5 resultados para Risk map

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Soil erosion models and soil erosion risk maps are often used as indicators to assess potential soil erosion in order to assist policy decisions. This paper shows the scientific basis of the soil erosion risk map of Switzerland and its application in policy and practice. Linking a USLE/RUSLE-based model approach (AVErosion) founded on multiple flow algorithms and the unit contributing area concept with an extremely precise and high-resolution digital terrain model (2 m × 2 m grid) using GIS allows for a realistic assessment of the potential soil erosion risk, on single plots, i.e. uniform and comprehensive for the agricultural area of Switzerland (862,579 ha in the valley area and the lower mountain regions). The national or small-scale soil erosion prognosis has thus reached a level heretofore possible only in smaller catchment areas or single plots. Validation was carried out using soil loss data from soil erosion damage mappings in the field from long-term monitoring in different test areas. 45% of the evaluated agricultural area of Switzerland was classified as low potential erosion risk, 12% as moderate potential erosion risk, and 43% as high potential erosion risk. However, many of the areas classified as high potential erosion risk are located at the transition from valley to mountain zone, where many areas are used as permanent grassland, which drastically lowers their current erosion risk. The present soil erosion risk map serves on the one hand to identify and prioritise the high-erosion risk areas, and on the other hand to promote awareness amongst farmers and authorities. It was published on the internet and will be made available to the authorities in digital form. It is intended as a tool for simplifying and standardising enforcement of the legal framework for soil erosion prevention in Switzerland. The work therefore provides a successful example of cooperation between science, policy and practice.

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Off-site effects of soil erosion are becoming increasingly important, particularly the pollution of surface waters. In order to develop environmentally efficient and cost effective mitigation options it is essential to identify areas that bear both a high erosion risk and high connectivity to surface waters. This paper introduces a simple risk assessment tool that allows the delineation of potential critical source areas (CSA) of sediment input into surface waters concerning the agricultural areas of Switzerland. The basis are the erosion risk map with a 2 m resolution (ERM2) and the drainage network, which is extended by drained roads, farm tracks, and slope depressions. The probability of hydrological and sedimentological connectivity is assessed by combining soil erosion risk and extended drainage network with flow distance calculation. A GIS-environment with multiple-flow accumulation algorithms is used for routing runoff generation and flow pathways. The result is a high resolution connectivity map of the agricultural area of Switzerland (888,050 ha). Fifty-five percent of the computed agricultural area is potentially connected with surface waters, 45% is not connected. Surprisingly, the larger part of 34% (62% of the connected area) is indirectly connected with surface waters through drained roads, and only 21% are directly connected. The reason is the topographic complexity and patchiness of the landscape due to a dense road and drainage network. A total of 24% of the connected area and 13% of the computed agricultural area, respectively, are rated with a high connectivity probability. On these CSA an adapted land use is recommended, supported by vegetated buffer strips preventing sediment load. Even areas that are far away from open water bodies can be indirectly connected and need to be included in planning of mitigation measures. Thus, the connectivity map presented is an important decision-making tool for policy-makers and extension services. The map is published on the web and thus available for application.

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Tajikistan is judged to be highly vulnerable to risk, including food insecurity risks and climate change risks. By some vulnerability measures it is the most vulnerable among all 28 countries in the World Bank’s Europe and Central Asia Region – ECA (World Bank 2009). The rural population, with its relatively high incidence of poverty, is particularly vulnerable. The Pilot Program for Climate Resilience (PPCR) in Tajikistan (2011) provided an opportunity to conduct a farm-level survey with the objective of assessing various dimensions of rural population’s vulnerability to risk and their perception of constraints to farming operations and livelihoods. The survey should be accordingly referred to as the 2011 PPCR survey. The rural population in Tajikistan is highly agrarian, with about 50% of family income deriving from agriculture (see Figure 4.1; also LSMS 2007 – own calculations). Tajikistan’s agriculture basically consists of two groups of producers: small household plots – the successors of Soviet “private agriculture” – and dehkan (or “peasant”) farms – new family farming structures that began to be created under relevant legislation passed after 1992 (Lerman and Sedik, 2008). The household plots manage 20% of arable land and produce 65% of gross agricultural output (GAO). Dehkan farms manage 65% of arable land and produce close to 30% of GAO. The remaining 15% of arable land is held in agricultural enterprises – the rapidly shrinking sector of corporate farms that succeeded the Soviet kolkhozes and sovkhozes and today produces less than 10% of GAO (TajStat 2011) The survey conducted in May 2011 focused on dehkan farms, as budgetary constraints precluded the inclusion of household plots. A total of 142 dehkan farms were surveyed in face-to-face interviews. They were sampled from 17 districts across all four regions – Sughd, Khatlon, RRP, and GBAO. The districts were selected so as to represent different agro-climatic zones, different vulnerability zones (based on the World Bank (2011) vulnerability assessment), and different food-insecurity zones (based on WFP/IPC assessments). Within each district, 3-4 jamoats were chosen at random and 2-3 farms were selected in each jamoat from lists provided by jamoat administration so as to maximize the variability by farm characteristics. The sample design by region/district is presented in Table A, which also shows the agro-climatic zone and the food security phase for each district. The sample districts are superimposed on a map of food security phases based on IPC April 2011.

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The epidemiology of "Lyme borreliosis" in Europe and the significance of positive antibody titers against Borrelia burgdorferi is not well known. Since "orienteering", a competitive cross country sport with a map and a compass, usually in forests, elevates the risk of being bitten by ticks and infected by B. burgdorferi, nearly 1000 orienteerers were included in a prospective study. - In this population the prevalence of positive IgG-antibodies (immunofluorescence technique) was almost 20% and of IgM-antibodies 4%. However, the frequency of associated symptoms in the clinical history of the probands was very low, even in individuals with highly positive titers. - We conclude that the rate of asymptomatic Borrelia infections is high in this special group, and probably also in the general population, and that one has therefore to be cautious in interpreting an isolated positive "Lyme titer". Further investigations are needed, and, in particular, follow-up of the many "positive" subjects without clinical symptoms may be helpful in understanding this fascinating disease better.

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The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.