Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems
<p>Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWSs) have relied solely on rainfall event information. In previous decades, sever...
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Copernicus Publications
2025-01-01
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| Series: | Natural Hazards and Earth System Sciences |
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| author | B. B. Mirus B. B. Mirus T. Bogaard R. Greco M. Stähli |
| author_facet | B. B. Mirus B. B. Mirus T. Bogaard R. Greco M. Stähli |
| author_sort | B. B. Mirus |
| collection | DOAJ |
| description | <p>Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWSs) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWSs. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms through the ability to characterize infiltration during – as well as the drainage and drying processes between – major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWSs. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.</p> |
| format | Article |
| id | doaj-art-b92ddf96faae49dbae663fe6a49ba5f6 |
| institution | Kabale University |
| issn | 1561-8633 1684-9981 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Natural Hazards and Earth System Sciences |
| spelling | doaj-art-b92ddf96faae49dbae663fe6a49ba5f62025-01-07T10:47:23ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812025-01-012516918210.5194/nhess-25-169-2025Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systemsB. B. Mirus0B. B. Mirus1T. Bogaard2R. Greco3M. Stähli4United States Geological Survey (USGS), Geologic Hazards Science Center, Golden, Colorado, USASwiss Federal Institute for Forest, Snow and Landscape Research WSL, Mountain Hydrology and Mass Movements, Birmensdorf, SwitzerlandDepartment of Water Management, Delft University of Technology, Delft, the NetherlandsDepartment of Engineering, University of Campania “Luigi Vanvitelli”, Aversa, ItalySwiss Federal Institute for Forest, Snow and Landscape Research WSL, Mountain Hydrology and Mass Movements, Birmensdorf, Switzerland<p>Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWSs) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWSs. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms through the ability to characterize infiltration during – as well as the drainage and drying processes between – major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWSs. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.</p>https://nhess.copernicus.org/articles/25/169/2025/nhess-25-169-2025.pdf |
| spellingShingle | B. B. Mirus B. B. Mirus T. Bogaard R. Greco M. Stähli Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems Natural Hazards and Earth System Sciences |
| title | Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems |
| title_full | Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems |
| title_fullStr | Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems |
| title_full_unstemmed | Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems |
| title_short | Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems |
| title_sort | invited perspectives integrating hydrologic information into the next generation of landslide early warning systems |
| url | https://nhess.copernicus.org/articles/25/169/2025/nhess-25-169-2025.pdf |
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