With the expansion of offshore renewable energy, countries across the world are researching the different ways to maximize the space between wind turbines by coupling multiple maritime activities within the same ocean space. This technique is referred to as co-location and can result in economic and environmental benefits. Using data from a choice experiment and random utility modeling, this research quantifies public preferences for various co-location options within the lease area of a developing wind farm off Virginia's coastline. Our estimates show that the average Virginia public household is willing-to-pay upwards of $20 per 1,000 acres for co-location activities. By comparing our results to estimated implementation and management costs of each activity, there is a strong indication that the benefits of co-location exceed the costs. The experimental design of this study can be applied to other offshore wind installments around the U.S. and abroad.

Excessive nitrogen (N) pollution in the Chesapeake Bay is threatening ecological health. This study presents a multilayer N flow network model where each network layer represents a stage in the production step from raw agricultural commodities such as corn to final products such as packaged meat. We use this model to assess the impacts of alternative future agricultural production and land use changes on multiple pathways of N pollution within the Chesapeake Bay Watershed (CBW). We analyzed N loss via all pathways under multiple future scenarios, considering crop-specific projections based on empirical data and US Department of Agriculture projections. We found two model parameters, fertilizer nitrogen application rate (FNAR) and feed conversion ratio (FCR), to be particularly important for seeing measurable N loss reductions in the Bay. Our results indicate a large increase in N loss under the business-as-usual trajectory in geographic locations with intensive agricultural production. We found that numerous management scenarios including improvements in FNAR and FCR, N losses fall short of the 25% total maximum daily load targets. Our work suggests that achieving the CBW N loss reduction goals will necessitate large deviations from business as usual. Our model also highlights substantial regional variations in nitrogen loss across the U.S., with central regions like the Corn Belt and Central Valley of California experiencing the highest losses from crop-related stages, while eastern areas such as the Chesapeake Bay exhibit major losses from live animal production, underscoring the need for region-specific management strategies. Thus, implementation of effective N management strategies, combined with improved crop residue management, remains pivotal in mitigating N pollution in the Chesapeake Bay.

High tunnels have been reported to extend the harvest season for fruits and vegetables in several North American regions. This study was conducted to evaluate whether there are additional economic returns from strawberries produced in high tunnel structures compared to open-field in the Commonwealth of Virginia. A total of eight strawberry cultivars were evaluated in a randomized complete block under high tunnel and open-field conditions. Total costs were estimated for all eight cultivars under high tunnel and open-field, and gross and net revenues from all cultivars were estimated over three marketing strategies (pre-pick wholesale, pre-pick retail, and U-pick) for both high tunnel and open-field. The average net revenues per hectare in the high tunnel were −$62,077 (−$25,122 ac−1), −$15,151 (−$6131 ac−1), and −$27,938 (−$11,306 ac−1) for pre-pick wholesale, pre-pick retail, and U-pick, respectively, compared to open-field net revenues of $39,816 ($16,113 ac−1), $112,102 ($45,366 ac−1), and $81,850 ($33,123 ac−1) for wholesale, pre-pick retail, and U-pick, respectively. Net revenues in the high tunnel were lower due to lower yields and higher production costs including overhead cost of the high tunnel structure. Almost all cultivars in the high tunnel generated negative net revenues regardless of the marketing strategy. The exceptions were ‘Camino Real’ which generated positive net revenues with U-pick and pre-pick retail marketing and ‘Merced’ which generated positive net revenues for pre-pick retail marketing. In contrast, net revenues from open-field cultivars were always positive. Results imply that growers should focus on open-field rather than high-tunnel strawberry production. Results are from one season of production. Replication of the study under one or more production seasons would contribute to more robust findings of the economic viability of strawberry production under a high tunnel.

Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program's (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States' largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework's current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.

The Total Maximum Daily Load (TMDL) program established by the United States Environmental Protection Agency (US EPA) to improve America's water quality is being applied to the Chesapeake Bay watershed to mitigate the "dead zone" problem. Agricultural activities are the major nonpoint source of nitrogen (N), contributing 44% of total N to the Bay. Best Management Practices (BMPs) are recognized as an effective way to mitigate N loss of agricultural activities. However, because of physical and economic heterogeneity in agricultural regions, targeting BMPs to areas that produce disproportionate nutrient losses has the potential to reduce the costs of achieving water quality goals. The purpose of this study is to examine the potential to reduce costs of meeting a regional water quality goal by targeting N load reductions within- and across-counties. Based on TMDL developed by the US EPA in 2010 for the Chesapeake Bay watershed, the N reduction goal is 35% for Pennsylvania by 2025. We examine the effects of targeting the required reductions within counties, across counties, and both within and across counties for the Susquehanna watershed. Using the uniform strategy to meet 35% 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. 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.

Agricultural production is a major source of nonpoint source pollution contributing 44% of total nitrogen (N) discharged to the Chesapeake Bay. The United States Environmental Protection Agency (US EPA) established the Total Maximum Daily Load (TMDL) program to control this problem. For the Chesapeake Bay watershed, the TMDL program requires that nitrogen loadings be reduced by 25% by 2025. Climate change may affect the cost of achieving such reductions. Thus, it is necessary to develop cost-effective strategies to meet water quality goals under climate change. We investigate landscape targeting of best management practices (BMPs) based on topographic index (TI) to determine how targeting would affect costs of meeting N loading goals for Mahantango watershed, PA. We use the results from two climate models, CRCM and WRFG, and the mean of the ensemble of seven climate models (Ensemble Mean) 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 (423 ha) were compared under historical and future climate scenarios. Targeting BMP placement based on TI classes reduces costs for achieving water quality goals relative to uniform placement strategies under historical and future conditions. Compared with uniform placement, targeting methods reduce costs by 30, 34, and 27% under historical climate as estimated by the Ensemble Mean, CRCM and WRFG, respectively, and by 37, 43, and 33% under the corresponding estimates of future climate scenarios.

Climate change may increase precipitation, temperatures, and pollution loading and necessitate additional measures and costs to achieve water quality goals. We used two climate change models and the mean of the ensemble of seven climate models (Ensemble Mean), a yield prediction model (Soil and Water Assessment Tool-Variable Source Area), and a farm economic model to estimate how climate change would affect yields and the costs of reducing nitrogen (N) loading in an agricultural subbasin of the Chesapeake Bay. We estimated costs of meeting water quality goals based on the reduction in farm net returns from limits on N loadings under historical and future climate scenarios. Estimated costs of meeting water quality goals increase under future climate for one of the two climate models and for the Ensemble Mean. Major reasons for increased costs are higher predicted N loading from crops and higher N loading reductions to be achieved under future climate. The farm meets N limits by eliminating wheat and reducing corn and soybean production as well as increased use of best management practices (BMPs) including Conservation Reserve Program. Researchers should analyze effects of climate change on the costs of meeting water quality goals using multiple climate change prediction models and considering possible crop substitutions as well as crop and livestock BMPs. Further research should consider how commodity market reactions to producers' choices under climate change affect costs of meeting water quality goals.

The Water Poverty Index (WPI) expands the analysis of China’s water crises from hydrology to a broader focus on integrated water resources management including economic and social factors. This index was revised by principal component analysis (PCA) to avoid arbitrariness of weights and collinearity between variables. However, the traditional PCA is primarily oriented for static data, and it fails to reveal the evolutionary trend of data over time. Moreover, the conventional normalization methods are not adequate when the dimension of time is added to the data. In this study, the transformation of centralized logarithm of initial variable and holistic and dynamic principal component analysis are firstly proposed, then the improved methods are applied to assess water poverty in China using panel data from 2004 to 2012. The estimated WPI shows the growing scale and the clustering trend of regional water poverty. The analysis of influential factors reveals that aquatic environmental pollution is a vital driver of water poverty. Water resource endowment is the second important factor concerning regional water poverty. Inability to adapt to water scarcity, which leads to weak physical water access and low efficiency of water use, is still a critical driver of regional water poverty. Finally, the regional disparities and alleviation strategies of water poverty are discussed.

Reducing nutrient loadings in urban areas is important for water quality improvement programs in many watersheds. Urban nutrient loadings are expected to increase and become more variable under climate change (CC). In this study, a water quality simulation model (SWMM), land cover data layers, and mathematical programming models were used to compare costs of abating nutrient loads under CC in the Difficult Run Watershed located in Fairfax County, Virginia. Predicted costs of abating mean total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) loadings under current climate conditions were compared with those for CC under certainty with a Cost Minimization Model and under uncertainty with a Safety First Model. Total nitrogen loadings abatement had the highest cost followed by TP and TSS abatement in that order. Costs of controlling TP and TSS increased with CC, whereas there was little change in TN control costs. Introducing uncertainty of loadings caused control costs to increase substantially for all three pollutants. The preferred pollutant control strategy was urban stream restoration. Policy makers seeking to meet water quality goals over a multiyear horizon should consider frontloading supplemental best management practices (BMPs) to offset the changes in nutrient loadings predicted for CC. (C) 2017 American Society of Civil Engineers.

The U.S. nursery and greenhouse industry is facing twin challenges of reduced water availability and increased pressure to mitigate pollution from horticultural production. Water-recycling technology (WRT) has been adopted by some nursery producers to improve crop water productivity and to enhance water supply security. This study estimated the economic feasibility of WRT adoption if producers received some portion of retail price premiums for eco-labeled products. Three annual bedding plants, Geraniums (Pelargonium spp.), Petunias (Petunia spp.), and Chrysanthemums (Chrysanthemum spp.) and three broadleaf evergreen plants, Azaleas (Rhododendron spp.), Holly (Ilex spp.), and Boxwood (Buxus spp.) were analyzed based on their sales in the study region of Virginia (VA), Maryland (MD), and Pennsylvania (PA). Of the eight case study nurseries and two synthesized nurseries examined, five showed increased net costs with recycling. However, in almost all cases for which at least a portion of a retail consumer premium was returned to growers, the premium was adequate to compensate for recycling investment costs.

In the future, the U.S. ornamental horticulture industry may be faced with limited water resources and increased requirements to reduce pollution runoff from production areas. The concerns are most evident to outdoor, uncovered container crop production, which relies on daily irrigation. Capture of precipitation and irrigation runoff from ornamental horticulture nurseries to be recycled as irrigation could potentially generate cost savings relative to the cost of alternative water sources. Existing nurseries may incur large investment costs to modify their infrastructure for water capture to recycle. These added costs must be compared with costs of alternative sources such as off-farm municipal or on-farm well water. Using both existing case nurseries and simulated nurseries, this study employed partial budgeting for comparison of annual costs of recapture and recycling to the alternatives of either municipally delivered water or on-farm well extraction. On-site visits were conducted at mid-Atlantic ornamental horticulture operations that recycle water currently to gather data for constructing budgets and to determine factors that enhance or inhibit nursery adoption of recycling. The partial budgeting analysis was followed by breakeven analysis with regard to costs of regrading, pond excavation, and opportunity costs of land to isolate their effects on the nursery adoption decision. Six of eight case nurseries currently obtaining from 20% to 100% of their irrigation needs from recycled water achieve lower production costs as a result of recycling compared with using alternative municipal or well water sources. Recycling would also reduce pollution runoff as water containing nutrients and chemicals would be retained for reuse on the farm rather than being discharged to public water bodies. Two case nurseries and two simulated nurseries that were constructed based on average conditions for nurseries participating in a mail survey see higher production costs as a result of recycling. The cost of land regrading for water recapture, excavating the recapture pond, and the opportunity cost of production area occupied by the recapture pond are critical for determination of the least cost outcome. Public funding incentives for water collection and recycling could motivate increased water conservation and reduced pollution runoff within the horticulture industry.

The Chesapeake Bay Total Maximum Daily Load (TMDL) set by the EPA in 2010 mandates that the Chesapeake Bay watershed partner states (New York, Pennsylvania, Delaware, West Virginia, Maryland, Virginia, and District of Columbia) must significantly reduce their respective nutrient loadings (NL) draining into the Bay by 2025, where NL are defined as Nitrogen (N), Phosphorus (P), and Total Suspended Solids (TSS) loadings. A key component of this reduction will be from non-point source pollution, defined as pollution that cannot be readily traced to a single source. Urban environments, due to large amounts of impervious surface, have been identified as a key non-point source contributor of NL into surrounding watersheds. Surges of NL, or NL “spikes”, into local water systems are more damaging than mean NL alone. Virginia’s Watershed Implementation Plan (WIP), which details how Virginia will meet the Bay TMDL’s NL goals, outlined the need to reduce urban NL. Mean NL and NL variability are expected to increase under climate change (CC). While there are many studies that outline cost-effective ways in which NL may be abated from urban environments, there are comparatively fewer studies that develop predictive frameworks for abating NL under CC. Thus, there is a lack of information regarding water quality policy and how effective it will be in controlling urban NL in the future. Policy makers and their advisors need to begin planning how to address this change. The urbanizing Difficult Run watershed in Fairfax County Virginia was chosen as a test-bed watershed for examining how CC may affect water quality policy in urban environments. There are multiple databases readily available for Difficult Run, and it is similar to many other urban sub-watersheds in Chesapeake Bay watershed. As often prescribed by the Chesapeake Bay Commission, EPA, Chesapeake Bay Program, and Virginia’s WIP, this study will utilize Best Management Practices (BMPs) to reduce NL stemming from the watershed. The NL focus is on Nitrogen. For the purpose of this study, urban BMPs are defined as a type of water pollution control that reduces nutrient export via a stormwater runoff control mechanism. Examples of relevant BMPs include, but are not limited to, bioretention practices, installing green roofs, cultivating urban forest management, restoring urban streams, and reducing shoreline erosion. This study uses mathematical programming to compare how the costs of achieving a given NL reduction will differ under differing climates. More specifically, the first objective is to compare the costs of achieving a given level of reduction in mean NL in the watershed based on historical conditions to those predicted under CC. The second objective is to evaluate effects of changes in variability of nutrient loadings under CC on the costs of achieving NL reductions. The first mathematical programming model is a cost minimization, linear programming model which minimizes the total cost of BMP placement subject to a user-defined reduction in mean NL. Constraints are placed on the number of BMPs that can be allocated to the watershed based on watershed characteristics. For example, the amount of stream buffers that can be installed is constrained by available stream frontage in the watershed. The second model is based on Qiu, Prato, and McCamley’s Safety-First model, which pulls its core construction from the Target Minimization of the Absolute Total Deviation (MOTAD) construction. The model contains two key parameters that can be adjusted by the user, the NL Target, and the probability of exceeding the Target. NL for the watershed were simulated using EPA’s Storm Water Management Model (SWMM) 5.1. Using historical data collected by three USGS water monitoring stations stationed in the watershed, NL were calibrated and validated to match historical NL for years 1971-1998. CC nutrient loading data were then simulated for years 2041-2068 where SWMM used input data generated from the North American Regional Climate Change Assessment Program (NARCCAP) regional climate model (RCM) MM5I_cssm, which was modeled by Andrew Ross and Raymond Najjar of the Department of Meteorology at Penn State. Land constraints for the mathematical programming model were derived using a Geographic Information System (GIS). The data were compiled from sources including, but not limited to, Fairfax County Open GIS data base, USGS, ESRI, Virginia LIDAR, National Land Cover Database, and U.S. Soil Survey. Through analyzing these raster and vector data sets, geospatial information was derived regarding average slope percent, percent impervious surface, water table separation, and hydric soil grouping among others. The geospatial information was transferred into the mathematical programming models to limit the specific acreage for BMPs. Results Preliminary cost minimization results for N loading reduction show heavy favoritism for urban stream restoration, a commonly recommended and effective BMP. However, when taking into consideration the limited stream feet available for restoration due to Chesapeake Bay Protection Area land classifications, Low Impact Development (LID) practices become the principal BMPs chosen. Examples of LID include bioretention, bioswale, and permeable pavement. Percent N loading reductions were parametrically varied from zero to twenty-five percent in order to give policy makers additional information about the way in which costs behave for N loading abatement. From zero to roughly eighteen percent N loadings reduced, the costs rise in a linear fashion. From eighteen percent onward, the costs increase at an increasing rate forming a convex cost frontier. This behavior fits with most economic prediction where the marginal cost of pollution abatement is expected to increase at an increasing rate. Work is currently underway to evaluate the effects of climate change on costs of reducing mean NL and to evaluate costs of reducing NL under risk using the safety-first model. Preliminary results indicate that CC increases the variability of NL implying that costs of meeting water quality goals will be higher under CC when risk is considered. Discussion Potential Designing water quality policy that incorporates structural and land use change can no longer be based on historic conditions alone. CC is expected to alter many of the environmental variables which water quality and economic modelers utilize to construct policy recommendations. The public desires to improve water quality, yet resources to achieve goals are limited. Therefore, it is important that policy models incorporate the effects of CC, so water quality programs can be efficiently adapted to match these changing conditions. References: Qiu, Zeyuan, Tony Prato, and Francis McCamley. “Evaluating Environmental Risks Using Safety-First Constraints.” American Journal of Agricultural Economics 83(2)(May 2001): 402-413. Storm Water Management Model Reference Model Volume 1 – Hydrology (2015). Office of Research and Development: Water Supply and Water Resources Division. National Risk Management Laboratory. Environmental Protection Agency. Cincinnati, OH.

Recycling irrigation water can provide water during periods of drought for horticulture operations and can reduce nonpoint-source pollution, but water recycling increases production costs and can increase risk of disease infestation from waterborne pathogens such as Pythium and Phytophthora. This study of water recycling adoption by horticultural growers in Virginia, Maryland, and Pennsylvania finds that the potential for increased disease infestation would reduce growers' probability of adopting water recycling. Widespread adoption of recycling irrigation water would require government incentives or coercion or growers' ability to pass cost increases on to customers.

The Chesapeake Bay Total Maximum Daily Load (TMDL) set by the EPA in 2010 mandates that the Chesapeake Bay watershed partner states (New York, Pennsylvania, Delaware, West Virginia, Maryland, Virginia, and District of Columbia) must significantly reduce their respective nutrient loadings (NL) draining into the Bay by 2025, where NL are defined as Nitrogen (N), Phosphorus (P), and Total Suspended Solids (TSS) loadings. A key component of this reduction will be from non-point source pollution, defined as pollution that cannot be readily traced to a single source. Urban environments, due to large amounts of impervious surface, have been identified as a key non-point source contributor of NL into surrounding watersheds. Surges of NL, or NL “spikes”, into local water systems are more damaging than mean NL alone. Virginia’s Watershed Implementation Plan (WIP), which details how Virginia will meet the Bay TMDL’s NL goals, outlined the need to reduce urban NL. Mean NL and NL variability are expected to increase under climate change (CC). While there are many studies that outline cost-effective ways in which NL may be abated from urban environments, there are comparatively fewer studies that develop predictive frameworks for abating NL under CC. Thus, there is a lack of information regarding water quality policy and how effective it will be in controlling urban NL in the future. Policy makers and their advisors need to begin planning how to address this change. The urbanizing Difficult Run watershed in Fairfax County Virginia was chosen as a test-bed watershed for examining how CC may affect water quality policy in urban environments. There are multiple databases readily available for Difficult Run, and it is similar to many other urban sub-watersheds in Chesapeake Bay watershed. As often prescribed by the Chesapeake Bay Commission, EPA, Chesapeake Bay Program, and Virginia’s WIP, this study will utilize Best Management Practices (BMPs) to reduce NL stemming from the watershed. The NL focus is on Nitrogen. For the purpose of this study, urban BMPs are defined as a type of water pollution control that reduces nutrient export via a stormwater runoff control mechanism. Examples of relevant BMPs include, but are not limited to, bioretention practices, installing green roofs, cultivating urban forest management, restoring urban streams, and reducing shoreline erosion. This study uses mathematical programming to compare how the costs of achieving a given NL reduction will differ under differing climates. More specifically, the first objective is to compare the costs of achieving a given level of reduction in mean NL in the watershed based on historical conditions to those predicted under CC. The second objective is to evaluate effects of changes in variability of nutrient loadings under CC on the costs of achieving NL reductions. The first mathematical programming model is a cost minimization, linear programming model which minimizes the total cost of BMP placement subject to a user-defined reduction in mean NL. Constraints are placed on the number of BMPs that can be allocated to the watershed based on watershed characteristics. For example, the amount of stream buffers that can be installed is constrained by available stream frontage in the watershed. The second model is based on Qiu, Prato, and McCamley’s Safety-First model, which pulls its core construction from the Target Minimization of the Absolute Total Deviation (MOTAD) construction. The model contains two key parameters that can be adjusted by the user, the NL Target, and the probability of exceeding the Target. NL for the watershed were simulated using EPA’s Storm Water Management Model (SWMM) 5.1. Using historical data collected by three USGS water monitoring stations stationed in the watershed, NL were calibrated and validated to match historical NL for years 1971-1998. CC nutrient loading data were then simulated for years 2041-2068 where SWMM used input data generated from the North American Regional Climate Change Assessment Program (NARCCAP) regional climate model (RCM) MM5I_cssm, which was modeled by Andrew Ross and Raymond Najjar of the Department of Meteorology at Penn State. Land constraints for the mathematical programming model were derived using a Geographic Information System (GIS). The data were compiled from sources including, but not limited to, Fairfax County Open GIS data base, USGS, ESRI, Virginia LIDAR, National Land Cover Database, and U.S. Soil Survey. Through analyzing these raster and vector data sets, geospatial information was derived regarding average slope percent, percent impervious surface, water table separation, and hydric soil grouping among others. The geospatial information was transferred into the mathematical programming models to limit the specific acreage for BMPs. Results Preliminary cost minimization results for N loading reduction show heavy favoritism for urban stream restoration, a commonly recommended and effective BMP. However, when taking into consideration the limited stream feet available for restoration due to Chesapeake Bay Protection Area land classifications, Low Impact Development (LID) practices become the principal BMPs chosen. Examples of LID include bioretention, bioswale, and permeable pavement. Percent N loading reductions were parametrically varied from zero to twenty-five percent in order to give policy makers additional information about the way in which costs behave for N loading abatement. From zero to roughly eighteen percent N loadings reduced, the costs rise in a linear fashion. From eighteen percent onward, the costs increase at an increasing rate forming a convex cost frontier. This behavior fits with most economic prediction where the marginal cost of pollution abatement is expected to increase at an increasing rate. Work is currently underway to evaluate the effects of climate change on costs of reducing mean NL and to evaluate costs of reducing NL under risk using the safety-first model. Preliminary results indicate that CC increases the variability of NL implying that costs of meeting water quality goals will be higher under CC when risk is considered. Discussion Potential Designing water quality policy that incorporates structural and land use change can no longer be based on historic conditions alone. CC is expected to alter many of the environmental variables which water quality and economic modelers utilize to construct policy recommendations. The public desires to improve water quality, yet resources to achieve goals are limited. Therefore, it is important that policy models incorporate the effects of CC, so water quality programs can be efficiently adapted to match these changing conditions. References: Qiu, Zeyuan, Tony Prato, and Francis McCamley. “Evaluating Environmental Risks Using Safety-First Constraints.” American Journal of Agricultural Economics 83(2)(May 2001): 402-413. Storm Water Management Model Reference Model Volume 1 – Hydrology (2015). Office of Research and Development: Water Supply and Water Resources Division. National Risk Management Laboratory. Environmental Protection Agency. Cincinnati, OH.

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Policymakers are concerned about nitrogen and phosphorus export to water bodies. Exports may be reduced by paying farmers to adopt practices to reduce runoff or by paying performance incentives tied to estimated run-off reductions. We evaluate the cost-effectiveness of practice and performance incentives for reducing nitrogen exports. Performance incentives potentially improve farm-level and allocative efficiencies relative to practice incentives. However, the efficiency improvements can be undermined by baseline shifts when growers adopt crops that enhance the performance payments but cause more pollution. Policymakers must carefully specify rules for performance-incentive programs and payments to avoid such baseline shifting.

In response to economic and environmental concerns, Water-Recycling Technologies (WRT) have been developed to reduce water consumption and surface run-off in horticultural operations. Water recirculation provides the potential for water conservation and may also reduce grower costs in the long run. However, WRT comes with increased risk of disease from water-borne pathogens such as Pythium and Phytophthora, which can cause devastating plant losses. In addition, WRT entail infrastructure investment costs to capture, treat, and recirculate water. These cost and disease concerns dissuade some growers from adopting WRT. More information is needed about producers’ irrigation and disease management practices and their attitudes toward containment and recirculation of irrigation runoff. A mail survey was administered in February 2013 to horticultural nursery growers in Virginia, Maryland, and Pennsylvania. Information was gathered about the firm and respondents’ demographic characteristics, plus production, irrigation, and disease management practices. The survey incorporates a choice experiment analyzing willingness to accept water recycling based upon hypothetical disease outbreak and water shortage probabilities and associated percentage cost increases. This information is related to the respondent’s recycling choices using a conditional logit model to evaluate the effects of disease probability, drought probability, and water recirculation cost on producers’ willingness to adopt waterrecycling technologies.

Two formal preference‐elicitation methodologies—conjoint analysis and the analytical hierarchical process—were applied to examine the actions taken by homeowners living in a premise plumbing failure‐prone area and the decision‐making they used to minimize their risk resulting from corrosion, cost, and other issues related to home plumbing. Most households preferred simply to stay with their current plumbing materials rather than install an upgrade to reduce the risk of corrosion or purchase insurance against corrosion damage. Health, taste, and odor were dominant considerations for consumers. It was interesting that some survey respondents answered one way when stating preferences but behaved differently when making real‐life choices. This information will be helpful for policy experts and utility companies seeking new ways to deal with premise plumbing issues.