Articles | Volume 21, issue 9
https://doi.org/10.5194/hess-21-4525-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-4525-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Sep 2017
Research article |
| 12 Sep 2017
Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds
Francesco Marra
CORRESPONDING AUTHOR
Institute of Earth Sciences, Hebrew University of Jerusalem, 91904, Jerusalem, Israel
Elisa Destro
Department of Land, Environment, Agriculture and Forestry, University of Padova, Padua, Italy
Efthymios I. Nikolopoulos
Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT, USA
Davide Zoccatelli
Institute of Earth Sciences, Hebrew University of Jerusalem, 91904, Jerusalem, Israel
Department of Land, Environment, Agriculture and Forestry, University of Padova, Padua, Italy
Jean Dominique Creutin
Institut des Géosciences pour l'Environnement, Université de Grenoble Alpes/CNRS, Grenoble, France
Fausto Guzzetti
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, Italy
Marco Borga
Department of Land, Environment, Agriculture and Forestry, University of Padova, Padua, Italy
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47 citations as recorded by crossref.
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- Usage of antecedent soil moisture for improving the performance of rainfall thresholds for landslide early warning M. Abraham et al. 10.1016/j.catena.2021.105147
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- Geotechnical and hydrological characterization of hillslope deposits for regional landslide prediction modeling G. Bicocchi et al. 10.1007/s10064-018-01449-z
- Rainfall-induced landslide early warning system based on corrected mesoscale numerical models: an application for the southern Andes I. Fustos-Toribio et al. 10.5194/nhess-22-2169-2022
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- A multiobjective evolutionary optimization method based critical rainfall thresholds for debris flows initiation Y. Yan et al. 10.1007/s11629-019-5812-1
- How far are we from the use of satellite rainfall products in landslide forecasting? M. Brunetti et al. 10.1016/j.rse.2018.03.016
- Meteorological conditions leading to the 2015 Salgar flash flood: lessons for vulnerable regions in tropical complex terrain C. Hoyos et al. 10.5194/nhess-19-2635-2019
- Assessing the spatiotemporal impact of climate change on event rainfall characteristics influencing landslide occurrences based on multiple GCM projections in China Q. Lin et al. 10.1007/s10584-020-02750-1
- Comparison of the return period for landslide‐triggering rainfall events in Japan based on standardization of the rainfall period H. Tsunetaka 10.1002/esp.5228
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- Physically-based rainfall-induced landslide thresholds for the Tianshui area of Loess Plateau, China by TRIGRS model S. Ma et al. 10.1016/j.catena.2023.107499
- Preface: Landslide early warning systems: monitoring systems, rainfall thresholds, warning models, performance evaluation and risk perception S. Segoni et al. 10.5194/nhess-18-3179-2018
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- An Efficient In-Situ Debris Flow Monitoring System over a Wireless Accelerometer Network J. Ye et al. 10.3390/rs11131512
- Geographical landslide early warning systems F. Guzzetti et al. 10.1016/j.earscirev.2019.102973
- Debris flows rainfall thresholds in the Apennines of Emilia-Romagna (Italy) derived by the analysis of recent severe rainstorms events and regional meteorological data G. Ciccarese et al. 10.1016/j.geomorph.2020.107097
- High-Resolution Monthly Precipitation Fields (1913–2015) over a Complex Mountain Area Centred on the Forni Valley (Central Italian Alps) G. Alessio et al. 10.1155/2018/9123814
- Comparing methods for determining landslide early warning thresholds: potential use of non-triggering rainfall for locations with scarce landslide data availability D. Peres & A. Cancelliere 10.1007/s10346-021-01704-7
- Atmospheric triggering conditions and climatic disposition of landslides in Kyrgyzstan and Tajikistan at the beginning of the 21st century X. Wang et al. 10.5194/nhess-21-2125-2021
- The temporally varying roles of rainfall, snowmelt and soil moisture for debris flow initiation in a snow-dominated system K. Mostbauer et al. 10.5194/hess-22-3493-2018
- Reconstructing the 2015 Salgar flash flood using radar retrievals and a conceptual modeling framework in an ungauged basin N. Velásquez et al. 10.5194/hess-24-1367-2020
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- 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
- A hybrid machine-learning model to estimate potential debris-flow volumes J. Huang et al. 10.1016/j.geomorph.2020.107333
- Multi-hazard susceptibility mapping based on Convolutional Neural Networks K. Ullah et al. 10.1016/j.gsf.2022.101425
- How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering? S. Gariano et al. 10.1007/s11069-019-03830-x
- Open gridded climate datasets can help investigating the relation between meteorological anomalies and geomorphic hazards in mountainous areas R. Paranunzio & F. Marra 10.1016/j.gloplacha.2023.104328
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- TESSELLATION AS AN ALTERNATIVE AGGREGATION METHOD K. Zabarina 10.22630/MIBE.2018.19.1.8
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- Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany T. Ramsauer et al. 10.3390/rs10122029
- Debris Flow Risk Assessment Based on a Water–Soil Process Model at the Watershed Scale Under Climate Change: A Case Study in a Debris-Flow-Prone Area of Southwest China Q. Li et al. 10.3390/su11113199
- Landslide databases for climate change detection and attribution J. Wood et al. 10.1016/j.geomorph.2020.107061
- Rainfall-Induced Landslide Assessment under Different Precipitation Thresholds Using Remote Sensing Data: A Central Andes Case G. Maragaño-Carmona et al. 10.3390/w15142514
- A tool for the automatic calculation of rainfall thresholds for landslide occurrence M. Melillo et al. 10.1016/j.envsoft.2018.03.024
- Point cloud technology and 2D computational flow dynamic modeling for rapid hazards and disaster risk appraisal on Yellow Creek fan, Southern Alps of New Zealand C. Gomez & H. Purdie 10.1186/s40645-018-0208-3
- Assessment of climate change implications on landslides in mid and high hills of Himachal Pradesh, India S. Kumari et al. 10.1007/s12517-021-07668-1
- Changes of hydro-meteorological trigger conditions for debris flows in a future alpine climate R. Kaitna et al. 10.1016/j.scitotenv.2023.162227
- The impact of different rainfall products on landscape modelling simulations C. Skinner et al. 10.1002/esp.4894
- 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
46 citations as recorded by crossref.
- A systematic review on rainfall thresholds for landslides occurrence F. Gonzalez et al. 10.1016/j.heliyon.2023.e23247
- Usage of antecedent soil moisture for improving the performance of rainfall thresholds for landslide early warning M. Abraham et al. 10.1016/j.catena.2021.105147
- Decorrelation of Satellite Precipitation Estimates in Space and Time F. Tapiador et al. 10.3390/rs10050752
- The Selection of Rain Gauges and Rainfall Parameters in Estimating Intensity-Duration Thresholds for Landslide Occurrence: Case Study from Wayanad (India) M. Abraham et al. 10.3390/w12041000
- Geotechnical and hydrological characterization of hillslope deposits for regional landslide prediction modeling G. Bicocchi et al. 10.1007/s10064-018-01449-z
- Rainfall-induced landslide early warning system based on corrected mesoscale numerical models: an application for the southern Andes I. Fustos-Toribio et al. 10.5194/nhess-22-2169-2022
- Examples of Application of GASAKe for Predicting the Occurrence of Rainfall-Induced Landslides in Southern Italy O. Terranova et al. 10.3390/geosciences8020078
- A multiobjective evolutionary optimization method based critical rainfall thresholds for debris flows initiation Y. Yan et al. 10.1007/s11629-019-5812-1
- How far are we from the use of satellite rainfall products in landslide forecasting? M. Brunetti et al. 10.1016/j.rse.2018.03.016
- Meteorological conditions leading to the 2015 Salgar flash flood: lessons for vulnerable regions in tropical complex terrain C. Hoyos et al. 10.5194/nhess-19-2635-2019
- Assessing the spatiotemporal impact of climate change on event rainfall characteristics influencing landslide occurrences based on multiple GCM projections in China Q. Lin et al. 10.1007/s10584-020-02750-1
- Comparison of the return period for landslide‐triggering rainfall events in Japan based on standardization of the rainfall period H. Tsunetaka 10.1002/esp.5228
- A susceptibility-based rainfall threshold approach for landslide occurrence E. Monsieurs et al. 10.5194/nhess-19-775-2019
- Physically-based rainfall-induced landslide thresholds for the Tianshui area of Loess Plateau, China by TRIGRS model S. Ma et al. 10.1016/j.catena.2023.107499
- Preface: Landslide early warning systems: monitoring systems, rainfall thresholds, warning models, performance evaluation and risk perception S. Segoni et al. 10.5194/nhess-18-3179-2018
- Evaluation of rainfall thresholds triggering debris flows in western China with gauged- and satellite-based precipitation measurement Z. Liu 10.1016/j.jhydrol.2023.129500
- An Efficient In-Situ Debris Flow Monitoring System over a Wireless Accelerometer Network J. Ye et al. 10.3390/rs11131512
- Geographical landslide early warning systems F. Guzzetti et al. 10.1016/j.earscirev.2019.102973
- Debris flows rainfall thresholds in the Apennines of Emilia-Romagna (Italy) derived by the analysis of recent severe rainstorms events and regional meteorological data G. Ciccarese et al. 10.1016/j.geomorph.2020.107097
- High-Resolution Monthly Precipitation Fields (1913–2015) over a Complex Mountain Area Centred on the Forni Valley (Central Italian Alps) G. Alessio et al. 10.1155/2018/9123814
- Comparing methods for determining landslide early warning thresholds: potential use of non-triggering rainfall for locations with scarce landslide data availability D. Peres & A. Cancelliere 10.1007/s10346-021-01704-7
- Atmospheric triggering conditions and climatic disposition of landslides in Kyrgyzstan and Tajikistan at the beginning of the 21st century X. Wang et al. 10.5194/nhess-21-2125-2021
- The temporally varying roles of rainfall, snowmelt and soil moisture for debris flow initiation in a snow-dominated system K. Mostbauer et al. 10.5194/hess-22-3493-2018
- Reconstructing the 2015 Salgar flash flood using radar retrievals and a conceptual modeling framework in an ungauged basin N. Velásquez et al. 10.5194/hess-24-1367-2020
- Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds T. Bogaard & R. Greco 10.5194/nhess-18-31-2018
- 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
- A hybrid machine-learning model to estimate potential debris-flow volumes J. Huang et al. 10.1016/j.geomorph.2020.107333
- Multi-hazard susceptibility mapping based on Convolutional Neural Networks K. Ullah et al. 10.1016/j.gsf.2022.101425
- How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering? S. Gariano et al. 10.1007/s11069-019-03830-x
- Open gridded climate datasets can help investigating the relation between meteorological anomalies and geomorphic hazards in mountainous areas R. Paranunzio & F. Marra 10.1016/j.gloplacha.2023.104328
- A regional early warning model of geological hazards based on big data of real-time rainfall W. Zhao et al. 10.1007/s11069-023-05819-z
- Assessment of spatial uncertainty of heavy rainfall at catchment scale using a dense gauge network S. O & U. Foelsche 10.5194/hess-23-2863-2019
- Rainfall thresholds for landslide occurrence: systematic underestimation using coarse temporal resolution data F. Marra 10.1007/s11069-018-3508-4
- Research Progress of Initial Mechanism on Debris Flow and Related Discrimination Methods: A Review J. Du et al. 10.3389/feart.2021.629567
- Quantify the effect of antecedent effective precipitation on rainfall intensity-duration threshold of debris flow S. Zhang et al. 10.1007/s10346-023-02066-y
- TESSELLATION AS AN ALTERNATIVE AGGREGATION METHOD K. Zabarina 10.22630/MIBE.2018.19.1.8
- Determination of the Probabilities of Landslide Events—A Case Study of Bhutan R. Sarkar & K. Dorji 10.3390/hydrology6020052
- Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany T. Ramsauer et al. 10.3390/rs10122029
- Debris Flow Risk Assessment Based on a Water–Soil Process Model at the Watershed Scale Under Climate Change: A Case Study in a Debris-Flow-Prone Area of Southwest China Q. Li et al. 10.3390/su11113199
- Landslide databases for climate change detection and attribution J. Wood et al. 10.1016/j.geomorph.2020.107061
- Rainfall-Induced Landslide Assessment under Different Precipitation Thresholds Using Remote Sensing Data: A Central Andes Case G. Maragaño-Carmona et al. 10.3390/w15142514
- A tool for the automatic calculation of rainfall thresholds for landslide occurrence M. Melillo et al. 10.1016/j.envsoft.2018.03.024
- Point cloud technology and 2D computational flow dynamic modeling for rapid hazards and disaster risk appraisal on Yellow Creek fan, Southern Alps of New Zealand C. Gomez & H. Purdie 10.1186/s40645-018-0208-3
- Assessment of climate change implications on landslides in mid and high hills of Himachal Pradesh, India S. Kumari et al. 10.1007/s12517-021-07668-1
- Changes of hydro-meteorological trigger conditions for debris flows in a future alpine climate R. Kaitna et al. 10.1016/j.scitotenv.2023.162227
- The impact of different rainfall products on landscape modelling simulations C. Skinner et al. 10.1002/esp.4894
Latest update: 25 Apr 2024
Short summary
Previous studies have reported a systematic underestimation of debris flow occurrence thresholds, due to the use of sparse networks in non-stationary rain fields. We analysed high-resolution radar data to show that spatially aggregated estimates (e.g. satellite data) largely reduce this issue, in light of a reduced estimation variance. Our findings are transferable to other situations in which lower envelope curves are used to predict point-like events in the presence of non-stationary fields.
Previous studies have reported a systematic underestimation of debris flow occurrence...
