The Fish Health Risk Indicator: linking water quality and river flow data with fish health to improve our predictive capacity around fish death events

Davie, AW; Pera, JB

The Fish Health Risk Indicator: linking water quality and river flow data with fish health to improve our predictive capacity around fish death events

Davie, AW Pera, JB

Permalink

Publisher:: CSIRO Publishing
Publication Type:: Journal Article
Citation:: Marine and Freshwater Research, 2022, 73, (2), pp. 193
Issue Date:: 2022

Closed Access

	Filename	Description	Size
	MF20360.pdf	Published version	1.07 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Davie, AW
dc.contributor.author	Pera, JB
dc.date.accessioned	2023-02-14T03:35:18Z
dc.date.available	2023-02-14T03:35:18Z
dc.date.issued	2022
dc.identifier.citation	Marine and Freshwater Research, 2022, 73, (2), pp. 193
dc.identifier.issn	1323-1650
dc.identifier.uri	http://hdl.handle.net/10453/166105
dc.description.abstract	<jats:p>Severe drought conditions contributed to three mass fish mortality events in the Darling River near Menindee, part of the Murray–Darling Basin, Australia, during the summer of 2018–19. An independent assessment recommended the need for improved modelling approaches to identify when sections of rivers may be more susceptible to fish kill events. We present a geographic information system (GIS)-based tool that combines meteorological forecasts with river flow and algal biomass datasets to identify river reaches where additional stresses on fish health may produce an increased risk of mass fish deaths. At present the tool is still in development and will require the addition of extra datasets and testing using historical datasets to further validate its accuracy. Despite the tool being in its development stage, the decision support tool has been widely accepted and provides natural resource managers with a rapid way to understand and communicate risks to fish health, supporting improved water management options across the Murray–Darling Basin that may ultimately help reduce the frequency and severity of large-scale fish mortality events.</jats:p>
dc.language	en
dc.publisher	CSIRO Publishing
dc.relation.ispartof	Marine and Freshwater Research
dc.relation.isbasedon	10.1071/mf20360
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Marine Biology & Hydrobiology
dc.title	The Fish Health Risk Indicator: linking water quality and river flow data with fish health to improve our predictive capacity around fish death events
dc.type	Journal Article
utslib.citation.volume	73
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	closed_access	*
dc.date.updated	2023-02-14T03:35:17Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	73
utslib.citation.issue	2

Abstract:

Severe drought conditions contributed to three mass fish mortality events in the Darling River near Menindee, part of the Murray–Darling Basin, Australia, during the summer of 2018–19. An independent assessment recommended the need for improved modelling approaches to identify when sections of rivers may be more susceptible to fish kill events. We present a geographic information system (GIS)-based tool that combines meteorological forecasts with river flow and algal biomass datasets to identify river reaches where additional stresses on fish health may produce an increased risk of mass fish deaths. At present the tool is still in development and will require the addition of extra datasets and testing using historical datasets to further validate its accuracy. Despite the tool being in its development stage, the decision support tool has been widely accepted and provides natural resource managers with a rapid way to understand and communicate risks to fish health, supporting improved water management options across the Murray–Darling Basin that may ultimately help reduce the frequency and severity of large-scale fish mortality events.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/166105