Multisite Evaluation of APEX for Water Quality: II. Regional Parameterization

Crop growth, hydrology, and water quality dynamics in agricultural fields across the Western Lake Erie Basin: Multi-site verification of the Nutrient Tracking Tool (NTT)

Agricultural field- and watershed-scale water quality models are used to assess the potential impact of management practices to reduce nutrient and sediment exports. However, observed data are often not available to calibrate and verify these models. Three years of data from the U.S. Department of Agriculture-Agricultural Research Service's 12 paired edge-of-field sites in northwest Ohio were used to calibrate and validate the Nutrient Tracking Tool. The goal of this study was to identify a single optimal parameter set for the Nutrient Tracking Tool in simulating annual crop yields, water balance, and nutrient loads across the Western Lake Erie Basin. A multi-site and multi-objective auto-calibration subroutine was developed in R to perform model calibration across the edge-of-field sites. The statistical metrics and evaluation criteria used in comparing the simulated results with the observed data were: Cohen's D Effect Size (Cohen's D < 0.20) and Percent bias (PBIAS ± 10% for crop yields, subsurface (tile) discharge, and surface runoff and ± 25% for dissolved reactive phosphorus (DRP) and nitrate‑nitrogen (nitrate-N) in tile discharge, and DRP, particulate phosphorus, and nitrate-N in surface runoff). In both calibration and validation, the Cohen's D and PBIAS for annual crop yields, tile discharge, surface runoff, DRP, particulate P, and nitrate-N showed that the average simulated results were similar to the average observed values for each variable. The calibrated model simulated well the annual averages of crop yields, flows, and nutrient losses across fields. The tile drainage and phosphorus transport subroutines in the Nutrient Tracking Tool should be further improved to better simulate the dynamics of discharge and phosphorus transport through subsurface drainage. Stakeholders can use the verified model to evaluate the effectiveness of conservation practices in improving the water quality across the Western Lake Erie Basin.

Development of PLEAD: A Database Containing Event-based Runoff Phosphorus Loadings from Agricultural Fields

Computer models are commonly used 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 United States. 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, >1800 individual runoff events-ranging in duration from 0.4 to 97 h-have been included in the database. Event runoff P losses ranged from <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. The PLEAD database is available at .

Multisite Evaluation of APEX for Water Quality: I. Best Professional Judgment Parameterization

The Agricultural Policy Environmental eXtender (APEX) model is capable of estimating edge-of-field water, nutrient, and sediment transport and is used to assess the environmental impacts of management practices. The current practice is to fully calibrate the model for each site simulation, a task that requires resources and data not always available. The objective of this study was to compare model performance for flow, sediment, and phosphorus transport under two parameterization schemes: a best professional judgment (BPJ) parameterization based on readily available data and a fully calibrated parameterization based on site-specific soil, weather, event flow, and water quality data. The analysis was conducted using 12 datasets at four locations representing poorly drained soils and row-crop production under different tillage systems. Model performance was based on the Nash-Sutcliffe efficiency (NSE), the coefficient of determination () and the regression slope between simulated and measured annualized loads across all site years. Although the BPJ model performance for flow was acceptable (NSE = 0.7) at the annual time step, calibration improved it (NSE = 0.9). Acceptable simulation of sediment and total phosphorus transport (NSE = 0.5 and 0.9, respectively) was obtained only after full calibration at each site. Given the unacceptable performance of the BPJ approach, uncalibrated use of APEX for planning or management purposes may be misleading. Model calibration with water quality data prior to using APEX for simulating sediment and total phosphorus loss is essential.

Evaluation of Phosphorus Site Assessment Tools: Lessons from the USA

Critical source area identification through phosphorus (P) site assessment is a fundamental part of modern nutrient management planning in the United States, yet there has been only sparse testing of the many versions of the P Index that now exist. Each P site assessment tool was developed to be applicable across a range of field conditions found in a given geographic area, making evaluation extremely difficult. In general, evaluation with in-field monitoring data has been limited, focusing primarily on corroborating manure and fertilizer "source" factors. Thus, a multiregional effort (Chesapeake Bay, Heartland, and Southern States) was undertaken to evaluate P Indices using a combination of limited field data, as well as output from simulation models (i.e., Agricultural Policy Environmental eXtender, Annual P Loss Estimator, Soil and Water Assessment Tool [SWAT], and Texas Best Management Practice Evaluation Tool [TBET]) to compare against P Index ratings. These comparisons show promise for advancing the weighting and formulation of qualitative P Index components but require careful vetting of the simulation models. Differences among regional conclusions highlight model strengths and weaknesses. For example, the Southern States region found that, although models could simulate the effects of nutrient management on P runoff, they often more accurately predicted hydrology than total P loads. Furthermore, SWAT and TBET overpredicted particulate P and underpredicted dissolved P, resulting in correct total P predictions but for the wrong reasons. Experience in the United States supports expanded regional approaches to P site assessment, assuming closely coordinated efforts that engage science, policy, and implementation communities, but limited scientific validity exists for uniform national P site assessment tools at the present time.

The Promise, Practice, and State of Planning Tools to Assess Site Vulnerability to Runoff Phosphorus Loss

Over the past 20 yr, there has been a proliferation of phosphorus (P) site assessment tools for nutrient management planning, particularly in the United States. The 19 papers that make up this special section on P site assessment include decision support tools ranging from the P Index to fate-and-transport models to weather-forecast-based risk calculators. All require objective evaluation to ensure that they are effective in achieving intended benefits to protecting water quality. In the United States, efforts have been underway to compare, evaluate, and advance an array of P site assessment tools. Efforts to corroborate their performance using water quality monitoring data confirms previously documented discrepancies between different P site assessment tools but also highlights a surprisingly strong performance of many versions of the P Index as a predictor of water quality. At the same time, fate-and-transport models, often considered to be superior in their prediction of hydrology and water quality due to their complexity, reveal limitations when applied to site assessment. Indeed, one consistent theme from recent experience is the need to calibrate highly parameterized models. As P site assessment evolves, so too do routines representing important aspects of P cycling and transport. New classes of P site assessment tools are an opportunity to move P site assessment from general, strategic goals to web-based tools supporting daily, operational decisions.

Evaluation of the TBET Model for Potential Improvement of Southern P Indices

Due to a shortage of available phosphorus (P)-loss datasets, simulated data from an accurate quantitative P transport model could be used to evaluate a P Index. The objective of this study was to compare predictions from the Texas Best Management Practice Evaluation Tool (TBET) against measured P-loss data to determine whether the model could be used to improve P Indices in the southern region. Measured P-loss data from field-scale study sites in Arkansas, Georgia, and North Carolina were used to assess the accuracy of TBET for predicting field-scale loss of P. We found that event-based predictions using an uncalibrated model were generally poor. Calibration improved runoff predictions and produced scatterplot regression lines that had slopes near one and intercepts near zero. However, TBET predictions of runoff met the performance criteria (Nash-Sutcliffe efficiency ≥ 0.3, percent bias ≤ 35%, and mean absolute error ≤ 10 mm) in only one out of six comparisons: North Carolina during calibration. Sediment predictions were imprecise, and dissolved P predictions underestimated measured losses. In North Carolina, total P-loss predictions were reasonably accurate because TBET did a slightly better job of predicting sediment losses from cultivated land. In Arkansas and Georgia, where the experimental sites were in forage production, the underprediction of dissolved P led directly to the underpredictions of total P. We conclude that TBET cannot be used to improve southern P Indices, but a curve number approach could be incorporated into P Indices to improve runoff predictions.