Articles | Volume 22, issue 9
https://doi.org/10.5194/nhess-22-3063-2022
© Author(s) 2022. 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-22-3063-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Sep 2022
Research article |
| 19 Sep 2022
| 19 Sep 2022
Estimating global landslide susceptibility and its uncertainty through ensemble modeling
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Jean Poesen
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Faculty of Earth Sciences and Spatial Management, Maria-Curie Skłodowska University, Lublin, Poland
Michel Bechtold
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Matthias Vanmaercke
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Gabriëlle J. M. De Lannoy
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Related authors
Jonas Mortelmans, Anne Felsberg, Gabriëlle J. M. De Lannoy, Sander Veraverbeke, Robert D. Field, Niels Andela, and Michel Bechtold
Nat. Hazards Earth Syst. Sci., 24, 445–464, https://doi.org/10.5194/nhess-24-445-2024, https://doi.org/10.5194/nhess-24-445-2024, 2024
Short summary
Short summary
With global warming increasing the frequency and intensity of wildfires in the boreal region, accurate risk assessments are becoming more crucial than ever before. The Canadian Fire Weather Index (FWI) is a renowned system, yet its effectiveness in peatlands, where hydrology plays a key role, is limited. By incorporating groundwater data from numerical models and satellite observations, our modified FWI improves the accuracy of fire danger predictions, especially over summer.
This article is included in the Encyclopedia of Geosciences
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
Short summary
Short summary
The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
This article is included in the Encyclopedia of Geosciences
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
Hydrol. Earth Syst. Sci., 29, 465–483, https://doi.org/10.5194/hess-29-465-2025, https://doi.org/10.5194/hess-29-465-2025, 2025
Short summary
Short summary
The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two endmembers of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented supersites.
This article is included in the Encyclopedia of Geosciences
Louise Busschaert, Michel Bechtold, Sara Modanesi, Christian Massari, Dirk Raes, Sujay V. Kumar, and Gabrielle J. M. De Lannoy
EGUsphere, https://doi.org/10.2139/ssrn.4974019, https://doi.org/10.2139/ssrn.4974019, 2024
Short summary
Short summary
This study estimates irrigation in the Po Valley using AquaCrop and Noah-MP models with sprinkler irrigation. Noah-MP shows higher annual rates than AquaCrop due to more water losses. After adjusting, both align with reported irrigation ranges (500–600 mm/yr). Soil moisture estimates from both models match satellite data, though both have limitations in vegetation and evapotranspiration modeling. The study emphasizes the need for observations to improve irrigation estimates.
This article is included in the Encyclopedia of Geosciences
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
Short summary
Short summary
Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
This article is included in the Encyclopedia of Geosciences
Isis Brangers, Hans-Peter Marshall, Gabrielle De Lannoy, Devon Dunmire, Christian Mätzler, and Hans Lievens
The Cryosphere, 18, 3177–3193, https://doi.org/10.5194/tc-18-3177-2024, https://doi.org/10.5194/tc-18-3177-2024, 2024
Short summary
Short summary
To better understand the interactions between C-band radar waves and snow, a tower-based experiment was set up in the Idaho Rocky Mountains. The reflections were collected in the time domain to measure the backscatter profile from the various snowpack and ground surface layers. The results demonstrate that C-band radar is sensitive to seasonal patterns in snow accumulation but that changes in microstructure, stratigraphy and snow wetness may complicate satellite-based snow depth retrievals.
This article is included in the Encyclopedia of Geosciences
Jonas Mortelmans, Anne Felsberg, Gabriëlle J. M. De Lannoy, Sander Veraverbeke, Robert D. Field, Niels Andela, and Michel Bechtold
Nat. Hazards Earth Syst. Sci., 24, 445–464, https://doi.org/10.5194/nhess-24-445-2024, https://doi.org/10.5194/nhess-24-445-2024, 2024
Short summary
Short summary
With global warming increasing the frequency and intensity of wildfires in the boreal region, accurate risk assessments are becoming more crucial than ever before. The Canadian Fire Weather Index (FWI) is a renowned system, yet its effectiveness in peatlands, where hydrology plays a key role, is limited. By incorporating groundwater data from numerical models and satellite observations, our modified FWI improves the accuracy of fire danger predictions, especially over summer.
This article is included in the Encyclopedia of Geosciences
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
Short summary
Short summary
Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
This article is included in the Encyclopedia of Geosciences
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
Short summary
Short summary
The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
This article is included in the Encyclopedia of Geosciences
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 27, 4087–4114, https://doi.org/10.5194/hess-27-4087-2023, https://doi.org/10.5194/hess-27-4087-2023, 2023
Short summary
Short summary
We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
This article is included in the Encyclopedia of Geosciences
Ioanna S. Panagea, Antonios Apostolakis, Antonio Berti, Jenny Bussell, Pavel Čermak, Jan Diels, Annemie Elsen, Helena Kusá, Ilaria Piccoli, Jean Poesen, Chris Stoate, Mia Tits, Zoltan Toth, and Guido Wyseure
SOIL, 8, 621–644, https://doi.org/10.5194/soil-8-621-2022, https://doi.org/10.5194/soil-8-621-2022, 2022
Short summary
Short summary
The potential to reverse the negative effects caused in topsoil by inversion tillage, using alternative agricultural practices, was evaluated. Reduced and no tillage, and additions of manure/compost, improved topsoil structure and OC content. Residue retention had a positive impact on structure. We concluded that the negative effects of inversion tillage can be mitigated by reducing tillage intensity or adding organic materials, optimally combined with non-inversion tillage.
This article is included in the Encyclopedia of Geosciences
Sara Modanesi, Christian Massari, Michel Bechtold, Hans Lievens, Angelica Tarpanelli, Luca Brocca, Luca Zappa, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, https://doi.org/10.5194/hess-26-4685-2022, 2022
Short summary
Short summary
Given the crucial impact of irrigation practices on the water cycle, this study aims at estimating irrigation through the development of an innovative data assimilation system able to ingest high-resolution Sentinel-1 radar observations into the Noah-MP land surface model. The developed methodology has important implications for global water resource management and the comprehension of human impacts on the water cycle and identifies main challenges and outlooks for future research.
This article is included in the Encyclopedia of Geosciences
Louise Busschaert, Shannon de Roos, Wim Thiery, Dirk Raes, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 3731–3752, https://doi.org/10.5194/hess-26-3731-2022, https://doi.org/10.5194/hess-26-3731-2022, 2022
Short summary
Short summary
Increasing amounts of water are used for agriculture. Therefore, we looked into how irrigation requirements will evolve under a changing climate over Europe. Our results show that, by the end of the century and under high emissions, irrigation water will increase by 30 % on average compared to the year 2000. Also, the irrigation requirement is likely to vary more from 1 year to another. However, if emissions are mitigated, these effects are reduced.
This article is included in the Encyclopedia of Geosciences
Hans Lievens, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy
The Cryosphere, 16, 159–177, https://doi.org/10.5194/tc-16-159-2022, https://doi.org/10.5194/tc-16-159-2022, 2022
Short summary
Short summary
Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
This article is included in the Encyclopedia of Geosciences
Sara Modanesi, Christian Massari, Alexander Gruber, Hans Lievens, Angelica Tarpanelli, Renato Morbidelli, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 6283–6307, https://doi.org/10.5194/hess-25-6283-2021, https://doi.org/10.5194/hess-25-6283-2021, 2021
Short summary
Short summary
Worldwide, the amount of water used for agricultural purposes is rising and the quantification of irrigation is becoming a crucial topic. Land surface models are not able to correctly simulate irrigation. Remote sensing observations offer an opportunity to fill this gap as they are directly affected by irrigation. We equipped a land surface model with an observation operator able to transform Sentinel-1 backscatter observations into realistic vegetation and soil states via data assimilation.
This article is included in the Encyclopedia of Geosciences
Shannon de Roos, Gabriëlle J. M. De Lannoy, and Dirk Raes
Geosci. Model Dev., 14, 7309–7328, https://doi.org/10.5194/gmd-14-7309-2021, https://doi.org/10.5194/gmd-14-7309-2021, 2021
Short summary
Short summary
A spatially distributed version of the field-scale crop model AquaCrop v6.1 was developed for applications at various spatial scales. Multi-year 1 km simulations over central Europe were evaluated against biomass and surface soil moisture products derived from optical and microwave satellite missions, as well as in situ observations of soil moisture. The regional version of the AquaCrop model provides a suitable setup for subsequent satellite-based data assimilation.
This article is included in the Encyclopedia of Geosciences
Michiel Maertens, Gabriëlle J. M. De Lannoy, Sebastian Apers, Sujay V. Kumar, and Sarith P. P. Mahanama
Hydrol. Earth Syst. Sci., 25, 4099–4125, https://doi.org/10.5194/hess-25-4099-2021, https://doi.org/10.5194/hess-25-4099-2021, 2021
Short summary
Short summary
In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.
This article is included in the Encyclopedia of Geosciences
Jianxiu Qiu, Jianzhi Dong, Wade T. Crow, Xiaohu Zhang, Rolf H. Reichle, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 1569–1586, https://doi.org/10.5194/hess-25-1569-2021, https://doi.org/10.5194/hess-25-1569-2021, 2021
Short summary
Short summary
The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to Tb innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.
This article is included in the Encyclopedia of Geosciences
Benjamin Campforts, Charles M. Shobe, Philippe Steer, Matthias Vanmaercke, Dimitri Lague, and Jean Braun
Geosci. Model Dev., 13, 3863–3886, https://doi.org/10.5194/gmd-13-3863-2020, https://doi.org/10.5194/gmd-13-3863-2020, 2020
Short summary
Short summary
Landslides shape the Earth’s surface and are a dominant source of terrestrial sediment. Rivers, then, act as conveyor belts evacuating landslide-produced sediment. Understanding the interaction among rivers and landslides is important to predict the Earth’s surface response to past and future environmental changes and for mitigating natural hazards. We develop HyLands, a new numerical model that provides a toolbox to explore how landslides and rivers interact over several timescales.
This article is included in the Encyclopedia of Geosciences
Benjamin Campforts, Veerle Vanacker, Frédéric Herman, Matthias Vanmaercke, Wolfgang Schwanghart, Gustavo E. Tenorio, Patrick Willems, and Gerard Govers
Earth Surf. Dynam., 8, 447–470, https://doi.org/10.5194/esurf-8-447-2020, https://doi.org/10.5194/esurf-8-447-2020, 2020
Short summary
Short summary
In this contribution, we explore the spatial determinants of bedrock river incision in the tropical Andes. The model results illustrate the problem of confounding between climatic and lithological variables, such as rock strength. Incorporating rock strength explicitly into river incision models strongly improves the explanatory power of all tested models and enables us to clarify the role of rainfall variability in controlling river incision rates.
This article is included in the Encyclopedia of Geosciences
Anatoly Tsyplenkov, Matthias Vanmaercke, and Valentin Golosov
Proc. IAHS, 381, 87–93, https://doi.org/10.5194/piahs-381-87-2019, https://doi.org/10.5194/piahs-381-87-2019, 2019
Short summary
Short summary
Processes linked to climate change and intensified anthropogenic pressure influence the environment, the hydrology. Quantitative assessments of sediment fluxes and their temporal evolution in this mountain region are required for various environmental and engineering purposes, including the planning and maintenance of water reservoirs and other structures. we present a first analysis of the hitherto largest suspended sediment yield (SSY) database for the Caucasus region.
This article is included in the Encyclopedia of Geosciences
Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Béatrice Béchet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G. Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido-Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan-Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken
Earth Syst. Sci. Data, 10, 1237–1263, https://doi.org/10.5194/essd-10-1237-2018, https://doi.org/10.5194/essd-10-1237-2018, 2018
Short summary
Short summary
This paper presents and analyzes a global database of soil infiltration data, the SWIG database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists or they were digitized from published articles. We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models.
This article is included in the Encyclopedia of Geosciences
Liesbet Jacobs, Olivier Dewitte, Jean Poesen, John Sekajugo, Adriano Nobile, Mauro Rossi, Wim Thiery, and Matthieu Kervyn
Nat. Hazards Earth Syst. Sci., 18, 105–124, https://doi.org/10.5194/nhess-18-105-2018, https://doi.org/10.5194/nhess-18-105-2018, 2018
Short summary
Short summary
While country-specific, continental and global susceptibility maps are increasingly available, local and regional susceptibility studies remain rare in remote and data-poor settings. Here, we provide a landslide susceptibility assessment for the inhabited region of the Rwenzori Mountains. We find that higher spatial resolutions do not necessarily lead to better models and that models built for local case studies perform better than aggregated susceptibility assessments on the regional scale.
This article is included in the Encyclopedia of Geosciences
Annelie Säurich, Bärbel Tiemeyer, Axel Don, Michel Bechtold, Wulf Amelung, and Annette Freibauer
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-127, https://doi.org/10.5194/bg-2017-127, 2017
Manuscript not accepted for further review
Short summary
Short summary
Drained organic soils are hotspots of CO2 emissions. Due to mineralisation and mixing with mineral soil, the soil organic carbon (SOC) content of large areas of former peatlands decreased drastically. We evaluated potential CO2 emissions from such soils and true peat by aerobic incubation. Surprisingly, CO2 emissions increased in magnitude and variability with stronger disturbance and lower SOC content. This indicates that mixing peat with mineral soil is not a promising mitigation option.
This article is included in the Encyclopedia of Geosciences
Gabriëlle J. M. De Lannoy and Rolf H. Reichle
Hydrol. Earth Syst. Sci., 20, 4895–4911, https://doi.org/10.5194/hess-20-4895-2016, https://doi.org/10.5194/hess-20-4895-2016, 2016
Short summary
Short summary
The SMOS mission provides various various products to estimate soil moisture. This paper evaluates the performance of assimilating either Level-1-based multi-angle brightness temperature (Tb) observations, Level-1-based single-angle Tb observations, or Level 2 soil moisture retrievals, into the NASA Catchment land surface model.
This article is included in the Encyclopedia of Geosciences
C. Bosco, D. de Rigo, O. Dewitte, J. Poesen, and P. Panagos
Nat. Hazards Earth Syst. Sci., 15, 225–245, https://doi.org/10.5194/nhess-15-225-2015, https://doi.org/10.5194/nhess-15-225-2015, 2015
Short summary
Short summary
A new pan-European map of soil erosion is presented following a novel extension of the RUSLE model (e-RUSLE) designed for data-poor regional assessment and for identifying areas in Europe where to concentrate efforts for preventing soil degradation. e-RUSLE exploits the array-based semantics of a multiplicity of factors (semantic array programming). A climatic ensemble of an array of erosivity equations is considered along with a new factor for better considering soil stoniness within the model.
This article is included in the Encyclopedia of Geosciences
M. Dessie, N. E. C. Verhoest, V. R. N. Pauwels, T. Admasu, J. Poesen, E. Adgo, J. Deckers, and J. Nyssen
Hydrol. Earth Syst. Sci., 18, 5149–5167, https://doi.org/10.5194/hess-18-5149-2014, https://doi.org/10.5194/hess-18-5149-2014, 2014
Short summary
Short summary
In this study, topography is considered as a proxy for the variability of most of the catchment characteristics. The model study suggests that classifying the catchments into different runoff production areas based on topography and including the impermeable rocky areas separately in the modeling process mimics the rainfall–runoff process in the Upper Blue Nile basin well and yields a useful result for operational management of water resources in this data-scarce region.
This article is included in the Encyclopedia of Geosciences
M. Bechtold, B. Tiemeyer, A. Laggner, T. Leppelt, E. Frahm, and S. Belting
Hydrol. Earth Syst. Sci., 18, 3319–3339, https://doi.org/10.5194/hess-18-3319-2014, https://doi.org/10.5194/hess-18-3319-2014, 2014
Related subject area
Landslides and Debris Flows Hazards
Identifying unrecognised risks to life from debris flows
Predicting the thickness of shallow landslides in Switzerland using machine learning
Unraveling landslide failure mechanisms with seismic signal analysis for enhanced pre-survey understanding
Comparison of conditioning factor classification criteria in large-scale statistically based landslide susceptibility models
Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems
Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer
Limit analysis of earthquake-induced landslides considering two strength envelopes
Brief communication: Visualizing uncertainties in landslide susceptibility modeling using bivariate mapping
The vulnerability of buildings to a large-scale debris flow and outburst flood hazard cascade that occurred on 30 August 2020 in Ganluo, southwest China
Optimizing rainfall-triggered landslide thresholds for daily landslide hazard warning in the Three Gorges Reservoir area
Brief communication: Monitoring impending slope failure with very high-resolution spaceborne synthetic aperture radar
Size scaling of large landslides from incomplete inventories
InSAR-informed in situ monitoring for deep-seated landslides: insights from El Forn (Andorra)
A coupled hydrological and hydrodynamic modeling approach for estimating rainfall thresholds of debris-flow occurrence
Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico
More than one landslide per road kilometer – surveying and modeling mass movements along the Rishikesh–Joshimath (NH-7) highway, Uttarakhand, India
An integrated method for assessing vulnerability of buildings caused by debris flows in mountainous areas
Temporal clustering of precipitation for detection of potential landslides
Shallow-landslide stability evaluation in loess areas according to the Revised Infinite Slope Model: a case study of the 7.25 Tianshui sliding-flow landslide events of 2013 in the southwest of the Loess Plateau, China
From rockfall source areas identification to susceptibility zonation: a proposed workflow tested in El Hierro (Canary Islands, Spain)
Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall
Evaluating post-wildfire debris-flow rainfall thresholds and volume models at the 2020 Grizzly Creek Fire in Glenwood Canyon, Colorado, USA
A participatory approach to determine the use of road cut slope design guidelines in Nepal to lessen landslides
Addressing class imbalance in soil movement predictions
Assessing the impact of climate change on landslides near Vejle, Denmark, using public data
Analysis of three-dimensional slope stability combined with rainfall and earthquake
Assessing landslide damming susceptibility in Central Asia
Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico
Evaluation of debris-flow building damage forecasts
Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA
Morphological characteristics and conditions of drainage basins contributing to the formation of debris flow fans: an examination of regions with different rock strength using decision tree analysis
Characterizing the scale of regional landslide triggering from storm hydrometeorology
Comparison of debris flow observations, including fine-sediment grain size and composition and runout model results, at Illgraben, Swiss Alps
Simulation analysis of 3D stability of a landslide with a locking segment: a case study of the Tizicao landslide in Maoxian County, southwest China
Space–time landslide hazard modeling via Ensemble Neural Networks
Optimization strategy for flexible barrier structures: investigation and back analysis of a rockfall disaster case in southwestern China
Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment
Slope Unit Maker (SUMak): an efficient and parameter-free algorithm for delineating slope units to improve landslide modeling
Probabilistic Hydrological Estimation of LandSlides (PHELS): global ensemble landslide hazard modelling
A new analytical method for stability analysis of rock blocks with basal erosion in sub-horizontal strata by considering the eccentricity effect
Rockfall monitoring with a Doppler radar on an active rockslide complex in Brienz/Brinzauls (Switzerland)
Landslide initiation thresholds in data-sparse regions: application to landslide early warning criteria in Sitka, Alaska, USA
Lessons learnt from a rockfall time series analysis: data collection, statistical analysis, and applications
The concept of event-size-dependent exhaustion and its application to paraglacial rockslides
Coastal earthquake-induced landslide susceptibility during the 2016 Mw 7.8 Kaikōura earthquake, New Zealand
Characteristics of debris flows recorded in the Shenmu area of central Taiwan between 2004 and 2021
Semi-automatic mapping of shallow landslides using free Sentinel-2 images and Google Earth Engine
The role of thermokarst evolution in debris flow initiation (Hüttekar Rock Glacier, Austrian Alps)
Accounting for the effect of forest and fragmentation in probabilistic rockfall hazard
Comprehensive landslide susceptibility map of Central Asia
Mark Bloomberg, Tim Davies, Elena Moltchanova, Tom Robinson, and David Palmer
Nat. Hazards Earth Syst. Sci., 25, 647–656, https://doi.org/10.5194/nhess-25-647-2025, https://doi.org/10.5194/nhess-25-647-2025, 2025
Short summary
Short summary
Debris flows occur infrequently, with average recurrence intervals (ARIs) ranging from decades to millennia. Consequently, they pose an underappreciated hazard. We describe how to make a preliminary identification of debris-flow-susceptible catchments, estimate threshold ARIs for debris flows that pose an unacceptable risk to life, and identify the “window of non-recognition” where debris flows are infrequent enough that their hazard is unrecognised yet frequent enough to pose a risk to life.
This article is included in the Encyclopedia of Geosciences
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci., 25, 467–491, https://doi.org/10.5194/nhess-25-467-2025, https://doi.org/10.5194/nhess-25-467-2025, 2025
Short summary
Short summary
We developed a machine-learning-based approach to predict the potential thickness of shallow landslides to generate improved inputs for slope stability models. We selected 21 explanatory variables, including metrics on terrain, geomorphology, vegetation height, and lithology, and used data from two Swiss field inventories to calibrate and test the models. The best-performing machine learning model consistently reduced the mean average error by at least 20 % compared to previous models.
This article is included in the Encyclopedia of Geosciences
Jui-Ming Chang, Che-Ming Yang, Wei-An Chao, Chin-Shang Ku, Ming-Wan Huang, Tung-Chou Hsieh, and Chi-Yao Hung
Nat. Hazards Earth Syst. Sci., 25, 451–466, https://doi.org/10.5194/nhess-25-451-2025, https://doi.org/10.5194/nhess-25-451-2025, 2025
Short summary
Short summary
The study on the Cilan landslide (CL) demonstrates the utilization of seismic analysis results as preliminary data for geologists during field surveys. Spectrograms revealed that the first event of CL consisted of four sliding failures accompanied by a gradual reduction in landslide volume. The second and third events were minor toppling and rockfalls. Then combining the seismological-based knowledge and field survey results, the spatiotemporal variation in landslide evolution is proposed.
This article is included in the Encyclopedia of Geosciences
Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, and Snježana Mihalić Arbanas
Nat. Hazards Earth Syst. Sci., 25, 183–206, https://doi.org/10.5194/nhess-25-183-2025, https://doi.org/10.5194/nhess-25-183-2025, 2025
Short summary
Short summary
The paper focuses on classifying continuous landslide conditioning factors for susceptibility modelling, which resulted in 54 landslide susceptibility models that tested 11 classification criteria in combination with 5 statistical methods. The novelty of the research is that using stretched landslide conditioning factor values results in models with higher accuracy and that certain statistical methods are more sensitive to the landslide conditioning factor classification criteria than others.
This article is included in the Encyclopedia of Geosciences
Benjamin B. Mirus, Thom Bogaard, Roberto Greco, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 25, 169–182, https://doi.org/10.5194/nhess-25-169-2025, https://doi.org/10.5194/nhess-25-169-2025, 2025
Short summary
Short summary
Early warning of increased landslide potential provides situational awareness to reduce landslide-related losses from major storm events. For decades, landslide forecasts relied on rainfall data alone, but recent research points to the value of hydrologic information for improving predictions. In this paper, we provide our perspectives on the value and limitations of integrating subsurface hillslope hydrologic monitoring data and mathematical modeling for more accurate landslide forecasts.
This article is included in the Encyclopedia of Geosciences
Jui-Sheng Chou, Hoang-Minh Nguyen, Huy-Phuong Phan, and Kuo-Lung Wang
Nat. Hazards Earth Syst. Sci., 25, 119–146, https://doi.org/10.5194/nhess-25-119-2025, https://doi.org/10.5194/nhess-25-119-2025, 2025
Short summary
Short summary
This study enhances landslide prediction using advanced machine learning, including new algorithms inspired by historical explorations. The research accurately forecasts landslide movements by analyzing 8 years of data from Taiwan's Lushan, improving early warning and potentially saving lives and infrastructure. This integration marks a significant advancement in environmental risk management.
This article is included in the Encyclopedia of Geosciences
Di Wu, Yuke Wang, and Xin Chen
Nat. Hazards Earth Syst. Sci., 24, 4617–4630, https://doi.org/10.5194/nhess-24-4617-2024, https://doi.org/10.5194/nhess-24-4617-2024, 2024
Short summary
Short summary
This paper proposes a 3D limit analysis for seismic stability of soil slopes to address the influence of earthquakes on slope stabilities with nonlinear and linear criteria. Comparison results illustrate that the use of a linear envelope leads to the non-negligible overestimation of steep-slope stability, and this overestimation will be significant with increasing earthquakes. Earthquakes have a smaller influence on slope slip surfaces with a nonlinear envelope than those with a linear envelope.
This article is included in the Encyclopedia of Geosciences
Matthias Schlögl, Anita Graser, Raphael Spiekermann, Jasmin Lampert, and Stefan Steger
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-213, https://doi.org/10.5194/nhess-2024-213, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Communicating uncertainties is a crucial yet challenging aspect of spatial modelling – especially in applied research, where results inform decisions. In disaster risk reduction, susceptibility maps for natural hazards guide planning and risk assessment, yet their uncertainties are often overlooked. We present a new type of landslide susceptibility map that visualizes both susceptibility and associated uncertainty, alongside guidelines for creating such maps using free and open-source software.
This article is included in the Encyclopedia of Geosciences
Li Wei, Kaiheng Hu, Shuang Liu, Lan Ning, Xiaopeng Zhang, Qiyuan Zhang, and Md. Abdur Rahim
Nat. Hazards Earth Syst. Sci., 24, 4179–4197, https://doi.org/10.5194/nhess-24-4179-2024, https://doi.org/10.5194/nhess-24-4179-2024, 2024
Short summary
Short summary
The damage patterns of the buildings were classified into three types: (I) buried by primary debris flow, (II) inundated by secondary dam-burst flood, and (III) sequentially buried by debris flow and inundated by dam-burst flood. The threshold of the impact pressures in Zones (II) and (III) where vulnerability is equal to 1 is 84 kPa and 116 kPa, respectively. Heavy damage occurs at an impact pressure greater than 50 kPa, while slight damage occurs below 30 kPa.
This article is included in the Encyclopedia of Geosciences
Bo Peng and Xueling Wu
Nat. Hazards Earth Syst. Sci., 24, 3991–4013, https://doi.org/10.5194/nhess-24-3991-2024, https://doi.org/10.5194/nhess-24-3991-2024, 2024
Short summary
Short summary
Our research enhances landslide prevention using advanced machine learning to forecast heavy-rainfall-triggered landslides. By analyzing regions and employing various models, we identified optimal ways to predict high-risk rainfall events. Integrating multiple factors and models, including a neural network, significantly improves landslide predictions. Real data validation confirms our approach's reliability, aiding communities in mitigating landslide impacts and safeguarding lives and property.
This article is included in the Encyclopedia of Geosciences
Andrea Manconi, Yves Bühler, Andreas Stoffel, Johan Gaume, Qiaoping Zhang, and Valentyn Tolpekin
Nat. Hazards Earth Syst. Sci., 24, 3833–3839, https://doi.org/10.5194/nhess-24-3833-2024, https://doi.org/10.5194/nhess-24-3833-2024, 2024
Short summary
Short summary
Our research reveals the power of high-resolution satellite synthetic-aperture radar (SAR) imagery for slope deformation monitoring. Using ICEYE data over the Brienz/Brinzauls instability, we measured surface velocity and mapped the landslide event with unprecedented precision. This underscores the potential of satellite SAR for timely hazard assessment in remote regions and aiding disaster mitigation efforts effectively.
This article is included in the Encyclopedia of Geosciences
Oliver Korup, Lisa V. Luna, and Joaquin V. Ferrer
Nat. Hazards Earth Syst. Sci., 24, 3815–3832, https://doi.org/10.5194/nhess-24-3815-2024, https://doi.org/10.5194/nhess-24-3815-2024, 2024
Short summary
Short summary
Catalogues of mapped landslides are useful for learning and forecasting how frequently they occur in relation to their size. Yet, rare and large landslides remain mostly uncertain in statistical summaries of these catalogues. We propose a single, consistent method of comparing across different data sources and find that landslide statistics disclose more about subjective mapping choices than trigger types or environmental settings.
This article is included in the Encyclopedia of Geosciences
Rachael Lau, Carolina Seguí, Tyler Waterman, Nathaniel Chaney, and Manolis Veveakis
Nat. Hazards Earth Syst. Sci., 24, 3651–3661, https://doi.org/10.5194/nhess-24-3651-2024, https://doi.org/10.5194/nhess-24-3651-2024, 2024
Short summary
Short summary
This work examines the use of interferometric synthetic-aperture radar (InSAR) alongside in situ borehole measurements to assess the stability of deep-seated landslides for the case study of El Forn (Andorra). Comparing InSAR with borehole data suggests a key trade-off between accuracy and precision for various InSAR resolutions. Spatial interpolation with InSAR informed how many remote observations are necessary to lower error in a remote sensing re-creation of ground motion over the landslide.
This article is included in the Encyclopedia of Geosciences
Zhen Lei Wei, Yue Quan Shang, Qiu Hua Liang, and Xi Lin Xia
Nat. Hazards Earth Syst. Sci., 24, 3357–3379, https://doi.org/10.5194/nhess-24-3357-2024, https://doi.org/10.5194/nhess-24-3357-2024, 2024
Short summary
Short summary
The initiation of debris flows is significantly influenced by rainfall-induced hydrological processes. We propose a novel framework based on an integrated hydrological and hydrodynamic model and aimed at estimating intensity–duration (ID) rainfall thresholds responsible for triggering debris flows. In comparison to traditional statistical approaches, this physically based framework is particularly suitable for application in ungauged catchments where historical debris flow data are scarce.
This article is included in the Encyclopedia of Geosciences
Dianne L. Brien, Mark E. Reid, Collin Cronkite-Ratcliff, and Jonathan P. Perkins
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-141, https://doi.org/10.5194/nhess-2024-141, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Landslide runout zones are the areas downslope or downstream of landslide initiation. People often live and work in these areas, leading to property damage and deaths. We develop methods to identify potential runout zones from landslides. We apply our methods to create susceptibility maps for three study areas in Puerto Rico and assess the success of our methods based on mapped landslides from Hurricane Maria.
This article is included in the Encyclopedia of Geosciences
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024, https://doi.org/10.5194/nhess-24-3207-2024, 2024
Short summary
Short summary
The Himalayan road network links remote areas, but fragile terrain and poor construction lead to frequent landslides. This study on the NH-7 in India's Uttarakhand region analyzed 300 landslides after heavy rainfall in 2022 . Factors like slope, rainfall, rock type and road work influence landslides. The study's model predicts landslide locations for better road maintenance planning, highlighting the risk from climate change and increased road use.
This article is included in the Encyclopedia of Geosciences
Chenchen Qiu and Xueyu Geng
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-156, https://doi.org/10.5194/nhess-2024-156, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
We proposed an interated method with the combination of a physical vulnerability matric and a machine learning model to estimate the potential physical damage and associated economic loss caused by future debris flows based on the collected historical data on the Qinghai-Tibet Plateau regions.
This article is included in the Encyclopedia of Geosciences
Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 24, 2689–2704, https://doi.org/10.5194/nhess-24-2689-2024, https://doi.org/10.5194/nhess-24-2689-2024, 2024
Short summary
Short summary
Landslides are complex phenomena causing important impacts in vulnerable areas, and they are often triggered by rainfall. Here, we develop a new approach that uses information on the temporal clustering of rainfall, i.e. multiple events close in time, to detect landslide events and compare it with the use of classical empirical rainfall thresholds, considering as a case study the region of Lisbon, Portugal. The results could help to improve the prediction of rainfall-triggered landslides.
This article is included in the Encyclopedia of Geosciences
Jianqi Zhuang, Jianbing Peng, Chenhui Du, Yi Zhu, and Jiaxu Kong
Nat. Hazards Earth Syst. Sci., 24, 2615–2631, https://doi.org/10.5194/nhess-24-2615-2024, https://doi.org/10.5194/nhess-24-2615-2024, 2024
Short summary
Short summary
The Revised Infinite Slope Model (RISM) is proposed using the equal differential unit method and correcting the deficiency of the safety factor increasing with the slope increasing when the slope is larger than 40°, as calculated using the Taylor slope infinite model. The intensity–duration (I–D) prediction curve of the rainfall-induced shallow loess landslides with different slopes was constructed and can be used in forecasting regional shallow loess landslides.
This article is included in the Encyclopedia of Geosciences
Roberto Sarro, Mauro Rossi, Paola Reichenbach, and Rosa María Mateos
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-85, https://doi.org/10.5194/nhess-2024-85, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study proposes a novel workflow to precisely model rockfalls. It compares three methods for defining source areas to enhance model accuracy. Identified areas are inputted into a runout model to identify vulnerable zones. A new approach generates probabilistic susceptibility maps using ECDFs. Validation strategies employing various inventory types are included. Comparing six susceptibility maps highlights the impact of source area definition on model precision.
This article is included in the Encyclopedia of Geosciences
Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley
Nat. Hazards Earth Syst. Sci., 24, 2359–2374, https://doi.org/10.5194/nhess-24-2359-2024, https://doi.org/10.5194/nhess-24-2359-2024, 2024
Short summary
Short summary
Fire can dramatically increase the risk of debris flows to downstream communities with little warning, but hazard assessments have not traditionally included estimates of inundation. We unify models developed by the scientific community to create probabilistic estimates of inundation area in response to rainfall at forecast lead times (≥ 24 h) needed for decision-making. This work takes an initial step toward a near-real-time postfire debris-flow inundation hazard assessment product.
This article is included in the Encyclopedia of Geosciences
Francis K. Rengers, Samuel Bower, Andrew Knapp, Jason W. Kean, Danielle W. vonLembke, Matthew A. Thomas, Jaime Kostelnik, Katherine R. Barnhart, Matthew Bethel, Joseph E. Gartner, Madeline Hille, Dennis M. Staley, Justin K. Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgway, and Brendan P. Murphy
Nat. Hazards Earth Syst. Sci., 24, 2093–2114, https://doi.org/10.5194/nhess-24-2093-2024, https://doi.org/10.5194/nhess-24-2093-2024, 2024
Short summary
Short summary
Every year the U.S. Geological Survey produces 50–100 postfire debris-flow hazard assessments using models for debris-flow likelihood and volume. To refine these models they must be tested with datasets that clearly document rainfall, debris-flow response, and debris-flow volume. These datasets are difficult to obtain, but this study developed and analyzed a postfire dataset with more than 100 postfire storm responses over a 2-year period. We also proposed ways to improve these models.
This article is included in the Encyclopedia of Geosciences
Ellen B. Robson, Bhim Kumar Dahal, and David G. Toll
EGUsphere, https://doi.org/10.5194/egusphere-2024-1300, https://doi.org/10.5194/egusphere-2024-1300, 2024
Short summary
Short summary
Slopes excavated alongside roads in Nepal frequently fail (a landslide), resulting in substantial losses. Our participatory approach study involving road engineers aimed to assess the efficacy of the current slope design guidelines in Nepal. Our study revealed inconsistent guideline adherence due to their lack of user-friendliness and inadequate training. We recommend developing simpler, context-specific guidelines and comprehensive training to enhance resilience in Nepal's road network.
This article is included in the Encyclopedia of Geosciences
Praveen Kumar, Priyanka Priyanka, Kala Venkata Uday, and Varun Dutt
Nat. Hazards Earth Syst. Sci., 24, 1913–1928, https://doi.org/10.5194/nhess-24-1913-2024, https://doi.org/10.5194/nhess-24-1913-2024, 2024
Short summary
Short summary
Our study focuses on predicting soil movement to mitigate landslide risks. We develop machine learning models with oversampling techniques to address the class imbalance in monitoring data. The dynamic ensemble model with K-means SMOTE (synthetic minority oversampling technique) achieves high precision, high recall, and a high F1 score. Our findings highlight the potential of these models with oversampling techniques to improve soil movement predictions in landslide-prone areas.
This article is included in the Encyclopedia of Geosciences
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci., 24, 1897–1911, https://doi.org/10.5194/nhess-24-1897-2024, https://doi.org/10.5194/nhess-24-1897-2024, 2024
Short summary
Short summary
In our study, we analysed publicly available data in order to investigate the impact of climate change on landslides in Denmark. Our research indicates that the rising groundwater table due to climate change will result in an increase in landslide activity. Previous incidents of extremely wet winters have caused damage to infrastructure and buildings due to landslides. This study is the first of its kind to exclusively rely on public data and examine landslides in Denmark.
This article is included in the Encyclopedia of Geosciences
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024, https://doi.org/10.5194/nhess-24-1741-2024, 2024
Short summary
Short summary
With a simplified formula linking rainfall and groundwater level, the rise of the phreatic surface within the slope can be obtained. Then, a global analysis method that considers both seepage and seismic forces is proposed to determine the safety factor of slopes subjected to the combined effect of rainfall and earthquakes. By taking a slope in the Three Gorges Reservoir area as an example, the safety evolution of the slope combined with both rainfall and earthquake is also examined.
This article is included in the Encyclopedia of Geosciences
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024, https://doi.org/10.5194/nhess-24-1697-2024, 2024
Short summary
Short summary
Central Asia regions are marked by active tectonics, high mountains with glaciers, and strong rainfall. These predisposing factors make large landslides a serious threat in the area and a source of possible damming scenarios, which endanger the population. To prevent this, a semi-automated geographic information system (GIS-)based mapping method, centered on a bivariate correlation of morphometric parameters, was applied to give preliminary information on damming susceptibility in Central Asia.
This article is included in the Encyclopedia of Geosciences
Rex L. Baum, Dianne L. Brien, Mark E. Reid, William H. Schulz, and Matthew J. Tello
Nat. Hazards Earth Syst. Sci., 24, 1579–1605, https://doi.org/10.5194/nhess-24-1579-2024, https://doi.org/10.5194/nhess-24-1579-2024, 2024
Short summary
Short summary
We mapped potential for heavy rainfall to cause landslides in part of the central mountains of Puerto Rico using new tools for estimating soil depth and quasi-3D slope stability. Potential ground-failure locations correlate well with the spatial density of landslides from Hurricane Maria. The smooth boundaries of the very high and high ground-failure susceptibility zones enclose 75 % and 90 %, respectively, of observed landslides. The maps can help mitigate ground-failure hazards.
This article is included in the Encyclopedia of Geosciences
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 24, 1459–1483, https://doi.org/10.5194/nhess-24-1459-2024, https://doi.org/10.5194/nhess-24-1459-2024, 2024
Short summary
Short summary
Debris flows are a type of fast-moving landslide that start from shallow landslides or during intense rain. Infrastructure located downstream of watersheds susceptible to debris flows may be damaged should a debris flow reach them. We present and evaluate an approach to forecast building damage caused by debris flows. We test three alternative models for simulating the motion of debris flows and find that only one can forecast the correct number and spatial pattern of damaged buildings.
This article is included in the Encyclopedia of Geosciences
Luke A. McGuire, Francis K. Rengers, Ann M. Youberg, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Ryan Porter
Nat. Hazards Earth Syst. Sci., 24, 1357–1379, https://doi.org/10.5194/nhess-24-1357-2024, https://doi.org/10.5194/nhess-24-1357-2024, 2024
Short summary
Short summary
Runoff and erosion increase after fire, leading to a greater likelihood of floods and debris flows. We monitored debris flow activity following a fire in western New Mexico, USA, and observed 16 debris flows over a <2-year monitoring period. Rainstorms with recurrence intervals of approximately 1 year were sufficient to initiate debris flows. All debris flows initiated during the first several months following the fire, indicating a rapid decrease in debris flow susceptibility over time.
This article is included in the Encyclopedia of Geosciences
Ken'ichi Koshimizu, Satoshi Ishimaru, Fumitoshi Imaizumi, and Gentaro Kawakami
Nat. Hazards Earth Syst. Sci., 24, 1287–1301, https://doi.org/10.5194/nhess-24-1287-2024, https://doi.org/10.5194/nhess-24-1287-2024, 2024
Short summary
Short summary
Morphological conditions of drainage basins that classify the presence or absence of debris flow fans were analyzed in areas with different rock strength using decision tree analysis. The relief ratio is the most important morphological factor regardless of the geology. However, the thresholds of morphological parameters needed for forming debris flow fans differ depending on the geology. Decision tree analysis is an effective tool for evaluating the debris flow risk for each geology.
This article is included in the Encyclopedia of Geosciences
Jonathan P. Perkins, Nina S. Oakley, Brian D. Collins, Skye C. Corbett, and W. Paul Burgess
EGUsphere, https://doi.org/10.5194/egusphere-2024-873, https://doi.org/10.5194/egusphere-2024-873, 2024
Short summary
Short summary
Landslides are a global issue that results in deaths and economic losses annually. However, it is not clear how storm severity relates to landslide severity across large regions. Here we develop a method to estimate the footprint of landslide area and compare this to meteorologic estimates of storm severity. We find that total storm strength does not clearly relate to landslide area. Rather, landslide area depends on soil wetness and smaller storm structures that can produce intense rainfall.
This article is included in the Encyclopedia of Geosciences
Daniel Bolliger, Fritz Schlunegger, and Brian W. McArdell
Nat. Hazards Earth Syst. Sci., 24, 1035–1049, https://doi.org/10.5194/nhess-24-1035-2024, https://doi.org/10.5194/nhess-24-1035-2024, 2024
Short summary
Short summary
We analysed data from the Illgraben debris flow monitoring station, Switzerland, and we modelled these flows with a debris flow runout model. We found that no correlation exists between the grain size distribution, the mineralogical composition of the matrix, and the debris flow properties. The flow properties rather appear to be determined by the flow volume, from which most other parameters can be derived.
This article is included in the Encyclopedia of Geosciences
Yuntao Zhou, Xiaoyan Zhao, Guangze Zhang, Bernd Wünnemann, Jiajia Zhang, and Minghui Meng
Nat. Hazards Earth Syst. Sci., 24, 891–906, https://doi.org/10.5194/nhess-24-891-2024, https://doi.org/10.5194/nhess-24-891-2024, 2024
Short summary
Short summary
We developed three rock bridge models to analyze 3D stability and deformation behaviors of the Tizicao landslide and found that the contact surface model with high strength parameters combines advantages of the intact rock mass model in simulating the deformation of slopes with rock bridges and the modeling advantage of the Jennings model. The results help in choosing a rock bridge model to simulate landslide stability and reveal the influence laws of rock bridges on the stability of landslides.
This article is included in the Encyclopedia of Geosciences
Ashok Dahal, Hakan Tanyas, Cees van Westen, Mark van der Meijde, Paul Martin Mai, Raphaël Huser, and Luigi Lombardo
Nat. Hazards Earth Syst. Sci., 24, 823–845, https://doi.org/10.5194/nhess-24-823-2024, https://doi.org/10.5194/nhess-24-823-2024, 2024
Short summary
Short summary
We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
This article is included in the Encyclopedia of Geosciences
Li-Ru Luo, Zhi-Xiang Yu, Li-Jun Zhang, Qi Wang, Lin-Xu Liao, and Li Peng
Nat. Hazards Earth Syst. Sci., 24, 631–649, https://doi.org/10.5194/nhess-24-631-2024, https://doi.org/10.5194/nhess-24-631-2024, 2024
Short summary
Short summary
We performed field investigations on a rockfall near Jiguanshan National Forest Park, Chengdu. Vital information was obtained from an unmanned aerial vehicle survey. A finite element model was created to reproduce the damage evolution. We found that the impact kinetic energy was below the design protection energy. Improper member connections prevent the barrier from producing significant deformation to absorb energy. Damage is avoided by improving the ability of the nets and ropes to slide.
This article is included in the Encyclopedia of Geosciences
Sudhanshu Dixit, Srikrishnan Siva Subramanian, Piyush Srivastava, Ali P. Yunus, Tapas Ranjan Martha, and Sumit Sen
Nat. Hazards Earth Syst. Sci., 24, 465–480, https://doi.org/10.5194/nhess-24-465-2024, https://doi.org/10.5194/nhess-24-465-2024, 2024
Short summary
Short summary
Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards. Large-scale sediment disasters like landslides, debris flows, and flash floods happen frequently in the Himalayas because of their propensity for intense precipitation events. We provide a new framework that combines the Weather Research and Forecasting (WRF) model with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
This article is included in the Encyclopedia of Geosciences
Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, and Matthew M. Crawford
Nat. Hazards Earth Syst. Sci., 24, 1–12, https://doi.org/10.5194/nhess-24-1-2024, https://doi.org/10.5194/nhess-24-1-2024, 2024
Short summary
Short summary
Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.
This article is included in the Encyclopedia of Geosciences
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
Nat. Hazards Earth Syst. Sci., 23, 3805–3821, https://doi.org/10.5194/nhess-23-3805-2023, https://doi.org/10.5194/nhess-23-3805-2023, 2023
Short summary
Short summary
The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
This article is included in the Encyclopedia of Geosciences
Xushan Shi, Bo Chai, Juan Du, Wei Wang, and Bo Liu
Nat. Hazards Earth Syst. Sci., 23, 3425–3443, https://doi.org/10.5194/nhess-23-3425-2023, https://doi.org/10.5194/nhess-23-3425-2023, 2023
Short summary
Short summary
A 3D stability analysis method is proposed for biased rockfall with external erosion. Four failure modes are considered according to rockfall evolution processes, including partial damage of underlying soft rock and overall failure of hard rock blocks. This method is validated with the biased rockfalls in the Sichuan Basin, China. The critical retreat ratio from low to moderate rockfall susceptibility is 0.33. This method could facilitate rockfall early identification and risk mitigation.
This article is included in the Encyclopedia of Geosciences
Marius Schneider, Nicolas Oestreicher, Thomas Ehrat, and Simon Loew
Nat. Hazards Earth Syst. Sci., 23, 3337–3354, https://doi.org/10.5194/nhess-23-3337-2023, https://doi.org/10.5194/nhess-23-3337-2023, 2023
Short summary
Short summary
Rockfalls and their hazards are typically treated as statistical events based on rockfall catalogs, but only a few complete rockfall inventories are available today. Here, we present new results from a Doppler radar rockfall alarm system, which has operated since 2018 at a high frequency under all illumination and weather conditions at a site where frequent rockfall events threaten a village and road. The new data set is used to investigate rockfall triggers in an active rockslide complex.
This article is included in the Encyclopedia of Geosciences
Annette I. Patton, Lisa V. Luna, Joshua J. Roering, Aaron Jacobs, Oliver Korup, and Benjamin B. Mirus
Nat. Hazards Earth Syst. Sci., 23, 3261–3284, https://doi.org/10.5194/nhess-23-3261-2023, https://doi.org/10.5194/nhess-23-3261-2023, 2023
Short summary
Short summary
Landslide warning systems often use statistical models to predict landslides based on rainfall. They are typically trained on large datasets with many landslide occurrences, but in rural areas large datasets may not exist. In this study, we evaluate which statistical model types are best suited to predicting landslides and demonstrate that even a small landslide inventory (five storms) can be used to train useful models for landslide early warning when non-landslide events are also included.
This article is included in the Encyclopedia of Geosciences
Sandra Melzner, Marco Conedera, Johannes Hübl, and Mauro Rossi
Nat. Hazards Earth Syst. Sci., 23, 3079–3093, https://doi.org/10.5194/nhess-23-3079-2023, https://doi.org/10.5194/nhess-23-3079-2023, 2023
Short summary
Short summary
The estimation of the temporal frequency of the involved rockfall processes is an important part in hazard and risk assessments. Different methods can be used to collect and analyse rockfall data. From a statistical point of view, rockfall datasets are nearly always incomplete. Accurate data collection approaches and the application of statistical methods on existing rockfall data series as reported in this study should be better considered in rockfall hazard and risk assessments in the future.
This article is included in the Encyclopedia of Geosciences
Stefan Hergarten
Nat. Hazards Earth Syst. Sci., 23, 3051–3063, https://doi.org/10.5194/nhess-23-3051-2023, https://doi.org/10.5194/nhess-23-3051-2023, 2023
Short summary
Short summary
Rockslides are a major hazard in mountainous regions. In formerly glaciated regions, the disposition mainly arises from oversteepened topography and decreases through time. However, little is known about this decrease and thus about the present-day hazard of huge, potentially catastrophic rockslides. This paper presents a new theoretical framework that explains the decrease in maximum rockslide size through time and predicts the present-day frequency of large rockslides for the European Alps.
This article is included in the Encyclopedia of Geosciences
Colin K. Bloom, Corinne Singeisen, Timothy Stahl, Andrew Howell, Chris Massey, and Dougal Mason
Nat. Hazards Earth Syst. Sci., 23, 2987–3013, https://doi.org/10.5194/nhess-23-2987-2023, https://doi.org/10.5194/nhess-23-2987-2023, 2023
Short summary
Short summary
Landslides are often observed on coastlines following large earthquakes, but few studies have explored this occurrence. Here, statistical modelling of landslides triggered by the 2016 Kaikōura earthquake in New Zealand is used to investigate factors driving coastal earthquake-induced landslides. Geology, steep slopes, and shaking intensity are good predictors of landslides from the Kaikōura event. Steeper slopes close to the coast provide the best explanation for a high landslide density.
This article is included in the Encyclopedia of Geosciences
Yi-Min Huang
Nat. Hazards Earth Syst. Sci., 23, 2649–2662, https://doi.org/10.5194/nhess-23-2649-2023, https://doi.org/10.5194/nhess-23-2649-2023, 2023
Short summary
Short summary
Debris flows are common hazards in Taiwan, and debris-flow early warning is important for disaster responses. The rainfall thresholds of debris flows are analyzed and determined in terms of rainfall intensity, accumulated rainfall, and rainfall duration, based on case histories in Taiwan. These thresholds are useful for disaster management, and the cases in Taiwan are useful for global debris-flow databases.
This article is included in the Encyclopedia of Geosciences
Davide Notti, Martina Cignetti, Danilo Godone, and Daniele Giordan
Nat. Hazards Earth Syst. Sci., 23, 2625–2648, https://doi.org/10.5194/nhess-23-2625-2023, https://doi.org/10.5194/nhess-23-2625-2023, 2023
Short summary
Short summary
We developed a cost-effective and user-friendly approach to map shallow landslides using free satellite data. Our methodology involves analysing the pre- and post-event NDVI variation to semi-automatically detect areas potentially affected by shallow landslides (PLs). Additionally, we have created Google Earth Engine scripts to rapidly compute NDVI differences and time series of affected areas. Datasets and codes are stored in an open data repository for improvement by the scientific community.
This article is included in the Encyclopedia of Geosciences
Simon Seelig, Thomas Wagner, Karl Krainer, Michael Avian, Marc Olefs, Klaus Haslinger, and Gerfried Winkler
Nat. Hazards Earth Syst. Sci., 23, 2547–2568, https://doi.org/10.5194/nhess-23-2547-2023, https://doi.org/10.5194/nhess-23-2547-2023, 2023
Short summary
Short summary
A rapid sequence of cascading events involving thermokarst lake outburst, rock glacier front failure, debris flow development, and river blockage hit an alpine valley in Austria during summer 2019. We analyze the environmental conditions initiating the process chain and identify the rapid evolution of a thermokarst channel network as the main driver. Our results highlight the need to account for permafrost degradation in debris flow hazard assessment studies.
This article is included in the Encyclopedia of Geosciences
Camilla Lanfranconi, Paolo Frattini, Gianluca Sala, Giuseppe Dattola, Davide Bertolo, Juanjuan Sun, and Giovanni Battista Crosta
Nat. Hazards Earth Syst. Sci., 23, 2349–2363, https://doi.org/10.5194/nhess-23-2349-2023, https://doi.org/10.5194/nhess-23-2349-2023, 2023
Short summary
Short summary
This paper presents a study on rockfall dynamics and hazard, examining the impact of the presence of trees along slope and block fragmentation. We compared rockfall simulations that explicitly model the presence of trees and fragmentation with a classical approach that accounts for these phenomena in model parameters (both the hazard and the kinetic energy change). We also used a non-parametric probabilistic rockfall hazard analysis method for hazard mapping.
This article is included in the Encyclopedia of Geosciences
Ascanio Rosi, William Frodella, Nicola Nocentini, Francesco Caleca, Hans Balder Havenith, Alexander Strom, Mirzo Saidov, Gany Amirgalievich Bimurzaev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 23, 2229–2250, https://doi.org/10.5194/nhess-23-2229-2023, https://doi.org/10.5194/nhess-23-2229-2023, 2023
Short summary
Short summary
This work was carried out within the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project and is focused on the first landslide susceptibility analysis at a regional scale for Central Asia. The most detailed available landslide inventories were implemented in a random forest model. The final aim was to provide a useful tool for reduction strategies to landslide scientists, practitioners, and administrators.
This article is included in the Encyclopedia of Geosciences
Cited articles
Bates, D., Mächler, M., Bolker, B., and Walker, S.: Fitting Linear
Mixed-Effects Models Using lme4, J. Stat. Softw., 67,
1–48, https://doi.org/10.18637/jss.v067.i01, 2015. a
Blöschl, G. and Sivapalan, M.: Scale Issues in Hydrological Modelling: A
Review, Hydrol. Process., 9, 251–290, https://doi.org/10.1002/hyp.3360090305,
1995. a
Bosilovich, M. G., Lucchesi, R., and Suarez, M.: MERRA-2: File Specification, GMAO Office Note No. 9 (Version 1.1), 73 pp., http://gmao.gsfc.nasa.gov/pubs/office_notes (last access: 15 September 2021), 2016. a
Brenning, A.: Spatial prediction models for landslide hazards: review, comparison and evaluation, Nat. Hazards Earth Syst. Sci., 5, 853–862, https://doi.org/10.5194/nhess-5-853-2005, 2005. a, b, c
Broeckx, J., Rossi, M., Lijnen, K., Campforts, B., Poesen, J., and Vanmaercke,
M.: Landslide Mobilization Rates: A Global Analysis and Model, Earth-Sci.
Rev., 201, 102972, https://doi.org/10.1016/j.earscirev.2019.102972, 2020. a
Calvello, M. and Pecoraro, G.: FraneItalia: A Catalog of Recent Italian
Landslides (Version 2.0), 2, Mendeley [data set], https://doi.org/10.17632/zygb8jygrw.2, 2020. a
ampforts, B., Vanacker, V., Herman, F., Vanmaercke, M., Schwanghart, W., Tenorio, G. E., Willems, P., and Govers, G.: Parameterization of river incision models requires accounting for environmental heterogeneity: insights from the tropical Andes, Earth Surf. Dynam., 8, 447–470, https://doi.org/10.5194/esurf-8-447-2020, 2020. a
Crozier, M.: 7.26 Mass-Movement Hazards and Risks, in: Treatise on
Geomorphology, 7, 249–258,
https://doi.org/10.1016/B978-0-12-374739-6.00175-5, 2013. a, b
De Lannoy, G. J. M.: Assimilation of Soil Moisture Observations into a
Spatially Distributed Hydrologic Model, PhD thesis, Ghent University,
ISBN 9789059891418,
2006. a
De Lannoy, G. J. M., Reichle, R. H., Houser, P. R., Arsenault, K. R., Verhoest,
N. E. C., and Pauwels, V. R. N.: Satellite-Scale Snow Water Equivalent
Assimilation into a High-Resolution Land Surface Model, J.
Hydrometeorol., 11, 352–369, https://doi.org/10.1175/2009JHM1192.1, 2010. a
De Lannoy, G. J. M. D., Koster, R. D., Reichle, R. H., Mahanama, S. P. P., and
Liu, Q.: An Updated Treatment of Soil Texture and Associated Hydraulic
Properties in a Global Land Modeling System, J. Adv. Model.
Earth Sy., 6, 957–979, https://doi.org/10.1002/2014MS000330, 2014. a, b
Depicker, A., Jacobs, L., Delvaux, D., Havenith, H.-B., Maki Mateso, J.-C.,
Govers, G., and Dewitte, O.: The Added Value of a Regional Landslide
Susceptibility Assessment: The Western Branch of the East African Rift,
Geomorphology, 353, 106886, https://doi.org/10.1016/j.geomorph.2019.106886, 2020. a, b, c, d, e
Depicker, A., Jacobs, L., Mboga, N., Smets, B., Van Rompaey, A., Lennert, M.,
Wolff, E., Kervyn, F., Michellier, C., Dewitte, O., and Govers, G.:
Historical Dynamics of Landslide Risk from Population and Forest-Cover
Changes in the Kivu Rift, Nature Sustainability, 4, 965–974,
https://doi.org/10.1038/s41893-021-00757-9, 2021. a, b
Dille, A., Kervyn, F., Mugaruka Bibentyo, T., Delvaux, D., Ganza, G. B.,
Ilombe Mawe, G., Kalikone Buzera, C., Safari Nakito, E., Moeyersons, J.,
Monsieurs, E., Nzolang, C., Smets, B., Kervyn, M., and Dewitte, O.: Causes
and Triggers of Deep-Seated Hillslope Instability in the Tropics
– Insights from a 60-Year Record of Ikoma Landslide (DR
Congo), Geomorphology, 345, 106835, https://doi.org/10.1016/j.geomorph.2019.106835,
2019. a
Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G.,
Marquéz, J. R. G., Gruber, B., Lafourcade, B., Leitão, P. J.,
Münkemüller, T., McClean, C., Osborne, P. E., Reineking, B.,
Schröder, B., Skidmore, A. K., Zurell, D., and Lautenbach, S.:
Collinearity: A Review of Methods to Deal with It and a Simulation Study
Evaluating Their Performance, Ecography, 36, 27–46,
https://doi.org/10.1111/j.1600-0587.2012.07348.x, 2013. a
Emberson, R., Kirschbaum, D. B., Amatya, P., Tanyas, H., and Marc, O.: Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories, Nat. Hazards Earth Syst. Sci., 22, 1129–1149, https://doi.org/10.5194/nhess-22-1129-2022, 2022. a
EROS: Global Topographic 30 Arc-Second Hydrologic Digital Elevation
Model 1 Km, USGS [data set], https://doi.org/10.5066/F77P8WN0, 2018. a
Felsberg, A., De Lannoy, G. J. M., Poesen, J., Bechtold, M., and Vanmaercke, M.: Ensemble of global landslide susceptibility, Zenodo [data set], https://doi.org/10.5281/zenodo.6893230, 2022. a
Felsberg, A., De Lannoy, G. J. M., Girotto, M., Poesen, J., Reichle, R. H., and
Stanley, T.: Global Soil Water Estimates as Landslide Predictor: The
Effectiveness of SMOS, SMAP, and GRACE Observations, Land
Surface Simulations, and Data Assimilation, J. Hydrometeorol., 22, 1065–1084, https://doi.org/10.1175/JHM-D-20-0228.1, 2021. a, b
FSBIH – Federal State Budgetary Institution “Hydrospetzgeologiya”: Quarter Annual Reports of Exogenous Geological Processes on Territories of the Russian Federation, Center for monitoring the state of the subsoil, 2018. a
Giardini, D., Grünthal, G., Shedlock, K., and Zhang, P.: The GSHAP Global
Seismic Hazard Map, Lee, W., Kanamori, H., Jennings, P., and Kisslinger, C.
(Eds.): International Handbook of Earthquake & Engineering Seismology,
International Geophysics Series 81 B, Academic Press, Amsterdam,
1233–1239, ISBN 0-12-440658-0, 2003. a, b
Guzzetti, F., Reichenbach, P., Cardinali, M., Galli, M., and Ardizzone, F.:
Probabilistic Landslide Hazard Assessment at the Basin Scale, Geomorphology,
72, 272–299, https://doi.org/10.1016/j.geomorph.2005.06.002, 2005. a
Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M., and Galli, M.:
Estimating the Quality of Landslide Susceptibility Models, Geomorphology, 81,
166–184, https://doi.org/10.1016/j.geomorph.2006.04.007, 2006. a, b
Hartmann, J. and Moosdorf, N.: The New Global Lithological Map Database
GLiM: A Representation of Rock Properties at the Earth Surface,
Geochem. Geophy. Geosy., 13, Q12004,
https://doi.org/10.1029/2012GC004370, 2012. a, b
Hong, Y., Adler, R., and Huffman, G.: Use of Satellite Remote Sensing Data in
the Mapping of Global Landslide Susceptibility, Nat. Hazards,
43, 245–256, https://doi.org/10.1007/s11069-006-9104-z, 2007. a, b, c
Juang, C. S., Stanley, T. A., and Kirschbaum, D. B.: Using Citizen Science to
Expand the Global Map of Landslides: Introducing the Cooperative Open
Online Landslide Repository (COOLR), PLOS ONE, 14, e0218657,
https://doi.org/10.1371/journal.pone.0218657, 2019. a
Kalnay, E., Hunt, B., Ott, E., and Szunyogh, I.: Ensemble Forecasting and Data
Assimilation: Two Problems with the Same Solution?, in: Predictability of
Weather and Climate, edited by:
Palmer, T. and Hagedorn, R.,
Cambridge University Press,
Cambridge, 157–180, https://doi.org/10.1017/CBO9780511617652.008, 2006. a, b
Kirschbaum, D., Stanley, T., and Zhou, Y.: Spatial and Temporal Analysis of a
Global Landslide Catalog, Geomorphology, 249, 4–15,
https://doi.org/10.1016/j.geomorph.2015.03.016, 2015. a, b, c
Kirschbaum, D. B., Adler, R., Hong, Y., Hill, S., and Lerner-Lam, A.: A
Global Landslide Catalog for Hazard Applications: Method, Results, and
Limitations, Nat. Hazards, 52, 561–575, https://doi.org/10.1007/s11069-009-9401-4,
2010. a, b, c
Knevels, R., Petschko, H., Proske, H., Leopold, P., Maraun, D., and Brenning,
A.: Event-Based Landslide Modeling in the Styrian Basin, Austria:
Accounting for Time-Varying Rainfall and Land Cover, Geosciences,
10, 217, https://doi.org/10.3390/geosciences10060217, 2020. a, b, c, d
Knevels, R., Brenning, A., Gingrich, S., Heiss, G., Lechner, T., Leopold, P.,
Plutzar, C., Proske, H., and Petschko, H.: Towards the Use of Land Use
Legacies in Landslide Modeling: Current Challenges and Future
Perspectives in an Austrian Case Study, Land, 10, 954,
https://doi.org/10.3390/land10090954, 2021. a
Koster, R. D., Suarez, M. J., Ducharne, A., Stieglitz, M., and Kumar, P.: A
Catchment-Based Approach to Modeling Land Surface Processes in a General
Circulation Model: 1. Model Structure, J. Geophys. Res.-Atmos., 105, 24809–24822, https://doi.org/10.1029/2000JD900327, 2000. a
Lima, P., Steger, S., and Glade, T.: Counteracting Flawed Landslide Data in
Statistically Based Landslide Susceptibility Modelling for Very Large Areas:
A National-Scale Assessment for Austria, Landslides 18, 3531–3546,
https://doi.org/10.1007/s10346-021-01693-7, 2021. a, b
Lin, Q., Lima, P., Steger, S., Glade, T., Jiang, T., Zhang, J., Liu, T., and
Wang, Y.: National-Scale Data-Driven Rainfall Induced Landslide
Susceptibility Mapping for China by Accounting for Incomplete Landslide
Data, Geosci. Front., 12, 101248, https://doi.org/10.1016/j.gsf.2021.101248,
2021. a, b
Lloyd, S.: Least Squares Quantization in PCM, IEEE T.
Inform. Theory, 28, 129–137, https://doi.org/10.1109/TIT.1982.1056489, 1982. a, b
Maes, J., Kervyn, M., de Hontheim, A., Dewitte, O., Jacobs, L., Mertens, K.,
Vanmaercke, M., Vranken, L., and Poesen, J.: Landslide Risk Reduction
Measures: A Review of Practices and Challenges for the Tropics, Prog.
Phys. Geog., 41, 191–221, https://doi.org/10.1177/0309133316689344, 2017. a
Meijer, J. R., Huijbregts, M. A. J., Schotten, K. C. G. J., and Schipper,
A. M.: Global Patterns of Current and Future Road Infrastructure,
Environ. Res. Lett., 13, 064006, https://doi.org/10.1088/1748-9326/aabd42,
2018. a
Nowicki Jessee, M. A., Hamburger, M. W., Allstadt, K., Wald, D. J., Robeson,
S. M., Tanyas, H., Hearne, M., and Thompson, E. M.: A Global Empirical
Model for Near-Real-Time Assessment of Seismically Induced
Landslides, J. Geophys. Res.-Earth, 123,
1835–1859, https://doi.org/10.1029/2017JF004494, 2018. a, b, c
Petschko, H., Brenning, A., Bell, R., Goetz, J., and Glade, T.: Assessing the quality of landslide susceptibility maps – case study Lower Austria, Nat. Hazards Earth Syst. Sci., 14, 95–118, https://doi.org/10.5194/nhess-14-95-2014, 2014. a
Pourghasemi, H. R. and Rossi, M.: Landslide Susceptibility Modeling in a
Landslide Prone Area in Mazandarn Province, North of Iran: A
Comparison between GLM, GAM, MARS, and M-AHP Methods,
Theor. Appl. Climatol., 130, 609–633,
https://doi.org/10.1007/s00704-016-1919-2, 2016. a, b
R Core Team: R: A Language and Environment for Statistical Computing, R
Foundation for Statistical Computing, Vienna, Austria,
https://www.R-project.org/ (last access: 1 November 2021), 2020. a
Reichle, R. H., Liu, Q., Koster, R. D., Crow, W. T., De Lannoy, G. J. M.,
Kimball, J. S., Ardizzone, J. V., Bosch, D., Colliander, A., Cosh, M.,
Kolassa, J., Mahanama, S. P., Prueger, J., Starks, P., and Walker, J. P.:
Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data
Product, J. Adv. Model. Earth Sy., 11, 3106–3130,
https://doi.org/10.1029/2019MS001729, 2019. a
Roberts, D. R., Bahn, V., Ciuti, S., Boyce, M. S., Elith, J.,
Guillera-Arroita, G., Hauenstein, S., Lahoz-Monfort, J. J., Schröder,
B., Thuiller, W., Warton, D. I., Wintle, B. A., Hartig, F., and Dormann,
C. F.: Cross-Validation Strategies for Data with Temporal, Spatial,
Hierarchical, or Phylogenetic Structure, Ecography, 40, 913–929,
https://doi.org/10.1111/ecog.02881, 2017. a, b, c, d
Sidle, R. C. and Bogaard, T. A.: Dynamic Earth System and Ecological Controls
of Rainfall-Initiated Landslides, Earth-Sci. Rev., 159, 275–291,
https://doi.org/10.1016/j.earscirev.2016.05.013, 2016. a
Stanley, T. A., Kirschbaum, D. B., Benz, G., Emberson, R. A., Amatya, P. M.,
Medwedeff, W., and Clark, M. K.: Data-Driven Landslide Nowcasting at the
Global Scale, Front. Earth Sci., 9, 640043, https://doi.org/10.3389/feart.2021.640043,
2021. a, b, c
Steger, S., Bell, R., Petschko, H., and Glade, T.: Evaluating the Effect of
Modelling Methods and Landslide Inventories Used for Statistical
Susceptibility Modelling, in: Engineering Geology for Society and
Territory – Volume 2, edited by: Lollino, G., Giordan, D., Crosta, G. B., Corominas, J., Azzam, R., Wasowski, J., and Sciarra, N., Springer, Cham, 201–204,
https://doi.org/10.1007/978-3-319-09057-3_27, ISBN 978-3-319-09057-3, 2015. a
Steger, S., Brenning, A., Bell, R., and Glade, T.: The Influence of
Systematically Incomplete Shallow Landslide Inventories on Statistical
Susceptibility Models and Suggestions for Improvements, Landslides, 14,
1767–1781, https://doi.org/10.1007/s10346-017-0820-0, 2017. a, b
Steger, S., Schmaltz, E., and Glade, T.: The (f)Utility to Account for
Pre-Failure Topography in Data-Driven Landslide Susceptibility Modelling,
Geomorphology, 354, 107041, https://doi.org/10.1016/j.geomorph.2020.107041, 2020. a, b
Talagrand, O., Vautard, R., and Strauss, B.: Evaluation of Probabilistic
Prediction Systems, Workshop on Predictability, 20–22 October 1997, ECMWF, Reading, UK, 1–25,
1997. a
Van Den Eeckhaut, M., Hervás, J., Jaedicke, C., Malet, J.-P., Montanarella,
L., and Nadim, F.: Statistical Modelling of Europe-Wide Landslide
Susceptibility Using Limited Landslide Inventory Data, Landslides, 9,
357–369, https://doi.org/10.1007/s10346-011-0299-z, 2012. a, b, c, d
van Leeuwen, P. J.: Representation Errors and Retrievals in Linear and
Nonlinear Data Assimilation, Q. J. Roy. Meteor.
Soc., 141, 1612–1623, https://doi.org/10.1002/qj.2464, 2015. a
Vanmaercke, M., Ardizzone, F., Rossi, M., and Guzzetti, F.: Exploring the
Effects of Seismicity on Landslides and Catchment Sediment Yield: An
Italian Case Study, Geomorphology, 278, 171–183,
https://doi.org/10.1016/j.geomorph.2016.11.010, 2017. a
Verdin, K.: Final Report High Resolution Topographic Analysis for
GMAO's Catchment LSM, Tech. rep., Global Modeling and Assimilation
Office, NASA/Goddard Space Flight Center, Greenbelt, MD 201771, Technical report, https://gmao.gsfc.nasa.gov/gmaoftp/sarith/ROUTING_MODEL/docs/SRTM_TopoData_CompletionReport_Verdin2013.pdf (last access: 14 September 2021), 2013. a, b, c
Verdin, K. L., Godt, J., Funk, C., Pedreros, D., Worstell, B., and Verdin, J.:
Development of a Global Slope Dataset for Estimation of Landslide
Occurrence Resulting from Earthquakes, Open-File Report 2007-1188,
Colorado: U.S. Geological Survey, Reston, Virginia, https://pubs.usgs.gov/of/2007/1188/pdf/OF07-1188_508.pdf (last access: 14 September 2021), 2007. a, b
Whiteley, J. S., Chambers, J. E., Uhlemann, S., Wilkinson, P. B., and Kendall,
J. M.: Geophysical Monitoring of Moisture-Induced Landslides: A
Review, Rev. Geophys., 57, 106–145, https://doi.org/10.1029/2018RG000603,
2019. a
Wilde, M., Günther, A., Reichenbach, P., Malet, J.-P., and Hervás, J.:
Pan-European Landslide Susceptibility Mapping: ELSUS Version 2,
J. Maps, 14, 97–104, https://doi.org/10.1080/17445647.2018.1432511, 2018. a
Wilks, D. S.: Forecast Verification, in: International
Geophysics, chap. 8, edited by: Wilks, D. S., vol. 100 of Statistical
Methods in the Atmospheric Sciences, Academic
Press, 301–394, https://doi.org/10.1016/B978-0-12-385022-5.00008-7, 2011. a, b, c
Willmott, C. J. and Feddema, J. J.: A More Rational Climatic Moisture
Index*, Prof. Geogr., 44, 84–88,
https://doi.org/10.1111/j.0033-0124.1992.00084.x, 1992. a
Zêzere, J. L., Pereira, S., Melo, R., Oliveira, S. C., and Garcia, R.
A. C.: Mapping Landslide Susceptibility Using Data-Driven Methods, Sci.
Total Environ., 589, 250–267, https://doi.org/10.1016/j.scitotenv.2017.02.188,
2017. a, b
Zhu, J., Baise, L. G., and Thompson, E. M.: An Updated Geospatial
Liquefaction Model for Global Application, B.
Seismol. Soc. Am., 107, 1365–1385, https://doi.org/10.1785/0120160198,
2017. a, b
Zuur, A. F. (Ed.): Mixed Effects Models and Extensions in Ecology with R,
Statistics for Biology and Health, Springer, New York, NY, ISBN 978-0-387-87457-9,
ISBN 978-0-387-87458-6,
https://doi.org/10.1007/978-0-387-87458-6, 2009. a, b
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.
In this study we assessed global landslide susceptibility at the coarse 36 km spatial resolution...
Altmetrics
Final-revised paper
Preprint