Trends, challenges, and responses of a 20-year, volunteer water monitoring program in Alabama

Deutsch, William; Ruiz-Córdova, Sergio S.

doi:10.5751/es-07578-200314

Cited by 32 publications

(32 citation statements)

References 11 publications

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“…Not all communities will have access to this social capital -a further limitation to the broader social inclusiveness potential of VGI. In addition to knowledge and technological skills, responsibility for VGI project and data maintenance also requires considerable time and resources, which may become burdensome leading to volunteer fatigue (Deutsch and Ruiz-Córdova, 2015), thus reducing community connectedness and disaster resilience.…”

Section: Responsibility For Community-led Initiativesmentioning

confidence: 99%

“…These include undervaluing of community input, regularity barriers, unpredictability associated with public activities, lack of effective administrative structures, and lack of genuine community participation (Corbett and Keller, 2005;Brown, 2012). Further research is needed on the social learning value of community-led VGI initiatives, and community preparedness efforts will benefit from dissemination of positive outcome stories, a strategy known to aid in reducing barriers to participatory approaches such as volunteer dropout (Deutsch and Ruiz-Córdova, 2015).…”

Section: Responsibility For Community-led Initiativesmentioning

confidence: 99%

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The Good, the Bad, and the Uncertain: Contributions of Volunteered Geographic Information to Community Disaster Resilience

et al. 2018

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The adoption of location-based information sharing technologies, and the emergence of volunteered geographic information (VGI), has seen changes to community involvement in disaster management. The concept of resilience, and recognition of the capacity for renewal, reorganization , and societal development, has gained currency in disaster management. However, the opportunities presented by spatially referenced data for sourcing contextual information for understanding processes of socialecological resilience and fostering local inclusion has not been examined. We examine how web 2.0 platforms, including VGI and social media, can support resilience building, and critically evaluate how these technologies potentially undermine resilience. We concentrate our analysis on factors deemed important for community disaster resilience through review of recent literature, policy documents, and author experience. Establishing which elements of VGI in disaster management should be emphasized, such as increased flexibility or individual empowerment, and which require careful management, such as compromised privacy or data quality, will enable VGI to become less opportunistic, data-centric, disruptive, and exclusionary, and allow for more reliable, community-centric, complementary, and socially inclusive practices. Incorporating awareness and training on collaborative geoweb technologies into disaster preparedness programs will equip individuals to make informed judgments on VGI content and reduce unintended consequences of social media initiatives.

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Section: Responsibility For Community-led Initiativesmentioning

confidence: 99%

Section: Responsibility For Community-led Initiativesmentioning

confidence: 99%

The Good, the Bad, and the Uncertain: Contributions of Volunteered Geographic Information to Community Disaster Resilience

et al. 2018

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“…The selection of volunteers is an important and quite sensitive task [23][24][25]. In our study we recruited local governmental and administrative staff without a background in water quality monitoring, but who are working in the regional offices of the DWIR.…”

Section: Volunteers Recruitmentmentioning

confidence: 99%

A Low-Cost Water Quality Monitoring System for the Ayeyarwady River in Myanmar Using a Participatory Approach

Win

Bogaard

Giesen

2019

Water

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Newly developed mobile phone applications in combination with citizen science are used in different fields of research, such as public health monitoring, environmental monitoring, precipitation monitoring, noise pollution measurement and mapping, earth observation. In this paper, we present a low-cost water quality mobile phone measurement technique combined with sensor and test strips, and reported the weekly-collected data of three years of the Ayeyarwady River system by volunteers at seven locations and compared these results with the measurements collected by the lab technicians. We assessed the quality of the collected data and their reliability based on several indicators, such as data accuracy, consistency, and completeness. In this study, six local governmental staffs and one middle school teacher collected baseline water quality data with high temporal and spatial resolution. The quality of the data collected by volunteers was comparable to the data of the experienced lab technicians for sensor-based measurement of electrical conductivity and transparency. However, the lower accuracy (higher uncertainty range) of the indicator strips made them less useful in the Ayeyarwady with its relatively small water quality variations. We showed that participatory water quality monitoring in Myanmar can be a serious alternative for a more classical water sampling and lab analysis-based monitoring network, particularly as it results in much higher spatial and temporal resolution of water quality information against the very modest investment and running costs. This approach can help solving the invisible water crisis of unknown water quality (changes) in river and lake systems all over the world.

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“…TST maintains a Quality Assurance Project Plan (QAPP) that is reviewed regularly to adhere to current national standards for data collection and standardization [24]. The Texas program with professional oversight and quality assurance protocol is similar to those in other states, such as Colorado River Watch Network, Missouri Stream Team, Georgia Adopt-a-Stream, the Alabama Water Watch, and IOWATER [1,21,25,11]. According to a recent survey by Stepenuck and Genskow [26] there are 345 such volunteer monitoring programs in 47 states, with each state having between one and 30 volunteer programs nested within.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of long-term volunteer water monitoring data: A multiscale analysis from a statewide citizen science program

et al. 2020

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An increasing number of citizen science water monitoring programs is continuously collecting water quality data on streams throughout the United States. Operating under quality assurance protocols, this type of monitoring data can be extremely valuable for scientists and professional agencies, but in some cases has been of limited use due to concerns about the accuracy of data collected by volunteers. Although a growing body of studies attempts to address accuracy concerns by comparing volunteer data to professional data, rarely has this been conducted with large-scale datasets generated by citizen scientists. This study assesses the relative accuracy of volunteer water quality data collected by the Texas Stream Team (TST) citizen science program from 1992-2016 across the State of Texas by comparing it to professional data from corresponding stations during the same time period. Use of existing data meant that sampling times and protocols were not controlled for, thus professional and volunteer comparisons were refined to samples collected at stations within 60 meters of one another and during the same year. Results from the statewide TST dataset include 82 separate station/year ANOVAs and demonstrate that large-scale, existing volunteer and professional data with unpaired samples can show agreement of~80% for all analyzed parameters (DO = 77%, pH = 79%, conductivity = 85%). In addition, to assess whether limiting variation within the source datasets increased the level of agreement between volunteers and professionals, data were analyzed at a local scale. Data from a single partner city, with increased controls on sampling times and locations and correction of a systematic bias in DO, confirmed this by showing an even greater agreement of 91% overall from 2009-2017 (DO = 91%, pH = 83%, conductivity = 100%). An experimental sampling dataset was analyzed and yielded similar results, indicating that existing datasets can be as accurate as experimental datasets designed with researcher supervision. Our findings underscore the reliability of large-scale citizen science monitoring datasets already in existence, and their potential value to scientific research and water management programs.

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Trends, challenges, and responses of a 20-year, volunteer water monitoring program in Alabama

Cited by 32 publications

References 11 publications

The Good, the Bad, and the Uncertain: Contributions of Volunteered Geographic Information to Community Disaster Resilience

The Good, the Bad, and the Uncertain: Contributions of Volunteered Geographic Information to Community Disaster Resilience

A Low-Cost Water Quality Monitoring System for the Ayeyarwady River in Myanmar Using a Participatory Approach

Accuracy of long-term volunteer water monitoring data: A multiscale analysis from a statewide citizen science program

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