Impact of Eastern Redcedar encroachment on water resources in the Nebraska Sandhills.

Worldwide, tree or shrub dominated woodlands have encroached into herbaceous dominated grasslands. While very few studies have evaluated the impact of Eastern Redcedar (redcedar) encroachment on the water budget, none have analyzed the impact on water quality. In this study, we evaluated the impact of redcedar encroachment on the water budget in the Nebraska Sand Hills and how the decreased streamflow would increase nitrate and atrazine concentrations in the Platte River. We calibrated a Soil and Water Assessment Tool (SWAT model) for streamflow, recharge, and evapotranspiration. Using a moving window with a dilate morphological filter, encroachment scenarios of 11.9 %, 16.1 %, 28.0 %, 40.6 %, 57.5 %, 72.5 % and 100 % were developed and simulated by the calibrated model. At 11.9 % and 100 % encroachment, streamflow was reduced by 4.6 % and 45.5 %, respectively in the Upper Middle Loup River, a tributary to the Platte River. Percolation and deep aquifer recharge increased by 27 % and 26 % at 100 % encroachment. Streamflow in the Platte River, a major water source for Omaha and Lincoln, would decrease by 2.6 %, 5.5 % and 10.5 % for 28 %, 57.5 %, and 100 % encroachment of the Loup River watershed, respectively. This reduction in streamflow could increase nitrate and atrazine concentrations in the Platte River by 4 to 15 % and 4 to 30 %, respectively. While the density of redcedar is minimal, it is important to manage their encroachment to prevent reductions in streamflow and potential increases in pollutant concentrations.

A biological and chemical approach to restoring water quality: A case study in an urban eutrophic pond.

Efforts to improve water quality of eutrophic ponds often involve implementing changes to watershed management practices to reduce external nutrient loads. While this is required for long-term recovery and prevention, eutrophic conditions are often sustained through the recycling of internal nutrients already present within the waterbody. In particular, internal phosphorus bound to organic material and adsorbed to sediment has the potential to delay lake recovery for decades. Thus, pond and watershed management techniques are needed that not only reduce external nutrient loading but also mitigate the effects of internal nutrients already present. Therefore, our objective was to demonstrate a biological and chemical approach to remove and sequester nutrients present and entering an urban retention pond. A novel biological and chemical management technique was designed by constructing a 37 m2 (6.1 m × 6.1 m) floating treatment wetland coupled with a slow-release lanthanum composite inserted inside an airlift pump. The floating treatment wetland promoted microbial denitrification and plant uptake of nitrogen and phosphorus, while the airlift pump slowly released lanthanum to the water column over the growing season to reduce soluble reactive phosphorus. The design was tested at the microcosm and field scales, where nitrate-N and phosphate-P removal from the water column was significant (α = 0.05) at the microcosm scale and observed at the field scale. Two seasons of field sampling showed both nitrate-N and phosphate-P concentrations were reduced from 50 µg L-1 in 2020 to <10 µg L-1 in 2021. Load calculations of incoming nitrate-N and phosphate-P entering the retention pond from the surrounding watershed indicate the presented biological-chemical treatment is sustainable and will minimize the effects of nutrient loading from nonpoint source pollution.

Measuring the occurrence of antibiotics in surface water adjacent to cattle grazing areas using passive samplers.

A wide variety of antibiotics and other pharmaceuticals are used in livestock production systems and residues passed to the environment, often unmetabolized, after use and excretion. Antibiotic residues may be transported from manure-treated soils via runoff and are also capable of reaching surface and groundwater systems through a variety of pathways. The occurrence and persistence of antibiotics in the environment is a concern due to the potential for ecological effects and proliferation of environmental antibiotic resistance in pathogenic organisms. In the present study, the occurrence and seasonal variation of 24 commonly-used veterinary antibiotics was evaluated in surface water adjacent to several livestock production systems using Polar Organic Chemical Integrative Samplers (POCIS). Uptake rates for all compounds, nine of which have not been previously reported, were measured in the laboratory to permit estimation of changes in the time-weighted average (TWA) antibiotic concentrations during exposure. The antibiotics detected in POCIS extracts included sulfadimethoxine, sulfamethoxazole, trimethoprim, sulfamerazine, sulfadiazine, lincomycin, erythromycin, erythromycin anhydro- and monensin. The maximum TWA concentration belonged to sulfadiazine (25 ng/L) in the August-September sampling period and coincided with the highest number of precipitation events. With the exception of monensin that showed an increase in concentration over the stream path, none of the detected antibiotics were prescribed to livestock at the facility. The detection of antibiotics not prescribed by the facility may be attributable to the environmental persistence of previously used antibiotics, transfer by wind from other nearby livestock production sites or industrial uses, and/or the natural production of some antibiotics.

Predicting Escherichia coli loads in cascading dams with machine learning: An integration of hydrometeorology, animal density and grazing pattern.

Accurate prediction of Escherichia coli contamination in surface waters is challenging due to considerable uncertainty in the physical, chemical and biological variables that control E. coli occurrence and sources in surface waters. This study proposes a novel approach by integrating hydro-climatic variables as well as animal density and grazing pattern in the feature selection modeling phase to increase E. coli prediction accuracy for two cascading dams at the US Meat Animal Research Center (USMARC), Nebraska. Predictive models were developed using regression techniques and an artificial neural network (ANN). Two adaptive neuro-fuzzy inference system (ANFIS) structures including subtractive clustering and fuzzy c-means (FCM) clustering were also used to develop models for predicting E. coli. The performances of the predictive models were evaluated and compared using root mean squared log error (RMSLE). Cross-validation and model performance results indicated that although the majority of models predicted E. coli accurately, ANFIS models resulted in fewer errors compared to the other models. The ANFIS models have the potential to be used to predict E. coli concentration for intervention plans and monitoring programs for cascading dams, and to implement effective best management practices for grazing and irrigation during the growing season.

Influence of watershed characteristics on streambed hydraulic conductivity across multiple stream orders.

Streambeds are critical hydrological interfaces: their physical properties regulate the rate, timing, and location of fluxes between aquifers and streams. Streambed vertical hydraulic conductivity (Kv) is a key parameter in watershed models, so understanding its spatial variability and uncertainty is essential to accurately predicting how stresses and environmental signals propagate through the hydrologic system. Most distributed modeling studies use generalized Kv estimates from column experiments or grain-size distribution, but Kv may include a wide range of orders of magnitude for a given particle size group. Thus, precisely predicting Kv spatially has remained conceptual, experimental, and/or poorly constrained. This usually leads to increased uncertainty in modeling results. There is a need to shift focus from scaling up pore-scale column experiments to watershed dimensions by proposing a new kind of approach that can apply to a whole watershed while incorporating spatial variability of complex hydrological processes. Here we present a new approach, Multi-Stemmed Nested Funnel (MSNF), to develop pedo-transfer functions (PTFs) capable of simulating the effects of complex sediment routing on Kv variability across multiple stream orders in Frenchman Creek watershed, USA. We find that using the product of Kv and drainage area as a response variable reduces the fuzziness in selecting the "best" PTF. We propose that the PTF can be used in predicting the ranges of Kv values across multiple stream orders.

Pesticide occurrence and persistence entering recreational lakes in watersheds of varying land uses.

Currently little is known of newer pesticide classes and their occurrence and persistence in recreational lakes. Therefore, the objectives of this study were to (1) assess average pesticide concentrations and loadings entering recreational lakes in three mixed land use watersheds throughout the growing season, (2) evaluate pesticide persistence longitudinally within the lakes, and (3) perform an ecotoxicity assessment. Six sampling campaigns were conducted at three lakes from April through October 2018 to measure the occurrence and persistence during pre, middle, and post growing season. Polar organic chemical integrative samplers (POCIS) were placed in streams near lake inlets and monthly samples were collected for analysis of twelve pesticides. Additional monthly grab water samples were taken at each POCIS location and at the midpoint and outlet of each lake. All pesticide samples were analyzed using liquid chromatography/tandem mass spectrometry (LC/MS/MS) and individual pesticide loading rates were determined. Occurrence and persistence of specific pesticides were significantly different between lakes in varying watershed land uses. Specifically, the recreational lake receiving predominately urban runoff had the highest load of pesticides, likely in the form of biocides, entering the waterbody. Concentrations of imidacloprid exceeded acute and chronic invertebrate levels for 11% and 61% of the sampling periods, respectively, with the recreational lake receiving predominately urban runoff having the most occurrences. Findings from this study are critical for preventing and mitigating potential effects of pesticides, specifically applied as biocides in urban landscapes, from entering and persisting in recreational lakes.

Escherichia coli concentrations in waters of a reservoir system impacted by cattle and migratory waterfowl.

Recent pathogenic Escherichia coli contamination of fresh vegetables that originated from irrigation water has increased awareness and importance of identifying sources of E. coli entering agroecosystems. However, inadequate methods for accurately predicting E. coli occurrence and sources in waterways continue to limit the identification of appropriate and effective prevention and treatment practices. Therefore, the primary objectives of this study were to: (1) Determine the concentration of E. coli during storm events in a hydrologic controlled stream situated in a livestock research operation that is located in the Central Flyway for avian migration in the United States. Great Plains; and (2) Identify trends between E. coli concentrations, grazing rotations, and avian migration patterns. The study sampled five rainfall events (three summer and two fall) to measure E. coli concentrations throughout storm events. A combination of cattle density and waterfowl migration patterns were found to significantly impact E. coli concentrations in the stream. Cattle density had a significant impact during the summer season (p < .0001), while waterfowl density had a significant impact on E. coli concentrations during the fall (p = .0422). The downstream reservoir had exceedance probabilities above the Environmental Protection Agency freshwater criteria > 85% of the growing season following rainfall events. Based on these findings, implementation of best management practices for reducing E. coli concentrations during the growing season and testing of irrigation water prior to application are recommended.

Mitigating the risk of atrazine exposure: Identifying hot spots and hot times in surface waters across Nebraska, USA.

Atrazine, one of the most widely used herbicides in the world, threatens human health along with terrestrial and aquatic biota. Recent reports have found atrazine in drinking water to be associated with increased birth defects and incidences of Non-Hodgkin's Lymphoma, with higher levels of significance from exposure to both atrazine and nitrate-N. The Midwest region of the United States, which includes Nebraska, is one of the leading regions for high nitrate-N concentrations and agrochemicals, including atrazine, in surface waters. Therefore, the objective of this study was to provide a case study for completing an environmental risk analysis for the potential exposure of atrazine and nitrate-N to ecosystems and humans through interaction with surface waters using two approaches: (1) Identify watersheds across Nebraska that were at risk for exceeding atrazine and nitrate-N maximum contaminant limits (MCLs) in surface water; and (2) Determine the specific times of year where risks were greatest. Factors were then analyzed using Geographic Information System (GIS) software to identify areas of high risk. Impairments for both nitrate-N and atrazine in the surface water were found predominately during the early growing season in the southeastern region of Nebraska, in watershed areas with the highest amount of corn production and annual precipitation. Further, the methodology developed in this study has the potential for application in regions with higher dependency on surface water to determine multiple agrochemical load influxes from upstream regions and evaluate other surface water contaminants during the same time periods.

Evaluation of the TBET Model for Potential Improvement of Southern P Indices.

Due to a shortage of available phosphorus (P)-loss datasets, simulated data from an accurate quantitative P transport model could be used to evaluate a P Index. The objective of this study was to compare predictions from the Texas Best Management Practice Evaluation Tool (TBET) against measured P-loss data to determine whether the model could be used to improve P Indices in the southern region. Measured P-loss data from field-scale study sites in Arkansas, Georgia, and North Carolina were used to assess the accuracy of TBET for predicting field-scale loss of P. We found that event-based predictions using an uncalibrated model were generally poor. Calibration improved runoff predictions and produced scatterplot regression lines that had slopes near one and intercepts near zero. However, TBET predictions of runoff met the performance criteria (Nash-Sutcliffe efficiency ≥ 0.3, percent bias ≤ 35%, and mean absolute error ≤ 10 mm) in only one out of six comparisons: North Carolina during calibration. Sediment predictions were imprecise, and dissolved P predictions underestimated measured losses. In North Carolina, total P-loss predictions were reasonably accurate because TBET did a slightly better job of predicting sediment losses from cultivated land. In Arkansas and Georgia, where the experimental sites were in forage production, the underprediction of dissolved P led directly to the underpredictions of total P. We conclude that TBET cannot be used to improve southern P Indices, but a curve number approach could be incorporated into P Indices to improve runoff predictions.

Comparing an Annual and a Daily Time-Step Model for Predicting Field-Scale Phosphorus Loss.

A wide range of mathematical models are available for predicting phosphorus (P) losses from agricultural fields, ranging from simple, empirically based annual time-step models to more complex, process-based daily time-step models. In this study, we compare field-scale P-loss predictions between the Annual P Loss Estimator (APLE), an empirically based annual time-step model, and the Texas Best Management Practice Evaluation Tool (TBET), a process-based daily time-step model based on the Soil and Water Assessment Tool. We first compared predictions of field-scale P loss from both models using field and land management data collected from 11 research sites throughout the southern United States. We then compared predictions of P loss from both models with measured P-loss data from these sites. We observed a strong and statistically significant ( < 0.001) correlation in both dissolved (ρ = 0.92) and particulate (ρ = 0.87) P loss between the two models; however, APLE predicted, on average, 44% greater dissolved P loss, whereas TBET predicted, on average, 105% greater particulate P loss for the conditions simulated in our study. When we compared model predictions with measured P-loss data, neither model consistently outperformed the other, indicating that more complex models do not necessarily produce better predictions of field-scale P loss. Our results also highlight limitations with both models and the need for continued efforts to improve their accuracy.

Development and testing of an in-stream phosphorus cycling model for the soil and water assessment tool.

The Soil and Water Assessment Tool is widely used to predict the fate and transport of phosphorus (P) from the landscape through streams and rivers. The current in-stream P submodel may not be suitable for many stream systems, particularly those dominated by attached algae and those affected by point sources. In this research, we developed an alternative submodel based on the equilibrium P concentration concept coupled with a particulate scour and deposition model. This submodel was integrated with the SWAT model and applied to the Illinois River Watershed in Oklahoma, a basin influenced by waste water treatment plant discharges and extensive poultry litter application. The model was calibrated and validated using measured data. Highly variable in-stream P concentrations and equilibrium P concentration values were predicted spatially and temporally. The model also predicted the gradual storage of P in streambed sediments and the resuspension of this P during periodic high-flow flushing events. Waste water treatment plants were predicted to have a profound effect on P dynamics in the Illinois River due to their constant discharge even under base flow conditions. A better understanding of P dynamics in stream systems using the revised submodel may lead to the development of more effective mitigation strategies to control the impact of P from point and nonpoint sources.