UMich Data learning for better drinking water in small utilities

Loading...
Thumbnail Image

Keywords

public interest technology, PIT, community technology, technology community, data analytics, public utilities, water, climate, environment, analytics, access & digital divide, Data Literacy, Civic Technology, Technology civic, health IT, Technology health, Technology public, Educational Opportunities

Project

Authors

Hardin, Rebecca

Date Submitted

8/30/23

Material Type

Online Course Module

Secondary Material Type

Data sets

Institution

University of Michigan

Industry Partner

License

CC BY-NC-SA

Funding Source

Network Challenge Grant TAACCCT Round 3

Additional Public Access

https://midas.umich.edu/2022-d4pg/research-talks/
https://conference.oeglobal.org/2023/about-oeglobal-conference-2023/
https://lookerstudio.google.com/reporting/a9815da8-0266-4c34-b2a3-c6aabb8e8376/page/p_42a4vutuuc
https://seas.umich.edu/news/big-tech-faces-scrutiny-24-universities-get-36mmajor- foundations-fuel-inclusive-public
https://youtu.be/BBGJEBSioSI
https://dx.doi.org/10.7302/7422

Abstract

The University of Michigan developed a master training module with three different interactive data-rich learning exercises based on actual drinking water quality monitoring and management practices from the Ann Arbor system. The pilot module will focus on distribution system flushing programs, which serve as i) one of the few ways utilities can actually impact water quality after it leaves the treatment plant, ii) a low-barrier entry point for developing industry-applied data-science competencies and innovation, iii) a nexus between what the drinking water consumer can perceive about their water quality and what other imperceptible water quality parameters the utility manages. A series of nested training modules will be developed from the research findings of Doctoral Candidate, Matthew Vedrin, on the City of Ann Arbor’s flushing program. The modules will focus on 1) the short and long-term effectiveness of the flushing program to achieve the targeted water quality improvements, 2) monitoring drinking water quality in the distribution system and identifying important trends, and 3) using water quality data from the flushing program to make evidence-based changes to the flushing program and other distribution system water quality management practices.

Industry (NAISC)

Public Interest Technology -- Data -- Algorithms

Occupation (SOC)

Computer and Mathematical Occupations -- Operations Research Analysts (15-2031)

Instructional Program (CIP)

Natural Resources and Conservation (03)

Credit Type

Credential Type

Bachelors Degree

Educational Level

2nd Year Community College or equivalent
Upper division of Bachelors degree or equivalent

Skill Level

Intermediate Level

Quality Assurance Organization