Usability of Existing Volunteer Water Monitoring Data: What Can the Literature Tell Us?

For decades citizen science has been used in environmental monitoring, and perhaps most commonly in water quality monitoring, as a tool to supplement professional data. Hundreds of volunteer monitoring efforts have generated datasets that cover large geographic areas over multiple years, and these l...

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Bibliographic Details
Main Authors: Kelly Albus, Ruthanne Thompson, Forrest Mitchell
Format: Article
Language:English
Published: Ubiquity Press 2019-11-01
Series:Citizen Science: Theory and Practice
Subjects:
Online Access:https://theoryandpractice.citizenscienceassociation.org/articles/222
Description
Summary:For decades citizen science has been used in environmental monitoring, and perhaps most commonly in water quality monitoring, as a tool to supplement professional data. Hundreds of volunteer monitoring efforts have generated datasets that cover large geographic areas over multiple years, and these large-scale datasets have been shown to be especially valuable for monitoring changes over time. Although volunteer water monitoring programs continue to grow worldwide, research shows that many of the existing datasets are still underutilized due to concerns about the accuracy of volunteer-collected data. An increasing number of “comparison studies” have attempted to address quality concerns by comparing volunteer data to professional data to assess relative accuracy, and the majority have reported that volunteer data are of a quality comparable to professional data. Nearly all of these studies, however, focused on a small subset of volunteer program data or data collected under experimental controls, and as such the results may not be applicable to existing, large-scale datasets with unknown controls and high levels of variation. Through a comprehensive look at water quality comparison studies to date, this review reveals a need for additional studies that specifically address the quality of highly variable, large-scale volunteer datasets and ultimately serve as a framework by which decades of volunteer efforts already in existence across the country can be better utilized.
ISSN:2057-4991