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• W2625791054 abstract "Photo courtesy of Iowa Learning Farms. Runoff of phosphorus (P) from farm fields in the U.S. is a widespread problem, contributing to eutrophication in bodies of water from the Great Lakes to the Gulf of Mexico. To reduce P runoff, farmers and land managers first need to identify where it is occurring and then implement nutrient management strategies. Tools have been developed to perform site assessments, which evaluate the risk of P loss, including the P Index, which is widely used in the U.S. An upcoming issue of the Journal of Environmental Quality will include a special section titled, “The Evolving Science of Phosphorus Site Assessment.” ASA and SSSA member Peter Kleinman, Research Leader and Soil Scientist at the USDA-ARS, acted as a guest editor for these papers, describing it as “probably the most comprehensive review in recent years of the performance of various models in predicting phosphorus loss at the field scale.” The goal of this collection of papers is to present the state of the science and take a close look at the accuracy of the tools being used for site assessment. Here, we highlight some of the topics covered in this special section, including the accuracy of processed-based models, a review of short-term management tools, and a watershed-scale study of P stratification. Although the P Index is widely used, there are limited data sets to evaluate its effectiveness. “We turned to using process-based models to estimate phosphorus loss, and then we could use the model-generated data to evaluate our phosphorus index,” explains Nathan Nelson, Associate Professor of Soil Fertility and Nutrient Management at Kansas State University. However, to use model-generated data, the researchers would first need to test the accuracy of a process-based model. Nelson, a member of the ASA and SSSA, and Claire Baffaut, a Research Hydrologist with the USDA-ARS, are the lead authors of two studies included in this special section. These papers evaluate a process-based model, specifically the Agricultural Policy Environmental eXtender, or APEX, model. The researchers developed two calibration methods for the APEX model and compared the predicted values with edge-of-field data from four sites in Missouri and Kansas. The first paper of the pair (http://bit.ly/2qALR2j) uses “best professional judgment” calibration, which does not require extensive data collection. It is instead based on knowledge of the site, including management and soil as well as an understanding of the biological processes and APEX model. The authors found that best professional judgment calibration was fairly accurate at estimating runoff, having acceptable values for two-thirds of the sites. “I was actually nicely surprised that it worked as well as it did for the runoff part,” says Baffaut, “[but] I was fairly worried about the extent to which it did not work [for] the sediment and the phosphorus.” The authors report that performance of the best professional judgment calibration was not acceptable for sediment and total P loss. Exploring the outcome, researchers determined the problem was an overestimation of sediment loss and total P loss. Total phosphorus is calculated in part from sediment loss, so this is an instance where miscalculation of one process has subsequent effects on other model output variables. Given that this best professional judgment calibration may represent how some people are applying the APEX model, the paper suggests more rigorous calibration is needed to get accurate estimates. While time-consuming to do a full calibration, Nelson hopes that “people who have done modeling work without that calibration might see this and be cautioned about that use in the future.” The second paper takes a similar approach to the first, using a regional calibration model developed from five site-specific calibrated models. “The regional calibration is a step toward creating a model that's more broadly applicable, so it can be used at multiple sites, but still has been calibrated and validated so that we can have some confidence in the results,” Nelson says. Similar to the best professional judgment, the regional calibration model appeared well calibrated for runoff but again did a poor job of estimating sediment loss. And while the estimates of sediment loss were inaccurate, the total phosphorus loss estimates were in the acceptable range. When comparing the regional calibration model to the site-specific calibration models, the authors determined the regional calibration was not capturing the mechanisms for total P loss and report that this calibration is not robust enough for widespread use. These two papers demonstrate that acceptable estimates for one variable do not mean the whole model is working well for the site. Even if it works well for some sites, Baffaut also cautions that “there will be a greater number for which it doesn't work, and there is no way to know ahead of time if it is going to work for your site or not.” In both studies, the calibration for sediment loss led to inaccuracies in model predictions. While a site-specific calibration may be able to overcome this, more calibration is not necessarily the solution. Farmers and land managers typically lack the time to collect edge-of-field data to calibrate site-specific models. They need tools that are easy to use and accurate. Having a better understanding of inaccuracies in the model may help improve these products and their ability to be accurate without a great deal of calibration. The P Index is used for long-term planning, helping to identify the maximum amount of manure that can be spread on a field or fields where manure cannot be applied. But farmers also need to make day-to day decisions that can impact nutrient management. To address this need, short-term planning tools have been developed to predict the potential for P runoff. Zachary Easton, Associate Professor of Biological Systems Engineering at Virginia Tech, and co-authors evaluated six short-term nutrient management decision support tools currently available to farmers (see http://bit.ly/2rUex6q). Easton was part of a research group funded by the USDA to develop tools to guide nutrient management on farms in Virginia and New York. “There was a recognized need [for these tools], not just at USDA and NRCS, but from a lot of producers who have come under regulatory scrutiny for water quality issues,” Easton says. The researchers evaluated tools from six states: Wisconsin, Pennsylvania, Virginia, New York, Washington, and Missouri. Some, like the tools for Pennsylvania and Virginia, are newly developed, whereas the Wisconsin tool has been available for use since 2011. And while all tools have the same goal of identifying conditions when manure should not be applied due to high risk of runoff, each is unique, taking into account the regional practices and conditions. The authors describe and compare the tools based on the forecasts utilized and outputs. For example, the simplest tool, from Missouri, is forecast rainfall based on radar while the more complex, including Wisconsin, New York, and Virginia, incorporate forecasts and hydrological models. The tools use three different types of forecasts, runoff risk (Wisconsin and Pennsylvania), saturated area extent (Virginia and New York), and precipitation risk (Washington and Missouri). For all tools included, forecasts are issued at least once a day, but runoff lead times vary from 24 to 72 hours, with some tools having lead times of 96 hours. Missouri's Design Storm Alert System. The scale at which predictions are made and used vary from region to region. For example, Easton says farmers on the East Coast “were interested in looking at field-based predictions, whereas [in] Wisconsin, one really big issue is frozen soil,” which is predicted for a broad geographic area. Like any model, the predictions are only as good as the forecast they are based on. While uncertainty may be perceived as negative, it is important to make end-users aware of how uncertain (or certain) the predicted conditions are. “Several of the tools incorporate [uncertainty] explicitly into the framework,” Easton says. This uncertainty is the result of using multiple forecasts where low uncertainty indicates high agreement across forecast predictions. Including a measure of uncertainty is especially important considering that many farmers are using these tools to mitigate the risk of a runoff event occurring. Easton is hopeful that use of these tools for making management decisions for risk mitigation will offer a level of protection for farmers. For example, if a farmer spreads manure based on a tool predicting a low chance of precipitation with high certainty, that farmer should not be penalized in the event of an unexpected thunderstorm that causes a runoff event. Part of the development of these short-term tools has involved farmer feedback. This feedback is not only useful for improving the tools but also builds trust with the end-users, which may increase the use of short-term tools by farmers. Easton points out that using short- and long-term tools together are an important part of an overall nutrient management plan. Wisconsin's Runoff Risk Advisory Forecast. Watersheds depicted in red and orange show areas of high and medium runoff risk, respectively. In the 1980s, actions were initiated to reduce agricultural runoff and pollution of Lake Erie from Ohio farmland. One major change in management was the shift to no-till and reduced-till farming to reduce particulate phosphorus loading to tributaries. This strategy was used to supplement phosphorus removal at municipal sewage treatment plants that had been initiated in the 1970s. Together, these changes seemed successful, and pollution in Lake Erie declined. Look for the Journal of Environmental Quality special section, “The Evolving Science of Phosphorus Site Assessment,” in an upcoming issue. Currently, the papers discussed here, along with others, are available in “Just Published” at https://dl.sciencesocieties.org/publications/jeq/justpublished. The National Center for Water Quality Research(NCWQR) at Heidelberg University in Ohio has been involved in water quality monitoring in the region since these changes were implemented. “What happened as we moved toward the late 1990s was that Lake Erie began to undergo more significant eutrophication again,” recalls David Baker, Director Emeritus of NCWQR and SSSA member. “At the same time, the monitoring programs were showing increases in loading of highly bioavailable dissolved phosphorus.” Researchers set out to determine the source of the dissolved P increase and report their finding in this special section (http://bit.ly/2rlkqqk). The authors had two objectives: 1) to identify if P stratification (the buildup of soil-test P in the upper soil layer) was occurring in the watershed and 2) to determine if stratification was contributing to P runoff problems. Photo courtesy of Q.M. Ketterings. To collect data from across the watershed, the researchers enlisted the help of Certified Crop Advisers (CCAs). The CCAs collected stratified soil samples, divided into either two-parts (0–5 and 5–20 cm) or four-parts (0–2.5, 2.5–5.0, 5.0–12.5, and 12.5–20 cm), alongside their agronomic soil samples (0–20 cm core). Samples from more than 1,600 fields were collected from 2008–2012 and submitted for analysis to a soil testing laboratory. Stratification was present across the watershed with soil test P levels in the top 2.5 cm of soil averaging 55% higher than levels for the entire 0- to 20-cm core. It was notable that the stratification was highly variable and did not correlate with agronomic soil tests. “I think that this paper shows that if you want to target programs to the sources of high dissolved phosphorus runoff, you need to have stratified soil sampling,” Baker says. The authors also report that fields with stratification are at higher risk for dissolved P runoff, making stratified fields the location where mitigation strategies can have the greatest impact. But, Baker says, “If you look at approaches to reducing dissolved phosphorus runoff, then a draw-down, just applying less fertilizer, is not going to be very efficient.” Draw-down is generally a slow process, and release of phosphorus from the breakdown of surficial crop residues may sustain high levels of stratification. Although the region has focused on no-till practices for many years, the most effective way to eliminate stratification is through inversion tillage. The authors report that if the approximately 30% of fields with stratification increments greater than 30 ppm were treated with a one-time inversion tillage, the runoff risk would be reduced by almost 20%. Identifying fields with stratification and working inversion tillage into management is an option. “There's very little 100% no-till in these watersheds,” Baker points out. Soy and wheat do well with no-till, but corn typically involves aggressive vertical tillage, proving an opportunity within the rotation to reduce or eliminate stratification. The authors suggest inversion tillage be followed with best management practices to reduce erosion, like planting cover crops. To reduce subsequent stratification, subsurface placement of P fertilizer is recommended, rather than broadcast application. Baker reflects on the history of the problem, saying, “[In the] 1970s, it was known that no-till could increase dissolved phosphorus runoff because of stratification… . The judgment at that time was that the benefits of a reduction in particulate phosphorus would outweigh any risk from increased dissolved phosphorus.” In any management scenario, there is always the potential for unanticipated negative effects. This study demonstrates how long-term monitoring can detect when a strategy is not working as anticipated and provide an opportunity to make changes. Inversion tillage. Screenshot of a YouTube video courtesy of the Grains Research and Development Corporation." @default.
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• W2625791054 title "The Evolving Science of Phosphorus Site Assessment" @default.
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