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Understanding urban water performance at the city-region scale using an urban water metabolism evaluation framework

Overview of attention for article published in Water Research, June 2018
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Title
Understanding urban water performance at the city-region scale using an urban water metabolism evaluation framework
Published in
Water Research, June 2018
DOI 10.1016/j.watres.2018.01.070
Pubmed ID
Authors

Marguerite A. Renouf, Steven J. Kenway, Ka Leung Lam, Tony Weber, Estelle Roux, Silvia Serrao-Neumann, Darryl Low Choy, Edward A. Morgan

Abstract

Water sensitive interventions are being promoted to reduce the adverse impacts of urban development on natural water cycles. However it is currently difficult to know the best strategy for their implementation because current and desired urban water performance is not well quantified. This is particularly at the city-region scale, which is important for strategic urban planning. This work aimed to fill this gap by quantifying the water performance of urban systems within city-regions using 'urban water metabolism' evaluation, to inform decisions about water sensitive interventions. To do this we adapted an existing evaluation framework with new methods. In particular, we used land use data for defining system boundaries, and for estimating natural hydrological flows. The criteria for gauging the water performance were water efficiency (in terms of water extracted externally) and hydrological performance (how much natural hydrological flows have changed relative to a nominated pre-urbanised state). We compared these performance criteria for urban systems within three Australian city-regions (South East Queensland, Melbourne and Perth metropolitan areas), under current conditions, and after implementation of example water sensitive interventions (demand management, rainwater/stormwater harvesting, wastewater recycling and increasing perviousness). The respective water efficiencies were found to be 79, 90 and 133 kL/capita/yr. In relation to hydrological performance, stormwater runoff relative to pre-urbanised flows was of most note, estimated to be 2-, 6- and 3- fold, respectively. The estimated performance benefits from water sensitive interventions suggested different priorities for each region, and that combined implementation of a range of interventions may be necessary to make substantive gains in performance. We concluded that the framework is suited to initial screening of the type and scale of water sensitive interventions needed to achieve desired water performance objectives.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 27%
Student > Master 7 19%
Researcher 5 14%
Student > Bachelor 4 11%
Unspecified 3 8%
Other 8 22%
Readers by discipline Count As %
Environmental Science 12 32%
Engineering 10 27%
Unspecified 8 22%
Social Sciences 3 8%
Computer Science 2 5%
Other 2 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 February 2018.
All research outputs
#9,587,750
of 12,481,741 outputs
Outputs from Water Research
#4,152
of 5,824 outputs
Outputs of similar age
#226,465
of 340,436 outputs
Outputs of similar age from Water Research
#97
of 165 outputs
Altmetric has tracked 12,481,741 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,824 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 340,436 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.