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MODELLING AND SIMULATION OF VOLUMETRIC RAINFALL FOR A CATCHMENT IN THE MURRAY–DARLING BASIN

Published online by Cambridge University Press:  08 September 2016

J. BOLAND
Affiliation:
Scheduling and Control Group (SCG), Centre for Industrial and Applied Mathematics (CIAM), School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, 5095, South Australia email john.boland@unisa.edu.au, phil.howlett@unisa.edu.au, julia.piantadosi@unisa.edu.au
P. HOWLETT*
Affiliation:
Scheduling and Control Group (SCG), Centre for Industrial and Applied Mathematics (CIAM), School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, 5095, South Australia email john.boland@unisa.edu.au, phil.howlett@unisa.edu.au, julia.piantadosi@unisa.edu.au
J. PIANTADOSI
Affiliation:
Scheduling and Control Group (SCG), Centre for Industrial and Applied Mathematics (CIAM), School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, 5095, South Australia email john.boland@unisa.edu.au, phil.howlett@unisa.edu.au, julia.piantadosi@unisa.edu.au
R. ZAKARIA
Affiliation:
Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Kuantan Pahang, Malaysia email roslinazairimah@ump.edu.my
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Abstract

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We discuss modelling and simulation of volumetric rainfall in a catchment of the Murray–Darling Basin – an important food production region in Australia that was seriously affected by a recent prolonged drought. Consequently, there has been sustained interest in development of improved water management policies. In order to model accumulated volumetric catchment rainfall over a fixed time period, it is necessary to sum weighted rainfall depths at representative sites within each sub-catchment. Since sub-catchment rainfall may be highly correlated, the use of a Gamma distribution to model rainfall at each site means that catchment rainfall is expressed as a sum of correlated Gamma random variables. We compare four different models and conclude that a joint probability distribution for catchment rainfall constructed by using a copula of maximum entropy is the most effective.

Type
Research Article
Copyright
© 2016 Australian Mathematical Society 

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