Characterization of subsurface phosphorus loss in artificially-drained fields on the Delmarva Peninsula
Date
2016
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Publisher
University of Delaware
Abstract
Long-term applications of broiler manure to Delmarva agricultural soils at rates that exceed crop uptake led to the buildup of phosphorus (P) in soils to concentrations that exceed agronomic optimum. This legacy soil P is at risk for losses through artificial drainage systems that are installed to allow agricultural production of soils with high water tables and drainage problems throughout the Delmarva region. Transport of P through artificial drainage systems to sensitive waterbodies like the Chesapeake Bay and Delaware Inland Bays is an important pathway for P losses from agriculture on Delmarva. However, knowledge about the mechanism and frequency of subsurface P transport events remains limited. The objectives of this study were to: 1) develop a method for using geophysics to study subsurface flowpaths in an agricultural field; 2) better understand how P interacts with subsurface hydrology, as applied at a small field site at the University of Maryland, Eastern Shore research farm; 3) determine how subsurface P loss risk is accounted for in several P indices used for artificially drained fields; and 4) determine recommended risk factors for inclusion in a future version of the Delaware Phosphorus Site Index.
Electrical Resistivity Imaging (ERI) and a bromide (Br) salt tracer were used at the University of Maryland Eastern Shore research farm to better understand subsurface water flows and potential for P loss in subsurface lateral flow. Electrical resistivity was monitored in real time during two storm events (October 2015 and February 2016) following application of a Br tracer within a trench located within the larger ERI monitoring grid (7 m x 12.5 m). The ERI visualization revealed the presence of tracer within and slightly below the trench (possible density dependent flow); however, minimal lateral movement was seen likely due to the low intensity of the storm events. Continued monitoring during heavier storm events at this site is recommended. Additionally, better corroboration of ERI data with both hydrologic and visual monitoring is critically needed.
Phosphorus indices are field-based management tools used to identify fields with a high risk of P transport due to both site hydrology and presence of P sources. The P index is also an important tool to guide mitigation of P losses by incentivizing best management practices (BMPs). Subsurface P losses are often poorly accounted for in P indices due to lack of understanding of these processes. We compared regional (Delaware, Maryland, Virginia, and North Carolina) P index approaches to address the risk of subsurface P loss in the subsurface. Five P indices were calculated for conditions based on collected deep (approximately 1 m) soil cores collected from 13 field sites throughout the Delmarva. Overall P index scores and risk ratings were compared among indices as calculated for individual core samples at each site. In addition, calculated subsurface P risk scores were compared to concentrations of water extractable and Mehlich 3 P in soil near the estimated seasonal high water table. Based on comparisons of P Index score to field scenarios, the Delaware P Site Index and updated version of the University of Maryland P Management Tool (PMT2) most accurately predicted the overall P loss risk determined for various scenarios. However, the University of Maryland P Management tools (UM-PMT and PMT2) and Virginia P Index most accurately predicted the risk for subsurface P losses (based on soil P concentrations near the seasonal high water table). We recommend that future updates to Delaware’s PSI account for risk of both leaching potential and subsurface lateral flow potential by taking into account the following factors: soil P saturation ratio, calculated runoff and percolation volume, hydrologic soil group, soil drainage class, and drainage intensity. Updated P Indices should be evaluated using measured and modeled water quality data.