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Identification of nonlinearity in rainfall-flow response using data-based mechanistic modeling

Date

Authors

McIntyre, Neil

Young, Peter C

Orellana, Barbara

Marshall, Miles

Reynolds, Brian

Wheater, Howard

Publisher

American Geophysical Union

Abstract

Data-based mechanistic (DBM) modeling is an established approach to time series model identification and estimation, which seeks model structures and parameters that are both statistically optimal and consistent with plausible mechanistic interpretations

Keywords

Keywords: Complex surface; Conceptual model; DBM methods; Dry spells; Flow data; Flow pathways; Flow response; High precision; Identification of nonlinearities; Mass balance; Mechanistic interpretations; Mechanistic modeling; Model performance; Non-Linearity; Non-s

URI

http://hdl.handle.net/1885/69679

Collections

ANU Research Publications

Source

Water Resources Research

Type

Journal article

DOI

10.1029/2010WR009851

Restricted until

2037-12-31

Downloads

File

Description

01_McIntyre_Identification_of_nonlinearity_2011.pdf (1.49 MB)