Revised Method and Outcomes for Estimating Soil Phosphorus Losses from Agricultural Land in the Chesapeake Bay Watershed Model

Modeling of phosphorus loss from field to watershed: A review

Phosphorus (P) losses from nonpoint sources into surface water resources through surface runoff and tile drainage play a significant role in eutrophication. Accordingly, the number of studies involving the modeling of agricultural P losses, the uncertainties of such models, and the best management practices (BMPs) supported by the modeling of hypothetical P loss reduction scenarios has increased significantly around the world. Many improvements have been made to these models: separate manure P pools, variable source areas allowing the determination of critical source areas of P loss, analyses of modeling uncertainties, and understanding of legacy P. However, several elements are still missing or have yet to be sufficiently addressed: the incorporation of preferential flow into models, the modification of P sorption-desorption processes considering recent research data (e.g., pedotransfer functions for labile, active, or stable P, along with P sorption coefficients), BMP parameterization, and scale-up issues, as well as stakeholder-scientist and experimentalist-modeler interactions. The accuracy of P loss modeling can be improved by (a) incorporating dynamic P sorption-desorption processes and new P subroutines for direct P loss from manure, fertilizer, and dung, (b) modeling preferential flow, connectivity between field and adjacent water bodies, and P in-stream processes, (c) including an assessment of model uncertainty, (d) integrating field and watershed models for BMP calibration and scaling field results up to larger areas, and (e) building a holistic interaction between stakeholders, experimentalists, and modelers.

Modeling the Impacts of Manure on Phosphorus Loss in Surface Runoff and Subsurface Drainage

Simulation of phosphorus (P) transfer from manured agricultural lands to water bodies via surface runoff and subsurface drainage is potentially of great help in evaluating the risks and effects of eutrophication under a range of best management practice scenarios. However, it remains a challenge since few models are capable of providing a reasonably accurate prediction of P losses under manure treatment. The Environmental Policy Integrated Climate (EPIC) model was applied to simulate the impacts on dissolved reactive P (DRP) losses through surface runoff and subsurface drainage from a solid cattle manure-amended corn ( L.)-soybean [ (L.) Merr.] rotation on a clay loam soil (Vertisol) located in the Lake Erie region. Simulations of DRP loss in surface runoff and tile drainage were satisfactory; however, EPIC did not consider DRP loss directly from manure, weakening its accuracy in the prediction of DRP loss in surface runoff. Having previously drawn on EPIC-predicted surface runoff to initiate SurPhos (Surface Phosphorus and Runoff Model) predictions of DRP losses strictly in surface runoff, no comparison had been made of differences in manure application impacts on EPIC- or SurPhos-predicted DRP losses-accordingly, this was assessed. The SurPhos improved the estimation of DRP loss in surface runoff (Nash-Sutcliffe coefficient, 0.53), especially when large rain events occurred immediately after or within 6 wk of manure application. Generally, EPIC can capture the impacts of manure application on DRP loss in surface runoff and subsurface drainage; however, coupling of the EPIC and SurPhos models increased the accuracy of simulation of runoff DRP losses.

Mapping Crop Residue and Tillage Intensity Using WorldView-3 Satellite Shortwave Infrared Residue Indices

Crop residues serve many important functions in agricultural conservation including preserving soil moisture, building soil organic carbon, and preventing erosion. Percent crop residue cover on a field surface reflects the outcome of tillage intensity and crop management practices. Previous studies using proximal hyperspectral remote sensing have demonstrated accurate measurement of percent residue cover using residue indices that characterize cellulose and lignin absorption features found between 2100 nm and 2300 nm in the shortwave infrared (SWIR) region of the electromagnetic spectrum. The 2014 launch of the WorldView-3 (WV3) satellite has now provided a space-borne platform for the collection of narrow band SWIR reflectance imagery capable of measuring these cellulose and lignin absorption features. In this study, WorldView-3 SWIR imagery (14 May 2015) was acquired over farmland on the Eastern Shore of Chesapeake Bay (Maryland, USA), was converted to surface reflectance, and eight different SWIR reflectance indices were calculated. On-farm photographic sampling was used to measure percent residue cover at a total of 174 locations in 10 agricultural fields, ranging from plow-till to continuous no-till management, and these in situ measurements were used to develop percent residue cover prediction models from the SWIR indices using both polynomial and linear least squares regressions. Analysis was limited to agricultural fields with minimal green vegetation (Normalized Difference Vegetation Index < 0.3) due to expected interference of vegetation with the SWIR indices. In the resulting residue prediction models, spectrally narrow residue indices including the Shortwave Infrared Normalized Difference Residue Index (SINDRI) and the Lignin Cellulose Absorption Index (LCA) were determined to be more accurate than spectrally broad Landsat-compatible indices such as the Normalized Difference Tillage Index (NDTI), as determined by respective R2 values of 0.94, 0.92, and 0.84 and respective residual mean squared errors (RMSE) of 7.15, 8.40, and 12.00. Additionally, SINDRI and LCA were more resistant to interference from low levels of green vegetation. The model with the highest correlation (2nd order polynomial SINDRI, R2 = 0.94) was used to convert the SWIR imagery into a map of crop residue cover for non-vegetated agricultural fields throughout the imagery extent, describing the distribution of tillage intensity within the farm landscape. WorldView-3 satellite imagery provides spectrally narrow SWIR reflectance measurements that show utility for a robust mapping of crop residue cover.

Modeling phosphorus losses from soils amended with cattle manures and chemical fertilizers

While applied manure/fertilizer is an important source of P loss in surface runoff, few models simulate the direct transfer of phosphorus (P) from soil-surface-applied manure/fertilizer to surface runoff. The SurPhos model was tested with 2008-2010 growing season daily surface runoff data from clay loam experimental plots subject to different manure/fertilizer applications. Model performance was evaluated on the basis of the coefficient of determination (R²), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and the ratio of the root mean square error to the standard deviation of observed values (RSR). The model offered an acceptable performance in simulating soil labile P dynamics (R² = 0.75, NSE = 0.55, PBIAS = 10.43%, and RSR = 0.67) and dissolved reactive P (DRP) loss in surface runoff (R² ≥ 0.74 and NSE ≥ 0.69) for both solid and liquid cattle manure, as well as inorganic fertilizer. Simulated direct P loss in surface runoff from solid and liquid cattle manure accounted for 39% and 40% of total growing season DRP losses in surface runoff. To compensate for the unavailability of daily surface runoff observations under snow melt condition, the whole four years' (2008-2011) daily surface runoff predicted by EPIC (Environmental Policy Integrated Climate) was used as SurPhos input. The accuracy of simulated DRP loss in surface runoff under the different manure/fertilizer treatments was acceptable (R² ≥ 0.55 and NSE ≥ 0.50). For the solid cattle manure treatment, of all annual DRP losses, 19% were derived directly from the manure. Beyond offering a reliable prediction of manure/fertilizer P loss in surface runoff, SurPhos quantified different sources of DRP loss and dynamic labile P in soil, allowing a better critical assessment of different P management measures' effectiveness in mitigating DRP losses.

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.