible to predict the timing of the event from current satellite datasets.
Bastian van den Bout, Chenxiao Tang, Cees van Westen, and Victor Jetten
Nat. Hazards Earth Syst. Sci., 22, 3183–3209,Short summary
Natural hazards such as earthquakes, landslides, and flooding do not always occur as stand-alone events. After the 2008 Wenchuan earthquake, a co-seismic landslide blocked a stream in Hongchun. Two years later, a debris flow breached the material, blocked the Min River, and resulted in flooding of a small town. We developed a multi-process model that captures the full cascade. Despite input and process uncertainties, probability of flooding was high due to topography and trigger intensities.
Lucas Pelascini, Philippe Steer, Maxime Mouyen, and Laurent Longuevergne
Nat. Hazards Earth Syst. Sci., 22, 3125–3141,Short summary
Landslides represent a major natural hazard and are often triggered by typhoons. We present a new 2D model computing the respective role of rainfall infiltration, atmospheric depression and groundwater in slope stability during typhoons. The results show rainfall is the strongest factor of destabilisation. However, if the slope is fully saturated, near the toe of the slope or during the wet season, rainfall infiltration is limited and atmospheric pressure change can become the dominant factor.
Anne Felsberg, Jean Poesen, Michel Bechtold, Matthias Vanmaercke, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 22, 3063–3082,Short summary
In this study we assessed global landslide susceptibility at the coarse 36 km spatial resolution of global satellite soil moisture observations to prepare for a subsequent combination of the two. Specifically, we focus therefore on the susceptibility of hydrologically triggered landslides. We introduce ensemble techniques, common in, for example, meteorology but not yet in the landslide community, to retrieve reliable estimates of the total prediction uncertainty.
Txomin Bornaetxea, Ivan Marchesini, Sumit Kumar, Rabisankar Karmakar, and Alessandro Mondini
Nat. Hazards Earth Syst. Sci., 22, 2929–2941,Short summary
One cannot know if there is a landslide or not in an area that one has not observed. This is an obvious statement, but when landslide inventories are obtained by field observation, this fact is seldom taken into account. Since fieldwork campaigns are often done following the roads, we present a methodology to estimate the visibility of the terrain from the roads, and we demonstrate that fieldwork-based inventories are underestimating landslide density in less visible areas.
Katy Burrows, Odin Marc, and Dominique Remy
Nat. Hazards Earth Syst. Sci., 22, 2637–2653,Short summary
The locations of triggered landslides following a rainfall event can be identified in optical satellite images. However cloud cover associated with the rainfall means that these images cannot be used to identify landslide timing. Timings of landslides triggered during long rainfall events are often unknown. Here we present methods of using Sentinel-1 satellite radar data, acquired every 12 d globally in all weather conditions, to better constrain the timings of rainfall-triggered landslides.
Feiko Bernard van Zadelhoff, Adel Albaba, Denis Cohen, Chris Phillips, Bettina Schaefli, Luuk Dorren, and Massimiliano Schwarz
Nat. Hazards Earth Syst. Sci., 22, 2611–2635,Short summary
Shallow landslides pose a risk to people, property and infrastructure. Assessment of this hazard and the impact of protective measures can reduce losses. We developed a model (SlideforMAP) that can assess the shallow-landslide risk on a regional scale for specific rainfall events. Trees are an effective and cheap protective measure on a regional scale. Our model can assess their hazard reduction down to the individual tree level.
Chuxuan Li, Alexander L. Handwerger, Jiali Wang, Wei Yu, Xiang Li, Noah J. Finnegan, Yingying Xie, Giuseppe Buscarnera, and Daniel E. Horton
Nat. Hazards Earth Syst. Sci., 22, 2317–2345,Short summary
In January 2021 a storm triggered numerous debris flows in a wildfire burn scar in California. We use a hydrologic model to assess debris flow susceptibility in pre-fire and postfire scenarios. Compared to pre-fire conditions, postfire conditions yield dramatic increases in peak water discharge, substantially increasing debris flow susceptibility. Our work highlights the hydrologic model's utility in investigating and potentially forecasting postfire debris flows at regional scales.
Saskia de Vilder, Chris Massey, Biljana Lukovic, Tony Taig, and Regine Morgenstern
Nat. Hazards Earth Syst. Sci., 22, 2289–2316,Short summary
This study calculates the fatality risk posed by landslides while visiting Franz Josef Glacier and Fox Glacier valleys, New Zealand, for nine different scenarios, where the variables of the risk equation were adjusted to determine the range in risk values and associated uncertainty. The results show that it is important to consider variable inputs that change through time, such as the increasing probability of an earthquake and the impact of climate change on landslide characteristics.
Yiwei Zhang, Jianping Chen, Qing Wang, Chun Tan, Yongchao Li, Xiaohui Sun, and Yang Li
Nat. Hazards Earth Syst. Sci., 22, 2239–2255,Short summary
The disaster prevention and mitigation of debris flow is a very important scientific problem. Our model is based on geographic information system (GIS), combined with grey relational, data-driven and fuzzy logic methods. Through our results, we believe that the streamlining of factors and scientific classification should attract attention from other researchers to optimize a model. We also propose a good perspective to make better use of the watershed feature parameters.
Jan Pfeiffer, Thomas Zieher, Jan Schmieder, Thom Bogaard, Martin Rutzinger, and Christoph Spötl
Nat. Hazards Earth Syst. Sci., 22, 2219–2237,Short summary
The activity of slow-moving deep-seated landslides is commonly governed by pore pressure variations within the shear zone. Groundwater recharge as a consequence of precipitation therefore is a process regulating the activity of landslides. In this context, we present a highly automated geo-statistical approach to spatially assess groundwater recharge controlling the velocity of a deep-seated landslide in Tyrol, Austria.
Ivo Fustos-Toribio, Nataly Manque-Roa, Daniel Vásquez Antipan, Mauricio Hermosilla Sotomayor, and Viviana Letelier Gonzalez
Nat. Hazards Earth Syst. Sci., 22, 2169–2183,Short summary
We develop for the first time a rainfall-induced landslide early warning system for the south of Chile. We used forecast precipitation values at different scales using mesoscale models to evaluate the probability of landslides using statistical models. We showed the feasibility of implementing these models in future, supporting stakeholders and decision-makers.
Katrin M. Nissen, Stefan Rupp, Thomas M. Kreuzer, Björn Guse, Bodo Damm, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 22, 2117–2130,Short summary
A statistical model is introduced which quantifies the influence of individual potential triggering factors and their interactions on rockfall probability in central Europe. The most important factor is daily precipitation, which is most effective if sub-surface moisture levels are high. Freeze–thaw cycles in the preceding days can further increase the rockfall hazard. The model can be applied to climate simulations in order to investigate the effect of climate change on rockfall probability.
Andreas Schimmel, Velio Coviello, and Francesco Comiti
Nat. Hazards Earth Syst. Sci., 22, 1955–1968,Short summary
The estimation of debris flow velocity and volume is a fundamental task for the development of early warning systems and other mitigation measures. This work provides a first approach for estimating the velocity and the total volume of debris flows based on the seismic signal detected with simple, low-cost geophones installed along the debris flow channel. The developed method was applied to seismic data collected at three test sites in the Alps: Gadria and Cancia (IT) and Lattenbach (AT).
Judith Uwihirwe, Markus Hrachowitz, and Thom Bogaard
Nat. Hazards Earth Syst. Sci., 22, 1723–1742,Short summary
This research tested the value of regional groundwater level information to improve landslide predictions with empirical models based on the concept of threshold levels. In contrast to precipitation-based thresholds, the results indicated that relying on threshold models exclusively defined using hydrological variables such as groundwater levels can lead to improved landslide predictions due to their implicit consideration of long-term antecedent conditions until the day of landslide occurrence.
Andrea Manconi, Alessandro C. Mondini, and the AlpArray working group
Nat. Hazards Earth Syst. Sci., 22, 1655–1664,Short summary
Information on when, where, and how landslide events occur is the key to building complete catalogues and performing accurate hazard assessments. Here we show a procedure that allows us to benefit from the increased density of seismic sensors installed on ground for earthquake monitoring and from the unprecedented availability of satellite radar data. We show how the procedure works on a recent sequence of landslides that occurred at Piz Cengalo (Swiss Alps) in 2017.
Andrew Mitchell, Sophia Zubrycky, Scott McDougall, Jordan Aaron, Mylène Jacquemart, Johannes Hübl, Roland Kaitna, and Christoph Graf
Nat. Hazards Earth Syst. Sci., 22, 1627–1654,Short summary
Debris flows are complex, surging movements of sediment and water. Discharge observations from well-studied debris-flow channels were used as inputs for a numerical modelling study of the downstream effects of chaotic inflows. The results show that downstream impacts are sensitive to inflow conditions. Inflow conditions for predictive modelling are highly uncertain, and our method provides a means to estimate the potential variability in future events.
Tom Birien and Francis Gauthier
On highly fractured rockwall such as those found in northern Gaspésie, most rockfalls are triggered by weather conditions. This study highlights that in winter, rockfall frequency is 12 times higher during a superficial thaw than during a cold period in which temperature remains below 0 °C. In summer, rockfall frequency is 22 times higher during a heavy rainfall event than during a period mainly dry. This knowledge could be used to implement a risk management strategy.
Marc Peruzzetto, Yoann Legendre, Aude Nachbaur, Thomas J. B. Dewez, Yannick Thiery, Clara Levy, and Benoit Vittecoq
Volcanic edifices result from successive construction and dismantling phases. Thus, the geological units forming the volcano display complex geometries. We show that such geometries can be reconstructed thanks to aerial views, topographic surveys and photogrammetric models. In our case study of the Samperre Cliff (Martinique, Lesser Antilles), it allows to link destabilizations from a rocky cliff to the existence of a filled paleo valley, and estimate a potentially unstable volume.
Fabian Walter, Elias Hodel, Erik Mannerfelt, Nicolas Ackermann, Kristen Cook, Michael Dietze, Livia Estermann, Daniel Farinotti, Martin Fengler, Lukas Hammerschmidt, Flavia Hänsli, Jacob Hirschberg, Brian McArdell, and Peter Molnar
Debris flows are dangerous sediment-water mixtures in steep terrain. Their formation takes place in poorly accessible terrain, where instrumentation cannot be installed. Here we propose to monitor such source terrain with an autonomous drone for mapping sediments, which were left behind by debris flows or may contribute to future events. Short flight intervals elucidate changes of such sediments providing important information for landscape evolution and the likelihood of future debris flows.
Sansar Raj Meena, Silvia Puliero, Kushanav Bhuyan, Mario Floris, and Filippo Catani
Nat. Hazards Earth Syst. Sci., 22, 1395–1417,Short summary
The study investigated the importance of the conditioning factors in predicting landslide occurrences using the mentioned models. In this paper, we evaluated the importance of the conditioning factors (features) in the overall prediction capabilities of the statistical and machine learning algorithms.
Robert Emberson, Dalia B. Kirschbaum, Pukar Amatya, Hakan Tanyas, and Odin Marc
Nat. Hazards Earth Syst. Sci., 22, 1129–1149,Short summary
Understanding where landslides occur in mountainous areas is critical to support hazard analysis as well as understand landscape evolution. In this study, we present a large compilation of inventories of landslides triggered by rainfall, including several that are described here for the first time. We analyze the topographic characteristics of the landslides, finding consistent relationships for landslide source and deposition areas, despite differences in the inventories' locations.
Alexander L. Handwerger, Mong-Han Huang, Shannan Y. Jones, Pukar Amatya, Hannah R. Kerner, and Dalia B. Kirschbaum
Nat. Hazards Earth Syst. Sci., 22, 753–773,Short summary
Rapid detection of landslides is critical for emergency response and disaster mitigation. Here we develop a global landslide detection tool in Google Earth Engine that uses satellite radar data to measure changes in the ground surface properties. We find that we can detect areas with high landslide density within days of a triggering event. Our approach allows the broader hazard community to utilize these state-of-the-art data for improved situational awareness of landslide hazards.
Qiwen Lin, Yufeng Wang, Yu Xie, Qiangong Cheng, and Kaifeng Deng
Nat. Hazards Earth Syst. Sci., 22, 639–657,Short summary
Fracturing and fragmentation of rock blocks are important and universal phenomena during the movement of rock avalanches (large and long-run-out rockslide-debris avalanches). The movement of a fragmenting rock block is simulated by the discrete element method, aiming to quantify the fracturing and fragmentation effect of the block in propagation. The fracturing and fragmentation processes and their influences on energy transformation in the system are described in detail.
Napoleon Gudino-Elizondo, Matthew W. Brand, Trent W. Biggs, Alejandro Hinojosa-Corona, Álvaro Gómez-Gutiérrez, Eddy Langendoen, Ronald Bingner, Yongping Yuan, and Brett F. Sanders
Nat. Hazards Earth Syst. Sci., 22, 523–538,Short summary
Mass movement hazards in the form of gullies and landslides pose significant risks in urbanizing areas yet are poorly documented. This paper presents observations and modeling of mass movement events over a 5-year period in Tijuana, Mexico. Three major events were observed, and all were linked to water resources infrastructure failures (WRIFs), namely leaks and breaks in water supply pipes. Modeling shows that WRIF-based erosion was also a non-negligible contributor to the total sediment budget.
David G. Milledge, Dino G. Bellugi, Jack Watt, and Alexander L. Densmore
Nat. Hazards Earth Syst. Sci., 22, 481–508,Short summary
Earthquakes can trigger thousands of landslides, causing severe and widespread damage. Efforts to understand what controls these landslides rely heavily on costly and time-consuming manual mapping from satellite imagery. We developed a new method that automatically detects landslides triggered by earthquakes using thousands of free satellite images. We found that in the majority of cases, it was as skilful at identifying the locations of landslides as the manual maps that we tested it against.
Sohrab Sharifi, Michael T. Hendry, Renato Macciotta, and Trevor Evans
Nat. Hazards Earth Syst. Sci., 22, 411–430,Short summary
This study is devoted to comparing the effectiveness of three different filters for noise reduction of instruments. It was observed that the Savitzky–Golay and Gaussian-weighted moving average filters outperform the simple moving average. Application of these two filters in real-time landslide monitoring leads to timely detection of acceleration moment and better preservation of information regarding displacement and velocity.
Alex Garcés, Gerardo Zegers, Albert Cabré, Germán Aguilar, Aldo Tamburrino, and Santiago Montserrat
Nat. Hazards Earth Syst. Sci., 22, 377–393,Short summary
We propose a workflow to model the response of an alluvial fan located in the Atacama Desert during an extreme storm event. For this alluvial fan, five different deposits were identified and associated with different debris flow surges. Using a commercial software program, our workflow concatenates these surges into one model. This study depicts the significance of the mechanical classification of debris flows to reproduce how an alluvial fan controls the tributary–river junction connectivity.
Jim S. Whiteley, Arnaud Watlet, J. Michael Kendall, and Jonathan E. Chambers
Nat. Hazards Earth Syst. Sci., 21, 3863–3871,Short summary
This work summarises the contribution of geophysical imaging methods to establishing and operating local landslide early warning systems, demonstrated through a conceptual framework. We identify developments in geophysical monitoring equipment, the spatiotemporal resolutions of these approaches and methods to translate geophysical to geotechnical information as the primary benefits that geophysics brings to slope-scale early warning.
Vipin Kumar, Léna Cauchie, Anne-Sophie Mreyen, Mihai Micu, and Hans-Balder Havenith
Nat. Hazards Earth Syst. Sci., 21, 3767–3788,Short summary
The SE Carpathians belong to one of the most active seismic regions of Europe. In recent decades, extreme rainfall events have also been common. These natural processes result in frequent landslides, particularly of a debris flow type. Despite such regimes, the region has been little explored to understand the response of the landslides in seismic and rainfall conditions. This study attempts to fill this gap by evaluating landslide responses under seismic and extreme-rainfall regimes.
Karel Martínek, Kryštof Verner, Tomáš Hroch, Leta A. Megerssa, Veronika Kopačková, David Buriánek, Ameha Muluneh, Radka Kalinová, Miheret Yakob, and Muluken Kassa
Nat. Hazards Earth Syst. Sci., 21, 3465–3487,Short summary
This study combines field geological and geohazard mapping with remote sensing data. Geostatistical analysis evaluated precipitation, land use, vegetation density, rock mass strength, and tectonics. Contrasting tectonic and climatic setting of the Main Ethiopian Rift and uplifted Ethiopian Plateau have major impacts on the distribution of landslides.
Lauren Zweifel, Maxim Samarin, Katrin Meusburger, and Christine Alewell
Nat. Hazards Earth Syst. Sci., 21, 3421–3437,Short summary
Mountainous grassland areas can be severely affected by soil erosion, such as by shallow landslides. With an automated mapping approach we are able to locate shallow-landslide sites on aerial images for 10 different study sites across Swiss mountain regions covering a total of 315 km2. Using a statistical model we identify important explanatory variables for shallow-landslide occurrence for the individual sites as well as across all regions, which highlight slope, aspect and terrain roughness.
Ivo Janos Fustos-Toribio, Bastian Morales-Vargas, Marcelo Somos-Valenzuela, Pablo Moreno-Yaeger, Ramiro Muñoz-Ramirez, Ines Rodriguez Araneda, and Ningsheng Chen
Nat. Hazards Earth Syst. Sci., 21, 3015–3029,Short summary
Links between debris flow and volcanic evolution are an open question in the southern Andes. We modelled the catastrophic debris flow using field data, a geotechnical approach and numerical modelling of the Petrohué event (Chile, 2017). Our results indicated new debris-flow-prone zones. Finally, we propose considering connections between volcanoes and debris flow in the southern Andes.
Katy Burrows, David Milledge, Richard J. Walters, and Dino Bellugi
Nat. Hazards Earth Syst. Sci., 21, 2993–3014,Short summary
When cloud cover obscures optical satellite imagery, there are two options remaining for generating information on earthquake-triggered landslide locations: (1) models which predict landslide locations based on, e.g., slope and ground shaking data and (2) satellite radar data, which penetrates cloud cover and is sensitive to landslides. Here we show that the two approaches can be combined to give a more consistent and more accurate model of landslide locations after an earthquake.
Jacob Hirschberg, Alexandre Badoux, Brian W. McArdell, Elena Leonarduzzi, and Peter Molnar
Nat. Hazards Earth Syst. Sci., 21, 2773–2789,Short summary
Debris-flow prediction is often based on rainfall thresholds, but uncertainty assessments are rare. We established rainfall thresholds using two approaches and find that 25 debris flows are needed for uncertainties to converge in an Alpine basin and that the suitable method differs for regional compared to local thresholds. Finally, we demonstrate the potential of a statistical learning algorithm to improve threshold performance. These findings are helpful for early warning system development.
Jason Goetz, Robin Kohrs, Eric Parra Hormazábal, Manuel Bustos Morales, María Belén Araneda Riquelme, Cristián Henríquez, and Alexander Brenning
Nat. Hazards Earth Syst. Sci., 21, 2543–2562,Short summary
Debris flows are fast-moving landslides that can cause incredible destruction to lives and property. Using the Andes of Santiago as an example, we developed tools to finetune and validate models predicting likely runout paths over large regions. We anticipate that our automated approach that links the open-source R software with SAGA-GIS will make debris-flow runout simulation more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.
Christian Zangerl, Annemarie Schneeberger, Georg Steiner, and Martin Mergili
Nat. Hazards Earth Syst. Sci., 21, 2461–2483,Short summary
The Köfels rockslide in the Ötztal Valley (Austria) represents the largest known extremely rapid rockslide in metamorphic rock masses in the Alps and was formed in the early Holocene. Although many hypotheses for the conditioning and triggering factors were discussed in the past, until now no scientifically accepted explanatory model has been found. This study provides new data and numerical modelling results to better understand the cause and triggering factors of this gigantic natural event.
Nan Wang, Luigi Lombardo, Marj Tonini, Weiming Cheng, Liang Guo, and Junnan Xiong
Nat. Hazards Earth Syst. Sci., 21, 2109–2124,Short summary
This study exploits 66 years of flash flood disasters across China. The conclusions are as follows. The clustering procedure highlights distinct spatial and temporal patterns of flash flood disasters at different scales. There are distinguished seasonal, yearly and even long-term persistent flash flood behaviors of flash flood disasters. Finally, the decreased duration of clusters in the recent period indicates a possible activation induced by short-duration extreme rainfall events.
Xun Wang, Marco Otto, and Dieter Scherer
Nat. Hazards Earth Syst. Sci., 21, 2125–2144,Short summary
We applied a high-resolution, gridded atmospheric data set combined with landslide inventories to investigate the atmospheric triggers, define triggering thresholds, and characterize the climatic disposition of landslides in Kyrgyzstan and Tajikistan. Our results indicate the crucial role of snowmelt in landslide triggering and prediction in Kyrgyzstan and Tajikistan, as well as the added value of climatic disposition derived from atmospheric triggering conditions.
Andrea Abbate, Monica Papini, and Laura Longoni
Nat. Hazards Earth Syst. Sci., 21, 2041–2058,Short summary
In this paper the relation between the intensity of meteorological events and the magnitude of triggered geo-hydrological issues was examined. A back analysis was developed across a region of the central Alps. The meteorological triggers were interpreted using two approaches: the first using local rain gauge data and a new one considering meteorological reanalysis maps. The results obtained were compared and elaborated for defining a magnitude of each geo-hydrological event.
Isidro Cantarino, Miguel Angel Carrion, Jose Sergio Palencia-Jimenez, and Víctor Martínez-Ibáñez
Nat. Hazards Earth Syst. Sci., 21, 1847–1866,Short summary
Risk ratio (RR), developed in this paper, stands out as a robust indicator for finding the relationship between residential construction and its associated landslide risk. It proved especially useful for municipalities on the Mediterranean coast, since it differentiates between those that take on a higher risk and those that do not. Our research establishes valuable criteria to find how suitable a specific local entity's risk management is and explore what causes the incidence of landslide risk.
Marta Martinengo, Daniel Zugliani, and Giorgio Rosatti
Nat. Hazards Earth Syst. Sci., 21, 1769–1784,Short summary
Rainfall thresholds are relations between rainfall intensity and duration on which the forecast of the possible occurrence of a debris flow can be based. To check the robustness of a physically based stony debris flow rainfall threshold, in this work we developed a procedure to estimate the effects of various sources of error on the determination of the threshold parameters. Results show that these effects are limited and therefore show the good robustness of the threshold estimate.
Anne-Laure Argentin, Jörg Robl, Günther Prasicek, Stefan Hergarten, Daniel Hölbling, Lorena Abad, and Zahra Dabiri
Nat. Hazards Earth Syst. Sci., 21, 1615–1637,Short summary
This study relies on topography to simulate the origin and displacement of potentially river-blocking landslides. It highlights a continuous range of simulated landslide dams that go unnoticed in the field due to their small scale. The computation results show that landslide-dammed lake volume can be estimated from upstream drainage area and landslide volume, thus enabling an efficient hazard assessment of possible landslide-dammed lake volume – and flooding magnitude in case of dam failure.
Clàudia Abancó, Georgina L. Bennett, Adrian J. Matthews, Mark Anthony M. Matera, and Fibor J. Tan
Nat. Hazards Earth Syst. Sci., 21, 1531–1550,Short summary
In 2018 Typhoon Mangkhut triggered thousands of landslides in the Itogon region (Philippines). An inventory of 1101 landslides revealed that landslides mostly occurred in slopes covered by wooded grassland in clayey materials, predominantly facing E-SE. Satellite rainfall and soil moisture data associated with Typhoon Mangkhut and the previous months in 2018 were analyzed. Results showed that landslides occurred during high-intensity rainfall that coincided with the highest soil moisture values.
Nat. Hazards Earth Syst. Sci., 21, 1467–1471,Short summary
This is a perspective based on personal experience on whether a large number of landslides caused by a single trigger (e.g. an earthquake, an intense rainfall, a rapid snowmelt event) or by multiple triggers in a period can be predicted, in space and time, considering the consequences of slope failures.
Bogaard, T. and Greco, R.: Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds, Nat. Hazards Earth Syst. Sci., 18, 31–39, https://doi.org/10.5194/nhess-18-31-2018, 2018.
Caine, N.: The Rainfall Intensity-Duration Control of Shallow Landslides and Debris Flows, Soc. Swedish Ann. Geogr. Geogr. Phys., 62, 23–27, 1980.
Calvello, M. and Pecoraro, G.: FraneItalia: a catalog of recent Italian landslides, Geoenviron. Disast., 5, 13, https://doi.org/10.1186/s40677-018-0105-5, 2018.
Calvello, M. and Pecoraro, G.: The FraneItalia database, FraneItalia [data set], https://franeitalia.wordpress.com/database/, last access: 17 November 2021.
Conrad, J. L., Morphew, M. D., Baum, R. L., and Mirus, B. B.: HydroMet: A New Code for Automated Objective Optimization of Hydrometeorological Thresholds for Landslide Initiation, Water, 13, 1752, https://doi.org/10.3390/W13131752, 2021.
Froude, M. J. and Petley, D. N.: Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https://doi.org/10.5194/nhess-18-2161-2018, 2018.
Gariano, S. L., Brunetti, M. T., Iovine, G., Melillo, M., Peruccacci, S., Terranova, O., Vennari, C., and Guzzetti, F.: Calibration and validation of rainfall thresholds for shallow landslide forecasting in Sicily, southern Italy, Geomorphology, 228, 653–665, https://doi.org/10.1016/j.geomorph.2014.10.019, 2015.
Glade, T., Crozier, M., and Smith, P.: Applying probability determination to refine landslide-triggering rainfall thresholds using an empirical “Antecedent Daily Rainfall Model”, Pure Appl. Geophys., 157, 1059–1079, https://doi.org/10.1007/s000240050017, 2000.
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.
Haykin, S.: Neural Networks- A Comprehensive Foundation, 2nd Edn., Prentice Hall, ISBN 10 8120323734, ISBN 13 978-8120323735, 1999.
ISPRA – Istituto Superiore per la Protezione e la Ricerca Ambientale: Annali idrologici Storici, http://www.acq.isprambiente.it/annalipdf/, last access: 31 March 2022.
Marino, P., Peres, D. J., Cancelliere, A., Greco, R., and Bogaard, T. A.: Soil moisture information can improve shallow landslide forecasting using the hydrometeorological threshold approach, Landslides, 17, 2041–2054, https://doi.org/10.1007/s10346-020-01420-8, 2020.
Melillo, M., Brunetti, M. T., Peruccacci, S., Gariano, S. L., and Guzzetti, F.: An algorithm for the objective reconstruction of rainfall events responsible for landslides, Landslides, 12, 311–320, https://doi.org/10.1007/s10346-014-0471-3, 2015.
Melillo, M., Brunetti, M. T., Peruccacci, S., Gariano, S. L., and Guzzetti, F.: Rainfall thresholds for the possible landslide occurrence in Sicily (Southern Italy) based on the automatic reconstruction of rainfall events, Landslides, 13, 165–172, https://doi.org/10.1007/s10346-015-0630-1, 2016.
Melillo, M., Brunetti, M. T., Peruccacci, S., Gariano, S. L., Roccati, A., and Guzzetti, F.: A tool for the automatic calculation of rainfall thresholds for landslide occurrence, Environ. Model. Softw., 105, 230–243, https://doi.org/10.1016/J.ENVSOFT.2018.03.024, 2018.
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.
Peres, D. J. and Cancelliere, A.: Comparing methods for determining landslide early warning thresholds: potential use of non-triggering rainfall for locations with scarce landslide data availability, Landslides, 18, 3135–3147, https://doi.org/10.1007/s10346-021-01704-7, 2021.
Piciullo, L., Calvello, M., and Cepeda, J. M.: Territorial early warning systems for rainfall-induced landslides, Earth-Sci. Rev., 179, 228–247, https://doi.org/10.1016/J.EARSCIREV.2018.02.013, 2018.
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., and Guzzetti, F.: A review of statistically-based landslide susceptibility models, Earth-Sci. Rev., 180, 60–91, https://doi.org/10.1016/j.earscirev.2018.03.001, 2018.
Rosi, A., Segoni, S., Canavesi, V., Monni, A., Gallucci, A., and Casagli, N.: Definition of 3D rainfall thresholds to increase operative landslide early warning system performances, Landslides, 18, 1045–1057, https://doi.org/10.1007/s10346-020-01523-2, 2021.
Sala, G., Lanfranconi, C., Frattini, P., Rusconi, G., and Crosta, G. B.: Cost-sensitive rainfall thresholds for shallow landslides, Landslides, 18, 2979–2992, https://doi.org/10.1007/s10346-021-01707-4, 2021.
SIAS – Servizio Informativo Agrometeorologico Siciliano (Sicilian Agro-meteorological Information Service): Dati meteorologici (Meteorological data), http://www.sias.regione.sicilia.it/, last access: 31 March 2022.
van Natijne, A. L., Lindenbergh, R. C., and Bogaard, T. A.: Machine learning: New potential for local and regional deep-seated landslide nowcasting, Sensors, 20, 1–18, https://doi.org/10.3390/s20051425, 2020.
In the communication, we introduce the use of artificial neural networks (ANNs) for improving the performance of rainfall thresholds for landslide early warning. Results show how ANNs using rainfall event duration and mean intensity perform significantly better than a classical power law based on the same variables. Adding peak rainfall intensity as input to the ANN improves performance even more. This further demonstrates the potentialities of the proposed machine learning approach.
In the communication, we introduce the use of artificial neural networks (ANNs) for improving...