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Assessment of short term rainfall and stream flows in South Australia

Citation

Kamruzzaman, M and Shahriar, MS and Beecham, S, Assessment of short term rainfall and stream flows in South Australia, Water, 6, (11) pp. 3528-3544. ISSN 2073-4441 (2014) [Refereed Article]


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Copyright Statement

2014 by the authors; licensee MDPI, Basel, Switzerland. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/

DOI: doi:10.3390/w6113528

Abstract

The aim of this study is to assess the relationship between rainfall and stream flow at Broughton River in Mooroola, Torrance River in Mount Pleasant, and Wakefield River near Rhyine, in South Australia, from 1990 to 2010. Initially, we present a short term relationship between rainfall and stream flow, in terms of correlations, lagged correlations, and estimated variability between wavelet coefficients at each level. A deterministic regression based response model is used to detect linear, quadratic and polynomial trends, while allowing for seasonality effects. Antecedent rainfall data were considered to predict stream flow. The best fitting model was selected based on maximum adjusted R2 values (R2adj ), minimum sigma square (σ2), and a minimum Akaike Information Criterion (AIC). The best performance in the response model is lag rainfall, which indicates at least one day and up to 7 days (past) difference in rainfall, including offset cross products of lag rainfall. With the inclusion of antecedent stream flow as an input with one day time lag, the result shows a significant improvement of the R2adj values from 0.18, 0.26 and 0.14 to 0.35, 0.42 and 0.21 at Broughton River, Torrance River and Wakefield River, respectively. A benchmark comparison was made with an Artificial Neural Network analysis. The optimization strategy involved adopting a minimum mean absolute error (MAE).

Item Details

Item Type:Refereed Article
Keywords:akaike information criterion, artificial neural network, lag response model, rainfall and stream flow, wavelet coefficient
Research Division:Earth Sciences
Research Group:Hydrology
Research Field:Surface water hydrology
Objective Division:Environmental Management
Objective Group:Marine systems and management
Objective Field:Assessment and management of benthic marine ecosystems
UTAS Author:Shahriar, MS (Dr Sumon Shahriar)
ID Code:118069
Year Published:2014
Web of Science® Times Cited:9
Deposited By:Information and Communication Technology
Deposited On:2017-07-03
Last Modified:2017-10-17
Downloads:135 View Download Statistics

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