Author
Veith, Tameria - Tamie | |
Goslee, Sarah | |
BEEGLE, DOUG - Pennsylvania State University | |
WELD, JENNIFER - Pennsylvania State University | |
Kleinman, Peter |
Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 7/17/2017 Publication Date: 11/16/2017 Citation: Veith, T.L., Goslee, S.C., Beegle, D.B., Weld, J.L., Kleinman, P.J. 2017. Analyzing the distribution of hydrogeomorphic characteristics across Pennsylvania as a precursor to phosphorus index modifications. Journal of Environmental Quality. 46:1365-1371. doi: 10.2134/jeq2016.10.0416. DOI: https://doi.org/10.2134/jeq2016.10.0416 Interpretive Summary: Nutrient management guidelines are essential to modern watershed management strategies that seek to keep nutrients out of streams, but these guidelines may be biased by the studies and sites from which they are derived. To determine whether work to change Pennsylvania’s nutrient management guidelines was representative of agricultural conditions across the state, we analyzed a host of publically available data. This research will help to guide the development of management guidelines as well as to prioritize new studies on nutrient management in areas that are underrepresented. Technical Abstract: Phosphorus site assessment is used nationally and internationally to assess the vulnerability of agricultural fields to phosphorus (P) loss and identify “critical source areas” controlling watershed P export. Current efforts to update P site assessment tools must ensure that the tools are representative of the range of conditions to which they will be applied. We sought to identify key parameters available in public GIS data that are uniquely descriptive of critical source areas in Pennsylvania and ensure that all reasonable parameters combinations are considered in modifications of the P Index. Thus, spatial soil and topographic characteristics of Pennsylvania were compiled for all land with less than 20% organic matter and within 90 meters of the NHD streams. This data set was grouped at a 30-m resolution based on hydrogeomorphological characteristics by using k-means and classification tree statistics for variables corresponding with the P Index or with the water quality model being used in the P Index revision. Within counties, 2-5 groups adequately represented near-stream complexity, with available water capacity, soil saturation, and organic matter being the most important environmental variables. Discontinuities across soil survey boundaries made it impossible to develop clusterings at a broader spatial scale. For county-scale research and management efforts, these groupings provide a manageable approach to developing representative sites for near-stream agricultural lands. |