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Water 2010, 2(2), 239-256; doi:10.3390/w2020239

Best Fit and Selection of Theoretical Flood Frequency Distributions Based on Different Runoff Generation Mechanisms

1
Dipartimento di Ingegneria delle Acque e di Chimica, Politecnico di Bari, Campus Universitario, Via E. Orabona 4, 70125 Bari, Italy
2
Dipartimento di Ingegneria e Fisica dell’Ambiente, Università degli Studi della Basilicata, Via N. Sauro 85, 85100 Potenza, Italy
*
Author to whom correspondence should be addressed.
Received: 16 March 2010 / Revised: 13 May 2010 / Accepted: 19 May 2010 / Published: 28 May 2010
(This article belongs to the Special Issue Feature Papers)
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Abstract

Theoretically derived distributions allow the detection of dominant runoff generation mechanisms as key signatures of hydrologic similarity. We used two theoretically derived distributions of flood peak annual maxima: the first is the “IF” distribution, which exploits the variable source area concept, coupled with a runoff threshold having scaling properties; the second is the Two Component-IF (TCIF) distribution, which generalizes the IF distribution, and is based on two different threshold mechanisms, associated with ordinary and extraordinary events, respectively. By focusing on the application of both models to two river basins, of sub-humid and semi-arid climate in Southern Italy, we present an ad hoc procedure for the estimation of parameters and we discuss the use of appropriate techniques for model selection, in the case of nested distributions. View Full-Text
Keywords: runoff thresholds; frequency distributions; selection criteria; likelihood; model comparison runoff thresholds; frequency distributions; selection criteria; likelihood; model comparison
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Iacobellis, V.; Fiorentino, M.; Gioia, A.; Manfreda, S. Best Fit and Selection of Theoretical Flood Frequency Distributions Based on Different Runoff Generation Mechanisms. Water 2010, 2, 239-256.

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