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Desertification and erosion sensitivity. A case study in southern Italy: the Tusciano River catchment 总被引：1，自引：1，他引：0
The ESAs (Environmentally sensitive areas) procedure was recently developed in the framework of MEDALUS European project to identify desertification-sensitive areas and used in many Mediterranean countries (Greece, Portugal, Italy, Egypt). The identification of areas sensitive to desertification by using the ESAs model was carried out in the Tusciano River basin (261 km2) located in southern Italy (Campania region). All data characterizing the four groups of parameters related to soil quality, climate quality, vegetation quality and management quality were introduced in a geographical database, and superimposed using a GIS. A sensitivity analysis highlighted the impact of desertification on the river Tusciano catchment, highly diversified in terms of morphological, geological, climatic and land use features. The results of the ESAs model, showing that more than half of the area is sensitive to desertification, were compared with those related to soil loss, achieved by Revised Universal Soil Loss Equation, based approximately on the same environmental factors. Nevertheless, ESAs procedure considers a wider range of parameters, allowing to characterize in greater detail the catchment in terms of climate, geomorphology, vegetation cover and socio-economic features. The drawn map therefore characterizes the sensitivity to erosion/desertification of the Tusciano catchment and can be regarded as a synthesis-sensitivity map, showing the areas with higher vulnerability on which mitigation measures should be focused. 相似文献
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Flood risk assessment for informal settlements 总被引：3，自引：2，他引：1
R. De Risi F. Jalayer F. De Paola I. Iervolino M. Giugni M. E. Topa E. Mbuya A. Kyessi G. Manfredi P. Gasparini 《Natural Hazards》2013,69(1):1003-1032
The urban informal settlements are particularly vulnerable to flooding events, due to both their generally poor quality of construction and high population density. An integrated approach to the analysis of flooding risk of informal settlements should take into account, and propagate, the many sources of uncertainty affecting the problem, ranging from the characterization of rainfall curve and flooding hazard to the characterization of the vulnerability of the portfolio of buildings. This paper proposes a probabilistic and modular approach for calculating the flooding risk in terms of the mean annual frequency of exceeding a specific limit state for each building within the informal settlement and the expected number of people affected (if the area is not evacuated). The flooding risk in this approach is calculated by the convolution of flooding hazard and flooding fragility for a specified limit state for each structure within the portfolio of buildings. This is achieved by employing the flooding height as an intermediate variable bridging over the fragility and hazard calculations. The focus of this paper is on an ultimate limit state where the life of slum dwellers is endangered by flooding. The fragility is calculated by using a logic tree procedure where several possible combinations of building features/construction details, and their eventual outcome in terms of the necessity to perform structural analysis or the application of nominal threshold flood heights, are taken into account. The logic tree branch probabilities are characterized based on both the orthophoto recognition and the sample in situ building survey. The application of the methodology is presented for Suna, a sub-ward of Dar es Salaam City (Tanzania) in the Msimbazi River basin having a high concentration of informal settlements. 相似文献
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Fatemeh Jalayer Raffaele De Risi Francesco De Paola Maurizio Giugni Gaetano Manfredi Paolo Gasparini Maria Elena Topa Nebyou Yonas Kumelachew Yeshitela Alemu Nebebe Gina Cavan Sarah Lindley Andreas Printz Florian Renner 《Natural Hazards》2014,73(2):975-1001
Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia. 相似文献
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De Risi Raffaele Jalayer Fatemeh De Paola Francesco Carozza Stefano Yonas Nebyou Giugni Maurizio Gasparini Paolo 《Natural Hazards》2020,100(1):387-415
Natural Hazards - Flood risk maps for the built environment can be obtained by integrating geo-spatial information on hazard, vulnerability and exposure. They provide precious support for strategic... 相似文献
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