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USGS2025

Multiyear crop residue cover mapping using narrow-band vs. broad-band shortwave infrared satellite imagery

Crop residue serves an important role in agricultural systems as high levels of fractional crop residue cover ( f R ) can reduce erosion, preserve soil moisture, and build soil organic carbon. However, the ability to accurately quantify f R at scale has been limited. In this study we produced annual maps of f R for farmland in Maryland, USA using WorldView-3 (WV3) imagery paired with on-farm photographs ( n = 895) classified to f R using SamplePoint software. Univariate linear regressions were used to compare photograph f R to WV3 crop residue indices including: 1) Shortwave Infrared Normalized Difference Residue Index (SINDRI), 2) Shortwave Infrared Difference Residue Index (SIDRI), 3) Normalized Difference Tillage Index (NDTI), and 4) Shortwave Infrared Angle Index (SWIRA). SINDRI and SIDRI are based on narrow bands capable of measuring lignocellulose absorption features. NDTI and SWIRA are based on Landsat-comparable broad bands. Our findings demonstrated that SINDRI outperformed other indices in f R estimation in terms of coefficient of determination ( R 2 = 0.869) and root mean square error (RMSE = 0.111), when R 2 and RMSE were averaged across six individual years. For a univariate analysis combining five years of high-quality WV3 imagery, SINDRI again exhibited the highest f R estimation performance ( R 2 = 0.795; RMSE = 0.141), suggesting that SINDRI can map f R accurately with a singular relationship, potentially reducing the need for labor-intensive ground data collection. For broad-band indices, a multiple linear regression analysis that included a Water Index (WI) and Normalized Difference Vegetation Index (NDVI) as additional predictors increased the accuracy of f R estimation significantly, particularly for SWIRA ( R 2 = 0.767; RMSE = 0.144), but also NDTI ( R 2 = 0.654; RMSE = 0.174). Our findings suggest that while indices computed from narrow-band imagery are most accurate for f R estimation, SWIRA has the potential to improve f R estimation compared to NDTI, especially when used in conjunction with WI and NDVI. An index suite of SWIRA, WI, and NDVI can be computed with Landsat 4–9 imagery, providing a more accurate record of global f R dating back to 1982.

Soil and Tillage Research↗

USGS2014

Evaluation of a model framework to estimate soil and soil organic carbon redistribution by water and tillage using 137 Cs in two U.S. Midwest agricultural fields

Cultivated lands in the U.S. Midwest have been affected by soil erosion, causing soil organic carbon (SOC) redistribution in the landscape and other environmental and agricultural problems. The importance of SOC redistribution on soil productivity and crop yield, however, is still uncertain. In this study, we used a model framework, which includes the Unit Stream Power-based Erosion Deposition (USPED) and the Tillage Erosion Prediction (TEP) models, to understand the soil and SOC redistribution caused by water and tillage erosion in two agricultural fields in the U.S. Midwest. This model framework was evaluated for different digital elevation model (DEM) spatial resolutions (10-m, 24-m, 30-m, and 56-m) and topographic exponents ( m = 1.0–1.6 and n = 1.0–1.3) using soil redistribution rates from 137 Cs measurements. The results showed that the aggregated 24-m DEM, m = 1.4 and n = 1.0 for rill erosion, and m = 1.0 and n = 1.0 for sheet erosion, provided the best fit with the observation data at both sites. Moreover, estimated average SOC redistributions were 1.3 ± 9.8 g C m − 2 yr − 1 in field site 1 and 3.6 ± 14.3 g C m − 2 yr − 1 in field site 2. Spatial distribution patterns showed SOC loss (negative values) in the eroded areas and SOC gain (positive value) in the deposition areas. This study demonstrated the importance of the spatial resolution and the topographic exponents to estimate and map soil redistribution and the SOC dynamics throughout the landscape, helping to identify places where erosion and deposition from water and tillage are occurring at high rates. Additional research is needed to improve the application of the model framework for use in local and regional studies where rainfall erosivity and cover management factors vary. Therefore, using this model framework can help to improve the information about the spatial distribution of soil erosion across agricultural landscapes and to gain a better understanding of SOC dynamics within eroding and previously eroded fields.

Iowa↗

USGS2025

Increased soil greenhouse gas emissions from the combined use of cover crops and no‐tillage in producer‐ managed fields

Cover crop adoption offers multiple benefits and climate mitigation potential for agroecosystems, but is still an underutilized conservation practice. Recently, the combined use of cover cropping plus no-tillage (CCNT) has been increasingly promoted to achieve its synergistic effectiveness. Yet, how this combined practice affects soil greenhouse gas (GHG) emission remains a topic of debate. Existing studies are predominantly based on research-managed settings and often fail to assess all three major GHGs of carbon dioxide (CO 2 ), nitrous oxide (N 2 O), and methane (CH 4 ). To address these knowledge gaps, this study conducted a 30-month monitoring from producer-managed fields to quantify the soil greenhouse gas responses to CCNT compared to no-tillage (NT) alone. The findings showed that CCNT increased the soil global warming potential (GWP) by 15.2% relative to NT. CO 2 is the main contributor, accounting for over 91.7% of the total GWP. On average, the daily fluxes of CO 2 , N 2 O, and CH 4 were increased by 16.2%, 32.3%, and 55.6% under CCNT, respectively. Meteorological variables explained 85.3% of the CO 2 increase and 46.1% of the N 2 O increase associated with CCNT. Furthermore, two types of CCNT practices differed in GHG emission responses, though both strategies significantly reduced nitrogen losses. These quantitative results, derived from actual production systems, provide informed decision-making among local producers regarding the adoption of cover crops. Moreover, this field-based evidence offers a robust empirical foundation for future modeling efforts aimed at assessing the ecological benefits of cover crops under varying climatic and soil conditions.

Indiana↗

USGS2025

Satellite assessment of winter cover crop and conservation tillage outcomes to support adaptive management in working landscapes

The use of winter cover crops and conservation tillage are agricultural practices promoted to reduce nutrient and sediment loss from cropland, improve soil health, increase infiltration, and support farm nutrient cycling and ecosystem services. However, environmental performance of these practices is variable in the working farm landscape. The Lower Chesapeake Bay research project within the USDA Long-Term Agroecosystem Research (LTAR) network has collaboratively developed satellite remote sensing algorithms to measure the performance and phenology of winter cover crops (aboveground biomass, nitrogen content, fractional cover, and emergence and termination dates) using no-cost Harmonized Landsat and Sentinel-2 multispectral satellite imagery. This research supports annual operational assessment of >28,000 fields per year in four states. Results document the impacts of agronomic management on conservation outcomes, support adaptive management of incentive payment structures, and can reduce the workload for conservation district staff by remotely verifying cover crop management. Additionally, super-spectral satellite applications have been developed to accurately map crop residue cover by measuring lignocellulose absorption in shortwave infrared wavelengths, producing a 7-year time series of tillage intensity maps for the Delmarva Peninsula. These remote sensing products can be used in decision support and modeling to estimate changes in nutrient, sediment, and carbon cycling resulting from conservation practice implementation in the working farm landscape. This manuscript provides an overview of remote sensing research findings and applications associated with the USDA LTAR and Conservation Effects Assessment Projects (CEAP), documenting a variety of previously published outcomes with update and expansion of techniques using additional unpublished data and analyses as appropriate.

Maryland↗

USGS1993

Ground-water quality at the Management Systems Evaluation Area near Princeton, Minnesota, 1991-92

The northern cornbelt sand-plains Management Systems Evaluation Area (MSEA) program is a multiagency, multistate initiative to evaluate the effects of modified and prevailing farming systems on water quality in a sand-plain area in Minnesota and at satellite areas in North and South Dakota, and Wisconsin. The primary objective of Minnesota MSEA is to evaluate the effects of ridge-tillage practices in a corn and soybean farming system on ground-water quality. The Minnesota MSEA program is a cooperative study primarily between the U.S. Department of Agriculture Agricultural Research Service, the University of Minnesota Soil Science Department, and the U.S. Geological Survey. The Minnesota Pollution Control Agency and the Department of Geology and Geophysics at the University of Minnesota are also cooperating in the evaluation of groundwater quality at the MSEA.

Minnesota↗

USGS1993

Ground-water quality at the Management Systems Evaluation Area (MSEA) near Princeton, Minnesota, 1991

The northern cornbelt sand-plains Management Systems Evaluation Area (MSEA) program is a multiagency, multistate initiative to evaluate the effects of modified and prevailing fanning systems on water quality in a sand-plain area in Minnesota and at satellite areas in North and South Dakota, and Wisconsin (Delin and others, 1992). The primary objective of the northern cornbelt sand-plains MSEA is to evaluate the effects of ridge-tillage practices in a corn and soybean farming system on ground-water quality. The Minnesota MSEA program is a cooperative study primarily between the U.S. Department of Agriculture-Agricultural Research Service, the University of Minnesota Soil Science Department, and the U.S. Geological Survey. The Minnesota Pollution Control Agency and the Department of Geology and Geophysics at the University of Minnesota are also cooperating in the evaluation of ground-water quality at the MSEA.

Minnesota↗

USGS2011

Derived crop management data for the LandCarbon Project

The LandCarbon project is assessing potential carbon pools and greenhouse gas fluxes under various scenarios and land management regimes to provide information to support the formulation of policies governing climate change mitigation, adaptation and land management strategies. The project is unique in that spatially explicit maps of annual land cover and land-use change are created at the 250-meter pixel resolution. The project uses vast amounts of data as input to the models, including satellite, climate, land cover, soil, and land management data. Management data have been obtained from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) and USDA Economic Research Service (ERS) that provides information regarding crop type, crop harvesting, manure, fertilizer, tillage, and cover crop (U.S. Department of Agriculture, 2011a, b, c). The LandCarbon team queried the USDA databases to pull historic crop-related management data relative to the needs of the project. The data obtained was in table form with the County or State Federal Information Processing Standard (FIPS) and the year as the primary and secondary keys. Future projections were generated for the A1B, A2, B1, and B2 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) scenarios using the historic data values along with coefficients generated by the project. The PBL Netherlands Environmental Assessment Agency (PBL) Integrated Model to Assess the Global Environment (IMAGE) modeling framework (Integrated Model to Assess the Global Environment, 2006) was used to develop coefficients for each IPCC SRES scenario, which were applied to the historic management data to produce future land management practice projections. The LandCarbon project developed algorithms for deriving gridded data, using these tabular management data products as input. The derived gridded crop type, crop harvesting, manure, fertilizer, tillage, and cover crop products are used as input to the LandCarbon models to represent the historic and the future scenario management data. The overall algorithm to generate each of the gridded management products is based on the land cover and the derived crop type. For each year in the land cover dataset, the algorithm loops through each 250-meter pixel in the ecoregion. If the current pixel in the land cover dataset is an agriculture pixel, then the crop type is determined. Once the crop type is derived, then the crop harvest, manure, fertilizer, tillage, and cover crop values are derived independently for that crop type. The following is the overall algorithm used for the set of derived grids. The specific algorithm to generate each management dataset is discussed in the respective section for that dataset, along with special data handling and a description of the output product.

Open-File Report↗

USGS2008

Assessing manure management strategies through small-plot research and whole-farm modeling

Plot-scale experimentation can provide valuable insight into the effects of manure management practices on phosphorus (P) runoff, but whole-farm evaluation is needed for complete assessment of potential trade offs. Artificially-applied rainfall experimentation on small field plots and event-based and long-term simulation modeling were used to compare P loss in runoff related to two dairy manure application methods (surface application with and without incorporation by tillage) on contrasting Pennsylvania soils previously under no-till management. Results of single-event rainfall experiments indicated that average dissolved reactive P losses in runoff from manured plots decreased by up to 90% with manure incorporation while total P losses did not change significantly. Longer-term whole farm simulation modeling indicated that average dissolved reactive P losses would decrease by 8% with manure incorporation while total P losses would increase by 77% due to greater erosion from fields previously under no-till. Differences in the two methods of inference point to the need for caution in extrapolating research findings. Single-event rainfall experiments conducted shortly after manure application simulate incidental transfers of dissolved P in manure to runoff, resulting in greater losses of dissolved reactive P. However, the transfer of dissolved P in applied manure diminishes with time. Over the annual time frame simulated by whole farm modeling, erosion processes become more important to runoff P losses. Results of this study highlight the need to consider the potential for increased erosion and total P losses caused by soil disturbance during incorporation. This study emphasizes the ability of modeling to estimate management practice effectiveness at the larger scales when experimental data is not available.

Journal of Soil and Water Conservation↗

USGS2008

Reducing sedimentation of depressional wetlands in agricultural landscapes

Depressional wetlands in agricultural landscapes are easily degraded by sediments and contaminants accumulated from their watersheds. Several best management practices can reduce transport of sediments into wetlands, including the establishment of vegetative buffers. We summarize the sources, transport dynamics, and effect of sediments, nutrients, and contaminants that threaten wetlands and the current knowledge of design and usefulness of grass buffers for protecting isolated wetlands. Buffer effectiveness is dependent on several factors, including vegetation structure, buffer width, attributes of the surrounding watershed (i.e., area, vegetative cover, slope and topography, soil type and structure, soil moisture, amount of herbicides and pesticides applied), and intensity and duration of rain events. To reduce dissolved contaminants from runoff, the water must infiltrate the soil where microbes or other processes can break down or sequester contaminants. But increasing infiltration also diminishes total water volume entering a wetland, which presents threats to wetland hydrology in semi-arid regions. Buffer effectiveness may be enhanced significantly by implementing other best management practices (e.g., conservation tillage, balancing input with nutrient requirements for livestock and crops, precision application of chemicals) in the surrounding watershed to diminish soil erosion and associated contaminant runoff. Buffers require regular maintenance to remove sediment build-up and replace damaged or over-mature vegetation. Further research is needed to establish guidelines for effective buffer width and structure, and such efforts should entail a coordinated, regional, multi-scale, multidisciplinary approach to evaluate buffer effectiveness and impacts. Direct measures in "real-world" systems and field validations of buffer-effectiveness models are crucial next steps in evaluating how grass buffers will impact the abiotic and biotic variables attributes that characterize small, isolated wetlands. ?? 2008 The Society of Wetland Scientists.

Wetlands↗

USGS2005

Grass buffers for playas in agricultural landscapes: A literature synthesis

We summarize current knowledge about grass buffers for protecting small, isolated wetlands in agricultural contexts, including information relevant to protecting playas from runoff containing sediments, nutrients, pesticides, and other contaminants, and information on how buffers may affect densities and productivity of grassland birds. Land-uses surrounding the approximately 60,000 playas within the Playa Lakes Region (PLR), including intensive agriculture, feedlots, and oil extraction, can contribute to severe degradation of playas. Farming and grazing can lead to significant sedimentation in nearby playas, eliminating their ability to hold water, support the region’s biodiversity, or adequately recharge aquifers. Contaminants further degrade habitats and threaten the water quality of underlying aquifers, including the Ogallala Aquifer. Grass buffers hold promise as a management tool to reduce the amount of sediments and contaminants from agricultural runoff that enters playas. Effective buffer width is determined by acceptable sediment-reduction levels, potential water flow and velocity, landscape and soil variables, buffer species, and vegetation structure. Various models have been developed to predict buffer effectiveness; however, most of these models, including those provided by the Natural Resource Conservation Service (NRCS), remain unvalidated. The majority of buffer-effectiveness literature is based on simulated conditions in experimental trays or plots; no published studies of buffer design or effectiveness specifically address playas. Nonetheless, some general patterns have emerged regarding buffer design/effectiveness. Buffers 10–60 m wide are generally considered adequate for trapping most sediments, although in some cases buffers need to be >200 m. The U.S. Fish and Wildlife Service Partners for Wildlife Program in the Southern High Plains recommend a buffer width of ~33 m planted with a diverse mix of native shortgrasses and mixed grasses as a starting point. Most dissolved contaminants, however, are removed from runoff only when they infiltrate the soil, where microbes or other processes can break down or sequester contaminants. Promoting runoff infiltration requires wider buffers with denser stem densities than those required for filtering sediments, which may result in hydrological changes in playas. Ultimately, the balance between runoff and infiltration determines whether or not water eventually reaches a given basin. Long-term buffer effectiveness requires regular maintenance, including excavation to remove overburdens of sediments, repairing vegetation damage, and removing over-mature vegetation or invasions of noxious weeds. Buffers may not be enough to protect playas; best management practices (BMPs; e.g., conservation tillage, contour tilling, and mulching herbicides into soil after application) that diminish soil erosion and contaminant runoff also may be necessary. Nutrient loads in runoff can be minimized by balancing nutrient input with nutrient requirements for livestock and crops. Pesticide application practices also require careful evaluation. Mowing or grazing rather than use of herbicides offer alternatives for suppressing invasive or undesirable plant species in buffers. Future research should entail multiple-scale approaches at regional, wetland-complex, and individual watershed scales. Information needs include direct measures of buffer effectiveness in ‘real-world’ systems, refinement and field tests of buffer-effectiveness models, how buffers may affect floral and faunal communities of playas, and basic ecological information on playa function and playa wildlife ecology. Understanding how wildlife communities respond to patch size and habitat fragmentation is crucial for addressing questions regarding habitat quality of grass buffers in playa systems.

Open-File Report↗

USGS1983

Evaluating environmental and economic consequences of alternative pest management strategies: results of modeling workshops

The U.S. Environmental Protection Agency (EPA) needs a comprehensive method to evaluate the human health and environmental effects of alternative agricultural pest management strategies. This project explored the utility of Adaptive Environmental Assessment (AEA) techniques for meeting this need. The project objectives were to produce models for environmental impact analysis, improve communications, identify research needs and data requirements, and demonstrate a process for resolving conflicts. The project was structured around the construction (in an initial 2 1/2-day workshop) and examination (in a second 2 1/2-day workshop) of a simulation model of a corn agroecosystem. The model conceptualized at the first workshop simulates the effect of corn agrecosystem decisions on crop production, economic returns, and environmental indicators. The model is composed of five interacting submodels: 1) a Production Strategies submodel which makes decisions concerning tillage, planting, fertilizer and pesticide applications, and harvest; 2) a Hydrology/Chemical Transport submodel which represents soil hydrology, erosion, and concentrations of fertilizers and pesticides in the soil, runoff, surface waters, and percolation; 3) a Vegetation submodel which simulates growth of agricultural crops (corns and soybeans) and weeds; 4) a Pests submodel which calculates pest population levels and resulting crop damage; and 5) an Environmental Effects submodel which calculates indicators of potential fish kills, human health effects, and wildlife habitat. The most persistent data gaps encountered in quantifying the model were coefficients to relate environmental consequences to alternative pest management strategies. While the model developed in the project is not yet accurate enough to be used for real-world decisions about the use of pesticides on corn, it does contain the basic structure upon which such a model could be built. More importantly at this stage of development, the project has shown that very complex systems can be modeled in short periods of time and that the process of building such models increases understanding among disciplinary specialists and between diverse institutional interests. This process can be useful to EPA as the agency cooperates with other institutions to meet its responsibilities in less costly ways. Activities at the second 2 1/2-day workshop included a review of the model, incorporation of necessary corrections, simulation of policy scenarios, and examination of techniques to address remaining institutional conflicts. Participants were divided into three groups representing environmental, production or industry, and regulatory interests. Each group developed scenarios that would be most appealing to their particular interest and the scenarios were simulated by the agroecosystem computer model. Negotiators from each of the interest groups decided whether a hypothetical herbicide should be relabeled and if certain restrictions should be imposed on its use. Other participants functioned as experts and consultants on caucus teams. A solution to the hypothetical problem was successfully negotiated. Workshop participants and project staff agreed that the model and processes developed during the project should be used in training students, extension specialists, farmers, researchers, and chemical producers in collaborative problem solving methods. More productive research can be planned, and more realistic models of complex systems can be built in this way. More importantly, greater trust of decisionmakers in computer models, better understanding by technical experts about disciplines other than their own, and improved cooperation between institutional interests can be achieved. This trust, understanding, and cooperation are critical ingredients in solving problems that are too complex to be resolved by independent disciplinary activity and unilateral decision authority.

Report↗

USGS2026

What is the (real) rate of soil health practice adoption? Making sense of three data sources

Conservation stakeholders looking to quantify the impact of their investments to increase soil health practice adoption over time often face challenges in interpreting practice adoption data due to discrepancies in language and results among data sources. Similarly, efforts to estimate environmental outcomes of practice adoption, such as water quality and greenhouse gas emissions, can vary depending on different practice adoption input data. To help make sense of different adoption data sources, we compared county-level adoption data for winter cover crops (WCC), no-till (NT), and reduced tillage (RT) in three areas of the United States with contrasting climates and production systems: central Illinois (CIL), southern Illinois (SIL), and western New York (WNY). We analyzed data available during 2015 through 2022 from the Operational Tillage Information System (OpTIS, remote sensing), US Census of Agriculture (AgCensus, a farmer survey), and, specifically in Illinois, the Illinois Soil Conservation Transect Survey (Transect, a roadside survey). The magnitude of differences between the datasets depended on the practice and geographic location. For example, OpTIS and AgCensus tillage data were much more similar in Illinois (average difference of less than 4 percentage points) compared to New York (average differences of 20 percentage points). Similarly, there was less variability and smaller differences between OpTIS and AgCensus WCC data in Illinois compared to WNY. AgCensus tended to report lower WCC adoption for Illinois and greater adoption in WNY compared to OpTIS. All data sources agreed that the rate of change in tillage practices is slow (mainly –1% to 1%) and that adoption of WCC is low (assuming linear growth, it could take nearly a century to reach 50% WCC adoption in CIL). Differences among the datasets were attributed to definitional inconsistencies for RT and NT and how WCC data were acquired. For example, the AgCensus asks if a WCC was planted, whereas OpTIS and Transect evaluate the presence of a standing WCC. Data sources also reflect different time periods (calendar years or crop years) and types of cropland assessed (corn [ Zea mays L.], soybean [ Glycine max {L.} Merr.], or all cropland). We propose two recommendations to improve interpretation and consistency: (1) a working group to harmonize definitions and protocols and develop educational materials for data users, and (2) a research effort that integrates different adoption data types and produces publicly available adoption data at HUC-10 and county scales. Such activities could help improve data access and utility for evidence-based conservation decision-making and enhance the accuracy of environmental models that rely on adoption data as input.

Journal of Soil and Water Conservation↗

USGS1989

Effects of controlled agricultural practices on water quality in the Minnesota sand-plain aquifer

Recent studies of Minnesota's sand plains indicate that ground-water chemistry is related to agricultural practices. Surficial sand-plain aquifers cover 8,000,000 acres of Minnesota and are a major source of water for domestic use, irrigation, and some municipal systems. The sand-plain aquifers consist of sand and gravel deposits that are from 20 to greater than 100 feet thick and are covered by a thin sandy loam that generally is less than 2 feet thick. Sand-plain aquifers are recharged by the downward percolation of precipitation through the soil root zone and the unsaturated zone in the sand to the water table. The water table is the upper surface of the zone of saturation and forms the top of the sand-plain aquifer. Sand-plain aquifers are susceptible to contamination by agricultural chemicals (fertilizers and pesticides), if downward-percolating recharge water contains these chemicals. The concentrations of nitrate, pesticides, and some other chemical constituents fluctuate seasonally and differ with depth below the water table (Anderson, 1989). Despite the availability of water-quality data for about 260 wells that were collected during previous studies in three U.S. Geological Survey (USGS) project areas in Minnesota, it is not known how concentrations of agricultural chemicals in ground water relate to the rate and timing of fertilizer and pesticide application or to the tillage practices used. Field-scale research is needed to determine the effects of different farming practices on the concentrations of nitrate, pesticides, and other agricultural chemicals in ground water in the unsaturated and saturated zones.

Minnesota↗

USGS2010

A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios

he Energy Independence and Security Act of 2007 (EISA), Section 712, mandates the U.S. Department of the Interior to develop a methodology and conduct an assessment of the Nation’s ecosystems, focusing on carbon stocks, carbon sequestration, and emissions of three greenhouse gases (GHGs): carbon dioxide, methane, and nitrous oxide. The major requirements include (1) an assessment of all ecosystems (terrestrial systems, such as forests, croplands, wetlands, grasslands/shrublands; and aquatic ecosystems, such as rivers, lakes, and estuaries); (2) an estimate of the annual potential capacities of ecosystems to increase carbon sequestration and reduce net GHG emissions in the context of mitigation strategies (including management and restoration activities); and (3) an evaluation of the effects of controlling processes, such as climate change, land-use and land-cover change, and disturbances such as wildfires. The concepts of ecosystems, carbon pools, and GHG fluxes follow conventional definitions in use by major national and international assessment or inventory efforts. In order to estimate current ecosystem carbon stocks and GHG fluxes and to understand the potential capacity and effects of mitigation strategies, the method will use two time periods for the assessment: 2001 through 2010, which establishes a current ecosystem carbon and GHG baseline and will be used to validate the models; and 2011 through 2050, which will be used to assess potential capacities based on a set of scenarios. The scenario framework will be constructed using storylines of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES), along with both reference and enhanced land-use and land-cover (LULC) and land-management parameters. Additional LULC and land-management mitigation scenarios will be constructed for each storyline to increase carbon sequestration and reduce GHG fluxes in ecosystems. Input from regional experts and stakeholders will be solicited to construct these scenarios. The methods for mapping the current LULC and ecosystem disturbances will require the extensive use of both remote-sensing data and field-survey data (for example, forest inventories) to capture and characterize landscape-changing events. For potential LULC changes and ecosystem disturbances, key drivers such as socioeconomic and climate changes will be used in addition to the biophysical data. The result of these analyses will be a series of maps for each future year for each scenario. These annual maps will form the basis for estimating carbon storage and GHG emissions. For terrestrial ecosystems, carbon storage, carbon-sequestration capacities, and GHG emissions under the present conditions and future scenarios will be assessed using the LULC-change and ecosystem-disturbance estimates in map format with a spatially explicit biogeochemical ensemble modeling system that incorporates properties of management activities (such as tillage or harvesting) and properties of individual ecosystems (such as energy exchange, vegetation characteristics, hydrological cycling, and soil attributes). For aquatic ecosystems, carbon burial in sediments and fluxes of GHG are functions of the present and future potential stream flow and sediment transport and will be assessed using empirical hydrological modeling methods. Validation and uncertainty analysis methods described in the methodology will follow established guidelines to assess the quality of the assessment results. The U.S. Environmental Protection Agency’s Level II ecoregions map will be the practical instrument for developing and delivering assessment results. Consequently, the ecoregion (there are 22 modified ecoregions) will be the reporting unit of the assessment because the scenarios, assessment results, validation, and uncertainty analysis will be produced at that scale. The implementation of these methods will require collaborations among various Federal agencies, State agencies, nongovernmental organizations, and the science community. Using the method described in this document, the assessment can be completed in approximately 3 to 4 years. The primary deliverables will be assessment reports containing tables, charts, and maps that will present the estimated GHG parameters annually for 2001 through 2050 by ecosystem, pool, and scenario. The results will permit the evaluation of a range of policies, mitigation options, and research topics, such as the demographic, LULC-change, or climate-change effects on carbon stocks, carbon sequestration, and GHG fluxes in ecosystems.

Scientific Investigations Report↗

USGS2025

Exploring management and environment effects on edge-of-field phosphorus losses with linear mixed models

Evaluating how weather, farm management, and soil conditions impact phosphorus (P) loss from agricultural sites is essential for improving our waterways in agricultural watersheds. In this study, rainfall characteristics, manure application timing, tillage, surface condition, and soil test phosphorus (STP) were analyzed to determine their effects on total phosphorus (TP) and dissolved phosphorus (DP) loss using 125 site-years of runoff data collected by the University of Wisconsin Discovery Farms and Discovery Farms Minnesota. Three linear mixed models (LMMs) were then used to evaluate the influence of those factors on TP and DP losses: (1) a model that included all runoff events, (2) manured sites only, and (3) precipitation events only. Results show that the timing of manure application relative to the timing of a runoff event only had a marginal association with P loads and concentrations, although the majority of the runoff events were collected after 10 days of manure application. Tillage was as influential factor, with greater DP loads and concentrations associated with no-till, especially during frozen conditions. Fields in this study had high STP values, but the model results only showed positive associations between DP load and DP flow-weighted mean concentration (FWMC) loss at the 0- to 15-cm depth. The precipitation event LMM (which included precipitation characteristics) was the model that resulted in the largest R 2 value. While the predictive capacity of the LMMs was low, they did illuminate the relative importance of management and environmental variables on P loss, and can be used to guide future research on P loss in this region.

Minnesota, Wisconsin↗

USGS2019

Point sources and agricultural practices control spatial-temporal patterns of orthophosphate in tributaries to Chesapeake Bay

Orthophosphate (PO 4 ) is the most bioavailable form of phosphorus (P). Excess PO 4 may cause harmful algal blooms in aquatic ecosystems. A major restoration effort is underway for Chesapeake Bay (CB) to reduce P, nitrogen, and sediment loading to CB. Although PO 4 cycling and delivery to streams has been characterized in small-scale studies, regional drivers of PO 4 patterns remain poorly understood because most water quality trend assessment focus on total P. Moreover, these trend assessments are usually at an annual timestep. To address this research gap, we analyzed PO 4 patterns over a 9-year period at 53 monitoring stations across the CB watershed to: 1) characterize the role of PO 4 in total P fluxes and trends; 2) describe spatial and temporal patterns of PO 4 concentrations across seasons and streamflow ; and 3) explore factors explaining these patterns. Agricultural watersheds exported the most total P compared with watersheds under different land uses (e.g., urban or forest), with PO 4 comprising up to 50% of those exports. Although PO 4 exports are declining at many sites, some agricultural regions are experiencing increasing trends at a rate sufficient to drive total P trends. Regression modeling results suggest that point source load reductions are likely responsible for decreasing PO 4 concentrations observed at many sites. Watersheds with more Conservation Reserve Program enrollment had lower summer PO 4 concentrations, highlighting the effectiveness of this practice. Manure inputs strongly predicted PO 4 concentrations at high flows across all seasons. Both manure applications and conservation tillage were correlated with changes in PO 4 concentrations at high flow, suggesting these activities could contribute to increasing PO 4 concentrations. This study highlights the effectiveness of point source control for reducing PO 4 exports and underscores the need for management strategies to target sources, practices, and landscape factors determining PO 4 loss from soils where manure inputs remain high.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS1988

Assessment of the role of bottomland hardwoods in sediment and erosion control

Drainage and clearing of bottomland hardwoods have long been recognized by the U.S. Environmental Protection Agency (EPA) and the U.S. Fish and Wildlife Service (Service) as important impacts of Federal water projects in the lower Mississippi River Valley. More recently, the water quality impacts of such projects (e.g., increases in sediments, nutrients, and pesticides) have also become of concern. In 1984, in an effort to better define problems concerning wetland losses and water degradation, EPA initiated a cooperative project with the Western Energy and Land Use Team (now the National Ecology Research Center) of the Service. Three phases of the project were identified: 1. To collect existing literature and data; 2. To select, develop, and test the utility of methods to quantify the relationships between land use, cover types, soils, hydrology, and water quality (as represented by sediment); and 3. To apply selected methodologies to several sites within the Yazoo Basin of Mississippi to determine the, potential effectiveness of various management alternatives to reduce sediment yield, increase sediment deposition, and improve water quality. Methods development focused on linking a simulation of water and sediment movement to a computerized geographic information system. We had several objectives for the resulting model. We desired that it should: 1. Estimate the importance of bottomland and hardwoods as a cover type that performs the functions of erosion and sediment control, 2. Simulate effects of proportions of ' various cover types and their specific spatial configurations, 3. Be applicable to moderately large spatial areas with minimal site-specific calibration, 4. Simulate spatial patterns of sediment loss-gain over time, and 5. Represent both sediment detachment and transport. While it was recognized that impacts and management alternatives could be sorted roughly into landscape measures and channel measures, the decision was made to focus study efforts mainly on landscape measures. Landscape measures include altered drainage and flooding patterns, altered cover types (e.g., conversion of bottomland hardwoods to agricultural crops, reforestation of cropland to bottomland hardwoods, and creation of riparian buffer strips), altered cropping and tillage patterns, altered routing of water, and creation of buffer strips along wetlands and channel margins. Channel measures include vegetative bank stabilization, grade control structures, and regulation of channel water volume and velocity. During the first year of the study, EPA decided not to fund the third phase of the project. This required considerable rescoping of the project with the result that application of the sediment mobilization, routing, and deposition models to various management alternatives and portions of the Yazoo Basin was somewhat restricted. We believe, however, that this report will provide a good understanding of the various modes of sediment mobilization, transport, and deposition within the Yazoo Basin, as well as of the role of bottomland hardwoods. The model developed in this study could be applied to a variety of management or mitigation alternatives prior to implementation to determine their relative effectiveness. Policy, political, and socio-economic consequences of any proposed management/mitigation practice, however, must ultimately be taken into consideration by those charged with management of water resources within the Yazoo Basin before any practice is implemented. This study makes no effort to judge the feasibility of management alternatives in this regard.

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USGS2019

Assessment of site-specific agricultural Best Management Practices in the Upper East River watershed, Wisconsin, using a field-scale SWAT model

The Great Lakes “Priority Watershed” effort targeted the Upper East River watershed, a 116.5 km2 tributary watershed to Green Bay in Wisconsin, to reduce sediment and nutrients entering Green Bay. A Soil and Water Assessment Tool (SWAT) model was created to determine the effectiveness of Best Management Practices (BMPs) derived from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) Database. The model was calibrated at the monthly timestep for flow, sediment, dissolved reactive phosphorus (DRP), total phosphorus (TP), and total nitrogen (TN). Field- and watershed-scale sediment and nutrient reductions were calculated due to the implementation of 74 BMP combinations on dairy and cash grain rotations. Modeling results indicated that when multiple BMPs are placed on a field, especially those that included filter strips and grassed waterways, generally reduced sediment and nutrient loads more than a single BMP implementation. The most effective in-field practice at reducing DRP and TP on dairy fields was a combination of 5 different BMPs: cover crops, crop rotation, nutrient management plan, reduced tillage, and a filter strip. Conservation cover was the most effective practice at reducing sediment and nutrient yields. Sediment and nutrient loads decreased at the watershed scale as the quantity and coverage of BMPs increased. When all contracted NCP BMPs were simulated at the watershed scale, sediment loads were reduced 2%, while TP, DRP, TN and nitrate loads were reduced 20%, 9%, 24%, and 17%, respectively. Modeling scenarios indicated that as the number and area of BMPs were increased, sediment and nutrient load reductions were also increased.

Wisconsin↗