|Veith, Tameria - Tamie|
|MILLER, DOUGLAS - Pennsylvania State University|
|BILLS, BRIAN - Pennsylvania State University|
|SEBRING, RYAN - Pennsylvania State University|
Submitted to: Journal of Soil and Water Conservation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/27/2015
Publication Date: 9/1/2015
Citation: Veith, T.L., Richards, J.E., Goslee, S.C., Collick, A.S., Bryant, R.B., Miller, D.A., Bills, B., Buda, A.R., Sebring, R.L., Kleinman, P.J. 2015. Navigating spatial and temporal complexity in developing a long-term land use database for an agricultural watershed. Journal of Soil and Water Conservation. 70(5):288-296. doi:10.2489/jswc.70.5.288.
Interpretive Summary: Great interest exists in the ability to mitigate water quality problems through changes in agricultural management. Long-term watershed and farm management data sets are few and far between, making them a unique resource that can serve research, management and policy arenas, but must protect the privacy of farmers and land owners without sacrificing the spatially and temporally specific nature of the data. We developed a framework for land management, water quality and other related data that is intended to expand the utility of these data sets across the research community. This framework offers a model for other database management efforts.
Technical Abstract: No comprehensive protocols exist for the collection, standardization, and storage of agronomic management information into a database that preserves privacy, maintains data uncertainty, and translates everyday decisions into quantitative values. This manuscript describes the development of a database intended to meet the agronomic and ecosystem interests of potential users from a long-term experimental watershed located in a non-karst portion of Pennsylvania, USA’s Ridge and Valley Physiographic Province. We review design concerns, inaugural data population, and initial uses of a spatial and temporally explicit land management database for an agricultural watershed of about fifteen farms and nearly 300 fields. The final databases serves as foundation for other datasets and modeling efforts supporting research aimed at helping farmers meet long-term production, land stewardship, and water quality goals.