Journal article

A Bayesian method for multi-site stochastic data generation: Dealing with non-concurrent and missing data, variable transformation and parameter uncertainty

QJ Wang

ENVIRONMENTAL MODELLING & SOFTWARE | ELSEVIER SCI LTD | Published : 2008

Abstract

Stochastically generated stream flow and climatic data may be used as input to water resources simulation models for planning purposes. Dealing with non-concurrent and missing data, variable transformation and parameter uncertainty presents a significant challenge in the development of methods for stochastic data generation. In this paper, a Bayesian method is introduced for multi-site stochastic generation of annual stream flow and climatic data. A contemporaneous autoregressive lag-one model CAR(1) with the Box-Cox transformation is used to capture key statistical structure of multiple annual stream flow and climatic time series while keeping the number of model parameters to a minimum. Th..

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University of Melbourne Researchers