 Linear time-varying models to investigate complex distributed dynamics: A rainfall-runoff exampleJ.P. Norton and J.G. Chanat Mathematics and Computers in Simulation (MATCOM), 2005, vol. 69, issue 1, 123-134 Abstract: Many processes with distributed, non-linear dynamics may be modelled adequately over suitable time and spatial scales by low-order, linear, time-invariant models, but the limitations of such models must be examined. For example, catchment rainfall-runoff models taking pulse-response peak, steady-state gain and recession time constant as time-invariant are useful in assessing water availability, but may not be capable of capturing short-term response well. This paper employs models of a catchment in Virginia, USA, to illustrate how insight into shorter-term dynamics, non-linearities and other unmodelled behaviour can be obtained by allowing selected linear model parameters to vary with time. Those parameters are treated as random walks, estimated recursively by a long-established optimal smoothing algorithm. Attention is paid to interaction between gain and dominant time constant through the transfer function denominator coefficients, and to the role of a time-varying output offset term in the model. Keywords: Parameter estimation; Linear models; Rainfall-runoff; Time-varying parameters (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:69:y:2005:i:1:p:123-134 DOI: 10.1016/j.matcom.2005.02.029 Access Statistics for this article Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier |
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