Climate change impacts hydrology, nutrient cycling, agricultural conservation practices, and greenhouse gas (GHG) emissions. The Chesapeake Bay and its watershed are subject to the largest and most expensive Total Maximum Daily Load (TMDL) ever developed. It is unclear if the TMDL can be met given climate change and variability (e.g., extreme weather events). The objective of this dissertation is to quantify the impact of climate change and climate on water resources, nutrient cycling and export in agroecosystems, and agricultural conservation practices in the Chesapeake Bay watershed. This is accomplished by developing and employing a suite of modelling tools. GHG emissions from agroecosystems, particularly nitrous oxide (N2O), are an increasing concern. To quantify N2O emissions a routine was developed for the Soil and Water Assessment Tool (SWAT) model. The new routine predicts N2O and di-nitrogen (N2) emissions by coupling the C and N cycles with soil moisture, temperature, and pH in SWAT. The model uses reduction functions to predict total denitrification (N2 + N2O production) and partitions N2 from N2O using a ratio method. The SWAT nitrification routine was modified to predict N2O emissions using reduction functions. The new model was tested using GRACEnet data at University Park, Pennsylvania, and West Lafayette, Indiana. Results showed strong correlations between plot measurements of N2O flux and the model predictions for both test sites and suggest that N2O emissions are particularly sensitive to soil pH and soil N, and moderately sensitive to soil temperature/moisture and total soil C levels. The new GHG model was then used to analyze the impact of climate change and extreme weather conditions on the denitrification rate, N2O emissions, and nutrient cycling/export in the 7.4 km2 WE38 watershed in Pennsylvania. Climate change impacts hydrology and nutrient cycling by changing soil moisture, stoichiometric nutrient ratios, and soil temperature, potentially complicating mitigation measures. To quantify the impact of climate change we forced the new GHG model with downscaled and bias-corrected regional climate model output and derived climate anomalies to assess their impact on hydrology, nitrate (NO3-), phosphorus (P), and sediment export, and on emissions of N2O and N2. Model-average (± standard deviation) results indicate that climate change, through an increase in precipitation, will result in moderate increases in winter/spring flow (2.7±10.6 %) and NO3- export (3.0±7.3 %), substantial increases in dissolved P (DP, 8.8±19.8 %), total P (TP, 4.5±11.7 %), and sediment (17.9±14.2 %) export, and greater N2O (63.3±50.8 %) and N2 (17.6±20.7 %) emissions. Conversely, decreases in summer flow (-12.4±26.7 %) and the export of P (-11.4±27.4 %), TP (-7.9±24.5 %), sediment (-4.1±21.4 %), and NO3- (-12.2±31.4 %) are driven by greater evapotranspiration from increasing summer temperatures. Increases in N2O (20.1±29.3 %) and decreases in N2 (-13.0±14.6 %) are also predicted in the summer and driven by increases in soil moisture and temperature. In an effort to assess the impact of climate change at a regional level, the model was then scaled-up to the entire Susquehanna River basin and was used to evaluate if agricultural best management practices (BMPs) can offset the impact of climate change. Agricultural BMPs are increasingly and widely employed to reduce diffuse nutrient pollution. Climate change can complicate the development, implementation, and efficiency of BMPs by altering hydrology, nutrient cycling, and erosion. We select and evaluate four common BMPs (buffer strips, strip crop, no-till, and tile drainage) to test their response to climate change. We force the calibrated model with six downscaled global climate models (GCMs) for a historic period (1990-2014) and two future scenario periods (2041-2065) and (2075-2099) and quantify the impact of climate change on hydrology, NO3-, total N (TN), DP, TP, and sediment export with and without BMPs. We also tested prioritizing BMP installation on the 30% of agricultural lands that generate the most runoff (e.g., critical source areas-CSAs). Compared against the historical baseline and excluding the impact of BMPs, the ensemble model mean (± standard deviation?) predictions indicate that climate change results in annual increases in flow (4.5±7.3%), surface runoff (3.5±6.1%), sediment export (28.5±18.2%) and TN (9.5±5.1%), but decreases in NO3- (12±12.8%), DP (14±11.5%), and TP (2.5±7.4%) export. When agricultural BMPs are simulated most do not appreciably change the overall water balance; however, tile drainage and strip crop decrease surface runoff generation and the export of sediment, DP, and TP, while buffer strips reduced N export substantially. Installing BMPs on critical source areas (CSAs) results in nearly the same level of performance for most practices and most pollutants. These results suggest that climate change will influence the performance of BMPs and that targeting BMPs to CSAs can provide nearly the same level of water quality impact as more widespread adoption. Finally, recognizing that all of these model applications have considerable uncertainty associated with their predictions, we develop and employ a Bayesian multi-model ensemble to evaluate structural model prediction uncertainty. The reliability of watershed models in a management context depends largely on associated uncertainties. Our Objective is to quantify structural uncertainty for predictions of flow, sediment, TN, and TP predictions using three models: the SWAT-Variable Source Area model (SWAT-VSA), the standard SWAT model (SWAT-ST), and the Chesapeake Bay watershed model (CBP-model). We initialize each of the models using weather, soil, and land use data and analyze outputs of flow, sediment, TN, and TP for the Susquehanna River basin at the Conowingo Dam in Conowingo, Maryland. Using these three models we fit Bayesian Generalized Non - Linear Multilevel Models (BGMM) for flow, sediment, TN, and TP and obtain estimated outputs with 95% confidence intervals. We compare the BGMM results against the individual model results and straight model averaging (SMA) results using a split time period analysis (training period and testing period) to assess the BGMM in a predictive fashion. The BGMM provided better predictions of flow, sediment, TN, and TP compared to individual models and the SMA during the training period. However, during the testing period the BGMM was not always the best predictor; in fact, there was no clear best model during the testing period. Perhaps more importantly, the BGMM provides estimates of prediction uncertainty, which can enhance decision making and improve watershed management by providing a risk-based assessment of outcomes. / Ph. D.

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

Stream crossings are an integral component of forest road systems that provide access for timber harvesting and silvicultural activities. Stream crossings and their associated approaches are often the most critical point of concern for water quality along forest roads. Several types of crossings are used for extracting timber, but limited studies actually compare different types of stream crossings with regard to their effect on water quality. The objectives of this study were to examine four different stream crossing structures: 1) steel bridges, 2) pole bridges (pipe with poles), 3) standard culverts, and 4) re-enforced fords (with GeoWeb or Geotextile) to determine the influence of stream crossing type on water quality and to evaluate erosion associated with stream crossing approaches. We also evaluated each site at four different time intervals to determine if water quality was more affected during different stages of the operations. Prior to operational timber harvests, we identified six replications for each type of crossings (4 fords) and collected data at four time intervals: 1) prior to reopening or installation of crossing, 2) after crossing installation, 3) during harvest operation, and 4) after road closure. Potential erosion rates from approaches to the crossings were estimated by collecting the road/site information necessary to estimate erosion with the Water Erosion Prediction Project for forest roads (WEPP) and the forest version of the Universal Soil Loss Equation (USLE). In-stream water samples were collected at fixed locations above and below each crossing and were evaluated for total dissolved solids (TDS), pH, conductivity, water temperature, and total suspended solids (TSS) or sediment concentration. Steel bridge crossings generally caused the least amount of water quality disturbance. Model-generated estimates of erosion demonstrated that culvert crossings were associated with the highest average soil loss potential. Although steel bridge crossings had the best overall results, pole bridges proved to be a viable option for ephemeral or intermittent streams due to low potential of soil loss. Ford crossings were found to impact water quality indicators, but showed a decrease in total dissolved solids (TDS) after installation, prior to harvest. Overall, the steel skidder bridges were generally the best crossing type, but any of the crossings can be used effectively with minimal impact under specific site conditions and with judicious installation, use, and closure. Road/skid trail location and adherence to existing road grade, water control, cover, and closure best management practices are critical for protection of water quality at stream crossings. / Master of Science

Master of Landscape Architecture / Department of Landscape Architecture/Regional and Community Planning / Lee R. Skabelund / Stormwater management is typically approached from different perspectives by practicing professionals. As such, stormwater planning/design is not always completed as a multi-disciplinary coalition of experts using holistic and synergistic methods. For a number of years, engineers and design professionals, particularly landscape architects, have been employing various strategies and techniques to address on-site stormwater management in terms of water quality and quantity. There is increasing awareness that in order to create solutions that are effective over both the short and long-term a landscape architect’s approach needs to account for the health, safety and welfare perspectives carried by engineers, the unique aspects of particular project sites, their surroundings and bio-regional context, as well as the perceptions of clients, other key stakeholders, and the broader public. This research investigates the various criteria integral to developing an analytic framework for ecologically-appropriate stormwater planning/design (Sustainable Stormwater Evaluation and Site Assessment or SSWESA). SSWESA is proposed as a type of decision-tree for site analysis of sustainable systems pertaining to stormwater. Using the SSWESA process is expected to help researchers and professionals make better planning and design decisions as they select and implement appropriate best management practices (BMPs) for a given site and context. My intent in developing SSWESA is to help designers assess existing and potential stormwater functions at the site scale in order to promote sustainable planning and design based upon the important principle: “First, do no harm”. It is also my intent to promote further research related to sustainability by providing references and sources from experts in the various fields related to ecologically-based stormwater management. A review of the literature related to ecological factors relevant to low impact stormwater management assisted in the development and refinement of the criteria for stormwater assessment and evaluation. In this report, the SSWESA framework is tested on a public school property in Manhattan, Kansas to demonstrate how the framework is applied and to understand the questions and issues that arise from its use.

Using data envelopment analysis with principal components, we calculate an adoption-intensity index for herbicide-resistance best management practices (BMPs). Empirical results for over 1,100 farmers in twenty-two U.S. states suggest that many farmers could improve their herbicide resistance BMP adoption. Two-limit truncated regression results show that higher yields and a greater proportion of acres planted with Roundup Ready (R) seeds motivate weed BMP adoption. While soybean and corn farmers have lower adoption intensity than cotton farmers, farmer educational attainment and greater concern for herbicide effectiveness and for human and environmental safety are found to help increase the adoption of weed BMPs.

A comprehensive literature review was undertaken in order to define and assess the sustainability and resiliency characteristics associated with grass-based and confinement dairy farming. Primarily as a result of reduced input costs, grass-based dairy farming often enhances profitability over confinement systems, especially on small farms. Further, conversion of tilled soil to permanent pasture has been shown to significantly reduce harmful sediment and nutrient transport into waterways. Perennial forage also acts as a carbon sink, curtailing or even negating a grass-based farm's carbon footprint. Finally, social benefits derived from enhanced nutrition and higher quality of life are also associated with grass-based dairy farming. Given that policy goals of the State of Vermont include both bolstering farm viability and reducing farm-related runoff, two questions are then raised. What is the most effective way to incentivize the adoption of rotational grazing in Vermont? And what types of farms are best suited to its use? A series of interviews with dairy experts and farmers was conducted as a preliminary investigation into these questions. This qualitative evidence suggested that farmers generally adopted grass-based dairying after observing a peer's success with the method, suggesting that a key leverage point may be peer-based learning. A behavioral economics game was developed to evaluate the role of peer networks in facilitating decision-making under conditions of uncertainty. A computerized game platform simulated networks of small dairy farm enterprises, with participants acting as farm managers. Treatments varied the size of peer networks, as well as the inclusion of a perfectly-performing automated 'seed player.' Participants could base their decisions upon the successes of their peers. They received a cash incentive based on their farms' performance. Results indicated that players with higher numbers of peers made better economic decisions on average. The inclusion of a 'seed player' within a network, which modeled the ideal behavior, also facilitated better decision-making. Both of these correlations were statistically significant. Furthermore, the shape of the 'diffusion curve' of new adoptees confirmed literature on the dynamics of innovation diffusion. Public policy implications from this work include an increased focus on facilitating peer-to-peer learning among farmers where Best Management Practice adoption is a policy goal. To further evaluate the potential for peer learning to facilitate positive change, the Dairy Farm Transitions Agent Based Model (DFTABM) was developed. The model was calibrated using existing datasets along with the qualitative and quantitative results described above. It forecasts effects on farm profitability, attrition, and soil loss arising from varying assumptions about peer network connectivity, peer emulation, macroeconomic trends, and agri-environmental policy. Nine experimental treatments were assessed. Overall, it was found that high rates of emulation coupled with high rates of connectivity'especially targeted connectivity among smaller farms'yielded the best balance of farm viability and reduction in soil loss. The establishment of a performance-based tax credit had no clear correlation with the resulting soil loss figures predicted by the model. Policy implications from this study include the finding that direct payment schemes for reduction in environmental harm may not always have their intended effects, whereas policies that enhance peer-to-peer learning opportunities, especially among the proprietors of smaller farms, may present an effective and relatively affordable means by which to bolster farm profitability while also reducing environmental degradation.

Snapping turtles (Chelydra serpentina) are being harvested in unprecedented numbers in the United States (US) to meet the needs of international markets. Over three million live snapping turtles from farm and wild caught stock were exported from the US to Asia in 2012-14 alone. In the Commonwealth of Virginia, records indicate that 29,860 snapping turtles were commercially harvested between 2000 and 2015. Size limits are often used to regulate harvest pressure in snapping turtles and other game species. I analyzed the historic harvest of eleven US states to test the efficacy of minimum-size limit regulations at reducing commercial harvest pressure. Further, I conducted a four-year mark-recapture study on three Virginia waterways that have each experienced a different level of historic commercial harvest. As part of the larger mark/recapture project, I conducted radio telemetry on 23 turtles to examine seasonal, body size, and sex-specific effects on home range size of snapping turtles in a lotic system. I incorporated survival and growth rates from this study, demographic rates from the literature, and state-collected harvest rates into a hybrid age/stage population matrix model to estimate the population growth rate at three harvest levels (0%, 21%, 58%) that were estimated based on annual commercial landing reports on file with the Virginia Department of Game and Inland Fisheries. I used the model to test population viability under multiple size limit regulations, and used sensitivity analyses to identify adult stages most critical to the overall population growth rate. Based on model estimates, size-limits were effective at reducing harvest by 30-87% in years with high harvest pressure. However, most size limit regulations result in the removal of larger breeding adults, which has been shown to be detrimental to long term population viability. Based on radio-telemetry data, I found evidence that snapping turtles utilize lotic and lentic habitats differently, which can have implications for management of this iconic species. Matrix population modelling predicted that population densities at the moderate and high harvest site were reduced by 47% and 62%, respectively, when compared to the no harvest site. Model results indicate that, while an increase to the minimum-size limit in 2012 protected a larger portion of the population, that the commercial harvest of snapping turtles in the Commonwealth of Virginia is not sustainable under current state regulations. Our analysis suggests that minimum-size limits of 35.6 cm curved carapace length or greater will maintain viable populations by protecting a larger portion of reproducing snapping turtles within a population.

This thesis presents the results of exploratory sociological research designed to better understand how farmers select agricultural practices with the potential to effect water quality. The primary research methodology is a Rapid Rural Appraisal of thirty farms in five rural municipalities in Saskatchewan, Canada during the year 2000 growing season. The data establishes that a variety of economic, institutional, organizational, and social factors interact in dynamic ways to influence farmer resource management decisions and that the resulting agricultural practices have the potential for subtle and dramatic effects on water quality in Saskatchewan. Risk-mitigating farming methods known as Best Management Practices (BMPs) are interpreted by farmers in the field research as being both appropriate and problematic. Alternative initiatives and communication strategies are identified in the field data that offer support to production and productivity in the agriculture sector while also promoting water quality. The research suggests that measures such as providing accessible public water quality data, promoting water treatment for individual households, and educating rural women and youth about water quality issues may merit further investigation.

This thesis presents the results of exploratory sociological research designed to better understand how farmers select agricultural practices with the potential to effect water quality. The primary research methodology is a Rapid Rural Appraisal of thirty farms in five rural municipalities in Saskatchewan, Canada during the year 2000 growing season. The data establishes that a variety of economic, institutional, organizational, and social factors interact in dynamic ways to influence farmer resource management decisions and that the resulting agricultural practices have the potential for subtle and dramatic effects on water quality in Saskatchewan. Risk-mitigating farming methods known as Best Management Practices (BMPs) are interpreted by farmers in the field research as being both appropriate and problematic. Alternative initiatives and communication strategies are identified in the field data that offer support to production and productivity in the agriculture sector while also promoting water quality. The research suggests that measures such as providing accessible public water quality data, promoting water treatment for individual households, and educating rural women and youth about water quality issues may merit further investigation.

This study focused on development of a continuous watershed-scale modelling approach capable of evaluating sediment removal performance of vegetative filter strips (VFS). This was done by integrating the single-event hydrologic and sediment transport model AGNPS with the event-based VFS model (VFSMOD) applying the methodology developed by Sebti and Rudra (2010), and also through the development and incorporation of sub-models capable of describing changes in hydrologic conditions between rainfall events into the integrated models. For modeling purposes, the buffer zone is divided to segments called “buffer cells”. The upstream source area corresponding to each buffer cell and the flow-path connecting the area to the stream are identified, and runoff and sediment generated within each area is simulated for each event applying AGNPS. Using VFSMOD, performance analysis of VFS is conducted for each buffer cell. By applying the developed “continuous simulation” sub-models the hydrologic conditions prior to each event were determined.