Floods are a global problem and are considered the most frequent natural disaster world-wide. Many studies showthat the severity and frequency of floods have increased in recent years and underline the difficulty to separate theeffects of natural climatic changes and human influences as land management practices, urbanization etc. Floodrisk analysis and assessment is required to provide information on current or future flood hazard and risks in orderto accomplish flood risk mitigation, to propose, evaluate and select measures to reduce it. Both components ofrisk can be mapped individually and are affected by multiple uncertainties as well as the joint estimate of floodrisk. Major sources of uncertainty include statistical analysis of extremes events, definition of hydrological input,channel and floodplain topography representation, the choice of effective hydraulic roughness coefficients. Theclassical procedure to estimate flood discharge for a chosen probability of exceedance is to deal with a rainfallrunoffmodel associating to risk the same return period of original rainfall, in accordance with the iso-frequencycriterion. Alternatively, a flood frequency analysis to a given record of discharge data is applied, but again the sameprobability is associated to flood discharges and respective risk. Moreover, since flood peaks and correspondingflood volumes are variables of the same phenomenon, they should be, directly, correlated and, consequently, multivariatestatistical analyses must be applied.This study presents an innovative approach to obtain flood hazard maps where hydrological input (synthetic flooddesign event) to a 2D hydraulic model has been defined by generating flood peak discharges and volumes from: a)a classical univariate approach, b) a bivariate statistical analysis, through the use of copulas.The univariate approach considers flood hydrographs generation by an indirect approach (rainfall-runoff transformationusing input rainfall hydrographs derived from IDF curves) and a direct approach (statistical inference onmeasured flood peaks).In the bivariate approach synthetic hydrographs were generated by means two different approaches: an indirectone, where rainfall were generated by a stochastic bivariate rainfall generator to be entered a distributed conceptualrainfall-runoff model that consisted of a soil moisture routine and a flow routing routine; and a direct one,where stochastic generation of flood peaks and flow volumes have been obtained via copulas, which are capable todescribe and model the correlation between these two variables.Finally, to highlight the advantages of the presented approach, probabilistic flood hazard maps (including uncertainty)derived by bivariate models are compared to maps from univariate analysis.The procedure is applied to a real case study located in the southern part of Sicily, Italy, where flood hazard andrisk maps have been obtained and compared.
|Numero di pagine||1|
|Stato di pubblicazione||Published - 2014|