Literature DB >> 21499932

Statistically integrated flow and flood modelling compared to hydrologically integrated quantity and quality model for annual flows in the regulated Macquarie river in arid Australia.

Shiquan Ren1, Richard T Kingsford.   

Abstract

Water resource management traditionally depends on use of highly complex hydrological models designed originally to manage water for abstraction but increasingly relied on to determine ecological impacts and test ecological rehabilitation opportunities. These models are rarely independently tested. We compared a relatively simple statistical model, integrated flow and flood modelling (IFFM), with a complex hydrological model, the integrated quality and quantity model (IQQM), on the highly regulated Macquarie River of the Murray-Darling Basin, southeastern Australia. We compared annual flows (1891-2007) at three gauges to actual data and modelled output: before dams and diversions (unregulated) and after river regulation (regulated), using the goodness of fit (Nash-Sutcliffe coefficient of efficiency) and nonparametric tests. IQQM underestimated impacts of river regulation respectively on median and average flows at the Macquarie Marshes (Oxley gauge) by about 10% and 16%, compared to IFFM. IFFM model output more closely matched actual unregulated and regulated flows than IQQM which tended to underestimate unregulated flows and overestimate regulated flows at the Ramsar-listed wetland. Output was reasonably similar for the two models at the other two flow gauges. Relatively simple statistical models could more reliably estimate ecological impact at floodplains of large river systems, as well as an independent assessment tool compared to complex hydrological models. Finally, such statistical models may be valuable for predicting ecological responses to environmental flows, given their simplicity and relative ease to run.

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Year:  2011        PMID: 21499932     DOI: 10.1007/s00267-011-9673-9

Source DB:  PubMed          Journal:  Environ Manage        ISSN: 0364-152X            Impact factor:   3.266


  4 in total

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Authors:  J D Thompson; F Plewniak; O Poch
Journal:  Nucleic Acids Res       Date:  1999-07-01       Impact factor: 16.971

2.  Irrigated Agriculture and Wildlife Conservation: Conflict on a Global Scale.

Authors: 
Journal:  Environ Manage       Date:  2000-05       Impact factor: 3.266

3.  The time-rescaling theorem and its application to neural spike train data analysis.

Authors:  Emery N Brown; Riccardo Barbieri; Valérie Ventura; Robert E Kass; Loren M Frank
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4.  The effects of large-scale afforestation and climate change on water allocation in the Macquarie River catchment, NSW, Australia.

Authors:  Natasha Herron; Richard Davis; Roger Jones
Journal:  J Environ Manage       Date:  2002-08       Impact factor: 6.789

  4 in total

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