Research Project: Sustainable Intensification in Agricultural Watersheds through Optimized Management and Technology

Location: Agroecosystems Management Research

2025 Annual Report

Objectives
Objective 1: Evaluate trends in hydrology and water quality in agricultural watersheds managed with current production practices. The research utilizes georeferenced data relating to landuse, terrain, cropping and animal production, observable use of conservation practices, and climate and meteorological data. 1.A: Document changes in land use, conservation practices, and climate as drivers of water quality trends in three Iowa watersheds. 1.B: Utilize new stream monitoring technology and terrain analyses to document stream bank movement and water quality changes along the SFIR, as related to adjacent land use and extreme weather events. Objective 2: In collaboration with other Long-Term Agroecosystem Research (LTAR) network sites, identify practices and factors that influence the effectiveness of conservation practices. 2.A: Compare the effects of ASP cropping system as part of the LTAR Common Experiment with other C-S cropping systems on targets such as N loss to drainage. 2.B: Determine crop water use using UAV imagery. Objective 3: Assess and improve models and remote sensing to characterize fields and watersheds. 3.A: Assess and improve modeling of Midwest conservation practices for sustainable intensification of agriculture. 3.B: Assess and improve mapping and analysis of subsurface drainage (e.g., patterns and intensity) using techniques from UAS and satellite imagery from several Midwest locations including four LTAR-drainage workgroup sites (Ames, St. Paul, W. Lafayette, Columbus).

Approach
This project will investigate the effects of agricultural management practices at field and watershed scales, investigate the dynamics of watershed hydrology, and assess and improve tools to characterize agricultural systems. Under the first objective, watershed studies will evaluate practices that can reduce loss of nitrate-nitrogen and phosphorous from cropped fields. These practices include saturated buffers, bioreactors, and blind surface inlets to subsurface drainage. Trend analysis will be conducted on long term records in the watershed studies to gain insight on water quality and streamflow variability over time. Streambank movement in these watersheds will be monitored with remote sensing. Under the second objective, field studies will be conducted as part of the Long-Term Agroecosystem Research network that will support research to sustain or enhance agricultural production and environmental quality in the Upper Mississippi River Basin (UMRB) region. The third objective will employ a mix of modeling and remote sensing studies to evaluate conservation practices and subsurface drainage systems. A breadth of watershed monitoring, remote sensing, controlled experiments in field and laboratory, and modeling techniques will be employed in the research. Publications, tools for conservation planning, and databases available to other scientists will be produced. Results are intended to enable agriculture to better manage water resources for multiple needs; particularly, in the UMRB.

Progress Report
Objective 1: Helping farmers improve water quality, manage nutrients, and build more resilient agricultural systems. In support of this objective, we continued monitoring water quantity and quality across our experimental watersheds, completing all 2024 laboratory analyses and advancing 2025 field sampling. All measurements have been integrated into the Sustaining the Earth’s Watersheds Agricultural Research Data System (STEWARDS) database, ensuring seamless access for both Conservation Effects Assessment Project (CEAP) and the Long-Term Agroecosystem Research (LTAR) network stakeholders. As part of the South Fork Water Alliance (SFWA) Batch and Build approach, we installed three new saturated-buffer sites, covering land survey, design, and construction costs, and we maintain biweekly water sampling on six existing buffers tracking nitrate removal. In collaboration with Iowa State University, we derived empirical weir equations and launched an interactive online tool for real-time flow estimation. This work, published in Applied Engineering in Agriculture, refines subsurface drainage and nitrate calibration, directly informing the design of nitrogen-reduction systems. From Fall 2022 through Fall 2024, four UAV-LiDAR surveys along the South Fork Iowa River (SFIR) quantified streambank migration and erosion adjacent to our network of flow gauges. Preliminary geospatial analysis highlights zones of bank retreat driven by secondary flows during high-discharge events in flashy drainage systems. Leveraging partnerships with ARS units in Missouri, Oklahoma, and Mississippi, we analyzed more than 50 years of weather and water flow records from four LTAR/CEAP watersheds within the Mississippi River Basin. Our findings, presented at the 2023 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America International Annual Meeting, show long-term precipitation, temperature, and streamflow trends that align closely with global model projections. Finally, we evaluated enhancements to the Soil & Water Assessment Tool (SWAT) model’s tile drainage and nitrogen (N) modules using data from the SFIR. The updated modules outperformed the originals in simulating daily streamflow and N loads, marking significant steps forward in model accuracy and reliability. Objective 2: Helping farmers reduce nutrient loss through improved conservation strategies. In support of this objective, we analyzed drainage from 24 plots at the Kelley field site near Ames, Iowa, to quantify how cropping systems, conservation practices, and N management affect water quality and nutrient fluxes. Hourly nitrate sensors captured concentration dynamics, and weekly grab samples during flow events measured losses of N, phosphorus (P), sulfur (S), and potassium (K). Introducing rye cover crops and woodchip denitrification bioreactors reduced N export by over 58%, compared with conventional tillage, without altering orthophosphate, total P, or S levels. Although oak woodchips in the bioreactors increased K leaching, concentrations remain below agronomic thresholds and pose no environmental concern. Objective 3: Smarter decision-making tools to better predict movement of water and nutrients through agricultural landscapes. Data collection at the Kelley site also supports SWAT model calibration and validation for winter cover crop impacts on N loss to drainage. Model simulations aligned closely with observed nitrate leaching and biomass growth, projecting a 42% decrease in nitrate drainage under cover cropping, which were consistent with observed field measurements. While the updated model excels at daily streamflow and N load predictions, further refinement is needed to capture N dynamics at sub-daily scales. Concurrent UAV flights at two Ames area sites, including a new organic system, have tested remote detections of subsurface tile lines. Despite no detections under current soil, moisture and residue conditions, collaborative trials with ARS researchers at Saint Paul, Minnesota, and Purdue University have had some preliminary successes at the Indiana sites. These results highlight the influence of soil texture, moisture, drainage rate, and surface residue cover on detectability. We are now developing a methodological framework to identify optimal Midwest conditions for UAV-based tile line mapping. Lastly, ARS scientists in Ames, Iowa released a user-friendly, standalone SWAT optimization tool to evaluate sustainable cropping systems under variable weather conditions and expanded SWAT’s irrigation module with two new scheduling schemes, each offering surface, sprinkler, and drip options to improve the simulation of irrigation water use efficiency.

Accomplishments
1. Double cropping winter rye with soybeans under low rye seeding rates could increase producer revenue. Double cropping rye-soybean occurs when both crops are grown and harvested in the same field in one year. This cropping system has shown promise as a useful way to simultaneously address multiple goals to create new revenue sources for farmers; contribute to the evolving domestic biofuels market and reduce imported fuel; increase overall crop production; increase green ground cover; provide land and soil benefits; improve water quality; and reduce nitrate loss to rivers. However, optimum management decisions such as seeding and fertilizer rates of rye for the most efficient production of both crops in the rotation are uncertain. ARS scientists in Ames, Iowa, and Temple, Texas, found that rye biomass production can be optimized with lower seeding rates than currently recommended and without nitrogen fertilization, which can reduce the costs and increase the adoption of double cropping rye. For example, these lower seeding rates could save a producer roughly $40 per hectare compared to recommended seeding rates. On the other hand, higher seeding rates increase spring ground cover that can help reduce erosion and weeds. This study revealed some tradeoffs between crop production, green ground cover, and inputs such as seeding and fertilizer rates when double cropping. These findings are important to producers, scientists, crop advisers, and policy makers trying to find the most promising cost-effective management practices to sustainably intensify agriculture in the North Central U.S.

2. Winter rye reduces nitrate leaching in U.S. North Central tile-drained fields nearly 60%. Corn and soybean fields with subsurface drainage in the Midwest facilitate the transport of excess nitrogen that eventually reaches the Gulf where it can potentially harm the ecosystem. Winter rye cover crops are among the most promising conservation practices to reduce nitrogen leaching losses but the complexity of these systems with subsurface drainage requires thoroughly tested computer models to help understand and predict interactive effects of weather, management, and soils. The Decision Support System for Agrotechnology Transfer (DSSAT) model is one of the more widely used agricultural models, but few model evaluations with long-term, field-measured data are available that include cover crops and subsurface drainage. ARS scientists in Ames, Iowa, and Temple, Texas, showed that the DSSAT model accurately simulated crop yield and nitrate-N losses to tile drainage in a corn-soybean rotation with and without winter rye cover crop in Central Iowa during the 2002–2010 growing seasons. For example, both observed and simulated nitrate loss reductions under rye cover crop were nearly 60%. The use of this thoroughly tested model and long-term dataset will help producers, scientists, crop advisers, and policy makers improve agricultural management and reduce nitrogen transport to streams and rivers.

3. A simple tool to quantitatively evaluate management options in agroecosystems. Agroecosystems, which are essential to supporting human populations, are complex entities that consist of several interacting components. Key components include food production and economics, available natural resources, and human capital. Understanding how different management decisions and factors, such as weather variability, affect each of these components and the performance of the whole agroecosystem is challenging and impossible to address with a single branch of knowledge. An ARS team from Ames, Iowa, and Mandan, North Dakota, determined that assessment of agroecosystem performance requires an integrated approach that considers how one component of the system affects the other, and in turn the whole agroecosystem state. Therefore, an Industrial Engineering modeling approach was adapted here to agroecosystems due to its established performance and simplicity for use in complex integrated systems with competing objectives. The developed tool predicted future responses of the agroecosystem components for a typical Midwestern agroecosystem transitioning from row crop agriculture to mixed farming systems with the ultimate goal to sustain available resources without jeopardizing food production. The tool provides managers and other stakeholders with a set of optimal solutions for decision making that consider the trade-offs between food production and sustainability of natural resources as one size does not fit all.

4. Managing nutrient runoff and surface conditions for sustainable farming. Manure runoff carries excess phosphorus (P) and nitrogen (N) into our waterways which can degrade water quality and harm aquatic life. However, current models oversimplify nutrient transport in relation to runoff and surface conditions, creating a need for more accurate representations. ARS scientists in Ames, Iowa, and Lincoln, Nebraska, observed P transport rises linearly with runoff at low application rates, but plateaus at higher rates, with outcomes predictable based on the manure’s P content. In contrast, N transport rises consistently with runoff across diverse settings, from cropland to feedlots. The research also revealed that bare fields (lacking surface cover) amplify peak runoff by over 130% compared to vegetated ones, underscoring the critical role of cover crops in slowing water and trapping nutrients. Storms and steeper slopes worsen runoff, but geospatial tools can identify high-risk areas where conservation practices like contour farming or crop interseeding can effectively reduce nutrient loss. By scaling small-plot data, this study paves the way for enhanced models with dynamic predictions, helping farmers to optimize fertilizer use, boost soil health, and protect rivers while guiding smarter policies.

5. An optimization tool to identify sustainable agricultural production systems-a systems modeling. Identifying agricultural practices that balance economic viability, conservation of soil and water resources, and a clean environment requires significant time and fiscal resources. Several multi-objective evolution algorithm (MOEA)-based optimization frameworks have been coupled with the soil and water assessment tool (SWAT) model to identify cost-effective best management practices (BMPs), considering their tradeoff with the environment but there are still gaps including requirement of high-performance computing resources and lack of economic functions. ARS scientists in Ames, Iowa, El Reno, Oklahoma, and university collaborators linked the SWAT model with a MOEA to develop SWAT- MOEA, a user-friendly standalone optimization tool to help identify sustainable agricultural production systems. The SWAT-MOEA allows for customized optimization for areas of interest and for creation of combinations of multiple agricultural production systems. An example case study in Oklahoma using the tool showed a 29% reduction in sediment as conventionally tilled winter wheat area converted into no-till winter wheat increased, with nominal decrease in profits of up to $0.70 ha-1. A slight increase in nitrogen fertilizer application from baseline of 40 to 41 kg ha-1, increased profit by up to $26.52 ha-1 with only a 0.015 kg ha- 1 increase in nitrate load, which are reasonable outcomes based on previous no-till farming impacts in the region. This tool will assist researchers and stakeholders in understanding the long-term economic and environmental impacts of the prevailing and alternative sustainable agricultural production systems.

6. A user-friendly online tool to estimate drainage volume. Edge-of-field conservation practices are implemented at the edge of agricultural fields to intercept and treat water from subsurface "tile" drains. Water control structures are used to manage water levels and estimate flow rates in drainage systems. Accurate estimation of flow rates is essential for calculating nutrient loads delivered to surface water and assessing the performance of edge-of-field conservation practices. ARS scientists in Ames, Iowa, and Iowa State University scientists developed weir equations and an easy-to-use online tool for obtaining equations for various sizes of control structure and flow conditions. This tool can be used by drainage water management professionals to accurately estimate flow rates, which improves estimated nitrogen (N) loads compared to previous studies. Accurately estimating nitrogen loads is critical in ensuring sustainable food production and maximizing farmer profitability. This research will help to accurately assess the impact of conservation practices and to design and implement effective management systems to reduce N loads to rivers.

7. Earlier soybean planting combined with cover crops contributes to reduced nutrient losses. Nutrient losses from upland crops that are planted at higher elevations are mainly caused by microbial processes in soil, which are difficult to control. To reduce these losses, the focus has been on improving nitrogen fertilizer management. Legumes, such as soybean, which generally do not receive nitrogen fertilizer, are assumed to contribute relatively little nitrogen loss and, therefore, offer little opportunity to reduce losses. ARS scientists in Ames, Iowa, in collaboration with Iowa State University, have shown that this assumption is incorrect. Approximately 40% of nitrogen losses from corn-soybean rotations are attributable to the soybean phase of the system. Using models trained on data from long-term ARS experiments, the researchers predict a systems approach that combines cover crops and earlier planting of soybean varieties with longer growth periods to reduce nutrient losses from soybean production by 30%. These practices complement nitrogen fertilizer management in corn and are widely accessible to farmers. Therefore, the proposed management changes represent an immediate opportunity to reduce the environmental impact of soybean production while increasing soybean yields, which is important to producers, scientists, crop advisers, and policy makers.

8. Leaching losses of essential nutrients occur through different mechanisms and is influenced by agricultural management practices. Leaching losses of specific nutrients is generally influenced by its chemical form, soil characteristics, environment, and management practices. ARS scientists in Ames, Iowa, demonstrated that no-tillage increased drainage flow and losses of phosphorous, and potassium compared to conventional tillage but had no impact on nitrogen (N) and sulfur losses. Installation of woodchip bioreactors (woodchip-filled trenches that remove nitrate from tile drainage water) curbed nitrate leaching, increased potassium leaching, and had no impact on phosphorous and sulfur loss in drainage. This work highlights that while there are many benefits of conservation tillage, its impact on water quality might be less evident and it can even lead to greater losses of essential nutrients via drainage. It was also shown that decomposition of soil organic matter is a major source of N loss in highly productive midwestern Mollisols, therefore reducing N fertilization below recommended rates in a no-till system might not be a viable strategy to significantly reduce N leaching loss. These findings are important to policy makers, conservationists, producers, scientists, and crop advisers.

9. Most soil health indicators are resilient to changes in land management practices in highly productive Mollisols. Conservation practices such as adoption of cover crops and no-tillage may promote soil health and productivity. However, there are significant gaps in long-term research on the cumulative effects of conservation practices on soil health indicators. ARS scientists in Ames, Iowa, showed that after 20 years of no-till and use of cover crops, soil health indicators including soil organic carbon (SOC) concentrations, bulk density, total nitrogen (N), potentially mineralizable N (fraction of soil N that can be converted into plant-available forms), and phosphorous, were not different from conventional corn-soybean management practices. The lack of differences in most soil health parameters indicate that soils with inherently high organic matter content such as Mollisols are highly resilient, despite the intensive use of tillage, thus, many soil health indicators may offer limited utility in guiding management decisions on these higher fertility soils. Therefore, no-tillage and cover crops may be better viewed as practices for reducing soil erosion while any increase in soil organic carbon storage is a co-benefit for the environment. These findings are important to policy makers, conservationists, producers, scientists, and crop advisers.

10. A new irrigation algorithm for soil and water assessment tool to facilitate water management and conservation in irrigated regions. Irrigation is indispensable for global food production, helping to address challenges posed by weather patterns and population growth. Accurate simulation of irrigation is key for effective water resources planning and management across various scales. ARS scientists in Ames, Iowa, and El Reno, Oklahoma, and university collaborators developed and incorporated a novel irrigation component into the Soil and Water Assessment Tool (SWAT), a hydrologic and water quality model to improve the simulation of how different irrigation systems and schedules influence water use in irrigated agricultural areas. This enhancement introduces two new irrigation options, each with three irrigation systems (surface, sprinkler, and drip). The utility of SWAT-Irrigation (IRR) is showcased through an application in central Oklahoma. Results demonstrate SWAT-IRR’s ability to capture the impacts of irrigation systems on the water budget and water allocation from the shallow aquifer. This tool will help water resource managers to develop adaptive irrigation water management strategies to protect water resources and enhance resilience to long-term weather variability in agricultural watersheds.

Review Publications
Xiang, Z., Moriasi, D.N., Samimi, M., Mirchi, A., Taghvaeian, S., Steiner, J.L., Verser, J.A., Starks, P.J. 2025. SWAT-IRR: A new irrigation algorithm for soil and water Assessment tool to facilitate water management and Conservation in irrigated regions. Computers and Electronics in Agriculture. 232. https://doi.org/10.1016/j.compag.2025.110142.
Rogovska, N.P., Kovar, J.L., Malone, R.W., O'Brien, P.L., Emmett, B.D., Ruis, S.J. 2024. Impact of tillage, cover crops, and in situ bioreactors on nutrient loss from an artificially drained Midwestern Mollisol. Journal of Environmental Quality. https://doi.org/10.1002/jeq2.20668.
Wyssmann, M., Coder, J., Schwartz, J., Papanicolaou, A.N. 2025. Volumetric characterization of spatially organized features of Reynolds stress anisotropy in the vicinity of submerged model boulders. Physics of Fluids. https://doi.org/10.1063/5.0265658.
Lee, S., Moriasi, D.N., Cibils, A.F., Barker, P. 2025. Increasing frequency and spatial extent of cattle heat stress conditions in the Southern plains of the USA. Scientific Reports. https://doi.org/10.1038/s41598-025-99621-5.
Papanicolaou, A.N., Basnet, K., O'Brien, P.L., Wacha, K.M., Malone, R.W., Archer, D.W. 2025. A system dynamics modeling framework to evaluate impacts on economic, environmental, and social quality components of a U.S. Midwestern agroecosystem transitioning from row crop agriculture to mixed farming systems. Ecological Modelling. 506. https://doi.org/10.1016/j.ecolmodel.2025.111142.
Kim, J., Blair, N., Papanicolaou, A.N. 2025. Molecular-level exploration of spatiotemporal dynamics of fluvial particulate organic carbon sources during storm events: Using a high-temporal resolution multi-biomarker approach. Science of the Total Environment. 963. https://doi.org/10.1016/j.scitotenv.2025.178447.
Kovar, J.L., Papanicolaou, A.N., Busch, D., Chatterjee, A., Cole, K.J., Dalzell, B.J., Emmett, B.D., Johnson, J.M., Malone, R.W., Morrow, A.J., Nowatzke, L.W., O'Brien, P.L., Prueger, J.H., Rogovska, N.P., Ruis, S.J., Todey, D.P., Wacha, K.M. 2024. The LTAR Croplands Common Experiment at Upper Mississippi River Basin - Ames. Journal of Environmental Quality. 53(6):978-988. https://doi.org/10.1002/jeq2.20646.
Cram, A.C., Moriasi, D.N., Moglen, G.E., Steiner, J.L., Aguirre, O.F., Verser, J.A., Xiang, Z. 2025. SWAT-MOEA: SWAT optimization tool for decision-making agricultural production systems among competing objectives. Journal of the American Water Resources Association. https://doi.org/10.1111/1752-1688.70013.
Chatterjee, A., Thorp, K.R., O'Brien, P.L., Kovar, J.L., Rogovska, N.P., Malone, R.W. 2025. Long-term DSSAT simulation of nitrogen loss to artificial subsurface drainage flow for a corn-soybean rotation with winter rye in Iowa. Agricultural Water Management. https://doi.org/10.1016/j.agwat.2025.109464.
Katuwal, S., Craig, A.J., Rupiper, A.W., Rogovska, N.P., Johnson, G.M., Isenhart, T.M., Malone, R.W. 2025. Parameterizing V-notch weir equations for flow monitoring in a drainage control structure. The Journal of Visualized Experiments (JoVE). https://doi.org/10.3791/67971-v.
Katuwal, S., Johnson, G.M., Craig, A.J., Rogovska, N.P., Isenhart, T.M., Malone, R.W. 2024. Calibration of V-notch and compound weirs for drainage water level control structures. Applied Engineering in Agriculture. 40(4). https://doi.org/10.13031/aea.16032.
Della Chiesa, T., Northrup, D., Miguez, F., Archontoulis, S., Baum, M., Venterea, R.T., Emmett, B.D., Malone, R.W., Iqbal, J., Necpalova, M., Castellano, M. 2024. Reducing greenhouse gas emissions from North American soybean production. Nature Sustainability. 7:1608-1615. https://doi.org/10.1038/s41893-024-01458-9.
Chen, X., Dong, H., Qi, Z., Gui, D., Ma, L., Thorp, K.R., Malone, R.W., Wu, H., Liu, B., Feng, S. 2025. Potential deficit irrigation adaptation strategies under climate change for sustaining cotton production in hyper–arid areas. Agricultural Water Management. 312. Article e109417. https://doi.org/10.1016/j.agwat.2025.109417.
Crespo, C., O'Brien, P.L., Rogovska, N.P., Martinez, D., Ruis, S.J., Kovar, A.E. 2025. Stover harvest increases yield stability in continuous corn systems. Agronomy Journal. https://doi.org/10.1002/agj2.70058.
Crespo, C., O'Brien, P.L., Nunes, M.R., Ruis, S.J., Emmett, B.D., Rogovska, N.P., Malone, R.W., Cambardella, C., Kovar, J.L. 2024. Contrasting soil management systems had limited effects on soil health and crop yields in a North Central U.S. Mollisol. Soil Science Society of America Journal. https://doi.org/10.1002/saj2.20716.
Gilley, J.E., Mcgehee, R.P., Wacha, K.M. 2025. Legacy nutrient transport by overland sheet flow. Journal of Environmental Engineering. 151(7). https://doi.org/10.1061/JOEEDU.EEENG-8077.
Gilley, J.E., Wacha, K.M. 2025. Identification of mechanisms influencing nutrient transport on sites containing beef cattle manure. Journal of Environmental Engineering. 151(3). Article 04025004. https://doi.org/10.1061/JOEEDU.EEENG-7838.
Crespo, C., Malone, R.W., Radke, A.G., Kovar, J.L., Emmett, B.D., Feyereisen, G.W., Thorp, K.R., Richard, T., O'Brien, P.L. 2025. Rye performance in central Iowa under different seeding and nitrogen fertilizer rates. Agronomy Journal. https://doi.org/10.1002/agj2.70112.