Articles | Volume 26, issue 8
https://doi.org/10.5194/nhess-26-3815-2026
© Author(s) 2026. 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-26-3815-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Aug 2026
Research article |
| 14 Aug 2026
| 14 Aug 2026
Modeling the combined effects of the 2023 Türkiye–Syria earthquake and an Atmospheric River event on landslide hazard
Hunter N. Jimenez
CORRESPONDING AUTHOR
Civil and Environmental Engineering Department, University of Washington, Seattle, WA, USA
Erkan Istanbulluoglu
Civil and Environmental Engineering Department, University of Washington, Seattle, WA, USA
Tolga Gorum
Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Türkiye
Thomas A. Stanley
GESTAR II, University of Maryland Baltimore County, Baltimore, MD, USA
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Pukar M. Amatya
GESTAR II, University of Maryland Baltimore County, Baltimore, MD, USA
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Hakan Tanyas
Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands
Mehmet C. Demirel
Civil Engineering Department, Istanbul Technical University, Istanbul, Türkiye
Aykut Akgun
Geological Engineering Department, Karadeniz Technical University, Trabzon, Türkiye
Department of Earthquake, Disaster and Emergency Management Authority (AFAD), Ankara, Türkiye
Deniz Bozkurt
Department of Meteorology, University of Valparaıso, Valparaıso, Chile
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIX-B3-2026, 481–486, https://doi.org/10.5194/isprs-archives-XLIX-B3-2026-481-2026, https://doi.org/10.5194/isprs-archives-XLIX-B3-2026-481-2026, 2026
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W18-2025, 77–82, https://doi.org/10.5194/isprs-archives-XLVIII-4-W18-2025-77-2026, https://doi.org/10.5194/isprs-archives-XLVIII-4-W18-2025-77-2026, 2026
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We demonstrate an approach for the development of inventories from internet sources to geolocalize geohazard incidents. We created a tool that autonomously gets news, processes it using natural language processing, and then builds inventories. Consequently, we present spatiotemporal inventories for geohazards, resulting in a total of 13 940 incidents between 1997 and 2023 in Türkiye. Our alternative and easy-to-implement development inventory method aids geohazard management and resilience.
Jeffrey Keck, Erkan Istanbulluoglu, Benjamin Campforts, Gregory Tucker, and Alexander Horner-Devine
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MassWastingRunout (MWR) is a new landslide runout model designed for sediment transport, landscape evolution, and hazard assessment applications. MWR is written in Python and includes a calibration utility that automatically determines best-fit parameters for a site and empirical probability density functions of each parameter for probabilistic model implementation. MWR and Jupyter Notebook tutorials are available as part of the Landlab package at https://github.com/landlab/landlab.
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We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
Anne Felsberg, Zdenko Heyvaert, Jean Poesen, Thomas Stanley, and Gabriëlle J. M. De Lannoy
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The Probabilistic Hydrological Estimation of LandSlides (PHELS) model combines ensembles of landslide susceptibility and of hydrological predictor variables to provide daily, global ensembles of hazard for hydrologically triggered landslides. Testing different hydrological predictors showed that the combination of rainfall and soil moisture performed best, with the lowest number of missed and false alarms. The ensemble approach allowed the estimation of the associated prediction uncertainty.
S. Coskun, C. Bayik, S. Abdikan, T. Gorum, and F. Balik Sanli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-1-2023, 497–502, https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-497-2023, https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-497-2023, 2023
Tomás Carrasco-Escaff, Maisa Rojas, René Darío Garreaud, Deniz Bozkurt, and Marius Schaefer
The Cryosphere, 17, 1127–1149, https://doi.org/10.5194/tc-17-1127-2023, https://doi.org/10.5194/tc-17-1127-2023, 2023
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In this study, we investigate the interplay between climate and the Patagonian Icefields. By modeling the glacioclimatic conditions of the southern Andes, we found that the annual variations in net surface mass change experienced by these icefields are mainly controlled by annual variations in the air pressure field observed near the Drake Passage. Little dependence on main modes of variability was found, suggesting the Drake Passage as a key region for understanding the Patagonian Icefields.
Ionut Cristi Nicu, Letizia Elia, Lena Rubensdotter, Hakan Tanyaş, and Luigi Lombardo
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Thaw slumps and thermo-erosion gullies are cryospheric hazards that are widely encountered in Nordenskiöld Land, the largest and most compact ice-free area of the Svalbard Archipelago. By statistically analysing the landscape characteristics of locations where these processes occurred, we can estimate where they may occur in the future. We mapped 562 thaw slumps and 908 thermo-erosion gullies and used them to create the first multi-hazard susceptibility map in a high-Arctic environment.
Robert Emberson, Dalia B. Kirschbaum, Pukar Amatya, Hakan Tanyas, and Odin Marc
Nat. Hazards Earth Syst. Sci., 22, 1129–1149, https://doi.org/10.5194/nhess-22-1129-2022, https://doi.org/10.5194/nhess-22-1129-2022, 2022
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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.
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Short summary
After a major earthquake struck near the Türkiye/Syria border in February 2023, a powerful storm brought intense rainfall to the region, triggering additional landslides. We used satellite data and a physics-based model to map probabilistic landslide hazard using both coseismic and hydrologic drivers. We also explored how the sequence of these disasters affected landslide risk. Finally, we offer a method for seasonal forecasting of landslide hazard in at-risk areas using the historic climate.
After a major earthquake struck near the Türkiye/Syria border in February 2023, a powerful storm...
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