Showing papers in "Transactions of the ASABE in 2006"

Cumulative uncertainty in measured streamflow and water quality data for small watersheds

Abstract: The scientific community has not established an adequate understanding of the uncertainty inherent in measured water quality data, which is introduced by four procedural categories: streamflow measurement, sample collection, sample preservation/storage, and laboratory analysis. Although previous research has produced valuable information on relative differences in procedures within these categories, little information is available that compares the procedural categories or presents the cumulative uncertainty in resulting water quality data. As a result, quality control emphasis is often misdirected, and data uncertainty is typically either ignored or accounted for with an arbitrary margin of safety. Faced with the need for scientifically defensible estimates of data uncertainty to support water resource management, the objectives of this research were to: (1) compile selected published information on uncertainty related to measured streamflow and water quality data for small watersheds, (2) use a root mean square error propagation method to compare the uncertainty introduced by each procedural category, and (3) use the error propagation method to determine the cumulative probable uncertainty in measured streamflow, sediment, and nutrient data. Best case, typical, and worst case “data quality” scenarios were examined. Averaged across all constituents, the calculated cumulative probable uncertainty (±%) contributed under typical scenarios ranged from 6% to 19% for streamflow measurement, from 4% to 48% for sample collection, from 2% to 16% for sample preservation/storage, and from 5% to 21% for laboratory analysis. Under typical conditions, errors in storm loads ranged from 8% to 104% for dissolved nutrients, from 8% to 110% for total N and P, and from 7% to 53% for TSS. Results indicated that uncertainty can increase substantially under poor measurement conditions and limited quality control effort. This research provides introductory scientific estimates of uncertainty in measured water quality data. The results and procedures presented should also assist modelers in quantifying the “quality” of calibration and evaluation data sets, determining model accuracy goals, and evaluating model performance.

Modeling long-term water quality impact of structural BMPs

Abstract: Structural best management practices (BMPs) that reduce soil erosion and nutrient losses have been recommended and installed on agricultural land for years. A structural BMP is expected to be fully functional only for a limited period after installation, after which degradation of the BMP is likely to lead to a reduction in the water quality improvement provided by the BMP. Assessing the impact of BMPs on water quality is of widespread interest, but no standard methods exist to determine the water quality impact of structural BMPs, particularly as the impact changes through time. The objective of this study was to determine the long-term (~20 year) impact of structural BMPs in two subwatersheds of Black Creek on sediment and phosphorus loads using the Soil and Water Assessment Tool (SWAT) model. The BMPs were represented by modifying SWAT parameters to reflect the impact the practice has on the processes simulated within SWAT, both when practices are fully functional and as their condition deteriorates. The current condition of the BMPs was determined using field evaluation results from a previously developed BMP condition evaluation tool. Based on simulations in the two subwatersheds, BMPs in good condition reduced the average annual sediment yield by 16% to 32% and the average annual phosphorus yield by 10% to 24%. BMPs in their current condition reduced sediment yield by only 7% to 10% and phosphorus yield by 7% to 17%.

Hydrologic evaluation of the soil and water assessment tool for a large tile-drained watershed in iowa

Abstract: The presence of subsurface tile drainage systems can facilitate nutrient and pesticide transport, thereby contributing to environmental pollution. The Soil and Water Assessment Tool (SWAT) water quality model is designed to assess nonpoint and point source pollution and was recently modified for tile drainage. Over 25% of the nation's cropland required improved drainage. In this study, the model's ability to validate the tile drainage component is evaluated with nine years of hydrologic monitoring data collected from the South Fork watershed in Iowa, since about 80% of this watershed is tile drained. This watershed is a Conservation Effects Assessment Program benchmark watershed and typifies one of the more intensively managed agricultural areas in the Midwest. Comparison of measured and predicted values demonstrated that inclusion of the tile drainage system is imperative for obtaining a realistic watershed water balance. Two calibration/validation scenarios tested if the results differed in how the data set was divided. The optimum scenario results for the simulated monthly and daily flows had Nash-Sutcliffe efficiency (ENS) values during the calibration/validation (1995-1998/1999-2004) periods of 0.9/0.7 and 0.5/0.4, respectively. The second scenario results for the simulated monthly and daily flows had ENS values during the calibration/validation (1995-2000/2001-2004) periods of 0.8/0.5 and 0.7/0.2, respectively. The optimum scenario reflects the distribution of peak rainfall events represented in both the calibration and validation periods. The year 2000, being extremely dry, negatively impacted both the calibration and validation results. Each water budget component of the model gave reasonable output, which reveals that this model can be used for the assessment of tile drainage with its associated practices. Water yield results were significantly different for the simulations with and without the tile flow component (25.1% and 16.9%, expressed as a percent of precipitation). The results suggest that the SWAT2005 version modified for tile drainage is a promising tool to evaluate streamflow in tile-drained regions when the calibration period contains streamflows representing a wide range of rainfall events.

Modeling bacteria fate and transport in watersheds to support TMDLs

Abstract: Fecal contamination of surface waters is a critical water-quality issue, leading to human illnesses and deaths. Total Maximum Daily Loads (TMDLs), which set pollutant limits, are being developed to address fecal bacteria impairments. Watershed models are widely used to support TMDLs, although their use for simulating in-stream fecal bacteria concentrations is somewhat rudimentary. This article provides an overview of fecal microorganism fate and transport within watersheds, describes current watershed models used to simulate microbial transport, and presents case studies demonstrating model use. Bacterial modeling capabilities and limitations for setting TMDL limits are described for two widely used watershed models (HSPF and SWAT) and for the load-duration method. Both HSPF and SWAT permit the user to discretize a watershed spatially and bacteria loads temporally. However, the options and flexibilities are limited. The models are also limited in their ability to describe bacterial life cycles and in their ability to adequately simulate bacteria concentrations during extreme climatic conditions. The load-duration method for developing TMDLs provides a good representation of overall water quality and needed water quality improvement, but intra-watershed contributions must be determined through supplemental sampling or through subsequent modeling that relates land use and hydrologic response to bacterial concentrations. Identified research needs include improved bacteria source characterization procedures, data to support such procedures, and modeling advances including better representation of bacteria life cycles, inclusion of more appropriate fate and transport processes, improved simulation of catastrophic conditions, and creation of a decision support tool to aid users in selecting an appropriate model or method for TMDL development.

Sediment and nutrient modeling for tmdl development and implementation

Abstract: At present, there are over 34,000 impaired waters and over 58,000 associated impairments officially listed in the U.S. Nutrients and sediment are two of the most common pollutants included in the list. States are required to identify and list those waters within their boundaries that are not meeting standards, to prioritize them, and to develop Total Maximum Daily Loads (TMDLs) for the pollutants of concern. Models are used to support development of TMDLs, typically to estimate source loading inputs, evaluate receiving water quality, and determine source load allocations so that receiving water quality standards are met. Numerous models are available today, and selection of the most suitable model for a specific TMDL project can be daunting. This article presents a critical review of models simulating sediment and nutrients in watersheds and receiving waters that have potential for use with TMDL development and implementation. The water quality models discussed, especially those with sediment and/or nutrient components, include loading models (GWLF and PLOAD), receiving water models (AQUATOX, BATHTUB, CE-QUAL-W2, QUAL2E, and QUAL2K), and watershed models having both loading and receiving components (AGNPS, AnnAGNPS, CASC2D/GSSHA, DWSM, HSPF, KINEROS2, LSPC, MIKE SHE, and SWAT). Additional models mentioned include another receiving water quality model (WASP), watershed models (ANSWERS storm event, ANSWERS continuous, PRMS storm event, SWMM, and WEPP), and BMP models (APEX, REMM, and VFSMOD). Model sources, structures, and procedures for simulating hydrology, sediment, and nutrients are briefly described for the reviewed models along with an assessment of their strengths, limitations, robustness, and potentials for using in sediment and/or nutrient TMDLs. Applications of AGNPS, APEX, BATHTUB, CE-QUAL-W2, GWLF, and SWAT in TMDL developments are presented. Applications of some of the other models (DWSM, GSSHA, and KINEROS2) relevant to TMDL studies are also presented. The models proved to be useful; however, they require a learning process. Simple models are easy to use but have limitations; comprehensive models are labor and data intensive but offer extensive analysis tools. Finally, recommendations are offered for advancing the sediment and nutrient modeling technologies as applied to TMDL development and implementation. Advances could be made towards: making the best use of existing models, enhancing the existing models, combining strengths of existing models, developing new models or supplemental components with physically based robust routines, numerous field applications, sensitivity analyses, full documentation, and rigorous education and training.

Uncertainty in tmdl models

Abstract: Although the U.S. Congress established the Total Maximum Daily Load (TMDL) program in the original Clean Water Act of 1972, Section 303(d), it did not receive attention until the 1990s. Currently, two methods are available for tracking pollution in the environment and assessing the effectiveness of the TMDL process on improving the quality of impaired water bodies: field monitoring and mathematical/computer modeling. Field monitoring may be the most appropriate method, but its use is limited due to high costs and extreme spatial and temporal ecosystem variability. Mathematical models provide an alternative to field monitoring that can potentially save time, reduce cost, and minimize the need for testing management alternatives. However, the uncertainty of the model results is a major concern. Uncertainty is defined as the estimated amount by which an observed or calculated value may depart from the true value, and it has important policy, regulatory, and management implications. The source and magnitude of uncertainty and its impact on TMDL assessment has not been studied in depth. This article describes the collective experience of scientists and engineers in the assessment of uncertainty associated with TMDL models. It reviews sources of uncertainty (e.g., input variability, model algorithms, model calibration data, and scale), methods of uncertainty evaluation (e.g., first-order approximation, mean value first-order reliability method, Monte Carlo, Latin hypercube sampling with constrained Monte Carlo, and generalized likelihood uncertainty estimation), and strategies for communicating uncertainty in TMDL models to users. Four case studies are presented to highlight uncertainty quantification in TMDL models. Results indicate that uncertainty in TMDL models is a real issue and should be taken into consideration not only during the TMDL assessment phase, but also in the design of BMPs during the TMDL implementation phase. First-order error (FOE) analysis and Monte Carlo simulation (MCS) or any modified versions of these two basic methods may be used to assess uncertainty. This collective study concludes that a more scientific method to account for uncertainty would be to develop uncertainty probability distribution functions and transfer such uncertainties to TMDL load allocation through the margin of safety component, which is selected arbitrarily at the present time. It is proposed that explicit quantification of uncertainty be made an integral part of the TMDL process. This will benefit private industry, the scientific community, regulatory agencies, and action agencies involved with TMDL development and implementation.

Denitrification of agricultural drainage using wood-based reactors

Abstract: Two denitrification reactor designs, utilizing alternate layers of fine and coarse wood particles, were monitored for their ability to achieve passive, maintenance-free nitrate removal in agricultural tile drainage. A lateral flow design was tested over a 26-month period on drainage from a cornfield in southern Ontario, and an upflow design was tested over a 20-month period on drainage from a golf course, also in southern Ontario. At the cornfield site, flow through the reactor averaged 7.7 L/min at an average influent NO3 concentration of 11.8 mg N/L, and removal averaged 3.9 mg N/L. At the golf course site, flow through the reactor averaged 7.8 L/min at an average influent NO3 concentration of 3.2 mg N/L, and removal averaged 1.7 mg N/L. Areal removal rates averaged 2.5 g N/m2/d in the cornfield reactor and 0.95 g N/m2/d in the golf course reactor, and are about an order of magnitude higher than rates reported for other passive treatment systems such as constructed wetlands even though average operating temperatures were relatively low (7°C to 9°C). Mass balance calculations indicate that carbon consumption from denitrification was <2% per year; thus, these reactors have the potential to operate for a number of years without the need for media replenishment. Both reactors were successful in achieving maintenance-free operation during all seasonal conditions, including unassisted startup after drought and freeze periods. Reactors such as these have the potential for a range of applications in agricultural settings because of their low cost and low maintenance characteristics. They are most usefully applied in the treatment of base flows rather than peak flows and can be readily used in combination with other treatment systems such as constructed wetlands.

Ammonia Emissions from Twelve U.S. Broiler Chicken Houses

Abstract: Twelve commercial broiler houses in the U.S. were each monitored for at least thirteen 48 h periods over the course of one year to obtain ammonia emission data. Paired repetition of houses on four farms represents current construction with variety in litter management (built-up or new litter each flock) and climate conditions (cold or mixed-humid). Ammonia concentration was determined using portable electrochemical sensors incorporating a fresh air purge cycle. Ventilation rate was determined via in-situ measurement of fan capacity, fan on-off times, and house static pressure difference. There were seasonal trends in exhaust ammonia concentration (highest in cold weather) and ventilation rates (highest in warm weather) but not for emission rate. Flocks with at least three monitoring periods (13 of 22 flocks) demonstrated similar emission rates at a given bird age among the four study farms and across the seasons. An analysis of emissions from all houses on the three farms using built-up litter resulted in predicted regression slopes of 0.028, 0.034, and 0.038 g NH3 bird-1 d-1 per day of age; the fourth farm, managed with new litter, had the lowest emission rate at 0.024 g NH3 bird-1 d-1. The intercept of these composite relationships was influenced by litter conditions, with flocks on new litter having essentially no emissions for about six days while built-up litter flocks had emissions starting at flock placement. Data from all four farms and all flocks provided a regression slope of 0.031(±0.001 std error) g NH3 bird-1 d-1 per day of age. Emission rate per animal unit for built-up litter flocks indicated very high emissions for the youngest birds (under 14 days of age), after which time the emissions decreased exponentially and were then relatively steady for the balance of the flock cycle.

Moisture Effect on the Physical Characteristics of Switchgrass Pellets

Abstract: Switchgrass was pelleted through a 4.76 mm (3/16 in.) diameter die. The physical characteristics of the pellets were measured. It was found that the bulk density, particle density, durability, and hardness of the pellets were significantly affected by moisture content. The maximum values of bulk density and particle densities were 708 and 1462 kg/m3, respectively. The force required to rupture the pellets varied from 32 N at 6.3% moisture content to 22 N at 17.4% moisture content. Durability of the pellets was also affected by moisture content and was maximum at 8.6% (wet basis) moisture content. The pellets absorbed moisture at rates that were significantly affected by air relative humidity (P < 0.05). The EMC-ERH data for the pellets were sigmoidal in shape and were best predicted by the modified Chung-Pfost equilibrium moisture equation.

Comparison of five models to scale daily evapotranspiration from one-time-of-day measurements

Abstract: Calculation of regional, spatially distributed evapotranspiration (ET) is possible using remotely sensed surface temperatures from sensors aboard air or space platforms. These platforms provide instantaneous data at frequencies of days to weeks, so that instantaneous latent heat flux can be computed from energy balance algorithms. However, instantaneous latent heat flux must be converted to ET and then scaled to daily (24 h) totals for most practical applications. We compared five scaling models where a single measurement of 0.5 h ET was used to estimate the daily total during clear days. Each model takes advantage of the clear day, quasi-sinusoidal nature of daytime ET and other daytime parameters including solar radiation, available energy, or reference ET. The surfaces were fully irrigated alfalfa, partially irrigated cotton, dryland grain sorghum, and bare soil (tilled fallow sorghum). Actual ET was measured by precision weighing lysimeters. Model agreement was evaluated on the basis the modified index of agreement (D) and the modified coefficient of efficiency (e), in addition to standard statistical parameters. For cropped surfaces, the models based on grass reference ET resulted in the best agreement between observed and predicted daily ET totals. For bare soil, the model based on available energy (i.e., evaporative fraction) resulted in the best agreement. Relative error between observed and predicted daily ET increased as daily ET decreased. Observed and predicted daily ET agreed well for the transpiring crops (RMSE of 0.33 to 0.46 mm d-1 for mean daily ET of 3.9 to 5.8 mm d-1) but poorly for bare soil (RMSE of 0.47 mm d-1 for mean daily ET of 1.4 mm d-1).

Influences of Potential Evapotranspiration Estimation Methods on SWAT's Hydrologic Simulation in a Northwestern Minnesota Watershed

Abstract: The Soil and Water Assessment Tool (SWAT), a widely used watershed hydrology and water quality model, provides three different methods (Hargreaves, Priestley-Taylor, and Penman-Monteith) for estimating potential evapotranspiration (PET) and the corresponding actual evapotranspiration (AET). Although these methods have been extensively tested, the effects of using them within SWAT's framework are largely unknown. The objective of this study was to test the three PET methods within SWAT's framework using data collected in the Wild Rice River watershed, located in northwestern Minnesota. The performance of the SWAT models was measured using three statistics: the Nash-Sutcliffe coefficient (Ej2), coefficient of determination (R2), and performance virtue (PVk). The three models were independently calibrated and validated using the observed daily stream flows at two USGS gauging stations. The simulated stream discharges were compared with the corresponding observed values and the estimated evapotranspiration examined in accordance with the wet-environment areal evapotranspiration (ETW) derived from the evaporation data for Williams Lake, located about 100 km southeast of the study watershed. The use of the three PET methods resulted in different values for two calibration parameters, namely the soil evaporation compensation factor and SCS curve number. At the lower station, which is near the watershed outlet, the observed annual mean discharge (8.33 m3/s) during the model validation period was predicted to be 10.25, 10.87, and 9.69 m3/s by SWAT-Penman, SWAT-Priestley, and SWAT-Hargreaves, respectively. The annual mean discharge (10.83 m3/s) was more accurately predicted during the model calibration period, with an absolute error of less than 0.5 m3/s. The prediction errors for the upper station were comparable with those for the lower station. In addition, all three models exhibited good performance when simulating the monthly, seasonal, and annual mean discharges (Ej2 >0.75 and PVk >0.80) and satisfactory performance when predicting the daily stream flows (Ej2 >0.36 and PVk >0.70). In estimating evapotranspiration for the study watershed, SWAT-Hargreaves seemed to be slightly superior to the other two models, while SWAT-Priestley might be more appropriate for an ETW value greater than 8.0 mm/d. Nevertheless, the AET values estimated by the three models shared a concurrent spatial pattern and temporal trend, and were insignificantly different from each other at a 5% significance level (p-values > 0.05). The results indicated that after calibration, using the three ET methods within SWAT produced very similar hydrologic (AET and discharge) predictions for the study watershed.

Diesel engine performance and nox emissions from oxygenated biofuels and blends with diesel fuel

Abstract: Increased pressure from federal and state agencies to improve air quality has resulted in extensive research into the use of biofuels to reduce diesel engine emissions. Oxygenated biofuels such as biodiesel and ethanol blended with diesel fuel are biodegradable, non-toxic, renewable alternatives to imported petroleum diesel, and their use not only creates new markets for domestic agricultural products, but also greatly reduces particulate emissions. Unfortunately, biodiesel has been shown to increase NOX emissions upwards of 10% compared to petroleum diesel. The objective of this investigation was to evaluate the performance and NOX emissions of selected biofuels and blends with petroleum-based diesel fuel in a turbocharged and intercooled diesel engine using a steady-state nonroad ISO 8-mode test schedule. Test fuels included traditional No. 2 diesel and four biofuels comprising 100% soy methyl ester biodiesel, 2% biodiesel, 10% ethanol-diesel fuel, and 5% ethanol in biodiesel. Exhaust NOX emissions were monitored with a Horiba NOX analyzer. Reductions in peak torque varying from less than 0.5% to about 10% were measured with the test fuels and were attributed mainly to reduced energy content. Biodiesel fuel showed a 12% increase in NOX emissions, while 2% biodiesel fuel increased emissions 2.3%. The ethanol-diesel fuel blend reduced NOX emissions by 2.7% and was highly sensitive to load, with increased temperature and NOX emissions at light load. Addition of only 5% ethanol to biodiesel suppressed NOX emissions, with only a 2.6% increase occurring. It was concluded that ethanol could act as an effective NOX emissions reducing additive.

Detection of corn kernels infected by fungi

Abstract: Single-kernel reflectance spectra (550 to 1700 nm), visible color reflectance images, x-ray images, multi-spectral transmittance images (visible and NIR), and physical properties (mass, length, width, thickness, and cross-sectional area) were analyzed to determine if they could be used to detect fungal-infected corn kernels Kernels were collected from corn ears inoculated with one of several different common fungi several weeks before harvest, and then collected at harvest time It was found that two NIR reflectance spectral bands centered at 715 nm and 965 nm could correctly identify 981% of asymptomatic kernels and 966% of kernels showing extensive discoloration and infected with Aspergillus flavus, Aspergillus niger, Diplodia maydis, Fusarium graminearum, Fusarium verticillioides, or Trichoderma viride These two spectral bands can easily be implemented on high-speed sorting machines for removal of fungal-damaged grain Histogram features from three transmittance images (blue and red components of color images and another at 960 nm) can distinguish 919% of infected kernels with extensive discoloration from 962% of asymptomatic kernels Similar classification accuracies were achieved using x-ray images and physical properties (kernel thickness, weight, length) A neural network was trained to identify infecting fungal species on single kernels using principle components of the reflectance spectra as input features

A novel continuous-flow reactor using reactive distillation for biodiesel production

Abstract: The production of biodiesel through batch and existing continuous-flow processes requires the use of a much higher excess alcohol, typically 100%, than the stoichiometric molar requirement in order to drive the transesterification reaction to completion. This excess alcohol must be recovered in a separate process, which involves additional capital and operating costs. In this study, a novel reactor system using reactive distillation (RD) was developed and investigated for biodiesel preparation from canola oil and methanol. The goal was to significantly reduce the use of excess methanol while maintaining a high methanol:glyceride molar ratio inside the RD reactor by recycling a small amount of methanol within the system. Reactant conversion rate and product yield were used as the criteria for the reactor evaluation. The effect of the methanol:glyceride ratio was studied on a laboratory-scale perforated-tray RD reactor system. Product parameters such as methyl ester content, glycerides, and methanol content were analyzed. Preliminary results showed that the RD reactor with a methanol:glyceride ratio of 4:1 (molar), in which the use of methanol was cut down by 66%, gave a satisfactory biodiesel yield and oil conversion rate at a column temperature of 65°C. Total reaction time in the pre-reactor and RD column was about 3 min, which is 20 to 30 times shorter than in typical batch processes. The productivity of the RD reactor system was about 6.6 m3 biodiesel per m3 reactor volume per hour, which is 6 to 10 times higher than that of batch and existing continuous-flow processes.

Practical guidance for discharge and water quality data collection on small watersheds

Abstract: Many sampling projects have been initiated or modified in recent years to quantify the effects of water quality protection and enhancement programs. Although comprehensive references on the theory and procedures related to discharge data collection have been published, similar guides to water quality sampling are not available. Several sources provide general guidance on sampling project design and on manual sampling procedures, but only recently has detailed information on automated storm water quality sampling been developed. As a result, a compilation of available information on the design of water quality sampling projects is needed to support sound decision-making regarding data collection resources and procedural alternatives. Thus, the objective of this article is to compile and present practical guidance for collection of discharge and water quality constituent data at the field and small watershed scale. The guidelines included are meant to increase the likelihood of project success, specifically accurate characterization of water quality within project resource constraints. Although many considerations are involved in establishing a successful sampling project, the following recommendations are generally applicable to field and small watershed studies: (1) consider wet-weather access, travel time, equipment costs, and sample collection method in the selection of sampling site numbers and locations; (2) commit adequate resources for equipment maintenance and repair; (3) assemble a well-trained, on-call field staff able to make frequent site visits; (4) establish reliable stage-discharge relationships for accurate discharge measurement; (5) use periodic manual grab sample collection with adequate frequency to characterize baseflow water quality; (6) use flow-interval or time-interval storm sampling with adequate frequency to characterize storm water quality; and (7) use composite sampling to manage sample numbers without substantial increases in uncertainty.

Oxidative Stability of Biodiesel by Dynamic Mode Pressurized-Differential Scanning Calorimetry (P-DSC)

Abstract: Biodiesel, an alternative diesel fuel made from transesterification of vegetable oils or animal fats, is composed of saturated and unsaturated long-chain fatty acid alkyl esters. During long-term storage, oxidation caused by contact with ambient air presents legitimate concerns for monitoring fuel quality. Extended oxidative degradation can affect kinematic viscosity, cetane number, and acid value of the fuel. This work investigates the suitability of dynamic mode (positive air purge) pressurized-differential scanning calorimetry (P-DSC) as a means for evaluating the oxidation reaction during non-isothermal heating scans. Methyl oleate, methyl linoleate, and soybean oil fatty acid methyl esters (FAME) were analyzed by P-DSC and the results compared with those from thermogravimetric analyses (TGA), conventional DSC, and static mode (zero purge gas flow) P-DSC scans. Results from TGA showed that ambient air pressure was too low to allow measurable oxidation during analyses. Although some degree of oxidation was detected for DSC and static mode P-DSC heating scans, results demonstrated that the highest degree of oxidation occurred during dynamic mode P-DSC scans. For DSC and P-DSC analyses, oxidation onset temperature (OT) increased with relative oxidative stability, with the highest values being observed for methyl oleate. Treating soybean oil FAME with antioxidants increased their relative oxidative stability, resulting in an increase in OT. Statistical comparison of response factors (RF) relative to methyl oleate obtained from non-isothermal heating scans with those obtained from OSI analyses showed the highest degree of correlation (P = 0.79) with respect to dynamic mode P-DSC.

Effects of soil moisture content on absorbance spectra of sandy soils in sensing phosphorus concentrations using uv-vis-nir spectroscopy

Abstract: This study was conducted to investigate the effects of soil moisture content on the absorbance spectra of sandy soils with different phosphorus (P) concentrations using ultraviolet (UV), visible (VIS), and near-infrared (NIR) absorbance spectroscopy. Sieve sizes were 125, 250, and 600 .m for fine, medium, and coarse, respectively. The medium size of the samples was used for the study. Investigations were conducted at 0, 12.5, 62.5, 175, 375, 750, and 1000 mg kg-1 P application rates. Three soil moisture contents (4%, 8%, and 12%) were investigated. P concentrations of the soil samples were analyzed and reflectance of the samples was measured between 225 and 2550 nm with a 1 nm interval. Dried soil samples reflected more light than wet soil in the 225-2550 nm range. As moisture content of the soils increased, reflectance from the soil sample decreased, which indicates that water is a strong light absorber in sandy soils. Dry soil spectra were reconstructed from the wet soil spectra by removing the moisture content effect and compared with the dry spectra of the same soil sample. Absorbance and reconstructed absorbance data were prepared as calibration and validation data sets in order to measure the performance of the spectral signal processing used for removing the moisture content effect on absorbance spectra. A partial least squares (PLS) analysis was applied to the data to predict P concentration before and after processing the spectra. The results showed that removing the moisture effect by spectral signal processing considerably improved prediction of P in soils.

Evaluation of swat in simulating nitrate nitrogen and atrazine fates in a watershed with tiles and potholes

Abstract: We evaluated a version of the Soil Water Assessment Tool (SWAT-M) that was modified to more accurately simulate tile drainage and water flow in a landscape dominated by closed surface depressions or potholes at a watershed scale using ten years of measured nitrate-nitrogen (NO3-N) and atrazine data in stream discharge in the Walnut Creek watershed (WCW). The model was calibrated during the period of 1992 to 1995 and validated during the period of 1996 to 2001. Stream sites in the middle and outlet of the WCW were selected to assess overall performance of the model, while one drainage district drain was used for investigating chemical loads in subsurface flows. With the introduction of an independent tile drain lag time parameter, the performance of SWAT-M for daily flow simulation was improved. In comparison to our previous results, the Nash-Sutcliffe E values for the calibrated daily flow at the mid-watershed and outlet simulated by the enhanced SWAT model rose from 0.55 to 0.69 and from 0.51 to 0.63, respectively. Of special note, the E value for calibrated flow rose from -0.23 to 0.40 for the drainage district drain, which was dominated by tile and subsurface flow. Both the predicted corn yields and N uptake by corn were very similar to the measured data. The predicted yield and N uptake by soybean were relatively lower than the measured values. The monthly NO3-N loads in stream discharges at the center and outlet of the Walnut Creek watershed were accurately predicted with good Nash-Sutcliffe E values of 0.91/0.80 and 0.85/0.67 in calibration/validation, respectively. Nevertheless, the model’s simulation of the daily NO3-N loads was not as good as the monthly simulation. The good agreement between the simulated and measured monthly NO3-N loads from the drainage district site leads us to conclude that SWAT can reasonably simulate tile flow from pothole-dominated landscapes, although the model needs to be improved in the simulation of daily subsurface NO3-N fluxes. The enhanced SWAT-M model simulated the NO3-N loads in a watershed with intensive tile drainage systems much more accurately than the original SWAT2000 version. A second pesticide degradation half-life in soil was added for SWAT-M, which greatly improved the model performance for predicting atrazine losses from the watershed. Overall, SWAT-M is capable of simulating atrazine loads in the stream discharge of the WCW and is a much-improved tool over SWAT2000 for predicting both daily and monthly atrazine losses in nearly level, tile-drained watersheds.

Hydrothermal processing of swine manure into oil using a continuous reactor system: development and testing

Abstract: Hydrothermal processing of swine manure is a novel technology that has shown very promising results in treatingwaste and producing oil. A batch hydrothermal process system that was previously developed at the University of Illinois atUrbana-Champaign successfully converted up to 70% of swine manure volatile solids into oil and reduced manure chemicaloxygen demand by up to 75%. Since a continuous system is more applicable for scale-up operations, a small-scale continuoushydrothermal process (CHTP) reactor system was developed to evaluate the technical feasibility of the continuous-modeprocess. The CHTP reactor system was composed of a high-pressure slurry feeder, a process gas feeder, a continuous stirredtank reactor, a product separation vessel, and process controllers. It had a capacity to process up to 48 kg of manure slurryper day. The CHTP reactor system was successfully operated continuously for up to 16 h per test. Oil yields ranging from62.0% to 70.4% were achieved. The heating value of the oil product ranged from 25,176 kJ/kg to 31,095 kJ/kg with the highestvalue at T = 305C, P = 10.3 MPa, and RT = 80 min.

Dielectric Spectroscopy of Honeydew Melons from 10 MHz to 1.8 GHz for Quality Sensing

Abstract: Honeydew melons were grown and harvested with a range of maturities for measurement of tissue permittivities (dielectric constant and loss factor) to study possible correlations between the dielectric properties and soluble solids (sweetness) for nondestructive sensing of maturity. Permittivities of tissue samples from 38 melons were measured at 25°C over the frequency range from 10 MHz to 1.8 GHz along with refractometer determinations of soluble solids content (SSC), tissue density, and moisture content. A high correlation (r = 0.96) was found between SSC and the permittivity as expressed in a complex-plane plot of the two components of the relative complex permittivity, each divided by SSC. Through this mathematical relationship, SSC can be calculated from measured permittivity values independent of tissue density and moisture content. Moderate correlations were noted between dielectric constant and SSC at 10 MHz and between the loss factor and SSC at 1.8 GHz. Correlations between the dielectric properties and both moisture content and tissue density were very low. The correlation between tissue density and SSC was also very low. A high correlation was noted between SSC and moisture content, with SSC decreasing as moisture content increased. Problems in using the high correlation between permittivity and SSC for practical, nondestructive sensing of honeydew melon maturity as determined by SSC are also considered.

A computer vision method for on-line behavioral quantification of individually caged poultry

Abstract: In addition to production, physiology, and health, behavior is an important issue with respect to animal welfare when evaluating novel housing systems. Behavioral characteristics are usually evaluated by audio-visual observation done by a human observer present on the scene. This method is time consuming, expensive, subjective, and prone to human error. Automated objective surveillance, by means of inexpensive cameras and image-processing techniques, has the ability to generate data that provide an objective measure of behavior, without disturbing the animals. The specific purpose of this study was to develop a fully automatic on-line image-processing technique to quantify the behavior of a single laying hen as opposed to the current human visual observation. The image-processing system is based on the principle that the classification of behavior can be translated into classification of time series of different postures of the hen. The hen’s postures can be recognized in the camera image. The classification of the hen’s behavior is performed by dynamic analysis of a set of measurable parameters, which are calculated from the images using image-processing techniques. The parameters were chosen based on their computational demands and analysis of their discriminative power regarding the different types of a specific behavior. A first implementation of the system allowed us to identify three different types of individual behavior (standing, walking, and scratching). The objective of further investigation will be the classification of up to 15 different types of behavior, such as pecking, eating, drinking, wing stretching, etc.

Evaluation of nitrate and potassium ion-selective membranes for soil macronutrient sensing

Abstract: On-the-go, real-time soil nutrient analysis would be useful in site-specific management of soil fertility The rapid response and low sample volume associated with ion-selective field-effect transistors (ISFETs) make them good soil fertility sensor candidates Ion-selective microelectrode technology requires an ion-selective membrane that responds selectively to one analyte in the presence of other ions in a solution This article describes: (1) the evaluation of nitrate and potassium ion-selective membranes, and (2) the investigation of the interaction between the ion-selective membranes and soil extractants to identify membranes and extracting solutions that are compatible for use with a real-time ISFET sensor to measure nitrate and potassium ions in soil The responses of the nitrate membranes with tetradodecylammonium nitrate (TDDA) or methlytridodecylammonium chloride (MTDA) and potassium membranes with valinomycin were affected by both membrane type and soil extractant A TDDA-based nitrate membrane would be capable of detecting low concentrations in soils to about 10 −5 mole/L NO3 − The valinomycin-based potassium membranes showed satisfactory selectivity performance in measuring potassium in the presence of interfering cations such as Na + , Mg 2+ , Ca 2+ , Al 3+ , and Li + as well as provided a consistent sensitivity when DI water, Kelowna, or Bray P1 solutions were used as base solutions The TDDA-based nitrate membrane and the valinomycin-based potassium membrane, used in conjunction with Kelowna extractant, would allow determination of nitrate and potassium levels, respectively, for site-specific control of fertilizer application

Towards one-step estimation of crop water requirements

Abstract: This article provides theoretical analyses that facilitate the use of the Penman-Monteith equation to make a one-step estimate of crop water requirements. Reluctance to using a one-step estimate results from two outstanding issues, both of which are addressed. First, no method has been yet defined to handle the problem that meteorological variables are commonly available only at 2 m above the ground while, when using the Penman-Monteith equation, they are required at some level above the crop. To resolve this, a blending height is defined in the atmospheric boundary layer (ABL) where meteorological conditions are independent of the underlying crop. Expressions are derived to calculate the aerodynamic resistances to, and the vapor pressure deficit at, the blending height from climate variables at 2 m. Consequently, 2 m climate data can be used in the Penman-Monteith equation, either to estimate transpiration from surface resistance or to calculate surface resistance from measured transpiration. Second, no table of effective values currently exists for the surface resistance of different crops equivalent to that for the crop coefficient. This article calls for field studies to address this need. However, recognizing the need for an interim source of crop-specific surface resistances, a methodology is given for translating the crop coefficient into equivalent surface resistance. To make this translation, it is necessary to specify the relationship between the radiative and aerodynamic energy inputs to evapotranspiration when the crop coefficients were calibrated. Finally, a Penman-Monteith-based, one-step estimation equation is derived that makes proper allowance for the different aerodynamic characteristics of crops in all conditions of atmospheric aridity, and that estimates crop evaporation for any crop of specified height from existing crop coefficients using standard 2 m climate data.

Predicting Management Effects on Ammonia Emissions from Dairy and Beef Farms

Abstract: Relationships were developed to predict ammonia (NH3) nitrogen losses from cattle manure in animal housing, during manure storage, following field application, and during grazing. Ammonia loss in each phase was predicted using a mechanistic model for NH3 volatilized from the surface of an aqueous solution of ammonium where the NH3 is transported to the free atmosphere through a pathway with finite resistance. Ammonia emission rate was a function of the ammoniacal N content in the manure, ambient temperature, manure pH, manure moisture content, and the exposed manure surface area. Model relationships were calibrated by selecting values for the resistance to NH3 transport for the various loss pathways, which predicted daily and annual emissions similar to those reported in published studies. In further evaluation, these calibrated relationships predicted average annual losses similar to those documented in previous work over a range in climate locations. These relationships were integrated into a whole-farm simulation model to provide a tool for evaluating and comparing long-term nitrogen losses along with other performance, environmental, and economic aspects of farm production. Whole-farm simulations illustrated that the use of a free stall barn, bottom-loaded slurry storage, and direct injection of manure into the soil reduced NH3 emissions by 33% to 50% compared to other commonly used dairy housing and manure handling systems in the northeastern U.S. The improvement in nitrogen utilization more than offset the increased cost in manure handling, providing a small increase in farm profit. The farm model provides a research and teaching tool for evaluating and comparing the economic and environmental sustainability of dairy and beef production systems.

Artificial Neural Network Model as a Data Analysis Tool in Precision Farming

Abstract: Spatial variation in landscape and soil properties combined with temporal variations in weather can result in yield patterns that change annually within a field. The complexity of interactions between a number of yield-limiting factors makes it difficult to accurately attribute yield losses to conditions that occur within a field. In this research, a back-propagation neural network (BPNN) model was developed to predict the spatial distribution of soybean yields and to understand the causes of yield variability. First, we developed a BPNN model by relating soybean yield to topography, soil, weather, and site factors and evaluated model predictions for the same field for independent years. We also explored the potential use of BPNN for predicting yields in independent fields. Finally, we evaluated the ability of the BPNN to attribute yield losses due to soybean cyst nematodes (SCN), soil pH, and weeds. A total of 14 input datasets with combinations of four controlling factors (topographic, soil fertility, weather, and site) were used. For each objective, data from fields in Iowa were used for training the BPNN, while a portion of the data was withheld to verify the accuracy of yield predictions. All BPNN models had fully connected feed-forward architecture with a back-propagation weight adjustment algorithm. When tested for a particular field, the BPNN captured the major patterns of yield variability in independent years; the root mean square error of prediction (RMSEP) was 14.2% of actual yield. When the BPNN was trained with inputs from five fields, the RMSEP at test sites was 11.2% of actual yield. When the BPNN was used to attribute yield losses to soil pH, SCN, and weed populations, standard errors were 92, 262, and 171 kg ha-1, respectively. The technique showed that the BPNN could predict spatial yield variability with an RMSEP of about 14%.

Foliar deposition and off-target loss with different spray techniques in nursery applications

Abstract: Information is lacking on spray techniques to improve deposit uniformity within nursery canopies and reduce off-target loss on the ground and via spray drift from the treated area. Spray deposits at various elevations within crabapple trees and on the ground were investigated with an air blast sprayer equipped with conventional hollow-cone nozzles, air-induction nozzles, and conventional hollow-cone nozzles with a drift retardant in a commercial nursery field. Airborne deposits at three elevations on sampling towers and on the ground at several distances from the sprayer were also investigated with the three spray treatments in an open area without trees. To compare field test results, wind tunnel experiments were conducted to assess spray deposits on the floor beyond 0.4 m downwind distance from the nozzles and airborne deposits at 2.1 m downwind from the spray discharge point with the three spray techniques without air assist. Droplet size distributions across spray patterns without air assist were measured with a laser particle/droplet image analysis system. In general, there was no significant difference for deposits within nursery tree canopies and on the ground with three different spray techniques. At the 700 L/ha application rate, which was 360 L/ha lower than the rate typically used in nursery application, the tree canopies received over 4 to 14.5 times as much spray deposit as actually needed from all treatments, and a large portion of spray volume deposited on the ground. Compared with conventional hollow-cone nozzles, drift reduction from air-induction nozzles or the spray mixture with drift retardant treatment was significant in wind tunnel tests but was not significant in field tests.

Evaluating channel-forming discharges: a study of large rivers in ohio

Abstract: Measured data were used to evaluate whether bankfull discharges were related to effective discharges for large rivers in Ohio. The frequency and sediment transport associated with these channel-forming discharges was also examined. Rural watersheds in the Midwest region of the U.S. are dominated by agricultural land uses that incorporate subsurface drainage improvements. Bankfull discharges were determined by measuring fluvial features at each USGS gage and then relating these features to the rating curve and historic daily discharge data for each gage. Effective discharges were determined by using suspended sediment data obtained at the gages, the Wolman-Miller method for calculating geomorphic work, and bin sizes based on stage intervals to group sediment and discharge data. There was good agreement between the effective discharge and bankfull discharge estimates. Bankfull and effective discharges were primarily related to flows that transported the middle 50% of the total sediment load. Recurrence intervals of the bankfull and effective discharges ranged from 0.3 to 1.4 years. These recurrence intervals are more frequent than generally reported in the literature. The duration of daily discharges that equaled or exceeded the channel-forming discharge ranged from 1 to 24 days annually, with mean values of 9 and 11 days for the bankfull discharge and effective discharge, respectively. Common methods for determining the recurrence interval are inadequate for frequent channel-forming discharges, and better insight is obtained by determining the number of days on which these flows are exceeded annually.

A new unified equation for wind-driven surficial oxygen transfer into stationary water bodies

Abstract: Wind-driven surficial oxygen transfer into stationary water bodies plays an important role in analyzing the fate and biochemical processes of environmentally important gases. This article (1) reviews research on oxygen and other gas transfers into non-moving, open water bodies, and (2) presents the synthesis of a new, unified equation for oxygen mass transfer coefficients based on gas transfer data published during the last 50 years. Both theoretical and empirically derived oxygen coefficients were reviewed using data derived from investigations in controlled wind tunnels, floating reaeration devices in open waters, and natural open waters. To facilitate the comparative analyses, gas transfer coefficient correlations for other gases were normalized to oxygen, and wind speeds were normalized to 10 m height. Wind was the major turbulence agent facilitating the gas transfer processes. Generally, low wind speed did not significantly influence the transfer coefficients. However, the transfer coefficients increased, even exponentially, with higher wind speeds. There were large variations among existing transfer coefficient correlations. Nonetheless, sufficient gas transfer data have been published in the last five decades to provide a solid basis for synthesizing a new unified oxygen transfer coefficient formula to estimate surficial oxygen transfer into treatment lagoons. The new unified equation for wind-driven surficial oxygen transfer is a function of Schmidt number, wind speed, and temperature.

Ground-Based Sensing System for Cotton Nitrogen Status Determination

Abstract: A ground-based sensing system was developed for determination of nitrogen (N) status in cotton plants. The system consists of a multi-spectral optical sensor, an ultrasonic sensor, and a data-acquisition and processing unit. The optical sensor's light source provides modulated panchromatic illumination of a plant canopy with light-emitting diodes. The sensor measures plant reflectance at four spectral wavebands (400 to 500 nm, 520 to 570 nm, 610 to 710 nm, and 750 to 1100 nm). The ultrasonic sensor is used to determine plant height. The data-acquisition and processing unit is based on a single-board computer that collects data from the multi-spectral optical sensor and the ultrasonic sensor, and spatial information from a Global Positioning System receiver. Field tests of the system over two years involved measuring spectral reflectance and plant height simultaneously in real time in situ. An artificial neural network was developed to predict N status in cotton plants based on data from the sensing system. The network was trained with actual leaf N concentration data that corresponded to sensor spectral data and plant height. Results showed that the spectral information and plant height measured by the sensing system had significant correlation with leaf N concentration of the cotton plants. Trained neural networks were able to predict N status of the cotton plants at 90% accuracy when N status was divided into two categories: deficiency and non-deficiency.

Evaluation of simplified covering systems to reduce gaseous emissions from livestock manure storage

Abstract: Ammonia, methane, and carbon dioxide are the primary atmospheric emissions from cattle and pig farms. A significant part of these emissions is produced by the decomposition of slurry organic matter during manure storage and treatment phases. Present solutions to contain emissions from storage lagoons generally involve reducing the free surface of the slurry by covering it either with permanent fixed structures or temporary floating ones. This study investigated the effectiveness of five simple floating covers in reducing emissions from pig and cattle slurry. The coverings included vegetable oil (a mixture of rapeseed and soybean oil), expanded clay, chopped maize stalks, chopped wheat straw, and chopped wood chips. All were tested at two different thicknesses: 70 and 140 mm for solid coverings, and 3 and 9 mm for liquid. Slurry samples covered with the above-mentioned materials were placed in nine stainless steel airtight cylinders measuring 190 dm3. Gaseous and odor concentrations in the headspace were monitored using a Bruel & Kjaer 1302 multi-gas monitor and a T07 olfactometer. The flotation aptitude of the different coverings was also tested. Results revealed substantial differences in ammonia emission reduction efficiency (1% to 100%) and odor abatement (0% to 90%), and high levels of reduction efficiency were achieved by all the tested covers at the higher thickness. However, equally valid results were not obtained for methane emissions reduction. In regard to flotation aptitude and cover deterioration on slurry, expanded clay and wood chips demonstrated long-term resistance to both deterioration and sinking.