1a. Objectives (from AD-416):
1: Develop process-level models to predict management effects on nutrient losses and gaseous emissions from farms. 1.A. Measure and model the crop production and environmental impacts of using new fertilizer technology. 1.B. Develop mechanistic relationships for the partitioning and transfer of volatile organic compounds from silage as affected by silage characteristics, management practices, and the environment. 1.C. Refine and evaluate process-level relationships for simulating ammonia, hydrogen sulfide, and greenhouse gas emissions from farms as influenced by animal, feed, and manure management. 2: Measure and model carbon sequestration potential of farming systems as a means of mitigating the impacts of agriculture on climate. 2.A. Measure the effect of enhanced nutrient availability on the carbon sequestration potential of permanent pastures. 2.B. Develop a sub-model for IFSM that represents belowground partitioning of assimilated carbon, soil respiration, and plant responses to current and elevated carbon dioxide levels. 2.C. Estimate carbon-sequestration potential of humid-temperate farm production systems using remote-sensing and associated models. 3: Refine and apply farm-scale models and analyze watershed data for integrated evaluations of management effects on nutrient losses, gaseous emissions, and the interacting effects on farm performance and profit. 3.A. Develop, evaluate, and release a Dairy Facility Gas Emission Model (DairyGEM) that expands the current DairyGHG model to include ammonia, hydrogen sulfide, and VOC emission predictions in addition to greenhouse gas emissions from dairy farms. 3.B. In support of the Conservation Effects Assessment Project, develop and apply methods for evaluating predictive uncertainty of individual and combined farm management practices. 3.C. In support of the Conservation Effects Assessment Project, publish a historical database collected from our Mahantango Creek experimental watershed to improve access, proper use, and long-term management of the data. 3.D. In support of collaborating projects working on air emissions, carbon sequestration, nutrient management, and bioenergy crop production, expand and use IFSM to evaluate the performance, environmental impact, and profitability of farming systems under historical and projected future climate scenarios.
1b. Approach (from AD-416):
Livestock operations can have a number of adverse impacts on the environment including nutrient leaching to ground water, nutrient runoff in surface water, emission of hazardous compounds to the atmosphere, and increased greenhouse gas emissions. These potential impacts are interrelated, so changes to reduce one environmental problem may increase another. A proper assessment of management changes and mitigation technologies requires a comprehensive approach that integrates all important environmental factors and their interactions along with effects on farm performance and profit. Process-level simulation, evaluated with experimental measurements, will be used to assess the environmental and economic implications of production strategies. This work will focus on further development, evaluation, and application of the Integrated Farm System Model and related software tools. Further development will improve the prediction of ammonia emission, add a component on hydrogen sulfide emission, and develop a component for predicting the emission of volatile organic compounds. An enhanced carbon sequestration component will model belowground plant processes, soil respiration, and crop responses to elevated carbon dioxide. Field and laboratory experimental measurements will help determine model parameters and provide data for model evaluation. The comprehensive models developed will be used to evaluate the effects of alternative technologies, management strategies, and climate on farm performance, environmental impact, and economics. The uncertainty of these complex models will be quantified through multiple simulations of given management practices across the ranges of relevant parameter inputs. The information and software produced will help direct producers and their consultants toward more environmentally and economically sustainable production systems.
3. Progress Report:
Under objective 1A of the project plan, a second year of field evaluations of alternative nitrogen fertilizers were completed. Rainfall was very low during the month following fertilizer application, which led to low nitrous oxide emissions. Little difference in nitrous oxide emissions, mid-season soil nitrogen levels, or grain yield was seen among fertilizer treatments. Under objective 1B, initial models were developed and refined that predict VOC emissions from silage and manure sources on farms. Work continues on evaluating and refining VOC emission predictions through comparisons to farm measured emission data. Under objective 1C, process-based models that predict ammonia and hydrogen sulfide emissions from manure were evaluated by simulating the farm conditions of published studies and comparing predicted and measured data. Seasonal and annual emissions of these compounds were properly predicted from all farm sources, and predicted emissions responded appropriately to the effects of temperature, protein in animal diets, and manure handling practices. Under objective 2A, the eighth year of eddy covariance CO2 flux data were collected from two cool-season pasture sites near State College, PA where one site received substantially greater nitrogen fertilization. The additional N led to greater photosynthesis but also greater ecosystem respiration so that net ecosystem exchange was the same as that of the low fertility site. Under objective 3C, critical source areas for nitrogen and phosphorus loss in the Mahantango watershed were identified using the Soil and Water Assessment Tool (SWAT) and several best management practices were optimized for cost-effective placement. Optimization of surface runoff suggested the need to focus on controlling sediment-bound nutrients because the majority of soluble nitrogen in this watershed is leached into the deep aquifer. Under objective 3D, multiple management strategies were defined and evaluated for reducing nutrient losses on three major farm types of southeastern PA: crop, modern dairy, and Plain Sect Amish dairy. Through simulation with the Integrated Farm System Model (IFSM), relative impacts of management practices by farm type were quantified with estimates of resulting improvements in air and water quality in the Chesapeake Bay Basin. Through collaboration with the Pennsylvania Centre for Dairy Excellence (Harrisburg, PA) farm management cost-effectiveness was evaluated for 30 surveyed dairies in five counties of southeastern PA. Survey responses were compiled into four groupings of similar management types, and representative farms were modeled with IFSM to determine sediment, phosphorus, and nitrogen losses. With this information, trade-offs of farmer cost versus environmental benefit in implementing best management practices were estimated. The beef production system used at the USDA/ARS Meat Animal Research Center, Clay Center, NE was simulated using IFSM to determine the carbon, energy and water footprints of the beef produced. The accuracy of the simulation is being evaluated by comparing predicted and actual performance and production costs of their beef production system.
1. Mahantango Creek Experimental Watershed Historical Database. Long term watershed data are vital to developing and evaluating models for predicting or estimating nutrient flows and losses from watersheds. A forty-year historical database of rainfall, streamflow, and water quality for the Mahantango Creek experimental watershed near Harrisburg, Pennsylvania was compiled by ARS researchers at University Park, Pennsylvania. The compiled data were annotated and made publically available through the USDA-ARS Sustaining the Earth's Watersheds—Agricultural Research Data System (STEWARDS), a digital repository for long-term watershed monitoring data. An accompanying web page with sources for regional geospatial data not maintained on STEWARDS was created for the University Park website and a suite of four papers were published documenting the database. This work improves public access and appropriate interpretation of these historical watershed data.
2. Predicting gaseous emissions from silage. Silage has been shown to be an important source of emissions of volatile organic compounds (VOCs), which contribute to the formation of ground-level ozone. Since measurement of these compounds is difficult and expensive, process level simulation provides an alternative approach for estimating these emissions from individual farms and evaluating the benefits of strategies for mitigating these emissions. Toward this goal, ARS researchers at University Park, Pennsylvania developed and evaluated a model for predicting alcohol and acetaldehyde emissions from silage in a feed bunk. This work provides the first tool available for estimating farm scale VOC emissions, providing a basis for evaluating mitigation strategies for use by producers.
Belflower, J.B., Bernard, J.K., Gattie, D.K., Hancock, D.W., Risse, L.M., Rotz, C.A. 2012. A case study of the potential environmental impacts of different dairy production systems in Georgia. Agricultural Systems. 108:84-93. DOI: 10.1016/j.agsy.2012.01.005.