Modeling Agricultural Production Considering Water Quality and Risk

Environmental goals often conflict with the economic goals of agricultural producers. The Cottonwood River in Minnesota is heavily polluted with nitrogen, phosphate and sediment from agricultural sources in the watershed. Goals of profit maximization for producers conflict with those of effluent alleviation. We incorporate water quality goals and risk into a mathematical programming framework to examine economically efficient means of pollution abatement while considering a wide range of alternative production practices.Production Economics,

A Nonlinear Offset Program to Reduce Nitrous Oxide Emissions Induced by Excessive Nitrogen Application

On average, U.S. farmers choose to apply nitrogen fertilizer at a rate that exceeds the ex post agronomically optimal rate. The technology underlying the yield response to nitrogen rewards producers who over apply in years when rainfall is excessive. The overapplication of nutrients has negative environmental consequences because the nitrogen that is not taken up by the plant will typically volatilize causing N2O emissions, or leach causing water pollution. We present a nonlinear offset program that induces farmers to reduce their nitrogen applications to the level that will be consumed by the plant in a typical year and, as a result, reduce N2O emissions from agriculture. The offset program is nonlinear because of the nonlinear relationship between N2O and nitrogen application rates. We assume that the farmer solves an expected utility maximization problem, choosing the optimal nitrogen application rate. The key contribution is a set of simulations that shows that modest offset payments will induce participation in the program and will have a significant impact on both expected and actual N2O emissions without having a significant impact on actual or expected yields. We also find that more risk-averse farmers will reduce emissions by a greater amount than less risk-averse farmers. Finally, we show the distribution of emission reductions induced by this nonlinear offset scheme.nitrogen fertilizer; carbon offsets; nitrous oxide; pollution; uncertainty.

Predicting Water Cycle Characteristics from Percolation Theory and Observational Data.

The fate of water and water-soluble toxic wastes in the subsurface is of high importance for many scientific and practical applications. Although solute transport is proportional to water flow rates, theoretical and experimental studies show that heavy-tailed (power-law) solute transport distribution can cause chemical transport retardation, prolonging clean-up time-scales greatly. However, no consensus exists as to the physical basis of such transport laws. In percolation theory, the scaling behavior of such transport rarely relates to specific medium characteristics, but strongly to the dimensionality of the connectivity of the flow paths (for example, two- or three-dimensional, as in fractured-porous media or heterogeneous sediments), as well as to the saturation characteristics (i.e., wetting, drying, and entrapped air). In accordance with the proposed relevance of percolation models of solute transport to environmental clean-up, these predictions also prove relevant to transport-limited chemical weathering and soil formation, where the heavy-tailed distributions slow chemical weathering over time. The predictions of percolation theory have been tested in laboratory and field experiments on reactive solute transport, chemical weathering, and soil formation and found accurate. Recently, this theoretical framework has also been applied to the water partitioning at the Earth's surface between evapotranspiration, ET, and run-off, Q, known as the water balance. A well-known phenomenological model by Budyko addressed the relationship between the ratio of the actual evapotranspiration (ET) and precipitation, ET/P, versus the aridity index, ET0/P, with P being the precipitation and ET0 being the potential evapotranspiration. Existing work was able to predict the global fractions of P represented by Q and ET through an optimization of plant productivity, in which downward water fluxes affect soil depth, and upward fluxes plant growth. In the present work, based likewise on the concepts of percolation theory, we extend Budyko's model, and address the partitioning of run-off Q into its surface and subsurface components, as well as the contribution of interception to ET. Using various published data sources on the magnitudes of interception and information regarding the partitioning of Q, we address the variability in ET resulting from these processes. The global success of this prediction demonstrated here provides additional support for the universal applicability of percolation theory for solute transport as well as guidance in predicting the component of subsurface run-off, important for predicting natural flow rates through contaminated aquifers

Balancing Ecological and Economic Objectives in Land Use and Management: Modeling to Identify Sustainable Spatial Patterns.

Human-driven land-use/cover (LULC) changes threaten the integrity of ecosystems in many ways. To evaluate possible impacts of future changes in LULC on ecosystem services and support more sustainable environmental management, it is essential to understand how land-use patterns affect both ecological and economic outcomes, and how alternative spatial land-use and -management strategies may improve sustainability in land-use systems. I developed and tested a spatial simulation approach that can help improve our understanding of how human-driven landscape conditions at the watershed scale might reshape impacts on both water quality and economic performance in a Lake Erie watershed under a changing climate. The dissertation is organized into three chapters. The first chapter describes a study in which I evaluated sensitivity of a stochastic land-change model (LCM) to pixel versus polygonal land unit derived from parcel maps. Performance of pixel- and polygon-based simulations suggest that using polygonal unit is helpful with generating more realistic landscape patterns, but at the cost of spatial allocation accuracy. For the second chapter, I developed the first integrated modeling approach that compares the relative economic efficiency of alternative spatial land-use and -management strategies for addressing non-point source (NPS) nutrient pollution. Using the Soil Water Assessment Tool (SWAT) and data on crop costs and prices, I evaluated joint impacts on nutrient reduction and economic returns for optimized patterns of land-use changes (LUCs) versus conservation practices (CPs) at the field scale. Simulated results showed relying on CPs alone might not be sufficient to restore water quality in Lake Erie, and a combination strategy including both LUCs and CPs would be necessary and more efficient. Finally, I examined sensitivity of optimized spatial patterns of land-use and -management (CPs) approaches to climate change. I found optimal land-use and -management placement can be quite sensitive to change in climatic conditions. CP targeting was found to be more robust to climate change than land-use change, but integration of both strategies would be necessary to achieve high DRP reduction (>65%) targets. Results from this study highlight the need for future spatial optimization studies to consider adaptive capacity of conservation actions under a changing climate.PhDNatural Resources and EnvironmentUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133330/1/xuhui_1.pd

MULTIPLE-OBJECTIVE DECISION MAKING FOR AGROECOSYSTEM MANAGEMENT

Multiple-objective decision making (MODEM) provides an effective framework for integrated resource assessment of agroecosystems. Two elements of integrated assessment are discussed and illustrated: (1) adding noneconomic objectives as constraints in an optimization problem; and (2) evaluating tradeoffs among competing objectives using the efficiency frontier for objectives. These elements are illustrated for a crop farm and watershed in northern Missouri. An interactive, spatial decision support system (ISDSS) makes the MODEM framework accessible to unsophisticated users. A conceptual ISDSS is presented that assesses the socioeconomic, environmental, and ecological consequences of alternative management plans for reducing soil erosion and nonpoint source pollution in agroecosystems. A watershed decision support system based on the ISDSS is discussed.Agribusiness,

A spatial optimization approach to watershed water quality management: A case of the Opequon Watershed

The Opequon Creek watershed is located in northern VA and the eastern panhandle of WV. Currently, the main creeks in the watershed do not meet VA or WV state water quality standards for recreational uses and aquatic life. In both states, the creeks are listed as impaired due to high levels of nutrients, bacteria, benthic and biologic impairment. The Opequon Creek is part of the upper Potomac River watershed, and ultimately impacts water quality in the Chesapeake Bay watershed. The main aim of this study was to develop a methodology that can be used to reduce nutrient loadings entering the bay area and improve water quality in Opequon watershed by implementing four innovative agricultural BMPs. The study develops an integrated approach to nutrient reduction incorporating three models involving water quality modeling, nutrient fate and transportation and an optimization model to recommend a least cost strategy for nutrient reduction.;Four optimization scenarios were evaluated, involving a uniform, holistic, prioritization, and targeted reduction approaches. A uniform reduction approach evaluated each subwatershed to meet a reduction goal. Using specific land use contributions, an annual cost of {dollar}5.9 million would be required to meet N and P reduction goals on 14 of the 17 subwatersheds. The holistic approach is a scenario whereby the entire watershed\u27s nutrient reduction strategy is evaluated to meet the nutrient reduction goal at the Opequon watershed mouth. However, no optimal solution was found for this approach using agricultural BMPs. When BMPs were implemented on all acres of crop and pasture land, a total cost of {dollar}19.3 million was computed with only 43% of the reduction goal is achieved for P and 42% for N. In the third scenario, a prioritization approach targets priority subwatersheds. High priority subwatersheds were identified using the WCMS nutrient levels and public participation prioritization exercise in watershed management. The same three subwatersheds were identified as high priority by both methods: Mill, Tuscarora and Middle Creeks. Using P as the only constraint, the total cost of BMP implementation for these three subwatersheds under the Chesapeake Bay values was approximately {dollar}1.1 million compared to {dollar}282,000 using specific land use specific values. This result showed that nutrient reduction costs are much lower under specific land use contributions than using the Chesapeake Bay wide averages. The final scenario involved a targeted approach where reduction goals are to be met for both the Virginia and West Virginia parts of the Opequon watershed. No optimal solution exists for these two points of evaluation. As with the second scenario, when BMPs were implements on all agricultural land, VA had 69% and 63% of reduction goals achieved for N and P while WV had 36% and 49% of reduction goals achieved for N and P, respectively.;From a perspective of water resource policy, this study showed that: (1) P goals are more attainable at reasonable cost than N goals so that trading on the Opequon watershed is more likely to be feasible for P than N; (2) compliance with WV and VA reduction goals across all subwatersheds is more achievable than meeting a holistic reduction goal for the entire watershed; and (3) local knowledge gives comparable information on priority subwatersheds as does watershed modeling

A hydro-economic modeling framework for optimal management of groundwater nitrate pollution from agriculture

La contaminación difusa por nitratos de las aguas subterráneas, la cual es principalmente originada por la agricultura, es una creciente preocupación en casi cualquier parte del mundo. Esto ha provocado el desarrollado de normativas; en Europa, en 1991 se estableció la Directiva de Nitratos y el año 2000 la Directiva Europea Marco del Agua (DMA). La DMA establece que las masas de agua deben alcanzar el buen estado en el año 2015, además reconoce el rol que la economía puede tener en alcanzar los objetivos ecológicos y ambientales. En este trabajo se presenta un modelo hidro-económico que sugiere la gestión óptima de fertilizantes para controlar la contaminación por nitratos de las agua subterráneas. El modelo holístico de optimización determina la distribución espacio-temporal de la tasa de aplicación de fertilizantes que maximiza los beneficios netos en la agricultura, limitada por los requerimientos de calidad en el agua subterránea en diferentes puntos de control. El modelo relaciona la aplicación de fertilizantes con las concentraciones de nitratos en el agua subterránea mediante el uso de modelos agronómicos, de simulación del flujo y transporte en el agua subterránea, con los cuales se generan soluciones unitarias que son integradas en matrices de respuesta (RM). Las RM dentro del modelo de gestión permiten simular la evolución de la concentración de nitratos en el agua subterránea mediante superposición en diferentes puntos de control a largo del tiempo, debido a la emisión de contaminantes en diferentes zonas distribuidas en el espacio y variables en el tiempo. Los beneficios de la agricultura se determinan a través de funciones de producción y el precio de los cultivos. El modelo desarrollado se aplicó a un acuífero sintético. Se obtuvo la aplicación óptima de fertilizantes para problemas con diferentes condiciones iniciales, horizontes de planeación y tiempos de recuperación.Peña Haro, S. (2010). A hydro-economic modeling framework for optimal management of groundwater nitrate pollution from agriculture [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7483Palanci

Land as a Renewable Resource: Integrating Climate, Energy, and Profitability Goals using an Agent-Based NetLogo Model

The objectives of this study center over the course of the beef production life cycle as a management strategy to optimize the financial and natural resource endowment on farms at the county level based on the data available. Although the application is to West Virginia, implications can be derived for other areas with similar resource endowments. The beef farms located in adjacent locations within a county are identified as suppliers of inputs to the farm of interest (or contracting farm) in order to provide the basic foundation for agglomeration economies.;Both an intertemporal component and a spatial component are involved since clustering systems are enhanced when key players are interconnected over space. This is accomplished by using an optimal control framework as the basis of a NetLogo agent-based model (ABM) that explicitly includes a spatial component. This model is intended to provide a foundation for developing agglomeration economies in which other locations are able to supply resources to given locations - or to serve as input markets - by taking advantage of the spatially integrated nature of the agriculture industry. The spatial component provides the basis for regional economic development through clustering among the agricultural and other sectors since they might share locally produced inputs/outputs in the supply chain, thereby enhancing both scope economies and agglomeration economies. Thus, the integration of environmentally friendly technologies that enhance diversified products for the area such as renewable energy as well as digested manure along with high quality beef products and carbon offsets would create new markets which expand market channels and spur economic development, of interest to policy makers at all levels. As a result, farmers would be able not only to produce essential inputs for their own farms but, given appropriate incentives, would also supply them to adjacent farms boosting the local economy. Furthermore, a comparison with conventional, confined animal feeding operations (CAFOs), is briefly provided for perspective as well as the basis for environmental improvement through PBB techniques. Our intention is to replicate a diversified PBB industry and its interaction with surrounding communities in order to identify the optimized paths of the farmer and society in an intertemporal setting. The design of policy instruments is based on the results from the ABM wherein maximizing farm-level profitability that is able to bring benefits to society in which clustering among locations contributes in intensifying the benefits from the adoption of sustainable best management practices (BMPs). Thus, the explicit recognition and use of multifunctional land attributes enables us to address bio-fuel production and climate-related issues such as carbon offsets as well as to expand adoption of sustainable BMPs across space and time. In order to determine policy instruments, we ran our ABM with the absence of carbon prices and cost-share programs as well as different carbon prices and cost-share percentages under different clustering systems along a planning horizon of 15 years. We also compared the profitability between a diversified entrepreneur with a specialized business as an approach to identify the financial motivation to establish our proposed business concept. Results indicate that in order to observe environmental and social benefits as well as economic development in Appalachia through the introduction of a diversified PBB industry, a combination of cost-share policies and carbon prices must be considered. Our results imply that for an average grass-fed beef enterprise with 93 acres of pastureland (as is typical of Appalachia) as the primary resource surrounded by nearby cow/calf farms within an approximate 20 mile radius, will need to rely on a minimum of {dollar}13 per ton CO2e reduced along with a cost share program willing to share the risk of no less than half of the capital investment associated with an anaerobic digester within a clustering system of up to two participants to successfully diversify its business bringing environmental and economic development to the region. Alternatively, a policy combination of 50 percent cost share with a {dollar}26 carbon price not only will enhance environmental improvement but also profitability under unexpected as well as certain weather conditions. We also found that more renewable energy can be generated when more farms join a regional cluster, implying a synergistic effect through clustering. We estimate results under both deterministic and stochastic situations. The latter relate primarily to weather uncertainty and animal death loss, since those are the variables for which data is available. (Abstract shortened by UMI.)

Review of integrated approaches to river basin, planning, development and management

Piecemeal approaches to river basin development and management may not fully recognize the interactions and interdependence among components of a river basin system. River basin management that focuses on a single water use, on a single sector, or on the supply to particular segment of the basin population may inadvertently disrupt other sectors of the economy (in time or space). Hence, advocating for a systems approach to river basin development - for models that could help account for a river basin's key components and help address various objectives. The authors review the literature on such economic models, including models that deal with issues of water quality and quantity or with environmental considerations, recreational demand, countrywide planning, and multiple objective planning. Their review may serve as a source of references for those who need to consider whether they can use a model. Readers can evaluate the suitability, advantages, and disadvantages of particular modeling approaches for specific objectives.Water Conservation,River Basin Management,Water and Industry,Environmental Economics&Policies,Decentralization,Environmental Economics&Policies,Water Conservation,Water Supply and Sanitation Governance and Institutions,Water and Industry,Town Water Supply and Sanitation

Containing the Risk of Phosphorus Pollution in Agricultural Watersheds

Phosphorus (P) is an essential nutrient to boost crop yields, but P runoff can cause nutrient over-enrichment in agricultural watersheds and can lead to irreversible effects on aquatic ecosystems and their biodiversity. Lake Erie is one prominent example as this watershed has experienced multiple episodes of harmful algal blooms over the last decades. Annual P loads crucially depend on yearly weather variations, which can create the risk of years with high runoff and excessive nutrient loads. Here we apply stochastic modeling to derive sustainable management strategies that balance crop yield optimization with environmental protection, while accounting for weather variability as well as weather trends as a result of climate change. We demonstrate that ignoring annual weather variations results in mitigation efforts for environmental pollution that are largely insufficient. Accounting explicitly for future variations in precipitation allows us to control the risk of emissions exceeding the P target loads. When realistic risk targets are imposed, we find that a package of additional measures is required to avoid P over-enrichment in the Lake Erie watershed. This package consists of a substantial reduction of P inputs (approximately 30 for different accepted risk levels), adoption of cover crops throughout the near- and mid-century, and cultivation of less nutrient-intensive crops (30 more soy at the expense of corn). Although climate change reinforces these conclusions, we find that the accepted risk level of exceeding P target loads is the predominant factor in defining a sustainable nutrient management policy