Peter A. Vadas

Estimating Phosphorus Loss in Runoff from Manure and Fertilizer for a Phosphorus Loss Quantification Tool

Nonpoint-source pollution of fresh waters by P is a concern because it contributes to accelerated eutrophication. Given the state of the science concerning agricultural P transport, a simple tool to quantify annual, field-scale P loss is a realistic goal. We developed new methods to predict annual dissolved P loss in runoff from surface-applied manures and fertilizers and validated the methods with data from 21 published field studies. We incorporated these manure and fertilizer P runoff loss methods into an annual, field-scale P loss quantification tool that estimates dissolved and particulate P loss in runoff from soil, manure, fertilizer, and eroded sediment. We validated the P loss tool using independent data from 28 studies that monitored P loss in runoff from a variety of agricultural land uses for at least 1 yr. Results demonstrated (i) that our new methods to estimate P loss from surface manure and fertilizer are an improvement over methods used in existing Indexes, and (ii) that it was possible to reliably quantify annual dissolved, sediment, and total P loss in runoff using relatively simple methods and readily available inputs. Thus, a P loss quantification tool that does not require greater degrees of complexity or input data than existing P Indexes could accurately predict P loss across a variety of management and fertilization practices, soil types, climates, and geographic locations. However, estimates of runoff and erosion are still needed that are accurate to a level appropriate for the intended use of the quantification tool.

Phosphorus indices: why we need to take stock of how we are doing.

Many states have invested significant resources to identify components of their Phosphorus (P) Index that reliably estimate the relative risk of P loss and incentivize conservation management. However, differences in management recommendations and manure application guidelines for similar field conditions among state P Indices, coupled with minimal reductions in the extent of P-impaired surface waters and soil test P (STP) levels, led the U.S. Natural Resources Conservation Service (NRCS) to revise the 590 Nutrient Management Standard. In preparation for this revision, NRCS requested that a review of the scientific underpinnings and accuracy of current P Indices be undertaken. They also sought to standardize the interpretation and management implications of P Indices, including establishment of ratings above which P applications should be curtailed. Although some states have initiated STP thresholds above which no application of P is allowed, STP alone cannot define a sites risk of P loss. Phosphorus Indices are intended to account for all of the major factors leading to P loss. A rigorous evaluation of P Indices is needed to determine if they are directionally and magnitudinally correct. Although use of observed P loss data under various management scenarios is ideal, such data are spatially and temporally limited. Alternatively, the use of a locally validated water quality model that has been shown to provide accurate estimates of P loss may be the most expedient option to conduct Index assessments in the short time required by the newly revised 590 Standard.

Simulating soil phosphorus dynamics for a phosphorus loss quantification tool.

Pollution of fresh waters by agricultural phosphorus (P) is a water quality concern. Because soils can contribute significantly to P loss in runoff, it is important to assess how management affects soil P status over time, which is often done with models. Our objective was to describe and validate soil P dynamics in the Annual P Loss Estimator (APLE) model. APLE is a user-friendly spreadsheet model that simulates P loss in runoff and soil P dynamics over 10 yr for a given set of runoff, erosion, and management conditions. For soil P dynamics, APLE simulates two layers in the topsoil, each with three inorganic P pools and one organic P pool. It simulates P additions to soil from manure and fertilizer, distribution among pools, mixing between layers due to tillage and bioturbation, leaching between and out of layers, crop P removal, and loss by surface runoff and erosion. We used soil P data from 25 published studies to validate APLEs soil P processes. Our results show that APLE reliably simulated soil P dynamics for a wide range of soil properties, soil depths, P application sources and rates, durations, soil P contents, and management practices. We validated APLE specifically for situations where soil P was increasing from excessive P inputs, where soil P was decreasing due to greater outputs than inputs, and where soil P stratification occurred in no-till and pasture soils. Successful simulations demonstrate APLEs potential to be applied to major management scenarios related to soil P loss in runoff and erosion.

Simulating management effects on phosphorus loss from farming systems

A process-level soil phosphorus (P) model including surface and subsurface components was incorporated into the Integrated Farm System Model (IFSM). Model evaluation indicated that sediment losses were adequately estimated compared to observed data for a corn production system in Texas. In a further evaluation, sediment losses simulated for a wide range in cropping systems and tillage practices were similar to those predicted by the current state-of-the art erosion estimation model (WEPP). Total P losses were accurately predicted when manure P was applied at suitable rates of less than 250 kg P ha-1, but at higher application rates overestimation of P loss was found. Compared to observed data, soluble P loss was underestimated and sediment P loss was overestimated, but this was primarily due to a difference in the differentiation between soluble and sediment P between the modeling and experimental studies. To illustrate the use of the model, IFSM simulations were performed to evaluate the effects of manure handling and tillage systems on P loss from farms in Pennsylvania. For a 100-cow dairy farm, a manure handling strategy that used a 6-month storage and application by injection decreased total P loss by 19% compared to daily surface application, but annual farm net return was decreased by

Testing the Wisconsin Phosphorus Index with Year-Round, Field-Scale Runoff Monitoring

57/cow. Compared to conventional tillage with a moldboard plow, use of conservation tillage and no-till systems reduced total P loss by 46% and 57%, respectively, with small increases in farm profitability. Reduced tillage increased soluble P loss, suggesting that conservation and no-till systems should be combined with practices such as manure injection to reduce all forms of P loss. The enhanced IFSM containing the soil P model provides a tool for whole-farm analysis of management effects on P loss along with other environmental and economic considerations.

Using a Phosphorus Loss Model to Evaluate and Improve Phosphorus Indices

The Wisconsin Phosphorus Index (WPI) is one of several P indices in the United States that use equations to describe actual P loss processes. Although for nutrient management planning the WPI is reported as a dimensionless whole number, it is calculated as average annual dissolved P (DP) and particulate P (PP) mass delivered per unit area. The WPI calculations use soil P concentration, applied manure and fertilizer P, and estimates of average annual erosion and average annual runoff. We compared WPI estimated P losses to annual P loads measured in surface runoff from 86 field-years on crop fields and pastures. As the erosion and runoff generated by the weather in the monitoring years varied substantially from the average annual estimates used in the WPI, the WPI and measured loads were not well correlated. However, when measured runoff and erosion were used in the WPI field loss calculations, the WPI accurately estimated annual total P loads with a Nash-Sutcliffe Model Efficiency (NSE) of 0.87. The DP loss estimates were not as close to measured values (NSE = 0.40) as the PP loss estimates (NSE = 0.89). Some errors in estimating DP losses may be unavoidable due to uncertainties in estimating on-farm manure P application rates. The WPI is sensitive to field management that affects its erosion and runoff estimates. Provided that the WPI methods for estimating average annual erosion and runoff are accurately reflecting the effects of management, the WPI is an accurate field-level assessment tool for managing runoff P losses.

Sensitivity and uncertainty analysis for the annual phosphorus loss estimator model.

In most states, the phosphorus (P) index (PI) is the adopted strategy for assessing a fields vulnerability to P loss; however, many state PIs have not been rigorously evaluated against measured P loss data to determine how well the PI assigns P loss risk-a major reason being the lack of field data available for such an analysis. Given the lack of P loss data available for PI evaluation, our goal was to demonstrate how a P loss model can be used to evaluate and revise a PI using the Pennsylvania (PA) PI as an example. Our first objective was to compare two different formulations-multiplicative and component-for calculating a PI. Our second objective was to evaluate whether output from a P loss model can be used to improve PI weighting by calculating weights for modified versions of the PA PI from model-generated P loss data. Our results indicate that several potential limitations exist with the original multiplicative index formulation and that a component formulation is more consistent with how P loss is calculated with P loss models and generally provides more accurate estimates of P loss. Moreover, using the PI weights calculated from the model-generated data noticeably improved the correlation between PI values and a large and diverse measured P loss data set. The approach we use here can be used with any P loss model and PI and thus can serve as a guide to assist states in evaluating and modifying their PI.

Watershed-level comparison of predictability and sensitivity of two phosphorus models.

Models are often used to predict phosphorus (P) loss from agricultural fields. Although it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study we assessed the effect of model input error on predictions of annual P loss by the Annual P Loss Estimator (APLE) model. Our objectives were (i) to conduct a sensitivity analyses for all APLE input variables to determine which variables the model is most sensitive to, (ii) to determine whether the relatively easy-to-implement first-order approximation (FOA) method provides accurate estimates of model prediction uncertainties by comparing results with the more accurate Monte Carlo simulation (MCS) method, and (iii) to evaluate the performance of the APLE model against measured P loss data when uncertainties in model predictions and measured data are included. Our results showed that for low to moderate uncertainties in APLE input variables, the FOA method yields reasonable estimates of model prediction uncertainties, although for cases where manure solid content is between 14 and 17%, the FOA method may not be as accurate as the MCS method due to a discontinuity in the manure P loss component of APLE at a manure solid content of 15%. The estimated uncertainties in APLE predictions based on assumed errors in the input variables ranged from ±2 to 64% of the predicted value. Results from this study highlight the importance of including reasonable estimates of model uncertainty when using models to predict P loss.

Quantifying the Impact of Seasonal and Short-term Manure Application Decisions on Phosphorus Loss in Surface Runoff

Buildup of phosphorus (P) in agricultural soils and transport of P to nearby surface waters due to excessive, long-term application of poultry litter is an environmental concern in many poultry-producing states. Watershed models are often used to quantify soil and water quality impacts of poultry litter applications. However, depending on how P transport is simulated in watershed models, the anticipated impact could be quite different. The objective of this study was to determine the predictability and sensitivity of the Soil and Water Assessment Tool (SWAT) P model and a newly developed, state-of-the-art manure P model called SurPhos in a poultry litter-applied pasture watershed. A small, predominantly agricultural watershed in Randolph County, Alabama was used for this study. The SWAT model, calibrated for surface runoff and total stream flows (Nash-Sutcliffe coefficient of 0.70 for both), was used to provide runoff inputs to the SurPhos model. Total dissolved P (TDP) exports simulated by the SWAT P and SurPhos models from the hay hydrological response units of the watershed were compared for different poultry litter application rates and different initial soil Solution P levels. Both models showed sensitivity to poultry litter application rates, with SWAT simulating linear and SurPhos simulating nonlinear increases in TDP exports with increase in poultry litter application rates. SWAT showed greater sensitivity to initial soil Solution P levels, which can lead to overestimation of TDP exports, especially at low poultry litter application rates. As opposed to the SurPhos model simulations and contrary to recent studies, SWAT simulated excessive accumulation of Solution P in the top 10 mm of soil. Because SurPhos appears to simulate P transport and build-up processes from manure-applied areas more accurately, this study suggests that SWAT be replaced by SurPhos to more accurately determine watershed-level effectiveness of P management measures.

Use of Annual Phosphorus Loss Estimator (APLE) Model to Evaluate a Phosphorus Index

Agricultural phosphorus (P) management is a research and policy issue due to P loss from fields and water quality degradation. Better information is needed on the risk of P loss from dairy manure applied in winter or when runoff is imminent. We used the SurPhos computer model and 108 site-years of weather and runoff data to assess the impact of these two practices on dissolved P loss. Model results showed that winter manure application can increase P loss by 2.5 to 3.6 times compared with non-winter applications, with the amount increasing as the average runoff from a field increases. Increased P loss is true for manure applied any time from late November through early March, with a maximum P loss from application in late January and early February. Shifting manure application to fields with less runoff can reduce P loss by 3.4 to 7.5 times. Delaying manure application when runoff is imminent can reduce P loss any time of the year, and sometimes quite significantly, but the number of times that application delays will reduce P loss is limited to only 3 to 9% of possible spreading days, and average P loss may be reduced by only 15% for winter-applied manure and 6% for non-winter-applied manure. Overall, long-term strategies of shifting manure applications to low runoff seasons and fields can potentially reduce dissolved P loss in runoff much more compared with near-term, tactical application decisions of avoiding manure application when runoff is imminent.