Development of PLEAD: a database containing event-based runoff phosphorus loadings from agricultural fields

Authors: Bolster, Carl; Baffaut, Claire; NELSON, NATHAN - Kansas State University; OSMOND, DEANNA - North Carolina State University; CABRERA, MIGUEL - University Of Georgia; RAMIREZ-AVILA, JOHN - Mississippi State University; SHARPLEY, ANDREW - University Of Arkansas; Veith, Tameria - Tamie; MCFARLAND, ANNE - Texas Institute For Applied Environmental Research; SENAVIRATNE, ANOMAA - Consultant; PIERZYNSKI, GARY - Kansas State University; UDAWATTA, RANJITH - University Of Missouri

Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/27/2018
Publication Date: 2/14/2019
Publication URL: https://handle.nal.usda.gov/10113/6471177
Citation: Bolster, C.H., Baffaut, C., Nelson, N.O., Osmond, D.L., Cabrera, M.L., Ramirez-Avila, J.J., Sharpley, A.N., Veith, T.L., McFarland, A.M., Senaviratne, A.G., Pierzynski, G.M., Udawatta, R.P. 2019. Development of PLEAD: a database containing event-based runoff phosphorus loadings from agricultural fields. Journal of Environmental Quality. 48:510-517. https://doi.org/10.2134/jeq2018.09.0337.
DOI: https://doi.org/10.2134/jeq2018.09.0337

Interpretive Summary: Computer simulation models are often employed to help land owners and planners evaluate how different management practices may affect risk of P loss in runoff from their fields. For P loss models to be useful tools, they must accurately predict, P loss under a wide range of climatic, physiographic, and land management conditions. One of the significant challenges to testing and evaluating models is the limited amount of data available for such analysis. Increasing awareness of the lack of available data for model evaluation has prompted making such data available to the public. In this study we compiled a diverse set of field-scale P loss data (published and unpublished) covering a wide range of land management, physiographic, and climatic conditions. The database includes dissolved and/or total P loss runoff loadings, field characteristics, and land use/management practices from agricultural fields collected at various research sites located throughout the Heartland and Southern regions of the US. In total, over 1800 individual runoff events are included in the database. The data contained in this database have been used by multiple research groups in multiple research studies to address important modeling questions relevant to P management planning. We foresee these data being used by other researchers to address similar questions with different models.

Technical Abstract: Computer models are commonly employed for predicting risks of runoff P loss from agricultural fields by enabling simulation of various management practices and climatic scenarios. For P loss models to be useful tools, however, they must accurately predict P loss for a wide range of climatic, physiographic, and land management conditions. A complicating factor in developing and evaluating P loss models is the relative scarcity of available measured field data that adequately capture P losses before and after implementing management practices in a variety of physiographic settings. Here, we describe the development of the P Loss in runoff Events from Agricultural fields Database (PLEAD) – a compilation of event-based, field-scale dissolved and/or total P loss runoff loadings from agricultural fields collected at various research sites located in the US Heartland and Southern US. The database also includes runoff and erosion rates; soil test P; tillage practices; planting and harvesting rates and practices; fertilizer application rate, method, and timing; manure application rate, method, and timing; and livestock grazing density and timing. In total, over 1800 individual runoff events – ranging in duration from 0.4 to 97 hr – have been included in the database. Event runoff P losses ranged from less than 0.05 to 1.3 and 3.0 kg P/ha for dissolved and total P, respectively. The data contained in this database have been used in multiple research studies to address important modeling questions relevant to P management planning. We provide these data to encourage additional studies by other researchers.