Evaluating the effects of spatial monitoring policy on groundwater quality portrayal

What size sample is sufficient for spatially sampling ambient groundwater quality? Water quality data are only as spatially accurate as the geographic sampling strategies used to collect them. This research used sequential sampling and regression analysis to evaluate groundwater quality spatial sampling policy changes proposed by California's Department of Water Resources. Iterative or sequential sampling of a hypothetical groundwater basin's water quality produced data sets from sample sizes ranging from 2.8% to 95% coverage of available point sample sites. Contour maps based on these sample data sets were compared to an original (control), mapped hypothetical data set, to determine at which point map information content and pattern portrayal are not improved by increasing sample sizes. Comparing series of contour maps of ground water quality concentration is a common means of evaluating the geographic extent of groundwater quality change. Comparisons included visual inspection of contout maps and statistical tests on digital versions of these map files, including correlation and regression products. This research demonstrated that, down to about 15% sample site coverage, there is no difference between contour maps produced from the different sampling strategies and the contout map of the original data set.     

Release,Dispersion, and Resuspension of Escherichia coli From Direct Fecal Deposits Under Controlled Flows1

Abstract: Water‐quality standards have been placed on fecal indicator organisms such as Escherichia coli in an attempt to limit the concentrations in water bodies. Cattle can be a significant source of bacteria to water systems, particularly when they are allowed direct access to streams. A flume study was conducted to quantify the effect and understand the transport of E. coli from directly deposited cattle manure. Five steady‐state flows, ranging from 0.00683 to 0.0176 m³/s, were studied and loads from a single cowpie exceeded the U.S. Environmental Protection Agency’s recommended water‐quality standards (235 CFU/100 ml) at each flow over the hour study period. Average E. coli concentrations ranged from 10² to 10⁵ CFU/100 ml over the hour sampling period for all flows. High spatial variations in E. coli concentrations were often seen at each sampling time, with higher concentrations typically at the bottom of the flume. E. coli resuspension was initially greater at 0.5 min after deposition, for the lowest flow (10⁵ CFU/m²/s); however, resuspension rates became similar over time, on the order of 10³ CFU/m²/s. This study demonstrates that the concentrations of E. coli can vary over the water column, and therefore grab samples may inaccurately measure bacteria concentrations and loads in streams. In addition, resuspension rates were often high, so the incorporation of this process into water‐quality models is important for bacteria prediction.     

PHYTOPLANKTON IN THE FOX CHAIN OF LAKES1

ABSTRACT: As part of a comprehensive water quality investigation on the Fox Chain of Lakes during May to October 1975, water samples from the Chain and Cedar Lake (reference) at 25 locations were collected weekly or bi-weekly to determine the species and densities of algae. The results have been evaluated for algal composition, density, and succession for each location. Sixty-four algal species were recovered from 414 samples. The number of species per sampling location varied from 10 at Channel Lake and Lake Marie to 26 on Fox Lake (main) and Grass Lake. Blue green algae were predominant and occurred at 25 of the 25 sampling stations. They consisted mainly of Aphanizomenon flos-aquae. The only flagellate of importance was Ceratium hirundinella, and significant concentrations of this organism were limited to Channel Lake and Lake Catherine. The only green alga bloom was created by Ulothrix variabilis on the waters of Pistakee Lake. Diatoms were quite significant on the shallower water bodies. Algal densities ranged from about 25 to 14,000 cts/ml. The highest count occurred on Mineola Bay. Other high counts (>10,000 cts/ml) observed were waters taken from Channel Lake, Grass Lake, and Fox Lake (main). In Grass Lake, 60 percent of the collections had algal densities in excess of 2,000 cts/ml. Most of these were the diatom Cyclotella meneghiniana.     

A METHOD FOR OBTAINING SLOPE INFORMATION FOR HYDROLOGIC MODELS1

: A method is described for obtaining surface slope information for analysis with other land resource and water quality data in hydrologic models of nonpoint sources of water pollution. The method described requires a point sampling scheme, topographic maps, and a coordinate digitizer. Sample point elevation, slope direction, and slope magnitude are calculated from locations of the sample point and the nearest upper and lower contour lines. Details of the data collection methodology and associated problems are discussed.     

INFLUENCE OF DIFFERENT TEMPORAL SAMPLING STRATEGIES ON ESTIMATING TOTAL PHOSPHORUS AND SUSPENDED SEDIMENT CONCENTRATION AND TRANSPORT IN SMALL STREAMS1

ABSTRACT: Various temporal sampling strategies are used to monitor water quality in small streams. To determine how various strategies influence the estimated water quality, frequently collected water quality data from eight small streams (14 to 110 km²) in Wisconsin were systematically subsampled to simulate typically used strategies. These subsets of data were then used to estimate mean, median, and maximum concentrations, and with continuous daily flows used to estimate annual loads (using the regression method) and volumetrically weighted mean concentrations. For each strategy, accuracy and precision in each summary statistic were evaluated by comparison with concentrations and loads of total phosphorus and suspended sediment estimated from all available data. The most effective sampling strategy depends on the statistic of interest and study duration. For mean and median concentrations, the most frequent fixed period sampling economically feasible is best. For maximum concentrations, any strategy with samples at or prior to peak flow is best. The best sampling strategy to estimate loads depends on the study duration. For one‐year studies, fixed period monthly sampling supplemented with storm chasing was best, even though loads were overestimated by 25 to 50 percent. For two to three‐year load studies and estimating volumetrically weighted mean concentrations, fixed period semimonthly sampling was best.     

A critical review of the water quality classification system in Turkey: A case study on Meric Basin

An 11-year period of water quality data, collected by the Directorate of Sate Water Works of Turkey are thoroughly analyzed for the purpose of implementing water quality classes to water resources in the Meric Basin, located on the European land mass of Turkey. Water quality parameters are divided into four groups as physical, organic, inorganic, and bacteriological. The quality class of each group is evaluated by taking into account the poorest quality of any parameter in the group, after which a quality rank is assigned to the sampling station and the waterbody in question. This method of water quality classification imposed by the Turkish Water Quality Act, is then criticized with respect to a statistical approach.     

WATER QUALITY SAMPLING SCHEMES FOR VARIABLE FLOW CANALS AT REMOTE SITES1

ABSTRACT: Growing interest in water quality has resulted in the development of monitoring networks and intensive sampling for various constituents. Common purposes are regulatory, source and sink understanding, and trend observations. Water quality monitoring involves monitoring system design; sampling site instrumentation; and sampling, analysis, quality control, and assurance. Sampling is a process to gather information with the least cost and least error. Various water quality sampling schemes have been applied for different sampling objectives and time frames. In this study, a flow proportional composite sampling scheme is applied to variable flow remote canals where the flow rate is not known a priori. In this scheme, historical weekly flow data are analyzed to develop high flow and low flow sampling trigger volumes for auto‐samplers. The median flow is used to estimate low flow sampling trigger volume and the five percent exceedence probability flow is used for high flow sampling trigger volume. A computer simulation of high resolution sampling is used to demonstrate the comparative bias in load estimation and operational cost among four sampling schemes. Weekly flow proportional composite auto‐sampling resulted in the least bias in load estimation with competitive operational cost compared to daily grab, weekly grab sampling and time proportional auto‐sampling.     

Zonal management of arsenic contaminated ground water in Northwestern Bangladesh

This paper used ordinary kriging to spatially map arsenic contamination in shallow aquifers of Northwestern Bangladesh (total area  35,000 km²). The Northwestern region was selected because it represents a relatively safer source of large-scale and affordable water supply for the rest of Bangladesh currently faced with extensive arsenic contamination in drinking water (such as the Southern regions). Hence, the work appropriately explored sustainability issues by building upon a previously published study (Hossain et al., 2007; Water Resources Management, vol. 21: 1245–1261) where a more general nation-wide assessment afforded by kriging was identified. The arsenic database for reference comprised the nation-wide survey (of 3534 drinking wells) completed in 1999 by the British Geological Survey (BGS) in collaboration with the Department of Public Health Engineering (DPHE) of Bangladesh. Randomly sampled networks of zones from this reference database were used to develop an empirical variogram and develop maps of zonal arsenic concentration for the Northwestern region. The remaining non-sampled zones from the reference database were used to assess the accuracy of the kriged maps. Two additional criteria were explored: (1) the ability of geostatistical interpolators such as kriging to extrapolate information on spatial structure of arsenic contamination beyond small-scale exploratory domains; (2) the impact of a priori knowledge of anisotropic variability on the effectiveness of geostatistically based management. On the average, the kriging method was found to have a 90% probability of successful prediction of safe zones according to the WHO safe limit of 10 ppb while for the Bangladesh safe limit of 50 ppb, the safe zone prediction probability was 97%. Compared to the previous study by Hossain et al. (2007) over the rest of the contaminated country side, the probability of successful detection of safe zones in the Northwest is observed to be about 25% higher. An a priori knowledge of anisotropy was found to have inconclusive impact on the effectiveness of kriging. It was, however, hypothesized that a preferential sampling strategy that honored anisotropy could be necessary to reach a more definitive conclusion in regards to this issue.     

Controls on Nutrients Across a Prairie Stream Watershed: Land Use and Riparian Cover Effects

Nutrient inputs generally are increased by human-induced land use changes and can lead to eutrophication and impairment of surface waters. Understanding the scale at which land use influences nutrient loading is necessary for the development of management practices and policies that improve water quality. The authors assessed the relationships between land use and stream nutrients in a prairie watershed dominated by intermittent stream flow in the first-order higher elevation reaches. Total nitrogen, nitrate, and phosphorus concentrations were greater in tributaries occupying the lower portions of the watershed, closely mirroring the increased density of row crop agriculture from headwaters to lower-elevation alluvial areas. Land cover classified at three spatial scales in each sub-basin above sampling sites (riparian in the entire catchment, catchment land cover, and riparian across the 2 km upstream) was highly correlated with variation in both total nitrogen (r² = 53%, 52%, and 49%, respectively) and nitrate (r² = 69%, 65%, and 56%, respectively) concentrations among sites. However, phosphorus concentrations were not significantly associated with riparian or catchment land cover classes at any spatial scale. Separating land use from riparian cover in the entire watershed was difficult, but riparian cover was most closely correlated with in-stream nutrient concentrations. By controlling for land cover, a significant correlation of riparian cover for the 2 km above the sampling site with in-stream nutrient concentrations could be established. Surprisingly, land use in the entire watershed, including small intermittent streams, had a large influence on average downstream water quality although the headwater streams were not flowing for a substantial portion of the year. This suggests that nutrient criteria may not be met only by managing permanently flowing streams.     

Application of Multivariate Statistical Methods and Water-Quality Index to Evaluation of Water Quality in the Kashkan River

The Kashkan River (KR), located in the west of Iran, is a major source of water supply for residential and agricultural areas as well as livestock. The objective of this study was to assess the spatial and long temporal variations of surface water quality of the KR based on measured chemical ions. The Canadian Council of Ministers of Environment Water Quality Index (CCME WQI) technique was utilized using measurements from 10 sampling stations during a period of 36 years (1974–2009). The measured data included cations (Na⁺, K⁺, Ca²⁺, Mg²⁺), anions (HCO₃ ^?, Cl^?, SO₄ ^2?), pH, and electrical conductivity. Principal component analysis was performed to identify which of the parameters to be included in the CCME WQI calculations were actually correlated and which ones were responsible for most of the variance observed in the water-quality data. In addition, KR water quality was evaluated for its suitability for drinking and irrigation purposes using conventional methods. Last, trend detection in the WQI time series of the KR showed water-quality degradation at all sampling stations, whereas the Jelhool sub-basin more adversely affects the quality of KR water in the watershed. Nonetheless, on average, the water quality of the KR was rated as fair.     

Quantifying and Evaluating Ecosystem Health: A Case Study from Moreton Bay, Australia

As part of the program monitoring the ecosystem health of Moreton Bay, Queensland, Australia, we developed a means for assessing ecosystem health that allows quantitative evaluation and spatial representations of the assessments. The management objectives for achieving ecosystem health were grouped into ecosystem objectives, water quality objectives, and human health objectives. For the first two groups, aspects of the ecosystem (e.g., trophic status) were identified, and an indicator was chosen for each aspect. Reference values for each indicator were derived from management objectives and compared with the mapped survey values. Subregions for which the indicator statistic was equal to or better than the assigned reference value are referred to as “compliant zones.” High-resolution surface maps were created from spatial predictions on a fine hexagonal grid for each of the indicators. Eight reporting subregions were established based on the depth and predicted residence times of the water. Within each reporting subregion, the proportion that was compliant was calculated. These results then were averaged to create an integrated ecosystem health index. The ratings by a team of ecosystem experts and the calculated ecosystem health indices had good correspondence, providing assurance that the approach was internally consistent, and that the management objectives covered the relevant biologic issues for the region. This method of calculating and mapping ecosystem health, relating it directly to management objectives, may have widespread applicability for ecosystem assessment.     

CONTINUOUS SIMULATION FOR WATER QUALITY PLANNING1

ABSTRACT: This paper describes a methodology for the evaluation of water quality plans analogous to procedures used in flood control planning, where flood damage frequency curves provide the basis for determining flood control benefits. The proposed method uses continuous water quality simulation to develop long term information from which water quality frequency curves can be obtained. This frequency information allows the evaluation of the impact of proposed water quality control plans taking into consideration the variable nature of the water resource. Using treatment costs and other economic indicators of water quality, the frequency information can be used to estimate the cost-effectiveness and economic efficiency of alternative plans. The method is demonstrated in a semi-hypothetical environment; real hydrologic and climatic characteristics are assigned to a hypothetical watershed configuration. Alternative management plans are simulated and analyzed for both physical and economic impacts. The advantages of continuous simulation and its use in water quality planning are explored.     

Application of best subset method for river water quality modeling: A study on Godavari River,India

The utilization of water quality analysis to inform optimal decision-making is imperative to achieve sustainable management of river water quality. A multitude of research works in the past has focused on river water quality modeling. Despite being a precise statistical regression technique that allows for fitting separate models for all potential combinations of predictors and selecting the optimal subset model, the application of best subset method in river water quality modeling is not widely adopted. The current research aims to validate the use of best subset method in evaluating the water quality parameters of the Godavari River, one of the largest rivers in India, by developing regression equations for different combinations of its physicochemical parameters. The study involves in formulating best subset regression equations to estimate the concentrations of river water quality parameters while also identifying and quantifying their variations. A total of 17 water quality parameters are analyzed at 13 monitoring sites using 13 years (1993–2005) of observed data for the monsoon (June–October) period and post-monsoon (November–February) period. The final subset model is selected among model combinations that are developed for each year's dataset through widely used statistical criteria such as R², F value, adjusted R²_a, AIC_c, and RSS. The final best subset model across all parameters exhibits R² values surpassing 0.8, indicating that the models possess the ability to account for over 80% of the variations in the concentrations of dependent parameters. Therefore, the findings demonstrated the appropriateness of this method in evaluating the water quality parameters in extensive rivers. This work is very useful for decision-making and in the management of river water quality for its sustainable use in the study area.     

Evaluating the Illinois Stream Valley Segment Model as an Effective Management Tool

Stream habitat assessments are conducted to evaluate biological potential, determine anthropogenic impacts, and guide restoration projects. Utilizing these procedures, managers must first select a representative stream reach, which is typically selected based on several criteria. To develop a consistent and unbiased procedure for choosing sampling locations, the Illinois Department of Natural Resources and the Illinois Natural History Survey have proposed a technique by which watersheds are divided into homogeneous stream segments called valley segments. Valley segments are determined by GIS parameters including surficial geology, predicted flow, slope, and drainage area. To date, no research has been conducted to determine if the stream habitat within a valley segment is homogeneous and if different valley segments have varying habitat variables. Two abutting valley segments were randomly selected within 13 streams in the Embarras River watershed, located in east-central Illinois. One hundred meter reaches were randomly selected within each valley segment, and a transect method was used to quantify habitat characteristics of the stream channel. Habitat variables for each stream were combined through a principal components analysis (PCA) to measure environmental variation between abutting valley segments. A multivariate analysis of variance (MANOVA) was performed on PCA axes 1–3. The majority of abutting valley segments were significantly different from each other indicating that habitat variability within each valley segment was less than variability between valley segments (5.37 ≤ F ≤ 245.13; P ≤ 0.002). This comparison supports the use of the valley segment model as an effective management tool for identifying representative sampling locations and extrapolating reach-specific information.     

SAMPLING FREQUENCY SELECTION FOR REGULATORY WATER QUALITY MONITORING1

ABSTRACT: The selection of sampling frequencies in order to achieve reasonably small and uniform confidence interval widths about annual sample means or sample geometric means of water quality constituents is suggested as a rational approach to regulatory monitoring network design. Methods are presented for predicting confidence interval widths at specified sampling frequencies while considering both seasonal variation and serial correlation of the quality time series. Deterministic annual cycles are isolated and serial dependence structures of the autoregressive, moving average type are identified through time series analysis of historic water quality records. The methods are applied to records for five quality constituents from a nine-station network in Illinois. Confidence interval widths about annual geometric means are computed over a range of sampling frequencies appropriate in regulatory monitoring. Results are compared with those obtained when a less rigorous approach, ignoring seasonal variation and serial correlation, is used. For a monthly sampling frequency the error created by ignoring both seasonal variation and serial correlation is approximately 8 percent. Finally, a simpler technique for evaluating serial correlation effects based on the assumption of AR(1) type dependence is examined. It is suggested that values of the parameter p₁, in the AR(1) model should range from 0.75 to 0.90 for the constituents and region studied.     

IMPACT ASSESSMENT MODEL FOR CLEAR WATER FISHES EXPOSED TO EXCESSIVELY CLOUDY WATER1

ABSTRACT: A new type of empirical model described here enables real time assessment of impacts caused by excessive water cloudiness as a function of (a) reduced visual clarity (excessive cloudiness) and (b) duration of exposure to cloudy conditions, in fisheries or fish life stages adapted to life in clear water ecosystems. This model takes the familiar form used in earlier suspended sediment dose effect models where z is severity of ill effect (SEV), x is duration of exposure (h), y is black disk sighting range (y BD, m)—a measure of water clarity, a is the intercept, and b and c are slope coefficients. As calibrated in this study the model is Severity of ill effect is ranked on a 15‐step scale that ranges from 0 to 14, where zero represents nil effect and 14 represents 100 percent mortality. This model, based on peer consultation and limited meta analysis of peer reviewed reports, accomplishes the following: (a) identifies the threshold of the onset of ill effects among clear water fishes; (b) postulates the rate at which serious ill effects are likely to escalate as a function of reduced visual clarity and persistence; (c) provides a context (the “visual clarity” matrix, with its cell coordinates) to share and compare information about impacts as a function of visual clarity “climate” (d) demonstrates changes in predator prey interactions at exposures greater than and less than the threshold of direct ill effects; (e) calibrates trout reactive distance (cm) as function of water clarity in the form where y represents reactive distance (cm) and x represents visual clarity (black disk sighting range, cm), and where a and b are intercept and slope respectively, such that (f) identifies black disk sighting range, in meters, and its reciprocal, beam attenuation, as preferred monitoring variables; and (g) provides two additional optical quality variables (Secchi disk extinction distance and turbidity) which, suitably calibrated as they have been in this study, expand the range of monitoring options in situations in which the preferred technology—beam attenuation equipment or black disk sighting equipment—is unavailable or impractical to use. This new model demonstrates the efficacy of peer collaboration and defines new research horizons for its refinement.     

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.     

QUALITY OF WATER AND BOTTOM SEDIMENTS IN THE TRINITY RIVER1

ABSTRACT: Data were developed to determine the quality of water and bottom sediments in the Trinity River, and the mobility of various contaminants when bottom sediments were mixed with the river water under simulated dredging conditions. Thirteen sampling sites were selected. A number of chemical tests including heavy metals and pesticides were conducted on river water, elutriates, and bottom sediments. Statis bioassays using Daphnia magna were conducted on river water and elutriates. Results indicated that the river in the upper reach is grossly polluted due to discharge of waste water effluents from several large treatment plants. High concentrations of nitrogen, phosphorus, organic carbon, COD, heavy metals, and pesticides were found in water and bottom sediments. The concentrations of most of these pollutants exceeded the EPA recommended limits. Elutriation gave no consistent results, perhaps because of release or uptake of contaminants from the sediments. High mortality of D. magna were also recorded in the upper reach of the river. The quality of water and bottom sediments gradually improved in lower reaches.     

Modeled Summer Background Concentration of Nutrients and Suspended Sediment in the Mid‐Continent (USA) Great Rivers1

Angradi, Ted R., David W. Bolgrien, Matt A. Starry, and Brian H. Hill, 2012. Modeled Summer Background Concentration of Nutrients and Suspended Sediment in the Mid‐Continent (USA) Great Rivers. Journal of the American Water Resources Association (JAWRA) 48(5): 1054‐1070. DOI: 10.1111/j.1752‐1688.2012.00669.x Abstract: We used regression models to predict summer background concentration of total nitrogen (N), total phosphorus (P), and total suspended solids (TSS), in the mid‐continent great rivers: the Upper Mississippi, the Lower Missouri, and the Ohio. From multiple linear regressions of water quality indicators with land use and other stressor variables, we determined the concentration of the indicators when the predictor variables were all set to zero — the y‐intercept. Except for total P on the Upper Mississippi River, we could predict background concentration using regression models. Predicted background concentration of total N was about the same on the Upper Mississippi and Lower Missouri Rivers (430 μg l^?1), which was lower than percentile‐based values, but was similar to concentrations derived from the response of sestonic chlorophyll a to great river total N concentration. Background concentration of total P on the Lower Missouri (65 μg l^?1) was also lower than published and percentile‐based concentrations. Background TSS concentration was higher on the Lower Missouri (40 mg l^?1) than the other rivers. Background TSS concentration on the Upper Mississippi (16 mg l^?1) was below a threshold (30 mg l^?1) designed to protect aquatic vegetation. Our model‐predicted concentrations for the great rivers are an attempt to estimate background concentrations for water quality indicators independent from thresholds based on percentiles or derived from stressor‐response relationships.     

Impacts of Man-Made Landscape Features on Numbers of Estuarine Waterbirds at Low Tide

The potential impact of human disturbance on wintering waterbirds using intertidal mudflats was considered by relating their numbers to the presence of nearby footpaths, roads, railroads, and towns. Data were obtained for six English estuaries from the Wetland Bird Survey Low Tide Count scheme. Counts were undertaken monthly from November to February, and data were available for an average of 2.8 years per estuary for the period 1992–1993 to 1999–2000. Count sections and the positions of man-made landscape features were mapped using a GIS. Generalized linear models tested whether bird numbers varied according to the estuary, month, area, whether or not the section bordered water, and the proportion of each section within a specified distance of each landscape feature. In addition, the proximity of sections to the nearest footpath access point was considered. Numbers of six of nine species, northern shelduck (Tadorna tadorna), red knot (Calidris canutus), dunlin (Calidris alpina), black-tailed godwit (Limosa limosa), Eurasian curlew (Numenius arquata) and common redshank (Tringa totanus), were significantly lower where a footpath was close to a count section, while those of brant (Branta bernicla) were greater. Northern shelduck, black-bellied plover (Pluvialis squatarola), dunlin, and black-tailed godwit numbers were reduced close to railroads and those of common ringed plover (Charadrius hiaticula), black-bellied plover, and Eurasian curlew close to roads. Common ringed plover numbers were greater close to towns. The relative distances to which species were affected by footpaths corresponded to published information concerning their flight distances in response to human disturbance. The study provided evidence that sustained disturbance associated with footpaths, roads, and railroads reduced local habitat quality for waterbirds and the carrying capacity of estuaries.