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Supporting data and tools for "Simulating Community Water Use Behavior and Potential Water Conservation Using Detailed End Use Event Data"
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Type: | Resource | |
Storage: | The size of this resource is 51.8 MB | |
Created: | Oct 12, 2021 at 6:52 p.m. | |
Last updated: | Jun 27, 2022 at 6:02 p.m. | |
Citation: | See how to cite this resource |
Sharing Status: | Public |
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Views: | 1056 |
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Abstract
The files provided here are the supporting data and code files for the analyses presented in "Simulating Community Water Use Behavior And Potential Water Conservation Using Detailed End Use Event Data" a manuscript submitted for publication. The resource contains standardized monthly water use data for single family residences (SFR) in the city of Logan, UT, USA and the detailed water end use events from the 2016 Residential End Uses of Water Study (REUWS) collected by AquaCraft, Inc. used as inputs to the case study simulation described in the paper. The code included in this resource demonstrates a new model of indoor residential water use that estimates water demand and conservation potential by end use for a target community by simulating indoor water end use events at a household level. The model uses end use event data from a set of representative residential households (selected from the REUWS dataset for our case study) to simulate a larger community and advances existing end use models by: 1) accounting for an expanded set of indoor water end uses; 2) considering the variability in flowrates, durations, and volumes for end use events over different days of the week; and 3) providing a generalized approach for simulating indoor water usage and potential conservation at the city level. The results of this paper are reproducible using the openly available code and data provided in this resource, representing an accessible platform for advancing water demand modeling using detailed water end use data.
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Funding Agencies
This resource was created using funding from the following sources:
Agency Name | Award Title | Award Number |
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National Science Foundation | CAREER: Cyberinfrastructure for Intelligent Water Supply (CIWS): Shrinking Big Data for Sustainable Urban Water | 1552444 |
Utah Water Research Laboratory |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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