Abstract
Volunteered Geographic Information, data contributed by community scientists, is an increasingly popular tool to collect scientific data, involve the community in scientific research, and provide information and education about a prominent issue. Johnson City, Tennnessee, USA has a long history of downtown flooding, and recent redevelopment of two land parcels has created new city parks that mitigate flooding through floodwater storage, additional channel capacity, and reduced impervious surfaces. At Founders Park, a project to collect stage data using text messages from community scientists has collected 1479 stage measurements from 597 participants from May 2017 through July 2021. Text messages were parsed to extract the stage and merged with local precipitation data to assess the stream’s response to precipitation. Of 1479 observations, 96.7% were correctly parsed. Only 3% of observations were false positives (parser extracted incorrect stage value) or false negatives (parser unable to extract correct value but usable data were reported). Less than 2% of observations were received between 11 p.m. and 7 a.m., creating an overnight data gap, and fewer than 7% of observations were made during or immediately following precipitation. Regression models for stage using antecedent precipitation explained 21.6% of the variability in stream stage. Increased participation and development of an automated system to record stage data at regular intervals will provide data to validate community observations and develop more robust rainfall–runoff models.
Highlights
Community science research relies on data collected and submitted by community volunteers and is an increasingly popular tool to collect scientific data, involve the community in scientific research, and provide information and education about a prominent issue [1,2]
In this study we describe a free automated system to collect stream stage data contributed by community scientists and match it with weather data to build a database of rainfall and stream stage
Failures consisted of false positive results where the parser reported the incorrect stage and false negatives where the parser was unable to extract the stage observation from the text message
Summary
Community science research relies on data collected and submitted by community volunteers and is an increasingly popular tool to collect scientific data, involve the community in scientific research, and provide information and education about a prominent issue [1,2]. Recent community science projects include collection of stage data [6,7,8,9], flood risk analysis [10], and capture of community perspectives of watershed issues [11], among others. Youth were tasked with documenting local watershed issues of perceived importance using Photovoice, and photos were later data-mined to distill the youth perspective [11]. Such community science research shares a common purpose: community members collaborate in scientific research to meet real-world goals that support conservation, raise environmental awareness, or inform policy decisions [5]. A more recent review examines benefits and obstacles in community science, classifying projects as related to geohazards, observation/classification, education/outreach, and other foci [12]
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