A regional probabilistic model for the estimation of medium-high return period flood quantiles is presented. The model is based on the use of theoretically derived probability distributions of annual maximum flood peaks (DDF). The general model is called TCIF (Two-Component IF model) and encompasses two different threshold mechanisms associated with ordinary and extraordinary events, respectively. Based on at-site calibration of this model for 33 gauged sites in Southern Italy, a regional analysis is performed obtaining satisfactory results for the estimation of flood quantiles for return periods of technical interest, thus suggesting the use of the proposed methodology for the application to ungauged basins. The model is validated by using a jack-knife cross-validation technique taking all river basins into consideration.
Flood quantiles estimation based on theoretically derived distributions: regional analysis in Southern Italy / Iacobellis, Vito; Gioia, Andrea; Manfreda, S; Fiorentino, M.. - In: NATURAL HAZARDS AND EARTH SYSTEM SCIENCES. - ISSN 1561-8633. - STAMPA. - 11:3(2011), pp. 673-695. [10.5194/nhess-11-673-2011]
Flood quantiles estimation based on theoretically derived distributions: regional analysis in Southern Italy
IACOBELLIS, Vito;GIOIA, Andrea;
2011-01-01
Abstract
A regional probabilistic model for the estimation of medium-high return period flood quantiles is presented. The model is based on the use of theoretically derived probability distributions of annual maximum flood peaks (DDF). The general model is called TCIF (Two-Component IF model) and encompasses two different threshold mechanisms associated with ordinary and extraordinary events, respectively. Based on at-site calibration of this model for 33 gauged sites in Southern Italy, a regional analysis is performed obtaining satisfactory results for the estimation of flood quantiles for return periods of technical interest, thus suggesting the use of the proposed methodology for the application to ungauged basins. The model is validated by using a jack-knife cross-validation technique taking all river basins into consideration.File | Dimensione | Formato | |
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