Keywords
flood, frequency analysis, extreme events, monte carlo simulation, uncertainty, pub
Start Date
1-7-2004 12:00 AM
Abstract
In this paper a Monte Carlo procedure for deriving frequency distributions of extreme dischargesstarting from a simplified description of rainfall and surface runoff processes and using regional data ispresented. The procedure is based on two modules: a stochastic rainfall generator module and a catchmentresponse module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for afixed duration, is assumed to follow the Two Components Extreme Value (TCEV) distribution whoseparameters have been estimated at regional scale for Sicily. The catchment response has been modelled byusing the Soil Conservation Service – Curve Number for the total-effective rainfall transformation and theclassical rational formula for the flood routing. This method allows incorporation of information on soiltype, land use, soil cover condition and Antecedent Soil Moisture (AMC). Furthermore, to take in accountfor the spatial variation of CN within the catchment, a semi-distributed approach of the rainfall-runoffmodel was implemented. Finally, the Generalised Likelihood Uncertainty Estimation (GLUE) procedure hasbeen used to explore the estimation of the uncertain knowledge of AMC affecting derivation of FFC.
A Regional Methodology for Deriving Flood Frequency Curves (FFC) in Partially Gauged Catchments with Uncertain Knowledge of Soil Moisture Conditions
In this paper a Monte Carlo procedure for deriving frequency distributions of extreme dischargesstarting from a simplified description of rainfall and surface runoff processes and using regional data ispresented. The procedure is based on two modules: a stochastic rainfall generator module and a catchmentresponse module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for afixed duration, is assumed to follow the Two Components Extreme Value (TCEV) distribution whoseparameters have been estimated at regional scale for Sicily. The catchment response has been modelled byusing the Soil Conservation Service – Curve Number for the total-effective rainfall transformation and theclassical rational formula for the flood routing. This method allows incorporation of information on soiltype, land use, soil cover condition and Antecedent Soil Moisture (AMC). Furthermore, to take in accountfor the spatial variation of CN within the catchment, a semi-distributed approach of the rainfall-runoffmodel was implemented. Finally, the Generalised Likelihood Uncertainty Estimation (GLUE) procedure hasbeen used to explore the estimation of the uncertain knowledge of AMC affecting derivation of FFC.
