Assessing Coastal Plain Risk Indices for Subsurface Phosphorus Loss

Abstract

Phosphorus (P) Index evaluations are critical to advancing nutrient management planning in the United States. However, most assessments until now have focused on the risks of P losses in surface runoff. In artificially drained agroecosystems of the Atlantic Coastal Plain, subsurface flow is the predominant mode of P transport, but its representation in most P Indices is often inadequate. We explored methods to evaluate the subsurface P risk routines of five P Indices from Delaware, Maryland (two), Virginia, and North Carolina using available water quality and soils datasets. Relationships between subsurface P risk scores and published dissolved P loads in leachate (Delaware, Maryland, and North Carolina) and ditch drainage (Maryland) were directionally correct and often statistically significant, yet the brevity of the observation periods (weeks to several years) and the limited number of sampling locations precluded a more robust assessment of each P Index. Given the paucity of measured P loss data, we then showed that soil water extractable P concentrations at depths corresponding with the seasonal high water table (WEP WT) could serve as a realistic proxy for subsurface P losses in ditch drainage. The associations between WEP WT and subsurface P risk ratings reasonably mirrored those obtained with sparser water quality data. As such, WEP WT is seen as a valuable metric that offers interim insight into the directionality of subsurface P risk scores when water quality data are inaccessible. In the long term, improved monitoring and modeling of subsurface P losses clearly should enhance the rigor of future P Index appraisals. T he Phosphorus (P) Index is an applied site assessment tool that quantifies the risk of P loss from agriculture by accounting for the principal source and transport factors controlling P flux (Sharpley et al., 2003, 2013). Since its inception in 1993 (Lemunyon and Gilbert, 1993), the P Index concept has expanded to 48 states (Sharpley et al., 2003), with each state taking its own approach to estimating P source and transport risk according to regional differences in hydroclimate, soil properties, and agricultural management. When evaluated separately, P Indices often have produced risk scores that are consistent in direction and magnitude with P fluxes in simulated overland flow (Eghball and Gilley, 2001; DeLaune et al., 2004) and edge-of-field runoff (Harmel et al., 2005; Good et al., 2012). However, when multiple P Indices were benchmarked against common datasets, as was done for 12 southern states by Osmond et al. (2006, 2012), the results were less encouraging, with researchers reporting significantly different risk scores among P Indices for similar P source and transport conditions and differential correspondence between risk scores and P losses in runoff. As a result, there are renewed calls for multistate assessments of P Indices and their components using shared verification data-sets across a range of hydrological and management conditions (Sharpley et al., 2013). To date, most P Index assessments have relied on field measurements of P loads in surface runoff to corroborate P risk ratings (Nelson and Shober, 2012). Quantifying P loss in concentrated hydrological flows from runoff plots (McDowell and