Landslides are present in all continents, and play an important role in the evolution of landscapes. They also represent a serious hazard in many areas of the world. In many regions, there is mounting interest towards the operational forecasting of landslides, and chiefly of rainfall induced landslides. A limited number of regional / national-scale forecasting and/or warning systems has been, or are operational. The systems use different methods and tools to prepare the forecasts and to issues the warnings, and cover areas of very different extent, from single sites to entire nations. The systems also differ for the frequency of the forecasts (daily to hourly) and their operation history, with only a limited number of systems that have been operational for several years. The aims of the systems also vary, with some of the system designed for civil protection purposes and other systems to provide information or advice to private business. The differences make it difficult to compare the systems and to relate and evaluate their performances. Designing an operational landslide forecasting and/or warning system is a challenging task that requires interdisciplinary skills and expertise. A typical forecasting system has many components, including landslide and meteorological data, forecasting models and tools to define their uncertainties, adequate SW and HW, and criteria and tools for validation of the forecasts and to deliver the warnings. It is critical that all components are robust, because a chain has the strength of its weakest element, and that the single components and the entire system relay on sound science, to be credible to the users. We propose an ICL project initiative (i) to review past and existing operational landslide forecasting and warning systems, and (ii) to propose recommendations for the design, the implementation, and the validation of operational landslide forecasting and warning systems. We propose to limit the project to the evaluation of systems aimed at predicting rainfall induced landslides and their consequences. For the Italian National Department for Civil Protection, the Institute of Research for the Hydrological Protection of the National Research Council of Italy (CNR IRPI) has designed and operates since 2010 a national system to forecast the possible occurrence of rainfall-induced landslides in Italy. The Department of Earth Sciences at the University of Florence, and the Laboratory of Environmental Cartography and Hydraulic and Geological Modeling at the University of Calabria, both long-term members of ICL, have consolidated experience in the design and the implementation of operational landslide forecast / warning systems, and have expressed interest in this project proposal. Further, the proposals is open to all ICL partners, and intends to build on the specific expertise of many of the ICL partners as well as on the lessons learned from other landslide experts.

Towards improved landslide mapping and forecasting

PARISE M;GUZZETTI F;
2016

Abstract

Landslides are present in all continents, and play an important role in the evolution of landscapes. They also represent a serious hazard in many areas of the world. In many regions, there is mounting interest towards the operational forecasting of landslides, and chiefly of rainfall induced landslides. A limited number of regional / national-scale forecasting and/or warning systems has been, or are operational. The systems use different methods and tools to prepare the forecasts and to issues the warnings, and cover areas of very different extent, from single sites to entire nations. The systems also differ for the frequency of the forecasts (daily to hourly) and their operation history, with only a limited number of systems that have been operational for several years. The aims of the systems also vary, with some of the system designed for civil protection purposes and other systems to provide information or advice to private business. The differences make it difficult to compare the systems and to relate and evaluate their performances. Designing an operational landslide forecasting and/or warning system is a challenging task that requires interdisciplinary skills and expertise. A typical forecasting system has many components, including landslide and meteorological data, forecasting models and tools to define their uncertainties, adequate SW and HW, and criteria and tools for validation of the forecasts and to deliver the warnings. It is critical that all components are robust, because a chain has the strength of its weakest element, and that the single components and the entire system relay on sound science, to be credible to the users. We propose an ICL project initiative (i) to review past and existing operational landslide forecasting and warning systems, and (ii) to propose recommendations for the design, the implementation, and the validation of operational landslide forecasting and warning systems. We propose to limit the project to the evaluation of systems aimed at predicting rainfall induced landslides and their consequences. For the Italian National Department for Civil Protection, the Institute of Research for the Hydrological Protection of the National Research Council of Italy (CNR IRPI) has designed and operates since 2010 a national system to forecast the possible occurrence of rainfall-induced landslides in Italy. The Department of Earth Sciences at the University of Florence, and the Laboratory of Environmental Cartography and Hydraulic and Geological Modeling at the University of Calabria, both long-term members of ICL, have consolidated experience in the design and the implementation of operational landslide forecast / warning systems, and have expressed interest in this project proposal. Further, the proposals is open to all ICL partners, and intends to build on the specific expertise of many of the ICL partners as well as on the lessons learned from other landslide experts.
2016
Dipartimento di Scienze del Sistema Terra e Tecnologie per l'Ambiente - DSSTTA
landslide
mapping
forecasting
hazard
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/315719
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