Exploring spatial relationships between stream channel features,water depths and flow velocities during flash floods using HEC-GeoRAS and Geographic Information Systems

Water depths and flow velocities decisively influence the damage caused by flash floods.Geographic Information System(GIS)is a powerful and useful tool,allowing the spatial analysis of results obtained by hydraulic modelling,namely from the HEC-RAS/HEC-GeoRAS software.The GIS spatial analysis performed in this study seeks to explain and quantify the spatial relationships between the stream channel features and flow components during flash flood events.Despite these relationships are generically known,there are few studies exploring this subject in different geographic contexts.A 1D hydraulic model was applied in a small watershed in Portugal,providing good results in the definition of floodable areas,water depths and longitudinal velocities.No direct relationship was found between water depths and velocities in the floodable areas;however,negative strong correlations were found between the two flow components along the stream centerlines.Bed slope,channel and flood width,and roughness prove to be highly relevant on the longitudinal variations of water depths and velocities and on the location of maximum values.Increasing peak discharges and return periods(R;)can change the relationships between water depths and velocities at the same location.Results can be improved with more accurate elevation data for stream channels and floodplains.

A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal

Social vulnerability,as one of the risk components,partially explains the magnitude of the impacts observed after a disaster.In this study,a spatiotemporally comparable assessment of social vulnerability and its drivers was conducted in Portugal,at the civil parish level,for three census frames.The first challenging step consisted of the selection of meaningful and consistent variables over time.Data were normalized using the Adjusted Mazziotta-Pareto Index(AMPI)to obtain comparable adimensional-normalized values.A joint principal component analysis(PCA)was applied,resulting in a robust set of variables,interpretable from the point of view of their self-grouping around vulnerability drivers.A separate PCA for each census was also conducted,which proved to be useful in analyzing changes in the composition and type of drivers,although only the joint PCA allows the monitoring of spatiotemporal changes in social vulnerability scores and drivers from 1991 to 2011.A general improvement in social vulnerability was observed for Portugal.The two main drivers are the economic condition(PC1),and aging and depopulation(PC2).The remaining drivers highlighted are uprooting and internal mobility,and daily commuting.Census data proved their value in the territorial,social,and demographic characterization of the country,to support medium-and long-term disaster risk reduction measures.