Allocating resources for natural hazard risk management has high priority in development banks and international agencies working in developing countries. Global hazard and risk maps for Rank landslides and avalanches were developed to identify the most ex- posed countries. Based on the global datasets of climate, lithology, earthquake activity, and topography, areas with the highest hazard, or “hotspots”, were identified. The applied model was based on classed values of all input data. The model output is a landslide and avalanche hazard index, which is globally scaled into nine levels. The model re- sults were calibrated and validated in selected areas where good data on slide events exist. The results from the landslide and avalanche hazard model together with global population data were then used as input for the risk assessment. Regions with the highest risk can be found in Colombia, Tajikistan, India, and Nepal where the estimated number of people killed per year per 100 km2 was found to be greater than one. The model made a reasonable prediction of the landslide hazard in 240 of 249 countries. More and better input data could im- prove the model further. Future work will focus on selected areas to study the applicability of the model on national and regional scales
Abstract. Rapid gravitational slope mass movements include all kinds of short term relocation of geological material, snow or ice. Traditionally, information about such events is collected separately in different databases covering selected geographical regions and types of movement. In Norway the terrain is susceptible to all types of rapid gravitational slope mass movements ranging from single rocks hitting roads and houses to large snow avalanches and rock slides where entire mountainsides collapse into fjords creating flood waves and endangering large areas. In addition, quick clay slides occur in desalinated marine sediments in South Eastern and Mid Norway. For the authorities and inhabitants of endangered areas, the type of threat is of minor importance and mitigation measures have to consider several types of rapid mass movements simultaneously.An integrated national database for all types of rapid mass movements built around individual events has been established. Only three data entries are mandatory: time, location and type of movement. The remaining optional parameters enable recording of detailed information about the terrain, materials involved and damages caused. Pictures, movies and other documentation can be uploaded into the database. A web-based graphical user interface has been developed allowing new events to be entered, as well as editing and querying for all events. An integration of the database into a GIS system is currently under development.Datasets from various national sources like the road authorities and the Geological Survey of Norway were imported into the database. Today, the database contains 33 000 rapid mass movement events from the last five hundred years covering the entire country. A first analysis of the data shows that the most frequent type of recorded rapid mass movement is rock slides and snow avalanches followed by debris slides in third place. Most events are recorded in the steep fjordCorrespondence to: C. Jaedicke (cj@ngi.no) terrain of the Norwegian west coast, but major events are recorded all over the country. Snow avalanches account for most fatalities, while large rock slides causing flood waves and huge quick clay slides are the most damaging individual events in terms of damage to infrastructure and property and for causing multiple fatalities. The quality of the data is strongly influenced by the personal engagement of local observers and varying observation routines. This database is a unique source for statistical analysis including, risk analysis and the relation between rapid mass movements and climate. The database of rapid mass movement events will also facilitate validation of national hazard and risk maps.
Landslides are a serious problem for humans and infrastructure in many parts of Europe. Experts know to a certain degree which parts of the continent are most exposed to landslide hazard. Nevertheless, neither the geographical location of previous landslide events nor knowledge of locations with high landslide hazard necessarily point out the areas with highest landslide risk. In addition, landslides often occur unexpectedly and the decisions on where investments should be made to manage and mitigate future events are based on the need to demonstrate action and political will. The goal of this study was to undertake a uniform and objective analysis of landslide hazard and risk for Europe. Two independent models, an expert-based or heuristic and a statistical model (logistic regression), were developed to assess the landslide hazard. Both models are based on applying an appropriate combination of the parameters representing susceptibility factors (slope, lithology, soil moisture, vegetation cover and other-factors if available) and triggering factors (extreme precipitation and seismicity). The weights of different susceptibility and triggering factors are calibrated to the information available in landslide inventories and physical processes. The analysis is based on uniform gridded data for Europe with a pixel resolution of roughly 30 m 9 30 m. A validation of the two hazard models by organizations in Scotland, Italy, and Romania showed good agreement for shallow landslides and rockfalls, but the hazard models fail to cover areas with slow moving landslides. In general, the results from the two models agree well pointing out the same countries with the highest total and relative area exposed to landslides. Landslide risk was quantified by counting the number of exposed people and exposed kilometers of roads and railways in each country. This process was repeated for both models. The results show the highest relative exposure to landslides in small alpine countries such as Lichtenstein. In terms of total values on a national level, Italy scores highest in both the extent of exposed area and the number for exposed population. Again, results agree between the two models, but differences between the models are higher for the risk than for the hazard results. The analysis gives a good overview of the landslide hazard and risk hotspots in Europe and allows a simple ranking of areas where mitigation measures might be most effective.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.