Suchergebnisse

In many countries of the world, floods continue to cause extensive damage to people and properties. This is also the case of Mexico, where meteorological phenomena cause flooding every year. In order to mitigate continuous losses and damages, crucial tools like hazard maps are essential for prevention. This review article analyzes the main reasons for the shortcomings on disasters caused by floods in Mexico. We argue that strong linking between the realm of technical hazard mappings and local governance as an integrated approach to manage disasters can be a basis for a new prevention policy in Mexico. This consideration is achieved through the description of the available information on the meteorological events that have caused major damage in recent years and the analysis of the interventions carried out at decision-making level by the government and the national civil protection system. The application that hazard maps have in the world and their usefulness is also discussed. From the analysis carried out it emerges that the inefficiency of the system in preventing damage caused by floods in Mexico is due to both the lack of high-level expertise in hazard maps design and the lack of their use in decision-making policies at the local level.

Abstract. This work defines a national flood susceptibility index for the Portuguese continental territory, by proposing the aggregation of different variables which represent natural conditions for permeability, runoff and accumulation. This index is part of the national vulnerability index developed in the scope of Flood Maps in Climate Change Scenarios (CIRAC) project, supported by the Portuguese Association of Insurers (APS). This approach expands on previous works by trying to bridge the gap between different flood mechanisms (e.g. progressive and flash floods) occurring at different spatial scales in the Portuguese territory through (a) selecting homogeneously processed data sets and (b) aggregating their values to better translate the spatially continuous and cumulative influence in floods at multiple spatial scales. Results show a good ability to capture, in the higher susceptibility classes, different flood types: fluvial floods and flash floods. Lower values are usually related to mountainous areas, low water accumulation potential and more permeable soils. Validation with independent flood data sets confirmed these index characteristics, although some overestimation can be seen in the southern region of Alentejo where, due to a dense hydrographic network and an overall low slope, floods are not as frequent as a result of lower precipitation mean values. Future work will focus on (i) including extreme precipitation data sets to represent the triggering factor, (ii) improving representation of smaller and stepper basins, (iii) optimizing variable weight definition process and (iii) developing more robust independent flood validation data sets.

Abstract: The social and economic impacts caused by floods in urban areas are diverse and increase as the land becomes gradually impervious. Due to the increasing urbanization of cities, it is necessary to implement a better planning process and optimize the urban spaces management and occupation. Thus, the government needs to gather reliable and useful data for the decision-making process. Therefore, the GIS plays an important role among urban planning instruments. Given the current situation in Campina Grande County, Paraiba State, Brazil - an area continually facing disturbances caused by occasional and concentrated rainfalls - the current study aims to map the areas seen as the most susceptible to floods, by using a MCDA GIS-based model (Multi-Criteria Decision Analysis). There are five quantitative criteria considered in the analysis: slope, altitude, roads with drainage infrastructure, distance from water bodies and land use. It is a pixel by pixel analysis based on predetermined assumptions. Fuzzy functions were developed and overlay operations were performed. The results were consistent with historical records and with previous studies about the county, thus adding reliability to the model, which can be considered a potential management instrument for the case study area, as well as for cities facing similar issues.

The social and economic impacts caused by floods in urban areas are diverse and increase as the land becomes gradually impervious. Due to the increasing urbanization of cities, it is necessary to implement a better planning process and optimize the urban spaces management and occupation. Thus, the government needs to gather reliable and useful data for the decision-making process. Therefore, the GIS plays an important role among urban planning instruments. Given the current situation in Campina Grande County, Paraiba State, Brazil - an area continually facing disturbances caused by occasional and concentrated rainfalls - the current study aims to map the areas seen as the most susceptible to floods, by using a MCDA GIS-based model (Multi-Criteria Decision Analysis). There are five quantitative criteria considered in the analysis: slope, altitude, roads with drainage infrastructure, distance from water bodies and land use. It is a pixel by pixel analysis based on predetermined assumptions. Fuzzy functions were developed and overlay operations were performed. The results were consistent with historical records and with previous studies about the county, thus adding reliability to the model, which can be considered a potential management instrument for the case study area, as well as for cities facing similar issues.

The social and economic impacts caused by floods in urban areas are diverse and increase as the land becomes gradually impervious. Due to the increasing urbanization of cities, it is necessary to implement a better planning process and optimize the urban spaces management and occupation. Thus, the government needs to gather reliable and useful data for the decision-making process. Therefore, the GIS plays an important role among urban planning instruments. Given the current situation in Campina Grande County, Paraiba State, Brazil - an area continually facing disturbances caused by occasional and concentrated rainfalls - the current study aims to map the areas seen as the most susceptible to floods, by using a MCDA GIS-based model (Multi-Criteria Decision Analysis). There are five quantitative criteria considered in the analysis: slope, altitude, roads with drainage infrastructure, distance from water bodies and land use. It is a pixel by pixel analysis based on predetermined assumptions. Fuzzy functions were developed and overlay operations were performed. The results were consistent with historical records and with previous studies about the county, thus adding reliability to the model, which can be considered a potential management instrument for the case study area, as well as for cities facing similar issues.

Abstract. There are various approaches available for assessing the flood vulnerability and damage to buildings and critical infrastructure. They cover pre- and post-event methods for different scales. However, there can hardly be found any method that allows for a large-scale pre-event assessment of the built structures with a high resolution. To make advancements in this respect, the paper presents, first, a conceptual framework for understanding the physical flood susceptibility of buildings and, second, a methodological framework for its assessment. The latter ranges from semi-automatic extraction of buildings, mainly from remote sensing with a subsequent classification and systematic characterisation, to the assessment of the physical flood susceptibility on the basis of depth–impact functions. The work shows results of the methodology's implementation and testing in a settlement of the city of Magangué, along the Magdalena River in Colombia.