Transfer function modelling, which is a statistical technique used to relate a dependent or output variable to one or more independent or input variables when there may be time lags between inputs and output, is used in this study to examine the dynamic relationships between the turbidity of the surface water of Lake Eppalock with the inflows from its tributary streams and rainfall. The formulation of transfer function models is considered first, then single-input and finally double-input models are given. Single-input models are identified using the sample cross-correlation function. The problems caused by correlated input series are overcome by identifying the double-input models with a biased regression technique. Akaike's Information Criterion is used to choose between competing models. The results indicate that the turbidity of the lake is mostly explained by the inflow from the Coliban River and the rainfall in the vicinity of the dam. We conclude that the catchment of the Coliban River and the foreshore of the lake are the most important regions affecting the turbidity of its surface waters.
Intervention analysis is a rigorous statistical modelling technique used to measure the effect of a shift in the mean level of a time series, caused by an intervention. A general formulation of an intervention model is applied to water-quality data for two streams in north-eastern Victoria, measuring the effect of drought on the electrical conductivity of one stream, and the effect of bushfires on the flow and turbidity of the other. The nature of the intervention is revealed using exploratory data-analysis techniques, such as smoothing and boxplots, on the time-series data. Intervention analysis is then used to confirm the identified changes and estimate their magnitude. The increased level of electrical conductivity due to drought is determined by three techniques of estimation and the results compared. The best of these techniques is then used to model changes in stream flow and turbidity following bushfires in the catchment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.