Articles | Volume 15, issue 4
https://doi.org/10.5194/nhess-15-853-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/nhess-15-853-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
16 Apr 2015
Research article |
| 16 Apr 2015
Technical Note: An operational landslide early warning system at regional scale based on space–time-variable rainfall thresholds
Department of Earth Sciences, University of Firenze, Florence, Italy
A. Battistini
Department of Earth Sciences, University of Firenze, Florence, Italy
G. Rossi
Department of Earth Sciences, University of Firenze, Florence, Italy
A. Rosi
Department of Earth Sciences, University of Firenze, Florence, Italy
D. Lagomarsino
Department of Earth Sciences, University of Firenze, Florence, Italy
F. Catani
Department of Earth Sciences, University of Firenze, Florence, Italy
S. Moretti
Department of Earth Sciences, University of Firenze, Florence, Italy
N. Casagli
Department of Earth Sciences, University of Firenze, Florence, Italy
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Cited
75 citations as recorded by crossref.
- The optimal rainfall thresholds and probabilistic rainfall conditions for a landslide early warning system for Chuncheon, Republic of Korea W. Lee et al. 10.1007/s10346-020-01603-3
- Rainfall threshold calculation for debris flow early warning in areas with scarcity of data H. Pan et al. 10.5194/nhess-18-1395-2018
- Rainfall and land use empirically coupled to forecast landslides in the Esino river basin, central Italy E. Gioia et al. 10.5194/nhess-15-1289-2015
- Preliminary establishment of a mass movement warning system for Taiwan using the soil water index C. Chen et al. 10.1007/s10346-021-01844-w
- A review of the recent literature on rainfall thresholds for landslide occurrence S. Segoni et al. 10.1007/s10346-018-0966-4
- Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds F. Marra et al. 10.5194/hess-21-4525-2017
- Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides R. Greco & L. Pagano 10.5194/nhess-17-2213-2017
- The impact of rainfall time series with different length in a landslide warning system, in the framework of changing precipitation trends S. Segoni et al. 10.1186/s40677-016-0057-6
- Adapting the EDuMaP method to test the performance of the Norwegian early warning system for weather-induced landslides L. Piciullo et al. 10.5194/nhess-17-817-2017
- Persistent Scatterers continuous streaming for landslide monitoring and mapping: the case of the Tuscany region (Italy) F. Raspini et al. 10.1007/s10346-019-01249-w
- Reliability analysis of an existing slope at a specific site considering rainfall triggering mechanism and its past performance records X. Liu & Y. Wang 10.1016/j.enggeo.2021.106144
- Comparing threshold definition techniques for rainfall‐induced landslides: A national assessment using radar rainfall B. Postance et al. 10.1002/esp.4202
- Assessing the performance of regional landslide early warning models: the EDuMaP method M. Calvello & L. Piciullo 10.5194/nhess-16-103-2016
- An optimized non-landslide sampling method for Landslide susceptibility evaluation using machine learning models S. Xu et al. 10.1007/s11069-024-07021-1
- A Regional-Scale Landslide Early Warning System Based on the Sequential Evaluation Method: Development and Performance Analysis J. Park et al. 10.3390/app10175788
- Application of geospatial technologies in developing a dynamic landslide early warning system in a humanitarian context: the Rohingya refugee crisis in Cox’s Bazar, Bangladesh B. Ahmed et al. 10.1080/19475705.2020.1730988
- Can global rainfall estimates (satellite and reanalysis) aid landslide hindcasting? U. Ozturk et al. 10.1007/s10346-021-01689-3
- Analyzing rainfall-induced mass movements in Taiwan using the soil water index C. Chen et al. 10.1007/s10346-016-0788-1
- Performance Testing of Optical Flow Time Series Analyses Based on a Fast, High-Alpine Landslide D. Hermle et al. 10.3390/rs14030455
- Identification of Rainfall Thresholds Likely to Trigger Flood Damages across a Mediterranean Region, Based on Insurance Data and Rainfall Observations K. Papagiannaki et al. 10.3390/w14060994
- Landslide databases for climate change detection and attribution J. Wood et al. 10.1016/j.geomorph.2020.107061
- Methods for Constructing a Refined Early-Warning Model for Rainstorm-Induced Waterlogging in Historic and Cultural Districts J. Wu et al. 10.3390/w16091290
- Sentinel-1-based monitoring services at regional scale in Italy: State of the art and main findings P. Confuorto et al. 10.1016/j.jag.2021.102448
- Effect of antecedent rainfall conditions and their variations on shallow landslide-triggering rainfall thresholds in South Korea S. Kim et al. 10.1007/s10346-020-01505-4
- Comparison of statistical methods and multi-time validation for the determination of the shallow landslide rainfall thresholds Y. Galanti et al. 10.1007/s10346-017-0919-3
- Estimation of rainfall thresholds for shallow landslides in the Sierra Madre Oriental, northeastern Mexico J. Salinas-Jasso et al. 10.1007/s11629-020-6050-2
- Comprehensive Analysis of the Use of Web-GIS for Natural Hazard Management: A Systematic Review M. Daud et al. 10.3390/su16104238
- Detailed and large-scale cost/benefit analyses of landslide prevention vs. post-event actions G. Salbego et al. 10.5194/nhess-15-2461-2015
- Validation of landslide hazard models using a semantic engine on online news A. Battistini et al. 10.1016/j.apgeog.2017.03.003
- Applying rainfall threshold estimates and frequency ratio model for landslide hazard assessment in the coastal mountain setting of South Asia A. Alam et al. 10.1016/j.nhres.2023.08.002
- Predicting storm-triggered debris flow events: application to the 2009 Ionian Peloritan disaster (Sicily, Italy) M. Cama et al. 10.5194/nhess-15-1785-2015
- Integrating real-time sensor data for improved hydrogeotechnical modelling in landslide early warning in Western Himalaya K. Gupta & N. Satyam 10.1016/j.enggeo.2024.107630
- Probabilistic rainfall thresholds for triggering debris flows in a human-modified landscape R. Giannecchini et al. 10.1016/j.geomorph.2015.12.012
- Combination of Rainfall Thresholds and Susceptibility Maps for Dynamic Landslide Hazard Assessment at Regional Scale S. Segoni et al. 10.3389/feart.2018.00085
- Definition and performance of a threshold-based regional early warning model for rainfall-induced landslides L. Piciullo et al. 10.1007/s10346-016-0750-2
- Near Real-Time Characterization of Spatio-Temporal Precursory Evolution of a Rockslide from Radar Data: Integrating Statistical and Machine Learning with Dynamics of Granular Failure S. Das & A. Tordesillas 10.3390/rs11232777
- Territorial early warning systems for rainfall-induced landslides L. Piciullo et al. 10.1016/j.earscirev.2018.02.013
- Landslide Event on 24 June in Sichuan Province, China: Preliminary Investigation and Analysis W. Meng et al. 10.3390/geosciences8020039
- Exploiting historical rainfall and landslide data in a spatial database for the derivation of critical rainfall thresholds D. Caracciolo et al. 10.1007/s12665-017-6545-5
- Geographical landslide early warning systems F. Guzzetti et al. 10.1016/j.earscirev.2019.102973
- Regional early warning model for rainfall induced landslide based on slope unit in Chongqing, China S. Liu et al. 10.1016/j.enggeo.2024.107464
- Landslides in the Mountain Region of Rio de Janeiro: A Proposal for the Semi-Automated Definition of Multiple Rainfall Thresholds A. Rosi et al. 10.3390/geosciences9050203
- Global changes in the spatial extents of precipitation extremes X. Tan et al. 10.1088/1748-9326/abf462
- An ensemble neural network approach for space–time landslide predictive modelling J. Lim et al. 10.1016/j.jag.2024.104037
- Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean F. Marra et al. 10.5194/hess-21-2389-2017
- Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system S. Segoni et al. 10.5194/nhess-18-807-2018
- Developing a Dynamic Web-GIS Based Landslide Early Warning System for the Chittagong Metropolitan Area, Bangladesh B. Ahmed et al. 10.3390/ijgi7120485
- Event-based rainfall warning regression model for landslide and debris flow issuing C. Chen 10.1007/s12665-020-8877-9
- Comparison of landslide forecasting services in Piedmont (Italy) and Norway, illustrated by events in late spring 2013 G. Devoli et al. 10.5194/nhess-18-1351-2018
- A Fast Deploying Monitoring and Real-Time Early Warning System for the Baige Landslide in Tibet, China Y. Wu et al. 10.3390/s20226619
- Machine Learning for Defining the Probability of Sentinel-1 Based Deformation Trend Changes Occurrence P. Confuorto et al. 10.3390/rs14071748
- Survey of spatial and temporal landslide prediction methods and techniques 10.7744/kjoas.20160053
- Landslide susceptibility of the Prato–Pistoia–Lucca provinces, Tuscany, Italy S. Segoni et al. 10.1080/17445647.2016.1233463
- Regional rainfall thresholds for landslide occurrence using a centenary database T. Vaz et al. 10.5194/nhess-18-1037-2018
- Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: The Case of Rio de Janeiro, Brazil A. Getirana et al. 10.3390/rs12244095
- A regional-scale landslide early warning methodology applying statistical and physically based approaches in sequence J. Park et al. 10.1016/j.enggeo.2019.105193
- A Rainfall Intensity-Duration Threshold for Mass Movement in Badulla, Sri Lanka E. Perera et al. 10.4236/gep.2017.512010
- Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model X. Tan et al. 10.1016/j.ejrh.2023.101327
- Low-Cost Sensors for the Measurement of Soil Water Content for Rainfall-Induced Shallow Landslide Early Warning Systems M. Pavanello et al. 10.3390/w16223244
- Landslide activation behaviour illuminated by electrical resistance monitoring A. Merritt et al. 10.1002/esp.4316
- Determination of rainfall thresholds for shallow landslides by a probabilistic and empirical method J. Huang et al. 10.5194/nhess-15-2715-2015
- The Weather Radar Observations Applied to Shallow Landslides Prediction: A Case Study From North-Western Italy R. Cremonini & D. Tiranti 10.3389/feart.2018.00134
- Revealing the relation between spatial patterns of rainfall return levels and landslide density S. Mtibaa & H. Tsunetaka 10.5194/esurf-11-461-2023
- Fronts and Cyclones Associated with Changes in the Total and Extreme Precipitation over China X. Wu et al. 10.1175/JCLI-D-21-0467.1
- Spatiotemporal modelling of rainfall-induced landslides using machine learning C. Ng et al. 10.1007/s10346-021-01662-0
- Satellite Rainfall Estimates for Debris Flow Prediction: An Evaluation Based on Rainfall Accumulation–Duration Thresholds E. Nikolopoulos et al. 10.1175/JHM-D-17-0052.1
- Radar-based quantitative precipitation estimation for the identification of debris flow occurrence over earthquake-affected regions in Sichuan, China Z. Shi et al. 10.5194/nhess-18-765-2018
- The Effects of Different Geological Conditions on Landslide-Triggering Rainfall Conditions in South Korea J. Lee et al. 10.3390/w14132051
- Rainfall thresholds for rainfall-induced landslides in Slovenia A. Rosi et al. 10.1007/s10346-016-0733-3
- Quantitative comparison between two different methodologies to define rainfall thresholds for landslide forecasting D. Lagomarsino et al. 10.5194/nhess-15-2413-2015
- A systematic review on rainfall thresholds for landslides occurrence F. Gonzalez et al. 10.1016/j.heliyon.2023.e23247
- Monitoring and prediction in early warning systems for rapid mass movements M. Stähli et al. 10.5194/nhess-15-905-2015
- Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterization S. Segoni et al. 10.1007/s10346-019-01340-2
- Statistical modelling of rainfall-induced shallow landsliding using static predictors and numerical weather predictions: preliminary results V. Capecchi et al. 10.5194/nhess-15-75-2015
- Updating EWS rainfall thresholds for the triggering of landslides A. Rosi et al. 10.1007/s11069-015-1717-7
71 citations as recorded by crossref.
- The optimal rainfall thresholds and probabilistic rainfall conditions for a landslide early warning system for Chuncheon, Republic of Korea W. Lee et al. 10.1007/s10346-020-01603-3
- Rainfall threshold calculation for debris flow early warning in areas with scarcity of data H. Pan et al. 10.5194/nhess-18-1395-2018
- Rainfall and land use empirically coupled to forecast landslides in the Esino river basin, central Italy E. Gioia et al. 10.5194/nhess-15-1289-2015
- Preliminary establishment of a mass movement warning system for Taiwan using the soil water index C. Chen et al. 10.1007/s10346-021-01844-w
- A review of the recent literature on rainfall thresholds for landslide occurrence S. Segoni et al. 10.1007/s10346-018-0966-4
- Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds F. Marra et al. 10.5194/hess-21-4525-2017
- Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides R. Greco & L. Pagano 10.5194/nhess-17-2213-2017
- The impact of rainfall time series with different length in a landslide warning system, in the framework of changing precipitation trends S. Segoni et al. 10.1186/s40677-016-0057-6
- Adapting the EDuMaP method to test the performance of the Norwegian early warning system for weather-induced landslides L. Piciullo et al. 10.5194/nhess-17-817-2017
- Persistent Scatterers continuous streaming for landslide monitoring and mapping: the case of the Tuscany region (Italy) F. Raspini et al. 10.1007/s10346-019-01249-w
- Reliability analysis of an existing slope at a specific site considering rainfall triggering mechanism and its past performance records X. Liu & Y. Wang 10.1016/j.enggeo.2021.106144
- Comparing threshold definition techniques for rainfall‐induced landslides: A national assessment using radar rainfall B. Postance et al. 10.1002/esp.4202
- Assessing the performance of regional landslide early warning models: the EDuMaP method M. Calvello & L. Piciullo 10.5194/nhess-16-103-2016
- An optimized non-landslide sampling method for Landslide susceptibility evaluation using machine learning models S. Xu et al. 10.1007/s11069-024-07021-1
- A Regional-Scale Landslide Early Warning System Based on the Sequential Evaluation Method: Development and Performance Analysis J. Park et al. 10.3390/app10175788
- Application of geospatial technologies in developing a dynamic landslide early warning system in a humanitarian context: the Rohingya refugee crisis in Cox’s Bazar, Bangladesh B. Ahmed et al. 10.1080/19475705.2020.1730988
- Can global rainfall estimates (satellite and reanalysis) aid landslide hindcasting? U. Ozturk et al. 10.1007/s10346-021-01689-3
- Analyzing rainfall-induced mass movements in Taiwan using the soil water index C. Chen et al. 10.1007/s10346-016-0788-1
- Performance Testing of Optical Flow Time Series Analyses Based on a Fast, High-Alpine Landslide D. Hermle et al. 10.3390/rs14030455
- Identification of Rainfall Thresholds Likely to Trigger Flood Damages across a Mediterranean Region, Based on Insurance Data and Rainfall Observations K. Papagiannaki et al. 10.3390/w14060994
- Landslide databases for climate change detection and attribution J. Wood et al. 10.1016/j.geomorph.2020.107061
- Methods for Constructing a Refined Early-Warning Model for Rainstorm-Induced Waterlogging in Historic and Cultural Districts J. Wu et al. 10.3390/w16091290
- Sentinel-1-based monitoring services at regional scale in Italy: State of the art and main findings P. Confuorto et al. 10.1016/j.jag.2021.102448
- Effect of antecedent rainfall conditions and their variations on shallow landslide-triggering rainfall thresholds in South Korea S. Kim et al. 10.1007/s10346-020-01505-4
- Comparison of statistical methods and multi-time validation for the determination of the shallow landslide rainfall thresholds Y. Galanti et al. 10.1007/s10346-017-0919-3
- Estimation of rainfall thresholds for shallow landslides in the Sierra Madre Oriental, northeastern Mexico J. Salinas-Jasso et al. 10.1007/s11629-020-6050-2
- Comprehensive Analysis of the Use of Web-GIS for Natural Hazard Management: A Systematic Review M. Daud et al. 10.3390/su16104238
- Detailed and large-scale cost/benefit analyses of landslide prevention vs. post-event actions G. Salbego et al. 10.5194/nhess-15-2461-2015
- Validation of landslide hazard models using a semantic engine on online news A. Battistini et al. 10.1016/j.apgeog.2017.03.003
- Applying rainfall threshold estimates and frequency ratio model for landslide hazard assessment in the coastal mountain setting of South Asia A. Alam et al. 10.1016/j.nhres.2023.08.002
- Predicting storm-triggered debris flow events: application to the 2009 Ionian Peloritan disaster (Sicily, Italy) M. Cama et al. 10.5194/nhess-15-1785-2015
- Integrating real-time sensor data for improved hydrogeotechnical modelling in landslide early warning in Western Himalaya K. Gupta & N. Satyam 10.1016/j.enggeo.2024.107630
- Probabilistic rainfall thresholds for triggering debris flows in a human-modified landscape R. Giannecchini et al. 10.1016/j.geomorph.2015.12.012
- Combination of Rainfall Thresholds and Susceptibility Maps for Dynamic Landslide Hazard Assessment at Regional Scale S. Segoni et al. 10.3389/feart.2018.00085
- Definition and performance of a threshold-based regional early warning model for rainfall-induced landslides L. Piciullo et al. 10.1007/s10346-016-0750-2
- Near Real-Time Characterization of Spatio-Temporal Precursory Evolution of a Rockslide from Radar Data: Integrating Statistical and Machine Learning with Dynamics of Granular Failure S. Das & A. Tordesillas 10.3390/rs11232777
- Territorial early warning systems for rainfall-induced landslides L. Piciullo et al. 10.1016/j.earscirev.2018.02.013
- Landslide Event on 24 June in Sichuan Province, China: Preliminary Investigation and Analysis W. Meng et al. 10.3390/geosciences8020039
- Exploiting historical rainfall and landslide data in a spatial database for the derivation of critical rainfall thresholds D. Caracciolo et al. 10.1007/s12665-017-6545-5
- Geographical landslide early warning systems F. Guzzetti et al. 10.1016/j.earscirev.2019.102973
- Regional early warning model for rainfall induced landslide based on slope unit in Chongqing, China S. Liu et al. 10.1016/j.enggeo.2024.107464
- Landslides in the Mountain Region of Rio de Janeiro: A Proposal for the Semi-Automated Definition of Multiple Rainfall Thresholds A. Rosi et al. 10.3390/geosciences9050203
- Global changes in the spatial extents of precipitation extremes X. Tan et al. 10.1088/1748-9326/abf462
- An ensemble neural network approach for space–time landslide predictive modelling J. Lim et al. 10.1016/j.jag.2024.104037
- Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean F. Marra et al. 10.5194/hess-21-2389-2017
- Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system S. Segoni et al. 10.5194/nhess-18-807-2018
- Developing a Dynamic Web-GIS Based Landslide Early Warning System for the Chittagong Metropolitan Area, Bangladesh B. Ahmed et al. 10.3390/ijgi7120485
- Event-based rainfall warning regression model for landslide and debris flow issuing C. Chen 10.1007/s12665-020-8877-9
- Comparison of landslide forecasting services in Piedmont (Italy) and Norway, illustrated by events in late spring 2013 G. Devoli et al. 10.5194/nhess-18-1351-2018
- A Fast Deploying Monitoring and Real-Time Early Warning System for the Baige Landslide in Tibet, China Y. Wu et al. 10.3390/s20226619
- Machine Learning for Defining the Probability of Sentinel-1 Based Deformation Trend Changes Occurrence P. Confuorto et al. 10.3390/rs14071748
- Survey of spatial and temporal landslide prediction methods and techniques 10.7744/kjoas.20160053
- Landslide susceptibility of the Prato–Pistoia–Lucca provinces, Tuscany, Italy S. Segoni et al. 10.1080/17445647.2016.1233463
- Regional rainfall thresholds for landslide occurrence using a centenary database T. Vaz et al. 10.5194/nhess-18-1037-2018
- Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: The Case of Rio de Janeiro, Brazil A. Getirana et al. 10.3390/rs12244095
- A regional-scale landslide early warning methodology applying statistical and physically based approaches in sequence J. Park et al. 10.1016/j.enggeo.2019.105193
- A Rainfall Intensity-Duration Threshold for Mass Movement in Badulla, Sri Lanka E. Perera et al. 10.4236/gep.2017.512010
- Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model X. Tan et al. 10.1016/j.ejrh.2023.101327
- Low-Cost Sensors for the Measurement of Soil Water Content for Rainfall-Induced Shallow Landslide Early Warning Systems M. Pavanello et al. 10.3390/w16223244
- Landslide activation behaviour illuminated by electrical resistance monitoring A. Merritt et al. 10.1002/esp.4316
- Determination of rainfall thresholds for shallow landslides by a probabilistic and empirical method J. Huang et al. 10.5194/nhess-15-2715-2015
- The Weather Radar Observations Applied to Shallow Landslides Prediction: A Case Study From North-Western Italy R. Cremonini & D. Tiranti 10.3389/feart.2018.00134
- Revealing the relation between spatial patterns of rainfall return levels and landslide density S. Mtibaa & H. Tsunetaka 10.5194/esurf-11-461-2023
- Fronts and Cyclones Associated with Changes in the Total and Extreme Precipitation over China X. Wu et al. 10.1175/JCLI-D-21-0467.1
- Spatiotemporal modelling of rainfall-induced landslides using machine learning C. Ng et al. 10.1007/s10346-021-01662-0
- Satellite Rainfall Estimates for Debris Flow Prediction: An Evaluation Based on Rainfall Accumulation–Duration Thresholds E. Nikolopoulos et al. 10.1175/JHM-D-17-0052.1
- Radar-based quantitative precipitation estimation for the identification of debris flow occurrence over earthquake-affected regions in Sichuan, China Z. Shi et al. 10.5194/nhess-18-765-2018
- The Effects of Different Geological Conditions on Landslide-Triggering Rainfall Conditions in South Korea J. Lee et al. 10.3390/w14132051
- Rainfall thresholds for rainfall-induced landslides in Slovenia A. Rosi et al. 10.1007/s10346-016-0733-3
- Quantitative comparison between two different methodologies to define rainfall thresholds for landslide forecasting D. Lagomarsino et al. 10.5194/nhess-15-2413-2015
- A systematic review on rainfall thresholds for landslides occurrence F. Gonzalez et al. 10.1016/j.heliyon.2023.e23247
4 citations as recorded by crossref.
- Monitoring and prediction in early warning systems for rapid mass movements M. Stähli et al. 10.5194/nhess-15-905-2015
- Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterization S. Segoni et al. 10.1007/s10346-019-01340-2
- Statistical modelling of rainfall-induced shallow landsliding using static predictors and numerical weather predictions: preliminary results V. Capecchi et al. 10.5194/nhess-15-75-2015
- Updating EWS rainfall thresholds for the triggering of landslides A. Rosi et al. 10.1007/s11069-015-1717-7
Saved (final revised paper)
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Latest update: 13 Dec 2024
Short summary
We monitor and forecast (with lead times up to 48h) regional-scale landslide hazard with an early warning system (EWS) implemented on a user-friendly WebGIS interface.
The EWS detects the most critical rainfall conditions using a mosaic of 25 site-specific thresholds. Moreover, when the rainfall paths recorded by the instruments are compared with the thresholds, the thresholds are shifted in the time axis and adjusted to all possible starting times until the most hazardous scenario is found.
We monitor and forecast (with lead times up to 48h) regional-scale landslide hazard with an...
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