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Probability Distributions for Explaining Hydrological Losses in South Australian Catchments : Volume 10, Issue 4 (10/04/2013)

By Gamage, S. H. P. W.

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Book Id: WPLBN0004011732
Format Type: PDF Article :
File Size: Pages 30
Reproduction Date: 2015

Title: Probability Distributions for Explaining Hydrological Losses in South Australian Catchments : Volume 10, Issue 4 (10/04/2013)  
Author: Gamage, S. H. P. W.
Volume: Vol. 10, Issue 4
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2013
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Beecham, S., Hewa, G. A., & P. W. Gamag, S. H. (2013). Probability Distributions for Explaining Hydrological Losses in South Australian Catchments : Volume 10, Issue 4 (10/04/2013). Retrieved from http://www.ebooklibrary.org/


Description
Description: School of Natural and Built Environments, University of South Australia, Adelaide, Australia. The wide variability of hydrological losses in catchments is due to multiple variables that affect the rainfall-runoff process. Accurate estimation of hydrological losses is required for making vital decisions in design applications that are based on design rainfall models and rainfall-runoff models. Using representative single values of losses, despite their wide variability, is common practice, especially in Australian studies. This practice leads to issues such as over or under estimation of design floods. Probability distributions can be used as a better representation of losses. In particular, using joint probability approaches (JPA), probability distributions can be incorporated into hydrological loss parameters in design models. However, lack of understanding of loss distributions limits the benefit of using JPA.

The aim of this paper is to identify a probability distribution function that can successfully describe hydrological losses in South Australian (SA) catchments. This paper describes suitable parametric and non-parametric distributions that can successfully describe observed loss data. The goodness-of-fit of the fitted distributions and quantification of the errors associated with quantile estimation are also discussed a two-parameter Gamma distribution was identified as one that successfully described initial loss (IL) data of the selected catchments. Also, a non-parametric standardised distribution of losses that describes both IL and continuing loss (CL) data were identified. The results obtained for the non-parametric methods were compared with similar studies carried out in other parts of Australia and a remarkable degree of consistency was observed. The results will be helpful in improving design flood applications.


Summary
Probability distributions for explaining hydrological losses in South Australian catchments

Excerpt
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