International audienceThe severity of the impact of a natural hazard on a society depends on, among other factors, the intensity of the hazard and the exposure and resistance ability of the elements at risk (e.g., persons, buildings and infrastructures). Social conditions strongly influence the vulnerability factors for both direct and indirect impact and therefore control the possibility to transform the occurrence of a natural hazard into a natural disaster. This article presents a model to assess the relative socioeconomic vulnerability to landslides at the local to regional scale. The model applies an indicator-based approach. The indicators represent the underlying factors that influence a community's ability to prepare for, deal with, and recover from the damage and loss associated with landslides. The proposed model includes indicators that characterize the demographic, social and economic setting as well as indicators representing the degree of preparedness, effectiveness of the response and capacity to recover. Although this model focuses primarily on the indirect losses, it could easily be extended to include physical indicators accounting for the direct losses. Each indicator is individually ranked from 1 (lowest vulnerability) to 5 (highest vulnerability) and weighted, based on its overall degree of influence. The final vulnerability estimate is formulated as a weighted average of the individual indicator scores. The proposed model is applied for six case studies in Europe. The case studies demonstrate that the method gives a reasonable ranking of the vulnerability. The practical experience achieved through the case studies shows that the model is straightforward for users with knowledge on landslide locations and with access to local census data
Nature-based solutions (NBS) are becoming increasingly important in both the EU and individual countries’ political agendas, as a sustainable means to reduce the risk posed by hydrometeorological hazards. However, as the use of NBS is increasing, a number of barriers regarding their practical implementation also become apparent. A number of review studies have summarized and classified barriers, mainly in urban settings. PHUSICOS is a Horizon 2020 Innovation Action to demonstrate the use of NBS in rural and mountain landscapes. Large-scale demonstrator case sites with several sub-projects are established in Italy, Norway and in the French and Spanish Pyrenees. The present paper describes the project’s NBS measures and their experienced barriers, some of which have resulted in full cancellation of the planned interventions. Many of the barriers experienced in rural settings have the same root causes as the ones described from urban areas, and the main barrier-creating mechanisms are institutional factors, resistance among stakeholders and technical and economic issues. The key element, however, is the lack of knowledge about the ability of NBS to deliver a series of co-benefits in addition to their risk-reducing effects and that long-term thinking is required to see the effect of many of these co-benefits.
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.
Literature on climate services presents a large diversity of different services and uses. Many climate services have ‘usability gaps’: the information provided, or the way it is visualized, may be unsuitable for end users to inform decision-making processes in relation to adaptation against climate change impacts or for the development of policies to this end. The aim of this article is to contribute to more informed and efficient decision-making processes in climate adaptation by developing a typology of usability gaps for climate services. To do so, we first present and demonstrate a so-called ‘climate information design’ (CID) template with which to study and potentially improve the visual communicative qualities of climate services. Then, two climates services are selected for a further, qualitative explorative case study of two cases in the north and south of the Netherlands. A combination of focus group sessions and semi-structured interviews are used to collect data from Dutch governmental stakeholders as well as private stakeholders and NGOs. This data is then coded to discover what usability gaps are present. We then present twelve different types of usability gaps that were encountered as a typology. This typology could be used to improve and redesign climate services.
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.