This study uses the Simplified International Model of agricultural Prices, Land use and the Environment, on a Grid (SIMPLE-G­), a partial equilibrium model of agricultural production, to explore how the scale and scope of environmental quality markets influence farm-level production decisions and market performance. I simulate how permit trading affects producers’ input use decisions, and ultimately pollution emissions, by modifying the supply nest structure of the model to include water quality permits as an additional output from agricultural production. Conservation practices improving water quality may also result in ecosystem co-benefits (e.g., reduced greenhouse gas emissions and habitat provision). Hence, I extend SIMPLE-G to quantify these co-benefits and simulate the effects of allowing conservationist producers to “stack” permits (i.e., to supply multiple permit types for each co-benefit). I find that, overall, permit production increases with the scale and scope of the markets. <a>At the smallest market size</a>—which allows trading only within 8-digit hydrological unit code watersheds—unintended policy implications arise as the stacked markets cause one conservation practice to crowd out the other. Meanwhile, the largest market—which allows trading across the Chesapeake Bay Watershed—produces nitrogen permits more efficiently which may lead to less of the secondary permits in comparison to other market configurations. The results of this study support the Environmental Protection Agency’s urging of the expansion of the scale and scope of ecosystem markets.

For over 30 years, federal and state governments have been engaged in a collective effort to improve the water quality and living resources in the Chesapeake Bay (CB), focusing particularly on reducing delivered nitrogen and phosphorus loads. However, achievement of water quality objectives remains elusive. In Virginia, agriculture represents the single largest source of nutrient loads to the Chesapeake Bay. Despite aggressive regulatory efforts in other nutrient source sectors, state authorities rely on educational programs and voluntary financial assistance programs to induce landowners to adopt best management practices (BMPs) that reduce agricultural nutrient loads. This study explores two economic aspects of efforts to reduce agricultural nonpoint source (NPS) pollution in the Virginia portion of the CB watershed. Firstly, current and possible future transactions costs associated with specific aspects of agricultural NPS participation in water quality trading (WQT) programs are examined in Chapter 1. A case study approach is used to consider the possible cost consequences of expanding the use of NPS credits from agricultural 'working lands' BMPs in Virginia. Findings indicate that overall transactions costs for nutrient trades involving agricultural NPS in Virginia are currently relatively low, due to the type of activities being credited: simple land conversions. Based on best available evidence, the administrative transactions costs of creating credits on agricultural 'working lands' using management and structural BMPs will be 2 to 5 times more costly on a per project basis than for credits generated from land conversions. Compliance monitoring protocols were found to be a significant driver of costs for credits generated from working agricultural lands. These results suggest an important cost/risk tradeoff between verification cost and compliance certainty for program designers to consider. The second study (Chapter 2) considers the economic cost of meeting pollution reduction targets for the Virginia portion of the CB Watershed. Existing cost models are based on simplifying behavioral assumptions about public transactions costs, conservation adoption rates, and implementation costs of agricultural BMPs. This study builds on the existing literature and uses the estimates of transactions costs from Chapter 1 together with information on producer BMP adoption rates to examine the implications of including transactions costs and differential BMP costs and adoption rates when estimating the minimum costs of achieving specified nutrient reduction goals in Virginia. The paper uses a cost-minimizing mathematical programming approach and models a number of different cost scenarios. Results indicate that inclusion of transactions costs substantially affects estimates of total costs of meeting nutrient reduction goals; on average total costs increased by 44 percent, but ranged between 19 and 81 percent depending on the scenario analyzed. Analysis of the modelled scenarios shows that those BMPs that account for the most implementation costs do not necessarily account for the most transactions costs (and vice versa). This suggests that transactions costs should be acknowledged to vary with the type of practices being implemented, rather than being approximated as either a fixed amount or a fixed proportion of implementation costs. In addition, the analysis highlights the disproportionate costs associated with achieving nutrient reductions via high-cost adopters, and suggests there may be a role for education or extension to assist landholders to lower opportunity costs of participating in conservation. / Master of Science

This dissertation explores the adoption of Best Management Practices (BMPs) in the Kentucky River watershed. Through a survey of farmers in the Kentucky River watershed, chapter two investigates farmers’ current BMP adoption and their willingness to engage in additional adoption incentivized through a proposed Water Quality Trading (WQT) program. This chapter includes two parts: the first part is to investigate the factors influencing farmers’ current usage of BMPs; the second part is to estimate farmers’ willingness to implement BMPs given different levels of compensation specified in the survey. Farmers’ experiences about BMPs are more likely to persuade them to adopt additional BMPs. The activities of using riparian buffers, fencing off animals and building up waste storage facilities are found to be responsive to the levels of compensation offered. The third chapter discusses farmers’ expected economic benefits from BMP adoption, and addresses the missing data issue. In the survey, of those respondents who indicated that they accept the offered level of compensation, about 20% of them did not answer the follow-up question of how much they would adopt the practice, creating missing data. We compare three methods to handle the issue of missing data: deletion method, mean imputation, and multiple imputation method. Following these methods, we estimate factors affecting how much farmers may engage in BMPs using a Tobit or Poisson model. The results show that increasing the compensation for using BMPs is more likely to encourage farmers to adopt riparian buffers. Results obtained using the method of multivariate imputation by chained equation are more promising than using the deletion or mean imputation method. The fourth chapter examines whether wealth change and local community interaction may affect BMP adoption. Survey data on BMP adoption are combined with the local community data from publically available sources. Results show that the decrease in land values between 2007 and 2012 discouraged the adoption of riparian buffers; the equine inventory in local communities has positive impact on the adoption of animal fences and nutrient management; the more rural the local communities are, the less likely farmers would fence off livestock from water resources.

Water quality management for agricultural production is a complicated and interesting problem. Hydrological and economic factors must be considered when designing strategies to reduce nutrient runoff from agricultural activities. This dissertation is composed of three chapters that investigate cost-effective ways to mitigate water pollution from agricultural nonpoint pollution sources and explore farmers' incentives when participating in water quality trading programs. Chapter 1 investigates landscape targeting of best management practices (BMPs) based on topographic index (TI) to determine how targeting would affect costs of meeting nitrogen (N) loading goals for Mahantango watershed, Pennsylvania. We use the results from two climate models and the mean of the ensemble of seven climate models to estimate expected climate changes and the Soil and Water Assessment Tool-Variable Source Area (SWAT-VSA) model to predict crop yields and N export. Costs of targeting and uniform placement of BMPs across the entire study area (4.23 km2) are compared under historical and future climate scenarios. We find that with a goal of reducing N loadings by 25%, spatial targeting methods could reduce costs by an average of 30% compared with uniform BMP placement under three historical climate scenarios. Cost savings from targeting are 38% under three future climate scenarios. Chapter 2 scales up the study area to the Susquehanna watershed (71,000 km2). We examine the effects of targeting the required reductions in N runoff within counties, across counties, and both within and across counties for the Susquehanna watershed. We set the required N reduction to 35%. Using the uniform strategy to meet the required N reduction as the baseline, results show that costs of achieving a regional 35% N reduction goal can be reduced by 13%, 31% and 36% with cross-county targeting, within-county targeting and within and across county targeting, respectively. Results from Chapters 1 and 2 suggest that cost effectiveness of government subsidy programs for water quality improvement in agriculture can be increased by targeting them to areas with lower N abatement costs. In addition, targeting benefits are likely to be even larger under climate change. Chapter 3 investigates the landowner's nutrient credit trading behavior when facing the price uncertainty given the credits are allowed to be banked for future use. A two-step decision model is used in this study. For the first step, we determine the landowner's application level of a BMP on working land in the initial time period. The nutrient credits awarded to the landowner depend on the nutrient reduction level at the edge of field generated by the BMP application. For the second step, we use an intertemporal model to examine the landowner's credit trading behavior with stochastic price fluctuations over time and with transaction costs. The theoretical framework is applied with a numerical simulation incorporated with a hydro-economic model and dynamic programming. Nutrient Management (NM) is selected as the BMP on working land to generate N credits. We find that gains to the landowner from credit banking increase with higher price volatility and with higher price drift, but that gains are larger with price volatility. However, for a landowner holding a small amount of nutrient credits, the gains from credit banking are small due to transaction costs. / Doctor of Philosophy / Two considerations are critical for efforts to mitigate nutrient runoff from nonpoint sources: cost effectiveness of strategies to reduce nutrient runoff and landowners' incentives to participate in these programs. This dissertation is composed of three manuscripts, aiming to evaluate the cost effectiveness of government subsidy programs for water quality management in agriculture and investigate the landowner's incentives to participate in water quality trading programs for the Chesapeake Bay watershed. Chapter 1 investigates gains from targeting Best Management Practices (BMPs) under current and future climate conditions based on the soil characteristics relative to uniform BMP application for a small experimental watershed (4.23km2). Chapter 2 scales up the study area to a 71,000 km2 watershed and treats each county within the watershed as a representative farm to explore economic gains from targeting within county and across county based on counties' physical conditions and agricultural patterns. Both Chapters show that cost-effectiveness of government subsidy programs can be improved by spatial targeting BMPs to areas with lower abatement costs. Gains from targeting increase under climate change. In Chapter 3 we shows how a landowner's revenues from nutrient credit selling will be affected if the credits are allowed to be banked for future use when she faces price uncertainty. We find that gains to the landowner from credit banking increase more with higher price volatility than with higher price drift. Gains from banking are largely reduced by transaction costs associated with trading.

Lake Okeechobee is the largest lake in the southeastern United States and is a central component of the hydrology and environment of the Everglades ecosystem in South Florida. The natural state of the lake has been degraded as wetlands and natural habitats in the Lake Okeechobee watershed have been replaced with farms, urban areas, and dairy operations. Excessive phosphorus loadings from these diverse sources have been identified as the leading causes of the lake’s impairment. For more than four decades, many resources have been allocated to regional and local restoration efforts to reduce phosphorus loadings into the lake. However, phosphorus loadings have not decreased and the recovery of the lake could take more time, particularly with today’s limited local budgets. Market-based instruments, such as water quality trading programs, have emerged over the past decades to cost-effectively achieve water quality objectives in impaired watersheds. The main objective of this dissertation was to assess the environmental and economic benefits of implementing a phosphorus trading program in Lake Okeechobee watershed, compared to a conventional command-and-control approach. A comprehensive literature overview of nationally and internationally implemented trading programs was conducted to highlight advantages and challenges of these programs towards achieving water quality goals, and to outline the essential elements of a successful program. Furthermore, a modeling framework, integrating a hydrologic-water quality model with an economic model, was developed to assess the potential cost savings that trading might offer over a command-and-control approach. The modeling framework was applied in three priority basins of the Lake Okeechobee watershed. In each case, while developing trading scenarios to achieve phosphorus load reduction targets, the trading program was less expensive than the conventional command-and-control approach. This research provided the foundation for stakeholders to better understand whether water quality trading has the potential to work in the Lake Okeechobee watershed and to facilitate the development of a pilot program. In addition, it offered some insights on the potential economic opportunities that pollution sources would have by participating in the trading program. The modeling framework developed in this dissertation could facilitate the assessment of future water quality trading programs in other watersheds.

No description available.