Measuring Water Use, Conservation, and Differences by Gender Using an Inexpensive, High Frequency Metering System
|Authors:||Jeffery Horsburgh Miguel E. Leonardo Adel Abdallah David Rosenberg|
|Owners:||Jeffery S. Horsburgh|
|Storage:||The size of this resource is 96.3 MB|
|Created:||Mar 10, 2017 at 5:10 p.m.|
|Last updated:||May 26, 2017 at 4:19 p.m. by Jeffery S. Horsburgh|
|Citation:||See how to cite this resource|
This resource contains the final data files and R scripts used in our analysis of water use across two high-traffic, public restrooms on Utah State University's campus. We used an inexpensive, open source, water metering system that uses off-the-shelf electronic components and inexpensive analog meters to measure water use quantity and behavior at high temporal frequency (< 5 s). We demonstrated this technology in the two restrooms at Utah State University before and after installing high efficiency, automatic faucets and toilet flush valves. We also integrated an inexpensive sensor to count user traffic to the restrooms. Sensing and recording restroom visits and water use events at high frequency allowed us to monitor water use behavior and identify water fixture malfunctions, such as undesired leaks. Results also show average water use per person, variability in water use by different fixtures (faucets versus urinals and toilets), variability in water use by fixtures compared to manufacturer specifications, gender differences in water use, and the difference in water use related to retrofit of the restrooms with high efficiency fixtures. The inexpensive metering system can help institutions remotely measure and record water use trends and behavior, identify leaks and fixture malfunctions, and schedule fixture maintenance or upgrades based on their operation, all of which can ultimately help them meet goals for sustainable water use.
Resource Level Coverage
This resource contains the final data files and code related to the restroom water use study conducted in the Business Building on Utah State University's campus. This resource is structured as follows: ----------- Code Folder ----------- This folder contains all of the R code used for the analyses that appear in the paper describing the results of this study. To execute this code, copy all of the code files to your machine and open in R. The code assumes that all of the code files and data files are located in the same directory on your machine. The following files are provided: * load_data.R - Run this script to load all of the data from the data files into a set of data frames in R for analysis * utility_functions.R - A set of utility functions used by the other scripts * Table3.R - Run this to generate the results for Table 3 in the manuscript * Table4.R - Run this to generate the results for Table 4 in the manuscript * Figure5.R - Run this to generate Figure 5. * Figure6.R - Run this to generate Figure 6. * Figure7.R - Run this to generate Figure 7. * pre_retrofit_toilet_analysis.R - An analysis of toilet flush volumes pre-retrofit. Not shown in the manuscript. * toilet_urinal_frequency_analysis.R - An analysis of the frequency of toilet use versus urinal use in the men’s restroom during the post-retrofit data collection period. NOTE: You must run the load_data.R script to read the data from the data files into R data frames prior to running any of the other scripts. The R code was developed using Version 3.3.2 of R. ----------- Data Folder ----------- This folder contains the finalized data files. To run the analyses and produce the results contained within the manuscript, copy the data files to your machine and put them in the same folder as the R code files or modify the path to the data files in the R scripts. The following files are provided: * Data_Spring2014.xlsx - All data from both restrooms for the Spring 2014 sampling period. * Data_Fall2014.xlsx - All data from both restrooms for the Fall 2014 sampling period. * Data_Spring2015.xlsx - All data from both restrooms for the Spring 2015 sampling period. Each of these files contains multiple worksheets, with each worksheet containing a time series of data for a deployment in one of the restrooms. Worksheets are prefixed with "BMB" for the men's restroom and "BWB" for women's restroom. The prefix is followed by the date range of data contained within the worksheet. Missing data are indicated as "NA".
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|Utah Water Research Laboratory|
|National Science Foundation||CAREER: Cyberinfrastructure for Intelligent Water Supply (CIWS): Shrinking Big Data for Sustainable Urban Water||1552444|
|National Science Foundation||Collaborative Research: CI-WATER, Cyberinfrastructure to Advance High Performance Water Resource Modeling||1135482|
|Utah State University Sustainability Office||Blue Goes Green Grant|
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