HR: 0800h
AN: ED11C-0627    [Abstracts]
TI: QA/QC Issues Related to Data From Volunteer Citizen Scientist Networks
AU: * Woodard, G C
EM: gwoodard@sahra.arizona.edu
AF: University of Arizona SAHRA Water Center, Marshall Bldg. 549d 845 N Park Avenue, 5th floor, Tucson, AZ 85721, United States
AU: Crimmins, M
EM: crimmins@u.arizona.edu
AF: University of Arizona, College of Agriculture, Tucson, AZ 85721, United States
AU: Vazquez, R
EM: ramon@sahra.arizona.edu
AF: University of Arizona SAHRA Water Center, Marshall Bldg. 549d 845 N Park Avenue, 5th floor, Tucson, AZ 85721, United States
AU: Rupprecht, C
EM: candicer@cals.arizona.edu
AF: University of Arizona, College of Agriculture, Tucson, AZ 85721, United States
AB: Earth science researchers increasingly are using field data gathered by volunteer citizen scientists, particularly where there is a need for dense or far-flung networks of instruments, or qualitative observations of environmental conditions (e.g., drought-caused plant stress, bird migration, spring ice break-up). Precipitation monitoring is a popular form of citizen science, with hundreds of local networks, and two regional networks - CoCoRaHS with observers in over 20 states, and RainLog, with over 1,200 observers in the Southwestern U.S. Dense networks of rain gages are especially valuable for capturing localized, convective storm events, with the data used for multiple purposes, including research, flood early warning, drought monitoring, and weather reporting. Researchers may be hesitant to use data collected by citizen scientists because of Quality Assurance/Quality Control issues associated with networks of volunteers. Gages vary in precision and accuracy, and citizen scientists have different levels of skill and experience. Backyard gages are not always ideally sited with respect to buildings and trees. Data entry issues include delays in reporting and input errors. Missing data are not only more prevalent than for official gages, the missing data are non-random. Spatial patterns of volunteers' gages reflect development patterns and socio-demographic factors, resulting in clusters and voids in gage distribution. Current interpolation methodologies do not handle these gage patterns well. RainLog is systematically quantifying these QA/QC issues, and where possible, developing procedures to mitigate them. Citizen scientists are kept informed and engaged and informed through a variety of web-based data visualization approaches. Automated monthly data reviews glean missing data and offer an opportunity to check outlier values. Various statistical approaches are used to estimate accuracy and precision for each gage. Finally, we are developing and implementing more robust interpolation algorithms.
UR: http://www.rainlog.org
DE: 0410 Biodiversity
DE: 0478 Pollution: urban, regional and global (0345, 4251)
DE: 0496 Water quality
DE: 0815 Informal education
DE: 1225 Global change from geodesy (1222, 1622, 1630, 1641, 1645, 4556)
SC: Education and Human Resources [ED]
MN: 2007 Fall Meeting