EPIC modeling of soil organic carbon sequestration in croplands of Iowa

Depending on management, soil organic carbon (SOC) is a potential source or sink for atmospheric CO(2). We used the EPIC model to study impacts of soil and crop management on SOC in corn (Zea mays L.) and soybean (Glycine max L. Merr.) croplands of Iowa. The National Agricultural Statistics Service crops classification maps were used to identify corn-soybean areas. Soil properties were obtained from a combination of SSURGO and STATSGO databases. Daily weather variables were obtained from first order meteorological stations in Iowa and neighboring states. Data on crop management, fertilizer application and tillage were obtained from publicly available databases maintained by the NRCS, USDA-Economic Research Service (ERS), and Conservation Technology Information Center. The EPIC model accurately simulated state averages of crop yields during 1970-2005 (R(2) = 0.87). Simulated SOC explained 75% of the variation in measured SOC. With current trends in conservation tillage adoption, total stock of SOC (0-20 cm) is predicted to reach 506 Tg by 2019, representing an increase of 28 Tg with respect to 1980. In contrast, when the whole soil profile was considered, EPIC estimated a decrease of SOC stocks with time, from 1835 Tg in 1980 to 1771 Tg in 2019. Hence, soil depth considered for calculations is an important factor that needs further investigation. Soil organic C sequestration rates (0-20 cm) were estimated at 0.50 to 0.63 Mg ha(-1) yr(-1) depending on climate and soil conditions. Overall, combining land use maps with EPIC proved valid for predicting impacts of management practices on SOC. However, more data on spatial and temporal variation in SOC are needed to improve model calibration and validation.     

SNOTEL,the Soil Climate Analysis Network,and water supply forecasting at the Natural Resources Conservation Service: Past,present, and future

The Snow Survey and Water Supply Forecasting (SSWSF) Program and the Soil Climate Analysis Network (SCAN) of the United States Department of Agriculture's Natural Resources Conservation Service (NRCS) generate key observational and predictive information for water managers. Examples include mountain climate and snow monitoring through manual snow surveys and the SNOw TELemetry (SNOTEL) and SNOtel LITE networks, in situ soil moisture data acquisition through the SCAN and SNOTEL networks, and water supply forecasting using river runoff prediction models. The SSWSF Program has advanced continuously over the decades and is a major source of valuable water management information across the western United States, and the SCAN network supports agricultural and other water users nationwide. Product users and their management goals are diverse, and use-cases range from guiding crop selection to seasonal flood risk assessment, drought monitoring and prediction, avalanche and fire prediction, hydropower optimization, tracking climate variability and change, environmental management, satisfying international treaty and domestic legal requirements, and more. Priorities going forward are to continue innovating to enhance the accuracy and completeness of the observational and model-generated data products these programs deliver, including expanded synergies with the remote sensing community and uptake of artificial intelligence while maintaining long-term operational reliability and consistency at scale.     

GEOGRAPHIC INFORMATION SYSTEM BASED NONPOINT POLLUTION MODELING1

ABSTRACT: The reauthorization of the Clean Water Act reemphasizes the need for regional scale monitoring and management of nonpoint pollution loads. The magnitude of the task will require that local governments and their consultants integrate information systems and modeling if they are to manage the massive data sets and conduct the array of simulations that will be needed to support the decision making processes. Interfacing geographic information systems (GIS) and nonpoint pollution modeling is a logical approach. The objective of the present study was to use the 37,000-acre area defined by the Kensington Quadrangle sheet in Montgomery County, Maryland, to show that GIS-supported nonpoint pollution modeling is practical and economically attractive. The purpose of the GIS is to estimate the spatial distribution of nonpoint nitrogen, phosphorous, zinc, lead, BOD, and sediment using a model developed by the Northern Virginia Planning District Commission. The system allows the user to change land uses in subareas to simulate the consequences of additional development or alternate management strategies. The tests show that in-house development of this type of special purpose GIS is a practical alternative to vendor supplied systems and that the required databases can be developed quite reasonably.     

Comparison of Evapotranspiration Simulation Performance by APEX Model in Dryland and Irrigated Cropping Systems

Accurate estimation of evapotranspiration (ET) is essential to improve water use efficiency of crop production systems managed under different water regimes. The Agricultural Policy/Environmental eXtender (APEX) model was used to simulate ET using four potential ET (ET_p) methods. The objectives were to determine sensitive ET parameters in dryland and irrigated cropping systems and compare ET simulation in the two systems using multiple performance criteria. Measured ET and crop yield data from lysimeter fields located in the United States Department of Agriculture‐Agricultural Research Service Bushland, Texas were used for evaluation. The number of sensitive parameters was higher for dryland (11–14) than irrigated cropping systems (6–8). Only four input parameters: soil evaporation plant cover factor, root growth soil strength, maximum rain intercept, and rain intercept coefficient were sensitive in both cropping systems. Overall, it is possible to find a set of robust parameter values to simulate ET accurately in APEX in both cropping systems using any ET_p method. However, more computation time is required for dryland than irrigated cropping system due to a relatively larger number of sensitive input parameters. When all inputs are available, the Penman–Monteith method takes the shortest computation time to obtain one model run with robust parameter values in both cropping systems. However, in areas with limited datasets, one can still obtain reasonable ET simulations using either Priestley–Taylor or Hargreaves. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

An Approach for Estimating Soil Carbon Using the National Nutrient Loss Database

Agricultural lands have the potential to contribute to greenhouse gas mitigation by sequestering organic carbon within the soil. Credible and consistent estimates will be necessary to design programs and policies to encourage management practices that increase carbon sequestration. Because a nationwide survey of soil carbon by the wide range of natural resources and management conditions of the United States is prohibitively expensive, a simulation modeling approach must be used. The National Nutrient Loss Database (NNLD) is a modeling and database system designed and built jointly by the USDA– Natural Resources Conservation Service (NRCS) and Texas A&M University to provide science-based inferences on environmental impacts from changes in agricultural management practices and programs at the regional and national level. Currently, the NNLD simulates 16 crops and covers 1.35 × 10⁸ ha. For estimating soil carbon sequestration, the database will be populated with 1.5 × 10⁶ field-level model runs using the EPIC (Environmental Policy Impact Calculator) model, which includes newly incorporated carbon equations consistent with those in the Century model. Each run will represent a unique situation defined by state, crop, climate, soil, irrigation type, conservation practice, tillage system, and nutrient management treatment (nutrient rate, application frequency, application timing, and manure category). Results are to be assigned to specific National Resource Inventory points (NRI) to simulate regional and national baselines. In this article we present the modeling approach and discuss the strengths and limitations. Published online     

Sampling Schemes for Policy Analyses Using Computer Simulation Experiments

/ Evaluating the environmental and economic impacts of agricultural policies is not a simple task. A systematic approach to evaluation would include the effect of policy-dependent factors (such as tillage practices, crop rotations, and chemical use) as well as the effect of policy-independent covariates (such as weather, topography, and soil attributes) on response variables (such as amount of soil eroded or chemical leached into the groundwater). For comparison purposes, the effects of these input combinations on the response variable would have to be assessed under competing policy scenarios. Because the number of input combinations is high in most problems, and because policies to be evaluated are often not in use at the time of the study, practitioners have resorted to simulation experiments to generate data. However, generating data from simulation models is often costly and time consuming; thus, the number of input combinations in a study may be limiting even in simulation experiments. In this paper, we discuss the problem of designing computer simulation experiments that require generating data for just a fraction of the possible input combinations. We propose an approach that is based on subsampling the 1992 National Resources Inventory (NRI) points. We illustrate the procedure by assessing soil erosion in a situation where there are "observed" data [reported by the Natural Resources Conservation Service (NRCS)] for comparison. Estimates for soil erosion obtained using the procedure we propose are in good agreement with NRCS reported values.KEY WORDS: Metamodel; National Resources Inventory; Nonpoint source pollution     

Information needs for water resources decision-making

Water and related resources planning and decision-making have developed to the state of multiple objective and/or multiple criteria analysis using complicated systems analysis. The objective of this paper is to indicate the major components of information needed to facilitate the planning process for resource utilization, and to provide desirable outputs from management schemes. The process could best be described as the proper development of Management Information Systems (MIS) or Decision Support Systems (DDS). Data and information systems are never completed and must be continually updated and modified. The exact composition of any system depends also upon the general type of decision techniques being used. A brief outline of the decision process is given with the remainder of the paper dealing with the types of information needed to support the decision system.     

Time Series Analysis of Nebraska Daily Rainfall Data to Simulate Atrazine Runoff1

Abstract: Measured atrazine concentrations in Nebraska surface water have been shown to exceed water‐quality standards, posing risks to humans and to the ecosystem. To assess this risk, atrazine runoff was simulated at the field‐scale in Nebraska based on the pesticide component of the AGNPS model. This project’s objective was to determine the frequency that the atrazine concentration at the field outlet exceeded three different atrazine water‐quality criteria. The simulation was conducted for different farm management practices, soil moisture conditions, and five Nebraska topographic regions. If the criteria were exceeded, a risk to the drinking water consumer or freshwater aquatic life was hypothesized to exist. Three pesticide fate and transport processes were simulated with the model. Degradation was simulated using first‐order kinetics. Adsorption/desorption was modeled assuming a linear soil‐water partitioning coefficient. Advection (runoff) was based primarily on the USDA‐NRCS curve number method. Daily rainfall from the National Weather Service was used to compute the soil moisture conditions for the 1985‐2000 growing seasons. After each runoff event, the pesticide runoff concentration was compared with each of the three atrazine water‐quality criteria. The results show that environmental receptors (i.e., freshwater aquatic species) are exposed to unacceptable atrazine runoff concentrations in 20‐50% of the runoff events.     

Developing decision support systems for integrated coastal management in the tropics: is the ICM decision-making environment too complex for the development of a useable and useful DSS?

Integrated coastal management in the tropics requires the conservation of vulnerable and diverse ecosystems such as coral reefs and mangroves as well as the management of land and marine-based human activities. Decision-making for integrated coastal management involves multiple decision-makers and multiple stakeholders often with conflicting needs and interests. Decision support systems can be developed to improve our understanding of the inter-relationships between the natural and socio-economic variables and hence result in improved decision-making. The question is whether this decision making environment is actually too complex for the development of useful and useable decision support systems. This paper describes the components of the decision making environment and the components of a decision support system. It also explores the various techniques available to deal with different modelling needs, the constraints of inadequate data and the multi-objective decision making environment. In addition, different techniques of developing decision support systems can play important roles within integrated coastal management. Three coastal decision support systems are evaluated in terms of their design and role in integrated coastal management and are used to evaluate the potential to develop decision support systems for integrated coastal management.     

Improvements in Fluvial Stability Associated with Two‐Stage Ditch Construction in Mower County,Minnesota

Water quality and stream habitat in agricultural watersheds are under greater scrutiny as hydrologic pathways are altered to increase crop production. Agricultural drainage ditches function to remove water quickly from farmed landscapes. Conventional ditch designs lack the form and function of natural stream systems and tend to be unstable and provide inadequate habitat. In October of 2009, 1.89 km of a conventional drainage ditch in Mower County, Minnesota, was converted to an alternative system with a two‐stage channel to investigate the improvements in water quality, stability, and habitat. Longitudinal surveys show a 12‐fold increase in the pool‐riffle formation. Cross‐sectional surveys show an average increase in bankfull width of approximately 10% and may be associated to an increased frequency in large storm events. The average increase in bankfull depth was estimated as 18% but is largely influenced by pool formation. Rosgen Stability Analyses show the channel to be highly stable and the banks at a low risk of erosion. The average bankfull recurrence interval was estimated to be approximately 0.30 years. Overall, the two‐stage ditch design demonstrates an increase in fluvial stability, creating a more consistent sediment budget, and increasing the frequency of important instream habitat features, making this best management practice a viable option for addressing issues of erosion, sediment imbalance, and poor habitat in agricultural drainage systems.     

MANAGEMENT AND POLICY EFFECTS ON POTENTIAL GROUNDWATER CONTAMINATION FROM DAIRY WASTE1

ABSTRACT: A combined economic and water quality modeling framework was used to evaluate impacts of alternative policies and management practices on reducing nitrate movement to groundwater for dairy farms in Rockingham County, Virginia. The analysis considers three on-farm manure storage options, cost-sharing programs for purchasing manure storage facilities, restrictions on nitrogen application rates, and a tax on commercial fertilizer. The CREAMS model was used to estimate nitrate leaching from the crop root zone for various nutrient (and manure) management practices, based on timing and rate of manure and fertilizer applications. The mixed-integer programming economic model considers water quality, policy, and economic constraints in comparing the profitability of alternative cropping and nutrient management systems that reduce groundwater contamination potential. The study provides both the environmental and economic effects of better management of dairy waste.     

Riverine Threat Indices to Assess Watershed Condition and Identify Primary Management Capacity of Agriculture Natural Resource Management Agencies

Managers can improve conservation of lotic systems over large geographies if they have tools to assess total watershed conditions for individual stream segments and can identify segments where conservation practices are most likely to be successful (i.e., primary management capacity). The goal of this research was to develop a suite of threat indices to help agriculture resource management agencies select and prioritize watersheds across Missouri River basin in which to implement agriculture conservation practices. We quantified watershed percentages or densities of 17 threat metrics that represent major sources of ecological stress to stream communities into five threat indices: agriculture, urban, point-source pollution, infrastructure, and all non-agriculture threats. We identified stream segments where agriculture management agencies had primary management capacity. Agriculture watershed condition differed by ecoregion and considerable local variation was observed among stream segments in ecoregions of high agriculture threats. Stream segments with high non-agriculture threats were most concentrated near urban areas, but showed high local variability. 60 % of stream segments in the basin were classified as under U.S. Department of Agriculture’s Natural Resources Conservation Service (NRCS) primary management capacity and most segments were in regions of high agricultural threats. NRCS primary management capacity was locally variable which highlights the importance of assessing total watershed condition for multiple threats. Our threat indices can be used by agriculture resource management agencies to prioritize conservation actions and investments based on: (a) relative severity of all threats, (b) relative severity of agricultural threats, and (c) and degree of primary management capacity.     

ARE WE READY FOR A CLOSED SYSTEM OF WATER SUPPLY TREATMENT,AND REUSE - TECHNOLOGY VS. PSYCHOLOGY?1

ABSTRACT: Up to date there are still not many instances that can be found on the practice of a totally closed system of water supply, treatment, and reuse. In the United States, this is partly because the Public Health Service has discouraged such a practice. However, are there sound scientific reasons to support such a decision or is it purely a matter of psychological reason? Are the treatment technologies available today able to achieve the integrated closed system at a reasonable cost, yet without risking the public health? Are there some extra precautions that must be taken in practicing the direct reuse for the drinking purpose? These questions are discussed in this article. Current available technologies for advanced waste treatment are briefly reviewed and the treated effluent qualities obtained by the authors and others are used as a focal point of discussion on the feasibility of practicing the closed system. For this purpose, the treated effluent qualities are compared to the “Ranges of Promulgated Standards for Raw Water Sources of Domestic Water Supply” which have been used by the Public Health Service and several state regulatory agencies.     

Conservation tillage: best management practice for nonpoint runoff

Decisionmakers are in the process of selecting remedial measures for controlling nonpoint pollution runoff. Conservation tillage (CT) is being looked to as one of the major recommended practices. Many different systems exist and vary in the amount of crop residue left and soil roughness produced. Therefore, varying results occur in terms of yield and potential water quality impacts. Differences vary with type of tillage system, soils, geographic region, and the farmer's management. The purpose of this review is to provide material to decisionmakers that points out the assets and liabilities of the various CT systems. Tillage effects on soil characteristics and plant growth are presented and include a discussion of soil moisture and temperature, weed and insect control, nutrient availability, and yields. Water quality aspects are addressed through a discussion of the effects CT systems have on sediment, water, pesticide, and phosphorus loss.This work was supported by the Soil Science Department, College of Agriculture and Life Sciences, University of Wisconsin-Madison, and the U.S. Environmental Protection Agency, Region V, Chicago, Illinois. (Grant No. G005139-01).     

EQUIVALENCE BETWEEN TOPMODEL AND THE NRCS CURVE NUMBER METHOD IN PREDICTING VARIABLE RUNOFF SOURCE AREAS1

An equivalence is proposed between two rainfall‐runoff methods with a long history of use in the United States and Europe. In watersheds where variable source areas dominate runoff, the two methods can have comparable probability distribution functions of moisture deficit, and therefore predict similar saturated runoff source areas. A novel approach is introduced to determine the S parameter in the Natural Resources Conservation Service (NRCS) method. This approach constrains S by the physical soil and topography characteristics of the catchment and depth to water table. The NRCS curve number method is at the core of many rainfall‐runoff models in hydrology. As a simple lumped parameter method, it is often scrutinized because it is not obvious how to derive S from catchment hydromorphological characteristics. The novel approach provides a clear physical meaning for S, allowing better estimation of this parameter in humid shallow water table environments where the variable source area can be the dominant runoff mechanism.     

FARM INCOME AND GROUND WATER QUALITY IMPLICATIONS FROM REDUCING SURFACE WATER SEDIMENT DELWERIES1

ABSTRACT: The potential surface water and ground water quality tradeoff implications from the nonpoint source provisions of the 1987 Water Quality Act are investigated in this paper using a national linear programming model developed at Iowa State University and modified by the Economic Research Service and the Leaching Evaluation of Agricultural Chemicals (LEACH) Handbook developed by the U.S. Environmental Protection Agency. The linear programming model is used to maximize net farm revenue using optimal combinations of crop rotations and tillage practices for each region of the United States given natural resource constraints. The LEACH handbook is used to determine the relative potential for pesticides to leach below the root zone for different soil types, hydrologic conditions, pesticides used, and tillage practices. The results indicate that imposing a surface water quality erosion constraint aimed at reducing sediment concentrations results in a larger decrease in farm income than imposing a uniform 5 ton per acre per year erosion constraint. Both constraints could result in regional improvement in ground water quality in some regions of the country while decreasing ground water quality in other regions.     

Effects of Land Management Change on Spatial Variability of Organic Matter and Nutrients in Paddy Field: A Case Study of Pinghu,China

The Household Responsibility System initiated in the late 1970s in China has brought a profound change to its rural economy. The shift from the collective farming system to individual family farms has changed land management. The change, including fertilization and crop systems, may have significant effects on soil quality and agro-environmental sustainability. However, very little research is being carried out on the impact of reformed land tenure systems on the spatial variability of soil nutrients. In this study, geostatistics was applied to analyze changes in the spatial variability of soil organic matter and nutrients in paddy fields in Pinghu County, China after 20 years of land management change. In 1984 and 2002, 617 and 131 locations were selected, respectively, for collecting surface soil samples to analyze soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK). From 1984 to 2002, variability of the SOM and TN changed from strongly to moderately spatial-dependent, and the variability of AP remained weakly dependent on space, but that of the AK changed from moderately to weakly spatial-dependent. That the trend of the variability of four soil properties in 2002 became weaker than that in 1984 showed that the extrinsic factors (soil management practices, such as fertilization) weakened the effect by intrinsic factors (soil formation factors, such as soil parent materials) owing to a long period of land management change. The temporal geographic maps of the SOM and nutrients spatial distributions suggested that the concentrations of the SOM and nutrients had been changed to different extents during the period. Significant increase in AP and decrease in AK were noted. The changes were likely due to the imbalance between N, P, and K fertilizers and increased grain yield.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

EVALUATION OF Ann AGNPS NITROGEN LOADING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: Pollutants entering a water system can be very destructive to the health of that system. Best Management Practices (BMPs) are used to reduce these pollutants, but understanding the most effective practices is very difficult. Watershed models are an effective tool to aid in the decision‐making process of selecting the BMPs that are most effective in reducing the pollutant loading and are also the most cost effective. The Annualized Agricultural Nonpoint Source Pollution model (AnnAGNPS 2.0) is a technological tool that can be used to estimate watershed response to agricultural management practices. The main purpose of this paper is to test the performance of AnnAGNPS 2.0 on nitrogen loading using comparisons with measurements from the Deep Hollow watershed of the Mississippi Delta Management Systems Evaluation Area (MDMSEA) project. Previous work has demonstrated the capability of the model to simulate runoff and sediment. From sensitivity analyses in this study, initial nitrogen concentration in the soil and crop nitrogen uptake had the most impact on the nitrogen loadings. AnnAGNPS simulations of monthly nitrogen loadings are poor. However, statistical test (t‐test) showed that the predicted nitrogen loading is not significantly different from observed nitrogen loading at the 95 percent level of confidence.