Estimation of upper centile concentrations using historical atrazine monitoring data from community water systems

A survey sampling approach is presented for estimating upper centiles of aggregate distributions of surface water pesticide measurements obtained from datasets with large sample sizes but variable sampling frequency. It is applied to three atrazine monitoring programs of Community Water Systems (CWS) that used surface water as their drinking water source: the nationwide Safe Drinking Water Act (SDWA) data, the Syngenta Voluntary Monitoring Program (VMP), and the Atrazine Monitoring Program (AMP).The VMP/AMP CWS were selected on the basis of atrazine monitoring history (CWS having at least one annual average concentration from SDWA ≥ 1.6 ppb atrazine since 1997 in the AMP). Estimates of the raw water 95th, 99th, and 99.9th centile atrazine concentrations for the VMP/AMP CWS are 4.82, 11.85, and 34.00 ppb, respectively. The corresponding estimates are lower for the finished drinking water samples, with estimates of 2.75, 7.94, and 22.66 ppb, respectively. Finished water centile estimates for the VMP/AMP CWS using only the SDWA data for these sites are consistent with the results. Estimates are provided for the April through July period and for CWS based on surface water source type (static, flowing, or mixed). Requisite sample sizes are determined using statistical tolerance limits, relative SE, and the Woodruff interval sample size criterion. These analyses provide 99.9% confidence that the existing data include the 99.9th centile atrazine concentration for CWS raw and finished water in the Midwest atrazine high-use areas and in the nationwide SDWA dataset. The general validity of this approach is established by a simulation that shows estimates to be close to target quantities for weights based on sampling probabilities or time intervals between samples. Recommendations are given for suitable effective sample sizes to reliably determine interval estimates.     

DESIGN CONSIDERATIONS FOR AMBIENT STREAM QUALITY MONITORING1

ABSTRACT: Existing ambient water quality monitoring programs have resulted in data which are often unsuitable for assessment of water quality trends. A primary concern in designing a stream quality monitoring network is the selection of a temporal sampling strategy. It is extremely important that data for trend assessment be collected uniformly in time. Greatly superior trend detection power results for such a strategy as compared to stratified sampling strategies. In general, it is desirable that sampling frequencies be at least monthly but not greater than biweekly; higher sampling frequencies usually result in little additional information. An upper limit on trend detectability exists such that for both five and ten year base periods it is often impossible to detect trends in time series where the ratio of the trend magnitude to time series standard deviation is less than about 0.5. For the same record lengths trends in records with trend to standard deviation ratios greater than about one can usually be detected with very high power when a uniform sampling strategy is followed.     

A DECISION SUPPORT SYSTEM FOR WATER QUALITY DATA AUGMENTATION: A CASE STUDY1

ABSTRACT: Recent developments in water quality monitoring have generated interest in combining non-probability and probability data to improve water quality assessment. The Interagency Task Force on Water Quality Monitoring has taken the lead in exploring data combination possibilities. In this paper we take a developed statistical algorithm for combining the two data types and present an efficient process for implementing the desired data augmentation. In a case study simulated Environmental Protection Agency (EPA) Environmental Monitoring and Assessment Program (EMAP) probability data are combined with auxiliary monitoring station data. Auxiliary stations were identified on the STORET water quality database. The sampling frame is constructed using ARC/INFO and EPA's Reach File-3 (RF3) hydrography data. The procedures for locating auxiliary stations, constructing an EMAP-SWS sampling frame, simulating pollutant exposure, and combining EMAP and auxiliary stations were developed as a decision support system (DSS). In the case study with EMAP, the DSS was used to quantify the expected increases in estimate precision. The benefit of using auxiliary stations in EMAP estimates was measured as the decrease in standard error of the estimate.     

REGRESSION MODELS FOR ESTIMATING HERBICIDE CONCENTRATIONS IN U.S. STREAMS FROM WATERSHED CHARACTERISTICS1

ABSTRACT: Regression models were developed for estimating stream concentrations of the herbicides alachlor, atrazine, cyanazine, metolachior, and trilluralin from use‐intensity data and watershed characteristics. Concentrations were determined from samples collected from 45 streams throughout the United States during 1993 to 1995 as part of the U.S. Geological Survey's National Water‐Quality Assessment (NAWQA). Separate regression models were developed for each of six percentiles (10th, 25th, 50th, 75th, 90th, 95th) of the annual distribution of stream concentrations and for the annual time‐weighted mean concentration. Estimates for the individual percentiles can be combined to provide an estimate of the annual distribution of concentrations for a given stream. Agricultural use of the herbicide in the watershed was a significant predictor in nearly all of the models. Several hydrologic and soil parameters also were useful in explaining the variability in concentrations of herbicides among the streams. Most of the regression models developed for estimation of concentration percentiles and annual mean concentrations accounted for 50 percent to 90 percent of the variability among streams. Predicted concentrations were nearly always within an order of magnitude of the measured concentrations for the model‐development streams, and predicted concentration distributions reasonably matched the actual distributions in most cases. Results from application of the models to streams not included in the model development data set are encouraging, but further validation of the regression approach described in this paper is needed.     

Effects of Antecedent Streamflow and Sample Timing on Trend Assessments of Fish,Invertebrate, and Diatom Communities

Detecting trends in biological attributes is central to many stream monitoring programs; however, understanding how natural variability in environmental factors affects trend results is not well understood. We evaluated the influence of antecedent streamflow and sample timing (covariates) on trend estimates for fish, invertebrate, and diatom taxa richness and biological condition from 2002 to 2012 at 51 sites distributed across the conterminous United States. A combination of linear regression and Kendall‐tau test for trends were used to evaluate covariate influence on trend estimates. Adjusting for covariates changed the magnitude of trend estimates in two‐thirds of cases on average by 21%, most often reducing the estimated magnitude of the trend. Additionally, covariates influenced the interpretation of over one‐third of trend estimates by either strengthening or weakening trends after adjustment. Our findings clearly indicate that antecedent streamflow and sample timing influences trend estimates and subsequent interpretation. Accounting for covariates during trend analysis will enhance stream monitoring programs by providing a better understanding and interpretation of estimated changes in biological endpoints at monitored sites. Failure to account for antecedent streamflow and sample timing may lead to mischaracterization of a trend and/or misunderstanding of potential causes.     

Evaluation of regression methodology with low-frequency water quality sampling to estimate constituent loads for ephemeral watersheds in Texas

Water quality regulation and litigation have elevated the awareness and need for quantifying water quality and source contributions in watersheds across the USA. In the present study, the regression method, which is typically applied to large (perennial) rivers, was evaluated in its ability to estimate constituent loads (NO(3)-N, total N, PO(4)-P, total P, sediment) on three small (ephemeral) watersheds with different land uses in Texas. Specifically, regression methodology was applied with daily flow data collected with bubbler stage recorders in hydraulic structures and with water quality data collected with four low-frequency sampling strategies: random, rise and fall, peak, and single stage. Estimated loads were compared with measured loads determined in 2001-2004 with an autosampler and high-frequency sampling strategies. Although annual rainfall and runoff volumes were relatively consistent within watersheds during the study period, measured annual nutrient and sediment concentrations and loads varied considerably for the cultivated and mixed watersheds but not for the pasture watershed. Likewise, estimated loads were much better for the pasture watershed than the cultivated and mixed landuse watersheds because of more consistent land management and vegetation type in the pasture watershed, which produced stronger correlations between constituent loads and mean daily flow rates. Load estimates for PO(4)-P were better than for other constituents possibly because PO(4)-P concentrations were less variable within storm events. Correlations between constituent concentrations and mean daily flow rate were poor and not significant for all watersheds, which is different than typically observed in large rivers. The regression method was quite variable in its ability to accurately estimate annual nutrient loads from the study watersheds; however, constituent load estimates were much more accurate for the combined 3-yr period. Thus, it is suggested that for small watersheds, regression-based annual load estimates should be used with caution, whereas long-term estimates can be much more accurate when multiple years of concentration data are available. The predictive ability of the regression method was similar for all of the low-frequency sampling strategies studied; therefore, single-stage or random strategies are recommended for low-frequency storm sampling on small watersheds because of their simplicity.     

Surrogate Measures for Providing High Frequency Estimates of Total Suspended Solids and Total Phosphorus Concentrations1

Spackman Jones, Amber, David K. Stevens, Jeffery S. Horsburgh, and Nancy O. Mesner, 2010. Surrogate Measures for Providing High Frequency Estimates of Total Suspended Solids and Total Phosphorus Concentrations. Journal of the American Water Resources Association (JAWRA) 1‐15. DOI: 10.1111/j.1752‐1688.2010.00505.x Abstract: Surrogate measures like turbidity, which can be observed with high frequency in situ, have potential for generating high frequency estimates of total suspended solids (TSS) and total phosphorus (TP) concentrations. In the semiarid, snowmelt‐driven, and irrigation‐regulated Little Bear River watershed of northern Utah, high frequency in situ water quality measurements were recorded in conjunction with periodic chemistry sampling. Site‐specific relationships were developed using turbidity as a surrogate for TP and TSS at two monitoring locations. Methods are presented for employing censored data and for investigating categorical explanatory variables (e.g., hydrologic conditions). Turbidity was a significant explanatory variable for TP and TSS at both sites, which differ in hydrologic and water quality characteristics. The relationship between turbidity and TP was stronger at the upper watershed site where TP is predominantly particulate. At both sites, the relationships between turbidity and TP varied between spring snowmelt and base flow conditions while the relationships between TSS and turbidity were consistent across hydrological conditions. This approach enables the calculation of high frequency time series of TP and TSS concentrations previously unavailable using traditional monitoring approaches. These methods have broad application for situations that require accurate characterization of fluxes of these constituents over a range of hydrologic conditions.     

RESERVOIR WATER QUALITY SAMPLING DESIGN1

ABSTRACT: The design of monitoring programs often serves as one of the major sources of error or uncertainty in water quality data. Properly designed programs should minimize uncertainty or at least provide a means by which variability can be partitioned into recognizable components. While the design of sampling programs has received recent attention, commonly employed strategies for limnological sampling of lakes may not be completely appropriate for many reservoirs. Based on NES data, reservoirs are generally larger, deeper, and morphologically more complex than natural lakes. Reservoirs also receive a majority of their inflow from a single tributary located a considerable distance from the point of outflow. The result is the establishment of marked physical, biological, and chemical gradients from headwater to dam. The existence of horizontal as well as vertical gradients, and their importance in water quality sampling design were the subject of intensive transect sampling efforts at DeGray Lake, a U.S. Army Corps of Engineers reservoir in southern Arkansas. Data collected were used to partition Variance, identify areas of similarity, and demonstrate how an equitable sampling program might be designed.     

Microbiological Monitoring of Marine Recreational Waters in Southern California

An inventory was conducted to assess the number, type, spatial distribution, and costs of microbiological monitoring programs in southern California marine waters from Point Conception to the US/Mexico International Border. The location of each sampling site was determined using global positioning system (GPS), and estimates of geographic coverage were determined using geographic information system (GIS) techniques. Twenty-one programs conducted 87,007 tests annually at 576 sites in the study area. The largest number of sites was sampled in Orange County, whereas the largest number of analyses was performed in Los Angeles County because monitoring programs in this area focused on daily monitoring. Fifteen of the 21 programs were managed by National Pollutant Discharge Elimination System (NPDES) permitted sewage effluent dischargers who sampled both offshore and shoreline waters and typically tested for three indicator bacteria (total coliform, fecal coliform, and enterococcus). Their combined efforts comprised 82% of all of the microbiological indicator analyses conducted on an annual basis. Five of the remaining monitoring organizations were public health agencies, which typically focus their efforts on testing only total coliforms. Laboratory methodology also varied considerably, with NPDES permittees predominantly utilizing membrane filtration while public health agencies generally used multiple tube fermentation or premanufactured test kits. Nearly three quarters of all the effort expended in southern California occurred along the shoreline as opposed to offshore locations. Two thirds of this shoreline effort was focused on high-use sandy beaches and in proximity to perennial freshwater outlets (storm drains and creeks). Most sampling occurred at a set of fixed sites that were revisited frequently, but only represented about 7% of the total shoreline. We estimated that roughly $3 million is spent annually on monitoring bathing water quality in southern California, exceeding that spent in any other part of the country.     

Reduced complexity models for regional aquatic habitat suitability assessment

Generalizable methods that identify suitable aquatic habitat across large river basins and regions are needed to inform resource management. Habitat suitability models intersect environmental variables to predict species occurrence, but are often data intensive and thus are typically developed at small spatial scales. This study estimated mean monthly aquatic habitat suitability throughout Utah (USA) for Bonneville Cutthroat Trout (Oncorhynchus clarkii utah) and Bluehead Sucker (Catostomus discobolus) with publicly available, geospatial datasets. We evaluated 15 habitat suitability models using unique combinations of percent of mean annual discharge, velocity, gradient, and stream temperature. Environmental variables were validated with observed conditions and species presence observations to verify habitat suitability estimates. Stream temperature, gradient, and discharge best predicted Bonneville Cutthroat Trout presence, and gradient and discharge best predicted Bluehead Sucker presence. Simple aquatic habitat suitability models outperformed models that used only streamflow to estimate habitat for both species, and are useful for conservation planning and water resources decision-making. This modeling approach could enable resource managers to prioritize stream restoration across vast regions within their management domain, and is potentially compatible with water management modeling to improve ecological objectives in management models.     

ESTIMATING IRRIGATION WATER USE THROUGH SELECTIVE MONITORING: A NORTH FLORIDA CASE STUDY1

ABSTRACT: Selective placement - under a rigorous statistical sampling design - of newly available monitoring equipment on irrigation systems may provide effective and economical estimates of total irrigation water use in areas where complete water use inventories are impractical. In 1979, a joint effort by the U.S. Geological Survey and Florida's Suwannee River Water Management District was launched to estimate the District's 1979 irrigation water use using a selective monitoring approach. Analysis of previous inventories of irrigation equipment and amounts of water applied in the District indicated that total 1979 water use estimates with six to nine percent sampling error could be obtained using selective monitoring, given the time and equipment limitations for the monitoring program. Restricting monitoring to a sample of farms can introduce systematic error to water use estimates if farmers' participation is related to their water use methods. Preliminary results of the 1979 study indicate tht declining participation rates, if unchecked, could lead to serious systematic eror in future North Florida selective monitoring studies.     

SAMPLING STRATEGIES FOR ESTIMATING ACUTE AND CHRONIC EXPOSURES OF PESTICIDES IN STREAMS1

ABSTRACT: The Food Quality Protection Act of 1996 requires that human exposure to pesticides through drinking water be considered when establishing pesticide tolerances in food. Several systematic and seasonally weighted systematic sampling strategies for estimating pesticide concentrations in surface water were evaluated through Monte Carlo simulation, using intensive datasets from four sites in northwestern Ohio. The number of samples for the strategies ranged from 4 to 120 per year. Sampling strategies with a minimal sampling frequency outside the growing season can be used for estimating time weighted mean and percentile concentrations of pesticides with little loss of accuracy and precision, compared to strategies with the same sampling frequency year round. Less frequent sampling strategies can be used at large sites. A sampling frequency of 10 times monthly during the pesticide runoff period at a 90 km² basin and four times monthly at a 16,400 km² basin provided estimates of the time weighted mean, 90^th, 95^th, and 99^th percentile concentrations that fell within 50 percent of the true value virtually all of the time. By taking into account basin size and the periodic nature of pesticide runoff, costs of obtaining estimates of time weighted mean and percentile pesticide concentrations can be minimized.     

Survey of state water quality monitoring programs

Budget changes, whether positive or negative, in water quality management agencies often mean a change in resources available for water quality monitoring. Many state agencies are currently facing monitoring budget cuts and, as a result, are reevaluating their monitoring programs. Such evaluations make use of a number of information sources, not the least of which are monitoring activities in other states. This article reports results of a survey of all fifty state water quality monitoring programs. Twenty questions were asked in the general areas of fixed-station monitoring, special studies, and biological monitoring. Each state was contacted by telephone at least twice during the survey. Fixed-station monitoring is conducted by 48 of 50 states. An average of 75 stations per state are sampled, generally on a monthly basis. There is a large variation in the way data are analyzed by the states; water quality indices and plots of concentration or loading over time are the most common methods. All but three states conduct special studies, but only seven repeat the studies on a regular basis. Special studies are generally problem specific as opposed to basin oriented. Biological monitoring is performed by 33 states; however, this is an area in which budget cuts are having a noticeable impact. In some cases, biological monitoring is being completely eliminated or suspended. Macroinvertebrate sampling is performed quarterly to biannualiy by 50% of the states; 75% of the states that sample macroinvertebrates do so annually. Periphyton sampling is performed by 33% of the states. Over 50% of the states are in the process of revising, or have revised, their monitoring program during the past five years. However, only four states had a detailed rationale and operating procedure for the entire monitoring system. Results of the survey are, therefore, averages of existing monitoring programs. Average results do not necessarily represent ideal situations, but do give an indication of how states are coping with their monitoring responsibilities.     

EFFECT OF SERIAL CORRECTION ON GROUND WATER QUALITY SAMPLING FREQUENCY1

ABSTRACT: Methods of calculating uncertainty in estimates of serial correlation coefficients, and correcting for bias in short and medium length (less than 50 data point) records, are presented. Uncertainty and bias in the estimation of serial correlation coefficients for ground water quality data is shown to be considerable and to result in inaccurate calculation of the sampling frequencies for monitoring purposes. The methods are applied to a ground water data set consisting of 87 monthly measurements of nitrate concentrations. The variation in serial correlation coefficients with variation of record length is examined. The optimum sampling frequencies for detection of changes in ground water nitrate concentrations are estimated.     

Influence of Sampling Frequency on Estimation of Annual Total Phosphorus and Total Suspended Solids Loads1

Abstract: The determination of sediment and nutrient loads is typically based on the collection and analysis of grab samples. The frequency and regularity of traditional sampling may not provide representation of constituent loading, particularly in systems with flashy hydrology. At two sites in the Little Bear River, Utah, continuous, high‐frequency turbidity was used with surrogate relationships to generate estimates of total phosphorus and total suspended solids concentrations, which were paired with discharge to estimate annual loads. The high frequency records were randomly subsampled to represent hourly, daily, weekly, and monthly sampling frequencies and to examine the effects of timing, and resulting annual load estimates were compared to the reference loads. Higher frequency sampling resulted in load estimates that better approximated the reference loads. The degree of bias was greater at the more hydrologically responsive site in the upper watershed, which required a higher sampling frequency than the lower watershed site to achieve the same level of accuracy in estimating the reference load. The hour of day and day of week of sampling impacted load estimation, depending on site and hydrologic conditions. The effects of sampling frequency on the determination of compliance with a water quality criterion were also examined. These techniques can be helpful in determining necessary sampling frequency to meet the objectives of a water quality monitoring program.     

POLLUTANT LOADS IN URBAN STORMWATER: REVIEW OF METHODS FOR PLANNING-LEVEL ESTIMATES1

ABSTRACT: A review of methods for planning-level estimates of pollutant loads in urban stormwater focuses on transfer of charac. teristic runoff quality data to unmonitored sites, runoff monitoring, and simulation models. Load estimation by transfer of runoff quality data is the least expensive, but the accuracy of estimates is unknown. Runoff monitoring methods provide best estimates of existing loads, but cannot be used to predict load changes resulting from runoff controls, or other changes of the urban system. Simulation models require extensive calibration for reliable application. Models with optional formulations of pollutant build up, washoff, and transport can be better calibrated and the selection of options should be based on a statistical analysis of calibration data. Calibrated simulation models can be used for evaluation of control alternatives.     

Filtering with a drill pump: an efficient method to collect suspended sediment

Water quality monitoring programs across multiple disciplines use total suspended solids (TSS), and volatile suspended solids (VSS), to assess potential impairments of surface water and groundwater. While previous methods for instream filtering have been developed, the need for rapid, cost‐effective, high volume sampling has increased with the need to verify and supplement data produced by sondes and instantaneous data loggers. We present an efficient method to filter water instream with a portable drill pump that results in reduced sample processing time, and potentially reduced error associated with sample transportation, preservation, contamination, and homogenization. This technical note outlines the advantages of filtering instream vs. in the laboratory. It also compares TSS and VSS concentrations filtered with a drill pump vs. standard filtration methods with a vacuum pump as outlined by USEPA methods 160.2 and 160.4. Samples were collected at 4 sites and filtered in the field, or transported to the laboratory and filtered within 12 or 24 h of collection. Overall TSS and VSS samples filtered instream with a drill pump vs. in the laboratory produced similar concentrations with a similar range in variability for each method. Sample filtering with a drill pump decreased processing time by five minutes per sample.     

IDENTIFICATION OF AN OPTIMAL SAMPLING STRATEGY FOR A CONSTRUCTED WETLAND1

ABSTRACT: The objective of this investigation was to determine the effect of sampling frequency and sampling type on estimates of monthly nutrient loads and flow‐weighted nutrient concentrations in a constructed wetland. Phosphorus and nitrogen loads and concentrations entering and leaving a subtropical wetland (the Everglades Nutrient Removal Project, ENRP) were calculated on the basis of three sampling frequencies. The first frequency included weekly composite samples (three daily samples composited for one week) and grab samples from August 1994 to July 1997, representing a base‐line condition for comparison with results using reduced sampling frequencies. The second and third sampling frequency included three and two composite samples per month, respectively, drawn from the weekly samples. Total phosphorus and nitrogen loads calculated using two and three samples per month were almost identical to results based on four samples per month (least‐squares regression coefficients ranged from 0.96 to 0.98). Results of monthly mean flow‐weighted nutrient concentrations, obtained using reduced sampling frequencies, also were strongly correlated to concentrations calculated using the base‐line sampling frequency (r²ranged from 0.82 to 0.93). Grab samples did not always provide good estimates of loads or concentrations, particularly at the inflow when data were highly variable. From the results of this study, we can recommend that bi‐weekly composite sampling be used to monitor nutrient concentrations and loads discharged from larger‐scale Everglades Stormwater Treatment Areas (STAs) now under construction. Because there are high costs associated with water sample collection and processing, studies to identify optimal sampling frequencies should be a key feature in the design of any comprehensive wetland‐monitoring program.     

RELATIONSHIPS BETWEEN PARTICLE MOVEMENT AND CHANNEL MORPHOLOGY IN SOME NORTHERN IDAHO STREAMS1

ABSTRACT: Data were collected in 1992 from 17 mountain streams located within fine- to coarse-grained schist formations on the Idaho Panhandle National Forests. These were used to examine predictive relationships potentially useful in monitoring stream channel stability and fishery habitat. Channel morphology, sediment, and lithological data were obtained at 123 riffle sites. An analysis of materials deposited on gravel bars showed that at most sites, critical grain size, calculated using Duboy's tractive force equation, often does not provide accurate estimates of particle sizes moved at bankfull discharge. The tractive force equation gave reasonable estimates (± 10 mm) at 16 percent of the sites, but significantly over- or underestimated the sizes at the remaining sites. Regression and discriminant analysis showed that the relationship between critical grain size and the geometric mean diameter of material deposited on gravel bars was influenced most by the substrate size, slope, and width-to-depth ratio. Similarly, lithology was correlated with the size of particles moved. Particle sizes moved at bankfull discharge were not well correlated with residual pool depth or pool length.