MODELING WATER QUALITY FOR SWITCHGRASS CROP PRODUCTION: IMPLICATIONS FOR BIOENERGY SUSTAINABILITY IN EAST TENNESSEE

With passing of the US Energy Independence and Security Act (EISA) of 2007, there has been considerable research conducted on the sustainability of bioenergy crop production in the United States; switchgrass has shown particular potential for bioenergy production in East Tennessee. Many studies evaluating the environmental impact switchgrass has on runoff and water quality use the Soil and Water Assessment Tool (SWAT) for watershed modeling. Because SWAT is a lumped watershed model, it evaluates the result of hydrological processes for each hydrologic response unit (HRU), without accounting for the physical interactions between these HRUs. The Water Erosion Prediction Project (WEPP) model is a physically derived, distributed watershed model that can simulated runoff and sediment transport within the watershed, accounting for the interactions that take place between these response units. This research sought to calibrate both a WEPP and SWAT model to measured data collected from a drainage basin in Lenoir City, Tennessee, an area known for growing switchgrass for bioenergy. In addition, this research evaluated the use of buffer strips as a sustainable approach to switchgrass implementation. Model calibration was evaluated based on the Nash-Sutcliffe Efficiency coefficient, which evaluates the extent to which a model reflects the measured data. Final discharge calibration yielded NSE coefficients of -0.18 and -0.09 for SWAT and WEPP, respectively. Final sediment calibration for the SWAT and WEPP models, however, could be calibrated to an NSE coefficient of -0.34 and -0.48, respectively. Calibration efforts failed, the WEPP model did outperform the SWAT model for runoff calibration. In simulating bioenergy buffer strips (BBSs), the WEPP model indicated that one or two strategically placed BBSs can have a 13% reduction in runoff and sediment delivery per storm event; results suggests that strategic use of bioenergy buffer strips can have improved reduction in runoff or sediment yield. The improved calibration results of the WEPP model indicated that a distributed hydrology and erosion model may be valuable for modeling water quality impacts of switchgrass production in a watershed. Results also indicated the potential for further investigation into how sediment transport is addressed in the SWAT and WEPP models

Changes in the Spatial Allocation of Cropland in the Ft. Cobb Watershed as a Result of Environmental Restrictions

Pollution runoff estimates from SWAT are used in a mathematical programming model to optimally model site-specific crop and conservation practices for pollution abatement in the Ft. Cobb watershed in Southwestern Oklahoma. Results indicate the tradeoffs between producer income, sediment and nutrient runoff and the spatial allocation of crops in the watershed.Environmental Economics and Policy,

Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

Modeling is a useful way to understand human and climate change impacts on the water resources of agricultural watersheds. Calibration and validation methodologies are crucial in forecasting assessments. This study explores the best calibration methodology depending on the level of hydrological alteration due to human-derived stressors. The Soil and Water Assessment Tool (SWAT) model is used to evaluate hydrology in South-West Europe in a context of intensive agriculture and water scarcity. The Index of Hydrological Alteration (IHA) is calculated using discharge observation data. A comparison of two SWAT calibration methodologies are done; a conventional calibration (CC) based on recorded in-stream water quality and quantity and an additional calibration (AC) adding crop managements practices. Even if the water quality and quantity trends are similar between CC and AC, water balance, irrigation and crop yields are different. In the context of rainfall decrease, water yield decreases in both CC and AC, while crop productions present opposite trends (+33% in CC and -31% in AC). Hydrological performance between CC and AC is correlated to IHA: When the level of IHA is under 80%, AC methodology is necessary. The combination of both calibrations appears essential to better constrain the model and to forecast the impact of climate change or anthropogenic influences on water resources

Modeling nitrogen loadings from agricultural soils in southwest China with modified DNDC

Degradation of water quality has been widely observed in China, and loadings of nitrogen (N) and other nutrients from agricultural systems play a key role in the water contamination. Process‐based biogeochemical models have been applied to quantify nutrient loading from nonpoint sources at the watershed scale. However, this effort is often hindered by the fact that few existing biogeochemical models of nutrient cycling are able to simulate the two‐dimensional soil hydrology. To overcome this challenge, we launched a new attempt to incorporate two fundamental hydrologic features, the Soil Conservation Service curve and the Modified Universal Soil Loss Equation functions, into a biogeochemistry model, Denitrification‐Decomposition (DNDC). These two features have been widely utilized to quantify surface runoff and soil erosion in a suite of hydrologic models. We incorporated these features in the DNDC model to allow the biogeochemical and hydrologic processes to exchange data at a daily time step. By including the new features, DNDC gained the additional ability to simulate both horizontal and vertical movements of water and nutrients. The revised DNDC was tested against data sets observed in a small watershed dominated by farmlands in a mountainous area of southwest China. The modeled surface runoff flow, subsurface drainage flow, sediment yield, and N loading were in agreement with observations. To further observe the behaviors of the new model, we conducted a sensitivity test with varied climate, soil, and management conditions. The results indicated that precipitation was the most sensitive factor determining the rate of N loading from the tested site. A Monte Carlo test was conducted to quantify the potential uncertainty derived by variations in four selected input parameters. This study demonstrates that it is feasible and effective to use enhanced biogeochemical models such as DNDC for quantifying N loadings by incorporating basic hydrological features into the model framework

A spatially distributed model for the dynamic prediction of sediment erosion and transport in mountainous forested watersheds

Erosion and sediment transport in a temperate forested watershed are predicted with a new sediment model that represents the main sources of sediment generation in forested environments (mass wasting, hillslope erosion, and road surface erosion) within the distributed hydrology-soil-vegetation model (DHSVM) environment. The model produces slope failures on the basis of a factor-of-safety analysis with the infinite slope model through use of stochastically generated soil and vegetation parameters. Failed material is routed downslope with a rule-based scheme that determines sediment delivery to streams. Sediment from hillslopes and road surfaces is also transported to the channel network. A simple channel routing scheme is implemented to predict basin sediment yield. We demonstrate through an initial application of this model to the Rainy Creek catchment, a tributary of the Wenatchee River, which drains the east slopes of the Cascade Mountains, that the model produces plausible sediment yield and ratios of landsliding and surface erosion when compared to published rates for similar catchments in the Pacific Northwest. A road removal scenario and a basin-wide fire scenario are both evaluated with the model

Modeling nitrogen loading in a small watershed in southwest China using a DNDC model with hydrological enhancements

The degradation of water quality has been observed worldwide, and inputs of nitrogen (N), along with other nutrients, play a key role in the process of contamination. The quantification of N loading from non-point sources at a watershed scale has long been a challenge. Process-based models have been developed to address this problem. Because N loading from non-point sources result from interactions between biogeochemical and hydrological processes, a model framework must include both types of processes if it is to be useful. This paper reports the results of a study in which we integrated two fundamental hydrologic features, the SCS (Soil Conservation Service) curve function and the MUSLE (Modified Universal Soil Loss), into a biogeochemical model, the DNDC. The SCS curve equation and the MUSLE are widely used in hydrological models for calculating surface runoff and soil erosion. Equipped with the new added hydrologic features, DNDC was substantially enhanced with the new capacity of simulating both vertical and horizontal movements of water and N at a watershed scale. A long-term experimental watershed in Southwest China was selected to test the new version of the DNDC. The target watershed\u27s 35.1 ha of territory encompass 19.3 ha of croplands, 11.0 ha of forest lands, 1.1 ha of grassplots, and 3.7 ha of residential areas. An input database containing topographic data, meteorological conditions, soil properties, vegetation information, and management applications was established and linked to the enhanced DNDC. Driven by the input database, the DNDC simulated the surface runoff flow, the subsurface leaching flow, the soil erosion, and the N loadings from the target watershed. The modeled water flow, sediment yield, and N loading from the entire watershed were compared with observations from the watershed and yielded encouraging results. The sources of N loading were identified by using the results of the model. In 2008, the modeled runoff-induced loss of total N from the watershed was 904 kg N yr−1, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr−1) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr−1) dominated the gaseous N losses. The study indicated that process-based biogeochemical models such as the DNDC could contribute more effectively to watershed N loading studies if the hydrological components of the models were appropriately enhanced

Using the soil and water assessment tool to simulate the pesticide dynamics in the data scarce Guayas River Basin, Ecuador

Agricultural intensification has stimulated the economy in the Guayas River basin in Ecuador, but also affected several ecosystems. The increased use of pesticides poses a serious threat to the freshwater ecosystem, which urgently calls for an improved knowledge about the impact of pesticide practices in this study area. Several studies have shown that models can be appropriate tools to simulate pesticide dynamics in order to obtain this knowledge. This study tested the suitability of the Soil and Water Assessment Tool (SWAT) to simulate the dynamics of two different pesticides in the data scarce Guayas River basin. First, we set up, calibrated and validated the model using the streamflow data. Subsequently, we set up the model for the simulation of the selected pesticides (i.e., pendimethalin and fenpropimorph). While the hydrology was represented soundly by the model considering the data scare conditions, the simulation of the pesticides should be taken with care due to uncertainties behind essential drivers, e.g., application rates. Among the insights obtained from the pesticide simulations are the identification of critical zones for prioritisation, the dominant areas of pesticide sources and the impact of the different land uses. SWAT has been evaluated to be a suitable tool to investigate the impact of pesticide use under data scarcity in the Guayas River basin. The strengths of SWAT are its semi-distributed structure, availability of extensive online documentation, internal pesticide databases and user support while the limitations are high data requirements, time-intensive model development and challenging streamflow calibration. The results can also be helpful to design future water quality monitoring strategies. However, for future studies, we highly recommend extended monitoring of pesticide concentrations and sediment loads. Moreover, to substantially improve the model performance, the availability of better input data is needed such as higher resolution soil maps, more accurate pesticide application rate and actual land management programs. Provided that key suggestions for further improvement are considered, the model is valuable for applications in river ecosystem management of the Guayas River basin

BIOECONOMIC MODELING TO ASSESS ECONOMIC AND WATER QUALITY IMPACTS OF LAND USE CHANGE

Changes in water quality and agricultural and forest revenues due to land use changes are compared. A biophysical model estimates the effect in nitrogen and phosphorus runoff and sediment deposition. The results are combined with farm enterprise budgets to estimate the economic returns resulting from land use changes.Land Economics/Use,

SEDIMENTATION OF RESERVOIRS: PREVENTION VS CLEANUP

Soil erosion from cropland contributes significantly to reducing storage capacity in reservoirs. A model is developed for comparing economic desirability of various catchment level soil conservation practices. Results from an illustrative case study show that prevention of sediment accumulation can be much more economical than sediment removal at the reservoir level.Resource /Energy Economics and Policy,

PHOSPHORUS-BASED NUTRIENT MANAGEMENT PLANNING ON DAIRY/POULTRY FARMS: IMPLICATIONS FOR ECONOMIC AND ENVIRONMENTAL RISKS

The effects of phosphorus (P)-based nutrient management plans on economic and environmental risks of dairy and dairy-poultry farms in Virginia were evaluated. Phosphorus-based nutrient management plans can greatly reduce P runoff risk but also reduce farmers' returns. P-based plans cause greater reductions in returns and P runoff on the dairy-poultry farm than on the dairy only farm.nutrient runoff, cost, mathematical programming, simulation, watershed, Environmental Economics and Policy, Livestock Production/Industries,