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Titel Rainstorms able to induce flash floods in a Mediterranean-climate region (Calabria, southern Italy)
VerfasserIn O. G. Terranova, S. L. Gariano
Medientyp Artikel
Sprache Englisch
ISSN 1561-8633
Digitales Dokument URL
Erschienen In: Natural Hazards and Earth System Sciences ; 14, no. 9 ; Nr. 14, no. 9 (2014-09-10), S.2423-2434
Datensatznummer 250118661
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/nhess-14-2423-2014.pdf
 
Zusammenfassung
Heavy rainstorms often induce flash flooding, one of the natural disasters most responsible for damage to man-made infrastructures and loss of lives, also adversely affecting the opportunities for socio-economic development of Mediterranean countries. The frequently dramatic damage of flash floods are often detected, with sufficient accuracy, by post-event surveys, but rainfall causing them are still only roughly characterized. With the aim of improving the understanding of the temporal structure and spatial distribution of heavy rainstorms in the Mediterranean context, a statistical analysis was carried out in Calabria (southern Italy) concerning rainstorms that mainly induced flash floods, but also shallow landslides and debris flows. Thus, a method is proposed – based on the overcoming of heuristically predetermined threshold values of cumulated rainfall, maximum intensity, and kinetic energy of the rainfall event – to select and characterize the rainstorms able to induce flash floods in the Mediterranean-climate countries. Therefore, the obtained (heavy) rainstorms were automatically classified and studied according to their structure in time, localization, and extension. Rainfall-runoff watershed models can consequently benefit from the enhanced identification of design storms, with a realistic time structure integrated with the results of the spatial analysis. A survey of flash flood events recorded in the last decades provides a preliminary validation of the method proposed to identify the heavy rainstorms and synthetically describe their characteristics. The notable size of the employed sample, including data with a very detailed resolution in time that relate to several rain gauges well-distributed throughout the region, gives robustness to the obtained results.
 
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