No abstract

One of the most commonly used models for describing solute sorption to soils is the Langmuir model. Because the Langmuir model is nonlinear, fitting the model to sorption data requires that the model be solved iteratively using an optimization program. To avoid the use of optimization programs, a linearized version of the Langmuir model is often used so that model parameters can be obtained by linear regression. Although the linear and nonlinear Langmuir equations are mathematically equivalent, there are several limitations to using linearized Langmuir equations. We examined the limitations of using linearized Langmuir equations by fitting P sorption data collected on eight different soils with four linearized versions of the Langmuir equation and comparing goodness‐of‐fit measures and fitted parameter values with those obtained with the nonlinear Langmuir equation. We then fit the sorption data with two modified versions of the Langmuir model and assessed whether the fits were statistically superior to the original Langmuir equation. Our results demonstrate that the use of linearized Langmuir equations needlessly limits the ability to model sorption data with good accuracy. To encourage the testing of additional nonlinear sorption models, we have made available an easily used Microsoft Excel spreadsheet (ars.usda.gov/msa/awmru/bolster/Sorption_spreadsheets) capable of generating best‐fit parameters and their standard errors and confidence intervals, correlations between fitted parameters, and goodness‐of‐fit measures. The results of our study should promote more critical evaluation of model fits to sorption data and encourage the testing of more sophisticated sorption models.

The series of papers in this issue of AMBIO represent technical presentations made at the 7th International Phosphorus Workshop (IPW7), held in September, 2013 in Uppsala, Sweden. At that meeting, the 150 delegates were involved in round table discussions on major, predetermined themes facing the management of agricultural phosphorus (P) for optimum production goals with minimal water quality impairment. The six themes were (1) P management in a changing world; (2) transport pathways of P from soil to water; (3) monitoring, modeling, and communication; (4) importance of manure and agricultural production systems for P management; (5) identification of appropriate mitigation measures for reduction of P loss; and (6) implementation of mitigation strategies to reduce P loss. This paper details the major challenges and research needs that were identified for each theme and identifies a future roadmap for catchment management that cost-effectively minimizes P loss from agricultural activities.

Abstract. Miscible displacement experiments were performed on intact sand columns ranging from 15 to 60 cm in length to determine whether bacterial deposition varies at the centimeter scale within aquifer sediments. A 1-pore-volume pulse of radiolabeled cell suspension was introduced into the columns followed by a 2-pore-volume flush of artificial groundwater. The columns were then drained and dissected along the axis of flow. At -1-cm intervals, nine samples were removed for the enumeration of sediment-associated bacteria. Concentrations of sediment-associated (deposited) bacteria varied by up to 2 orders of magnitude in the direction perpendicular to flow demonstrating that bacterial deposition cannot be described mechanistically by a single rate coefficient.

Most phosphorus (P) modeling studies of water quality have focused on surface runoff loses. However, a growing number of experimental studies have shown that P losses can occur in drainage water from artificially drained fields. In this review, we assess the applicability of nine models to predict this type of P loss. A model of P movement in artificially drained systems will likely need to account for the partitioning of water and P into runoff, macropore flow, and matrix flow. Within the soil profile, sorption and desorption of dissolved P and filtering of particulate P will be important. Eight models are reviewed (ADAPT, APEX, DRAINMOD, HSPF, HYDRUS, ICECREAMDB, PLEASE, and SWAT) along with P Indexes. Few of the models are designed to address P loss in drainage waters. Although the SWAT model has been used extensively for modeling P loss in runoff and includes tile drain flow, P losses are not simulated in tile drain flow. ADAPT, HSPF, and most P Indexes do not simulate flow to tiles or drains. DRAINMOD simulates drains but does not simulate P. The ICECREAMDB model from Sweden is an exception in that it is designed specifically for P losses in drainage water. This model seems to be a promising, parsimonious approach in simulating critical processes, but it needs to be tested. Field experiments using a nested, paired research design are needed to improve P models for artificially drained fields. Regardless of the model used, it is imperative that uncertainty in model predictions be assessed.

Escherichia coli is a commonly used indicator organism for detecting the presence of fecal-borne pathogenic microorganisms in water supplies. The importance of E. coli as an indicator organism has led to numerous studies looking at cell properties and transport behavior of this microorganism. In many of these studies, however, only a single strain of E. coli was used even though research has shown that significant genetic variability exists among different strains of E. coli. If this genetic diversity results in differences in cell properties that affect transport, different strains of E. coli may exhibit different rates of transport in the environment. Therefore, the objectives of our study were to investigate the variability in surface characteristics and transport behavior of E. coli isolates obtained from six different sources: beef cattle, dairy cattle, horse, human, poultry, and wildlife. Cell properties such as electrophoretic mobility, cell size and shape, hydrophobicity, charge density, and extracellular polymeric substance composition were measured for each isolate. In addition, the transport behavior of each isolate was assessed by measuring transport through 10-cm packed beds of clean quartz sand. Our results show a large diversity in cell properties and transport behavior for the different E. coli isolates. This diversity in transport behavior must be taken into account when making assessments of the suitability of using E. coli as an indicator organism for specific pathogenic microorganisms in groundwater environments as well as modeling the movement of E. coli in the subsurface.

Many states have invested significant resources to identify components of their Phosphorus (P) Index that reliably estimate the relative risk of P loss and incentivize conservation management. However, differences in management recommendations and manure application guidelines for similar field conditions among state P Indices, coupled with minimal reductions in the extent of P-impaired surface waters and soil test P (STP) levels, led the U.S. Natural Resources Conservation Service (NRCS) to revise the 590 Nutrient Management Standard. In preparation for this revision, NRCS requested that a review of the scientific underpinnings and accuracy of current P Indices be undertaken. They also sought to standardize the interpretation and management implications of P Indices, including establishment of ratings above which P applications should be curtailed. Although some states have initiated STP thresholds above which no application of P is allowed, STP alone cannot define a site's risk of P loss. Phosphorus Indices are intended to account for all of the major factors leading to P loss. A rigorous evaluation of P Indices is needed to determine if they are directionally and magnitudinally correct. Although use of observed P loss data under various management scenarios is ideal, such data are spatially and temporally limited. Alternatively, the use of a locally validated water quality model that has been shown to provide accurate estimates of P loss may be the most expedient option to conduct Index assessments in the short time required by the newly revised 590 Standard.

Aims:  To evaluate the survival of Campylobacter jejuni relative to that of Escherichia coli in groundwater microcosms varying in nutrient composition. Methods and Results:  Studies were conducted in groundwater and deionized water incubated for up to 470 days at 4°C. Samples were taken for culturable and total cell counts, nutrient and molecular analysis. Die‐off in groundwater microcosms was between 2·5 and 13 times faster for C. jejuni than for E. coli. Campylobacter jejuni had the lowest decay rate and longest culturability in microcosms with higher dissolved organic carbon (4 mg l−1). Escherichia coli survival was the greatest when the total dissolved nitrogen (12·0 mg l−1) was high. The transition of C. jejuni to the coccoid stage was independent of culturability. Conclusion:  The differences in the duration of survival and response to water nutrient composition between the two organisms suggest that E. coli may be present in the waters much longer and respond to water composition much differently than C. jejuni. Significance and Impact of the Study:  The data from these studies would aid in the evaluation of the utility of E. coli as an indicator of C. jejuni. This study also provided new information about the effect of nutrient composition on C. jejuni viability.