Abstract. Floods are the natural hazards that produce the highest number of casualties and material damage in the Western Mediterranean. An improvement in flood risk assessment and study of a possible increase in flooding occurrence are therefore needed. To carry out these tasks it is important to have at our disposal extensive knowledge on historical floods and to find an efficient way to manage this geographical data. In this paper we present a complete flood database spanning the 20th century for the whole of Catalonia (NE Spain), which includes documentary information (affected areas and damage) and instrumental information (meteorological and hydrological records). This geodatabase, named Inungama, has been implemented on a GIS (Geographical Information System) in order to display all the information within a given geographical scenario, as well as to carry out an analysis thereof using queries, overlays and calculus. Following a description of the type and amount of information stored in the database and the structure of the information system, the first applications of Inungama are presented. The geographical distribution of floods shows the localities which are more likely to be flooded, confirming that the most affected municipalities are the most densely populated ones in coastal areas. Regarding the existence of an increase in flooding occurrence, a temporal analysis has been carried out, showing a steady increase over the last 30 years.

Abstract. This contribution analyzes the evolution of perception of certain natural hazards over the past 25 years in a Mediterranean region. Articles from newspapers have been used as indicator. To this end a specific Spanish journal has been considered and an ACCESS database has been created with the summarized information from each news item. The database includes data such as the location of each specific article in the newspaper, its length, the number of pictures and figures, the headlines and a summary of the published information, including all the instrumental data. The study focused on hydrometeorological extremes, mainly floods and droughts, in the northeast of the Iberian Peninsula. The number of headlines per event, trends and other data have been analyzed and compared with "measured" information, in order to identify any bias that could lead to an erroneous perception of the phenomenon. The SPI index (a drought index based on standardized accumulated precipitation) has been calculated for the entire region, and has been used for the drought analysis, while a geodatabase implemented on a GIS built for all the floods recorded in Catalonia since 1900 (IN-UNGAMA) has been used to analyze flood evolution. Results from a questionnaire about the impact of natural hazards in two specific places have been also used to discuss the various perceptions between rural and urban settings. Results show a better correlation between the news about drought or water scarcity and SPI than between news on floods in Catalonia and the INUNGAMA database. A positive trend has been found for non-catastrophic floods, which is explained by decrease of the perception thresholds, the increase of population density in the most flood-prone areas and changes in land use.

Abstract. In assessing a flood event two risk components need to be considered: the intrinsic hazard of the hydrometeorological event causing the flood and the vulnerability of the area where the precipitation has been registered. In the present study four flood events selected by the FLASH European project have been classified according to the characteristics of the meteorological event (classification according to hazard) and according to the physical and economic damages caused (classification according to vulnerability). The social impact of these events is analysed taking into account the growth of the population. An increase in the number of extraordinary flash-floods was detected in the areas with a major growth of the population, as a consequence of an increased vulnerability of these areas, both from a physical perspective (exposure of infrastructures) and from an economic perspective (more goods exposed). In addition, the numerous non-native inhabitants of the region are not aware of the meteorological risks characteristic of the area, and this contributes to increased social vulnerability.

Abstract. Flood simulation studies use spatial-temporal rainfall data input into distributed hydrological models. A correct description of rainfall in space and in time contributes to improvements on hydrological modelling and design. This work is focused on the analysis of 2-D convective structures (rain cells), whose contribution is especially significant in most flood events. The objective of this paper is to provide statistical descriptors and distribution functions for convective structure characteristics of precipitation systems producing floods in Catalonia (NE Spain). To achieve this purpose heavy rainfall events recorded between 1996 and 2000 have been analysed. By means of weather radar, and applying 2-D radar algorithms a distinction between convective and stratiform precipitation is made. These data are introduced and analyzed with a GIS. In a first step different groups of connected pixels with convective precipitation are identified. Only convective structures with an area greater than 32 km 2 are selected. Then, geometric characteristics (area, perimeter, orientation and dimensions of the ellipse), and rainfall statistics (maximum, mean, minimum, range, standard deviation, and sum) of these structures are obtained and stored in a database. Finally, descriptive statistics for selected characteristics are calculated and statistical distributions are fitted to the observed frequency distributions. Statistical analyses reveal that the Generalized Pareto distribution for the area and the Generalized Extreme Value distribution for the perimeter, dimensions, orientation and mean areal precipitation are the statistical distributions that best fit the observed ones of these parameters. The statistical descriptors and the probability distribution functions obtained are of direct use as an input in spatial rainfall generators.