Fine-scale spatiotemporal variations in bacterial community diversity in agricultural pond water.

Microbial communities in surface waters are affected by environmental conditions and can influence changes in water quality. To explore the hypothesis that the microbiome in agricultural waters associates with spatiotemporal variations in overall water quality and, in turn, has implications for resource monitoring and management, we characterized the relationships between the microbiota and physicochemical properties in a model irrigation pond as a factor of sampling time (i.e., 9:00, 12:00, 15:00) and location within the pond (i.e., bank vs. interior sites and cross-sectional depths at 0, 1, and 2 m). The microbial communities, which were defined by 16S rRNA gene sequencing analysis, significantly varied based on all sampling factors (PERMANOVA P < 0.05 for each). While the relative abundances of dominant phyla (e.g., Proteobacteria and Bacteroidetes) were relatively stable throughout the pond, subtle yet significant increases in α-diversity were observed as the day progressed (ANOVA P < 0.001). Key water quality properties that also increased between the morning and afternoon (i.e., pH, dissolved oxygen, and temperature) positively associated with relative abundances of Cyanobacteria, though were inversely proportional to Verrucomicrobia. These properties, among additional parameters such as bioavailable nutrients (e.g., NH3, NO3, PO4), chlorophyll, phycocyanin, conductivity, and colored dissolved organic matter, exhibited significant relationships with relative abundances of various bacterial genera as well. Further investigation of the microbiota in underlying sediments revealed significant differences between the bank and interior sites of the pond (P < 0.05 for α- and ß-diversity). Overall, our findings emphasize the importance of accounting for time of day and water sampling location and depth when surveying the microbiomes of irrigation ponds and other small freshwater sources.

Fate and transport in environmental quality.

Changes in pollutant concentrations in environmental media occur both from pollutant transport in water or air and from local processes, such as adsorption, degradation, precipitation, straining, and so on. The terms "fate and transport" and "transport and fate" reflect the coupling of moving with the carrier media and biogeochemical processes describing local transformations or interactions. The Journal of Environmental Quality (JEQ) was one of the first to publish papers on fate and transport (F&T). This paper is a minireview written to commemorate the 50th anniversary of JEQ and show how the research interests, methodology, and public attention have been reflected in fate and transport publications in JEQ during the last 40 years. We report the statistics showing how the representation of different pollutant groups in papers changed with time. Major focus areas have included the effect of solution composition on F&T and concurrent F&T, the role of organic matter, and the relative role of different F&T pathways. The role of temporal and spatial heterogeneity has been studied at different scales. The value of long-term F&T studies and developments in modeling as the F&T research approach was amply demonstrated. Fate and transport studies have been an essential part of conservation measure evaluation and comparison and ecological risk assessment. For 50 years, JEQ has delivered new insights, methods, and applications related to F&T science. The importance of its service to society is recognized, and we look forward to new generations of F&T researchers presenting their contributions in JEQ.

Modeling the kinetics of manure-borne fecal indicator removal in runoff.

Several manure-borne microorganism removal models have been developed to provide accurate estimations of the number of microorganisms removed from manure or manured soils undergoing rainfall. It has been commonly assumed that these models perform equally well when used to simulate microbe removal in runoff from manures of different consistency and levels of weathering. The objectives of this work were (a) to observe kinetics of the removal of Escherichia coli and enterococci with runoff for two different manure consistencies and three manure weathering durations, and (b) to compare performance of the log-linear, Vadas-Kleinman-Sharpley, and Bradford-Shijven models in simulation of the observed kinetics. Liquid and solid dairy manure were applied to grassed soil boxes that received simulated rainfall immediately after application and subsequently at 1 and 2 wk. Runoff samples were collected for 1 h at increasing time intervals during each event. Only the effective rainfall depth at the start of runoff was significantly affected by manure consistency (p = .033), whereas other parameters were not (p > .05). Substantial differences in microorganism removal kinetics during the initial, 1-, and 2-wk rainfall events were manifested by the significant (p < .05) effect of the degree of manure weathering in about 70% of cases. The log-linear model produced the largest fitting error especially during the initial rainfall event. The Vadas-Kleinman-Sharpley model and the Bradford-Schijven model were comparable in accuracy for all events. The latter model was slightly more accurate, and the former model had better expressed dependencies of parameter values on manure weathering. Ignoring manure weathering may lead to incorrect parameterization of manure removal models.

Intraseasonal variation of phycocyanin concentrations and environmental covariates in two agricultural irrigation ponds in Maryland, USA.

Recently, cyanobacteria blooms have become a concern for agricultural irrigation water quality. Numerous studies have shown that cyanotoxins from these harmful algal blooms (HABs) can be transported to and assimilated into crops when present in irrigation waters. Phycocyanin is a pigment known only to occur in cyanobacteria and is often used to indicate cyanobacteria presence in waters. The objective of this work was to identify the most influential environmental covariates affecting the phycocyanin concentrations in agricultural irrigation ponds that experience cyanobacteria blooms of the potentially toxigenic species Microcystis and Aphanizomenon using machine learning methodology. The study was performed at two agricultural irrigation ponds over a 5-month period in the summer of 2018. Phycocyanin concentrations, along with sensor-based and fluorometer-based water quality parameters including turbidity (NTU), pH, dissolved oxygen (DO), fluorescent dissolved organic matter (fDOM), conductivity, chlorophyll, color dissolved organic matter (CDOM), and extracted chlorophyll were measured. Regression tree analyses were used to determine the most influential water quality parameters on phycocyanin concentrations. Nearshore sampling locations had higher phycocyanin concentrations than interior sampling locations and "zones" of consistently higher concentrations of phycocyanin were found in both ponds. The regression tree analyses indicated extracted chlorophyll, CDOM, and NTU were the three most influential parameters on phycocyanin concentrations. This study indicates that sensor-based and fluorometer-based water quality parameters could be useful to identify spatial patterns of phycocyanin concentrations and therefore, cyanobacteria blooms, in agricultural irrigation ponds and potentially other water bodies.

Drone-based imaging to assess the microbial water quality in an irrigation pond: A pilot study.

Microbial water quality datasets are essential in irrigated agricultural practices to detect and inform measures to prevent the contamination of produce. Escherichia coli (E. coli) concentrations are commonly used to evaluate microbial water quality. Remote sensing imagery has been successfully used to retrieve several water quality parameters that can be determinants of E. coli habitats in waterbodies. This pilot study was conducted to test the possibility of using imagery from a small unmanned aerial vehicle (sUAV or drone) to improve the estimation of microbial water quality in small irrigation ponds. In situ measurements of pH, turbidity, specific conductance, and concentrations of dissolved oxygen, chlorophyll-a, phycocyanin, and fluorescent dissolved organic matter were taken at depths of 0-15 cm in 23 locations across a pond in Central Maryland, USA. The pond surface was concurrently imaged using a drone with three modified GoPro cameras, and a multispectral MicaSense RedEdge camera with five spectral bands. The GoPro imagery was decomposed into red, blue, and green components. Mean digital numbers for 1-m radius areas in the images were combined with the water quality data to provide input for a regression tree-based analysis. The accuracy of the regression-tree data description with "only imagery" inputs was the same or better than that of trees constructed with "only water-quality parameters" as inputs. From multiple cross-validation runs with "only imagery" inputs for the regression trees, the average (±SD) determination coefficient and root-mean-squared error of the decimal logarithm of E. coli concentrations were 0.793 ±â€¯0.035 and 0.131 ±â€¯0.011, respectively. The results of this study demonstrate the opportunities for using sUAV imagery for obtaining a more accurate delineation of the spatial variation of E. coli concentrations in irrigation ponds.

Intraseasonal variation of E. coli and environmental covariates in two irrigation ponds in Maryland, USA.

The microbial quality of irrigation water is typically assessed by measuring the concentrations of E. coli in irrigation water reservoirs that are variable in space and time. E. coli concentrations are affected by water quality parameters that co-vary with E. coli concentrations and may be easily measured with currently available sensors. The objective of this work was to identify the most influential environmental covariates affecting E. coli concentrations during a three-month biweekly monitoring period within two irrigation ponds in Maryland during the summer of 2017. E. coli levels as well as sensor-based water quality parameters including turbidity, pH, dissolved oxygen, dissolved fluorescent organic matter, conductivity, and chlorophyll were measured at 23 and 34 locations in ponds 1 and 2, respectively. Regression tree analyses were used to determine the most influential water quality parameters for the prediction of E. coli levels. Correlations between E. coli and water quality covariates were not strong and were inconsistently significant. Shoreline sample locations had higher E. coli concentrations than interior pond samples and significant differences were observed when comparing these two groups. Regression trees provided fairly accurate predictions of E. coli levels based on water quality parameters with R2 values ranging from 0.70 to 0.93. Factors identified via the regression trees varied by sampling date but common leading covariates included cyanobacteria, organic matter, and turbidity. Results indicated environmental covariates, sensed either remotely or in situ, could be useful to delineate areas with different E. coli survival conditions across irrigation ponds and potentially other water bodies such as lakes, rivers, or bays.

Functional Evaluation of Three Manure-Borne Indicator Bacteria Release Models with Multiyear Field Experiment Data.

Modeling the fate and transport of Escherichia coli is of substantial interest because of how this organism serves as an indicator of fecal contamination in microbial water quality assessment. The efficacy of models used to assess the export of E. coli from agricultural fields is dependent, in part, on submodels they utilize to simulate E. coli release from land-applied manure and animal waste. Although several release submodels have been proposed, they have only been evaluated and compared with data from laboratory or small plot E. coli release experiments. Our objective was to evaluate and compare performances of three manure-borne bacteria release submodels at field-scale: exponential release (EM), two-parametric Bradford and Schijven (B-S), and two-parametric Vadas-Kleinman-Sharpley (VKS); each was independently incorporated and tested as a submodel within the export model KINEROS2/STWIR, using E. coli. Dairy manure was uniformly applied via surface broadcasting once a year for six consecutive years on a 0.28 ha experimental field site. Two irrigation events followed each application: the first immediately followed the initial application and the second occurred one week later. Manure and soil samples were collected before and after irrigation, respectively, and manure, soil, and edge-of-field runoff samples were analyzed for E. coli. Model performance was evaluated with the Akaike criterion, coefficients of determination (R2), and root mean squared errors (RMSE) values. The percentage of exported manure-borne E. coli varied from 0.1% to 10% in most cases, generally reflecting the lag time between initiation of irrigation and initiation ofedge-of-field runoff. The export model performed better when using the VKS submodel which was preferred in 55% of cases. The B-S and EM submodels were preferred in 27% and 18% of cases, respectively. Two-parametric submodels were ultimately preferred over the single parameter submodel.

Microbial Water Quality: Monitoring and Modeling.

Microbial water quality lies in the nexus of human, animal, and environmental health. Multidisciplinary efforts are under way to understand how microbial water quality can be monitored, predicted, and managed. This special collection of papers in the was inspired by the idea of creating a special section containing the panoramic view of advances and challenges in the arena of microbial water quality research. It addresses various facets of health-related microorganism release, transport, and survival in the environment. The papers analyze the spatiotemporal variability of microbial water quality, selection of predictors of the spatiotemporal variations, the role of bottom sediments and biofilms, correlations between concentrations of indicator and pathogenic organisms and the role for risk assessment techniques, use of molecular markers, subsurface microbial transport as related to microbial water quality, antibiotic resistance, real-time monitoring and nowcasting, watershed scale modeling, and monitoring design. Both authors and editors represent international experience in the field. The findings underscore the challenges of observing and understanding microbial water quality; they also suggest promising research directions for improving the knowledge base needed to protect and improve our water sources.

Differential release of manure-borne bioactive phosphorus forms to runoff and leachate under simulated rain.

Limited information exists on the unhindered release of bioactive phosphorus (P) from a manure layer to model the partitioning and transport of component P forms before they reach an underlying soil. Rain simulations were conducted to quantify effects of intensity (30, 60, and 90 mm h-1) on P release from an application of 60 Mg ha-1 of dairy manure. Runoff contained water-extractable- (WEP), exchangeable and enzyme-labile bioactive P (TBIOP), in contrast to the operationally defined "dissolved-reactive P" form. The released P concentrations and flow-weighed mass loads were described by the log-normal probability density function. At a reference condition of 30 mm h-1 and maintaining the surface at a 5% incline, runoff was minimal, and WEP accounted for 20.9% of leached total P (TP) concentrations, with an additional 25-30% as exchangeable and enzyme-labile bioactive P over the 1-h simulation. On a 20% incline, increased intensity accelerated occurrence of concentrationmax and shifted the skewed P concentration distribution more to the left. Differences in trends of WEP, TBIOP, or net enzyme-labile P (PHPo) cumulative mass released per unit mass of manure between intensities were attributable to the higher frequency of raindrops striking the manure layer, thus increasing detachment and load of colloidal PHPo of the water phases. Thus, detailed knowledge of manure physical characteristics, bioactive P distribution in relation to rain intensity, and attainment of steady-state of water fluxes were critical factors in improved prediction of partitioning and movement of manure-borne P under rainfall.

Depth-Dependent Survival of Escherichia coli and Enterococci in Soil after Manure Application and Simulated Rainfall.

Once released, manure-borne bacteria can enter runoff via interaction with the thin mixing layer near the soil surface. The objectives of this work were to document temporal changes in profile distributions of manure-borne Escherichia coli and enterococci in the near-surface soil layers after simulated rainfalls and to examine differences in survival of the two fecal indicator bacteria. Rainfall simulations were performed in triplicate on soil-filled boxes with grass cover and solid manure application for 1 h with rainfall depths of 30, 60, and 90 mm. Soil samples were collected weekly from depth ranges of 0 to 1, 1 to 2, 2 to 5, and 5 to 10 cm for 1 month. Rainfall intensity was found to have a significant impact on the initial concentrations of fecal indicator bacteria in the soil. While total numbers of enterococci rapidly declined over time, E. coli populations experienced initial growth with concentration increases of 4, 10, and 25 times the initial levels at rainfall treatment depths of 30, 60, and 90 mm, respectively. E. coli populations grew to the approximately the same level in all treatments. The 0- to 1-cm layer contained more indicator bacteria than the layers beneath it, and survival of indicator bacteria was better in this layer, with decimation times between 12 and 18 days after the first week of growth. The proportion of bacteria in the 0- to 1-cm layer grew with time as the total number of bacteria in the 0- to 10-cm layer declined. The results of this work indicate the need to revisit the bacterial survival patterns that are assumed in water quality models.

Response of coliform populations in streambed sediment and water column to changes in nutrient concentrations in water.

As sediments increasingly become recognized as reservoirs of indicator and pathogen microorganisms, an understanding of the persistence of indicator organisms becomes important for assessment and predictions of microbial water quality. The objective of this work was to observe the response of water column and sediment coliform populations to the change in nutrient concentrations in the water column. Survival experiments were conducted in flow-through chambers containing sandy sediments. Bovine feces were collected fresh and introduced into sediment. Sixteen days later, the same fecal material was autoclaved and diluted to provide three levels - 1×, 0.5×, and 0.1× of nutrient concentrations - spike in water column. Total coliforms, Escherichia coli, and total aerobic heterotrophic bacterial concentrations were monitored in water and sediment. Bacteria responded to the nutrient spike with initial growth both in the water column and in sediment. The response of bacterial concentrations in water column was nonlinear, with no significant changes at 0.1 and .5× spikes, but a substantial change at 1× spike. Bacteria in sediment responded to the spikes at all added nutrient levels. Coliform inactivation rates both in sediment and in water after the initial growth occurred, were not significantly different from the inactivation rates before spike. These results indicate that introduction of nutrients into the water column results in nonlinear response of E. coli concentrations both in water and in sediments, followed by the inactivation with the same rate as before introduction of nutrients.

Comparing temperature effects on Escherichia coli, Salmonella, and Enterococcus survival in surface waters.

UNLABELLED: The objective of this study was to compare dependency of survival rates on temperature for indicator organisms Escherichia coli and Enterococcus and the pathogen Salmonella in surface waters. A database of 86 survival datasets from peer-reviewed papers on inactivation of E. coli, Salmonella and Enterococcus in marine waters and of E. coli and Salmonella in lake waters was assembled. The Q10 model was used to express temperature effect on survival rates obtained from linear sections of semi-logarithmic survival graphs. Available data were insufficient to establish differences in survival rates and temperature dependencies for marine waters where values of Q10  = 3 and a survival rate of 0·7 day(-1) could be applied. The Q10 values in lake waters were substantially lower in marine waters, and Salmonella inactivation in lake water was, on average, twice as fast as E. coli; data on E. coli substantially outnumber data on Enterococcus and Salmonella. The relative increase in inactivation with increase in temperature is higher in marine waters than lake water, and differences in inactivation between Salmonella and E. coli at a given temperature were significant in lake water but not in marine waters. SIGNIFICANCE AND IMPACT OF THE STUDY: Microbiological quality of surface waters is of paramount importance for public health. The novelty of this work is using a large compendium of published data to develop the first comparison of temperature effects on survival of the pathogen Salmonella and water quality indicator micro-organisms Escherichia coli and Enterococcus in natural waters. The existing relatively large body of knowledge on E. coli survival appears to be useful to assess the effect of temperature on survival of Salmonella. Moreover, results of this work constitute an essential input in models to support environmental management decisions on the use of surface water sources in agriculture, aquaculture and recreation.

Performance of Weibull and Linear Semi-logarithmic Models in Simulating Inactivation in Waters.

Modeling inactivation of indicator microorganisms is a necessary component of microbial water quality forecast and management recommendations. The linear semi-logarithmic (LSL) model is commonly used to simulate the dependencies of bacterial concentrations in waters on time. There were indications that assumption of the semi-logarithmic linearity may not be accurate enough in waters. The objective of this work was to compare performance of the LSL and the two-parametric Weibull inactivation models with data on survival of indicator organism in various types of water from a representative database of 167 laboratory experiments. The Weibull model was preferred in >99% of all cases when the root mean squared errors and Nash-Sutcliffe statistics were compared. Comparison of corrected Akaike statistic values gave the preference to the Weibull model in only 35% of cases. This was caused by (i) a small number of experimental points on some inactivation curves, (ii) closeness of the shape parameter of the Weibull equation to one, and (iii) piecewise log-linear inactivation dynamic that could be well described by neither of the two models compared. Based on the Akaike test, the Weibull model was favored in agricultural, lake, and pristine waters, whereas the LSL model was preferred for groundwater, wastewater, rivers, and marine waters. The decimal reduction time parameter of both the LSL and Weibull models exhibited an Arrhenius-type dependence on temperature. Overall, the existing inactivation data indicate that the application of the Weibull model can improve the predictive capabilities of microbial water quality modeling.

Modeling transport of Escherichia coli in a creek during and after artificial high-flow events: three-year study and analysis.

Escherichia coli is the leading indicator of microbial contamination of natural waters, and so its in-stream fate and transport needs to be understood to eventually minimize surface water contamination by microorganisms. To better understand mechanisms of E. coli release and transport from soil sediment in a creek the artificial high-water flow events were created by releasing 60-80 m(3) of city water on a tarp-covered stream bank in four equal allotments in July 2008, 2009 and 2010. A conservative tracer difluorobenzoic acid (DFBA) was added to the released water in 2009 and 2010. Water flow rate, E. coli and DFBA concentrations as well as water turbidity were monitored with automated samplers at three in-stream weirs. A one-dimensional model was applied to simulate water flow, and E. coli and DFBA transport during these experiments. The Saint-Venant equations were used to calculate water depth and discharge while a stream solute transport model accounted for release of bacteria by shear stress from bottom sediments, advection-dispersion, and exchange with transient storage (TS). Reach-specific model parameters were estimated by evaluating observed time series of flow rates and concentrations of DFBA and E. coli at all three weir stations. Observed DFBA and E. coli breakthrough curves (BTC) exhibited long tails after the water pulse and tracer peaks had passed indicating that transient storage (TS) might be an important element of the in-stream transport process. Comparison of simulated and measured E. coli concentrations indicated that significant release of E. coli continued when water flow returned to the base level after the water pulse passed and bottom shear stress was small. The mechanism of bacteria continuing release from sediment could be the erosive boundary layer exchange enhanced by changes in biofilm properties by erosion and sloughing detachment.

Escherichia coli survival in waters: temperature dependence.

Knowing the survival rates of water-borne Escherichia coli is important in evaluating microbial contamination and making appropriate management decisions. E. coli survival rates are dependent on temperature, a dependency that is routinely expressed using an analogue of the Q10 model. This suggestion was made 34 years ago based on 20 survival curves taken from published literature, but has not been revisited since then. The objective of this study was to re-evaluate the accuracy of the Q10 equation, utilizing data accumulated since 1978. We assembled a database of 450 E. coli survival datasets from 70 peer-reviewed papers. We then focused on the 170 curves taken from experiments that were performed in the laboratory under dark conditions to exclude the effects of sunlight and other field factors that could cause additional variability in results. All datasets were tabulated dependencies "log concentration vs. time." There were three major patterns of inactivation: about half of the datasets had a section of fast log-linear inactivation followed by a section of slow log-linear inactivation; about a quarter of the datasets had a lag period followed by log-linear inactivation; and the remaining quarter were approximately linear throughout. First-order inactivation rate constants were calculated from the linear sections of all survival curves and the data grouped by water sources, including waters of agricultural origin, pristine water sources, groundwater and wells, lakes and reservoirs, rivers and streams, estuaries and seawater, and wastewater. Dependency of E. coli inactivation rates on temperature varied among the water sources. There was a significant difference in inactivation rate values at the reference temperature between rivers and agricultural waters, wastewaters and agricultural waters, rivers and lakes, and wastewater and lakes. At specific sites, the Q10 equation was more accurate in rivers and coastal waters than in lakes making the value of the Q10 coefficient appear to be site-specific. Results of this work indicate possible sources of uncertainty to be accounted for in watershed-scale microbial water quality modeling.

Persistence of Escherichia coli introduced into streambed sediments with goose, deer and bovine animal waste.

AIMS: The focus of this work was to compare the survival of Escherichia coli introduced into streambed sediments from goose, deer and bovine faeces vs indigenous E. coli. METHODS AND RESULTS: The survival experiments were conducted in flow-through chambers for 32days using two sediments (mineral and organic) obtained from a first-order creek in Maryland. Bovine, goose and deer faeces were collected fresh and diluted or enriched so that added E. coli and indigenous populations were equivalent. Escherichia coli and total coliforms were enumerated using the Colilert-18 Quanti-Tray system. Patterns of E. coli survival and inactivation rates were virtually identical for indigenous strains in both mineral and organic sediments. The addition of E. coli strains from bovine, goose or deer faeces had relatively little impact on final E. coli concentrations, with the exception of deer-borne E. coli populations in the organic sediment. CONCLUSION: These results indicate that indigenous sediment-borne E. coli strains are generally, or more, persistent than those deposited into sediments, including wildlife. SIGNIFICANCE AND IMPACT OF THE STUDY: This is the first study on the survival of E. coli originating from wildlife faeces, in sediments, as opposed to bovine faeces or laboratory-cultured strains. As wildlife are likely to be the primary source of E. coli in most non agricultural watersheds, an understanding of the persistence of these strains is important to understanding microbial water quality.

Effect of biofilm in irrigation pipes on microbial quality of irrigation water.

AIMS: The focus of this work was to investigate the contribution of native Escherichia coli to the microbial quality of irrigation water and to determine the potential for contamination by E. coli associated with heterotrophic biofilms in pipe-based irrigation water delivery systems. METHODS AND RESULTS: The aluminium pipes in the sprinkler irrigation system were outfitted with coupons that were extracted before each of the 2-h long irrigations carried out with weekly intervals. Water from the creek water and sprinklers, residual water from the previous irrigation and biofilms on the coupons were analysed for E. coli. High E. coli concentrations in water remaining in irrigation pipes between irrigation events were indicative of E. coli growth. In two of the four irrigations, the probability of the sample source, (creek vs sprinkler), being a noninfluential factor, was only 0.14, that is, source was an important factor. The population of bacteria associated with the biofilm on pipe walls was estimated to be larger than that in water in pipes in the first three irrigation events and comparable to one in the fourth event. CONCLUSION: Biofilm-associated E. coli can affect microbial quality of irrigation water and, therefore, should not be neglected when estimating bacterial mass balances for irrigation systems. SIGNIFICANCE AND IMPACT OF THE STUDY: This work is the first peer-reviewed report on the impact of biofilms on microbial quality of irrigation waters. Flushing of the irrigation system may be a useful management practice to decrease the risk of microbial contamination of produce. Because microbial water quality can be substantially modified while water is transported in an irrigation system, it becomes imperative to monitor water quality at fields, rather than just at the intake.

Survival of manure-borne E. coli in streambed sediment: effects of temperature and sediment properties.

Escherichia coli bacteria are commonly used as indicator organisms to designate of impaired surface waters and to guide the design of management practices to prevent fecal contamination of water. Stream sediments are known to serve as a reservoir and potential source of fecal bacteria (E. coli) for stream water. In agricultural watersheds, substantial numbers of E. coli may reach surface waters, and subsequently be deposited into sediments, along with fecal material in runoff from land-applied manures, grazing lands, or wildlife excreta. The objectives of this work were (a) to test the hypothesis that E. coli survival in streambed sediment in the presence of manure material will be affected by sediment texture and organic carbon content and (b) to evaluate applicability of the exponential die-off equation to the E. coli survival data in the presence of manure material. Experiments were conducted at three temperatures (4 degrees C, 14 degrees C, and 24 degrees C) in flow-through chambers using sediment from three locations at the Beaverdam Creek Tributary in Beltsville, Maryland mixed with dairy manure slurry in the proportion of 1000:1. Indigenous E. coli populations in sediments ranged from ca. 10(1) to 10(3)MPNg(-1) while approx 10(3) manure-borne E. coli MPNg(-1) were added. E. coli survived in sediments much longer than in the overlaying water. The exponential inactivation model gave an excellent approximation of data after 6-16 days from the beginning of the experiment. Slower inactivation was observed with the increase in organic carbon content in sediments with identical granulometric composition. The increase in the content of fine particles and organic carbon in sediments led not only to the slower inactivation but also to lower sensitivity of the inactivation to temperature. Streambed sediment properties have to be documented to better evaluate the role of sediments as reservoirs of E. coli that can affect microbiological stream water quality during high flow events.

Uncertainty evaluation of coliform bacteria removal from vegetated filter strip under overland flow condition.

Vegetated filter strips (VFS) have become an important component of water quality improvement by reducing sediment and nutrients transport to surface water. This management practice is also beneficial for controlling manure-borne pathogen transport to surface water. The objective of this work was to assess the VFS efficiency and evaluate the uncertainty in predicting the microbial pollutant removal from overland flow in VFS. We used the kinematic wave overland flow model as implemented in KINEROS2 coupled with the convective-dispersive overland transport model which accounts for the reversible attachment-detachment and surface straining of infiltrating bacteria. The model was successfully calibrated with experimental data obtained from a series of simulated rainfall experiments at vegetated and bare sandy loam and clay loam plots, where fecal coliforms were released from manure slurry applied on the top of the plots. The calibrated model was then used to assess the sensitivity of the VFS efficiency to the model parameters, rainfall duration, and intensity for a case study with a 6-m VFS placed at the edge of 200-m long field. The Monte Carlo simulations were also performed to evaluate the uncertainty associated with the VFS efficiency given the uncertainty in the model parameters and key inputs. The VFS efficiency was found to be <95% in 25%, <75% in 23%, and <25% in 20% of cases. Relatively long high-intensity rainfalls, low hydraulic conductivities, low net capillary drives of soil, and high soil moisture contents before rainfalls caused the partial failure of VFS to retain coliforms from the infiltration excess runoff.

Storm water pollutant removal performance of compost filter socks.

In 2005, the U.S. Environmental Protection Agency (USEPA) National Menu of Best Management Practices (BMPs) listed compost filter socks (FS) as an approved BMP for controlling sediment in storm runoff on construction sites. The objectives of this study were to determine if FS with or without the addition of a flocculation agent to the FS system can significantly remove (i) suspended clay and silt particulates, (ii) ammonium nitrogen (NH(4)-N) and nitrate-nitrite nitrogen (NO(3)-N), (iii) fecal bacteria, (iv) heavy metals, and (v) petroleum hydrocarbons from storm water runoff. Five separate (I-V) 30-min simulated rainfall-runoff events were applied to soil chambers packed with Hartboro silt loam (fine-loamy, mixed, active, nonacid, mesic fluvaquentic Endoaquepts) or a 6-mm concrete veneer on a 10% slope, and all runoff was collected and analyzed for hydraulic flow rate, volume, pollutant concentrations, pollutant loads, and removal efficiencies. In corresponding experiments, runoff was analyzed for (i) size of sediment particles, (ii) NH(4)-N and NO(3)-N, (iii) total coliforms (TC) and Escherichia coli, (iv) Cd, Cr, Cu, Ni, Pb and Zn, and (v) gasoline, diesel, and motor oil, respectively. Results showed that: (i) FS removed 65% and 66% of clay (<0.002 mm) and silt (0.002-0.05 mm), respectively; (ii) FS removed 17%, and 11% of NH(4)-N and NO(3)-N, respectively and when NitroLoxx was added to the FS, removal of NH(4)-N load increased to 27%; (iii) total coliform and E. coli removal efficiencies were 74 and 75%, respectively, however, when BactoLoxx was added, removal efficiency increased to 87 and 99% for TC and 89 and 99% for E. coli, respectively; (iv) FS removal efficiency for Cd, Cr, Cu, Ni, Pb, and Zn ranged from 37 to 72%, and, when MetalLoxx was added, removal efficiency ranged from 47 to 74%; and (v) FS removal efficiency for the three petroleum hydrocarbons ranged from 43 to 99% and the addition of PetroLoxx increased motor oil and gasoline removal efficiency in the FS system.