Spatial Variability of Pool-Tail Fines in Mountain Gravel-Bed Stream Affects Grid-Count Results1

Bunte, Kristin, John P. Potyondy, Kurt W. Swingle, and Steven R. Abt, 2012. Spatial Variability of Pool-Tail Fines in Mountain Gravel-Bed Stream Affects Grid-Count Results. Journal of the American Water Resources Association (JAWRA) 48(3): 530-545. DOI: 10.1111/j.1752-1688.2011.00629.x Abstract: Fine sediment (<2 and <6 mm) particles underlying a 49-intersection grid placed on a streambed at 25, 50, and 75% of the wetted pool-tail width are commonly counted to assess the status and trend of aquatic ecosystems or to monitor changes in the supply of fines in mountain gravel-bed streams. However, results vary even when crews perform nearly identical procedures. This study hypothesized that spatial variability of pool-tail fines affects grid-count results and that a sampling scheme can be optimized for precision and accuracy. Grid counts taken at seven evenly spaced locations across the wetted width of 10 pool tails in a pool-riffle study stream indicated a bankward fining trend with secondary peaks of fines within the stream center. Sampling locations close to the waterlines harbored more than twice as many fines as central locations. Most of the five grid-count schemes derived from the seven sampled locations produced significantly different results. Compared with sampling at all seven locations, schemes that focus near waterlines overpredicted fines, while those that focus on the center underpredicted them. Variability of fines among pool tails was the highest within a broad band along the waterlines; hence, focusing sampling there yielded the most variable results. The scheme sampling at 25, 50, and 75% of the wetted width had the lowest precision and moderate accuracy. Accuracy and precision of grid-count results can be greatly improved by sampling at seven even-spaced locations across the pool tail.     

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.     

Detecting acid precipitation impacts on lake water quality

The United States Environmental Protection Agency is planning to expand its long-term monitoring of lakes that are sensitive to acid deposition effects. Effective use of resources will require a careful definition of the statistical objectives of monitoring, a network design which balances spatial and temporal coverage, and a sound approach to data analysis. This study examines the monitoring objective of detecting trends in water quality for individual lakes and small groups of lakes. Appropriate methods of trend analysis are suggested, and the power of trend detection under seasonal (quarterly) sampling is compared to that of annual sampling. The effects of both temporal and spatial correlation on trend detection ability are described.     

Sequential sampling: A cost-effective approach for monitoring benthic macroinvertebrates in environmental impact assessments

Sequential sampling is a method for monitoring benthic macroinvertebrates that can significantly reduce the number of samples required to reach a decision, and consequently, decrease the cost of benthic sampling in environmental impact assessments.Rather than depending on a fixed number of samples, this analysis cumulatively compares measured parameter values (for example, density, community diversity) from individual samples, with thresholds that are based on specified degrees of precision.In addition to reducing sample size, a monitoring program based on sequential sampling can provide clear-cut decisions as to whethera priori-defined changes in the measured parameter(s) have or have not occurred. As examples, sequential sampling programs have been developed to evaluate the impact of geothermal energy development on benthic macroinvertebrate diversity at The Geysers, California, and for monitoring the impact of crude oil contamination on chironomid midge [Cricotopus bicinctus (Meigen) andC. mackenziensis Oliver] population densities in the Trail River, Northwest Territories, Canada.     

Assessment of environmental impacts part two: Data collection

Intervention analysis is a relatively new branch of time series analysis. The power of this technique, which gives the probability that changes in mean level can be distinguished from natural data variability, is quite sensitive to the way the data are collected. The principal independent variables influenced by the data collection design are overall sample size, sampling frequency, and the relative length of record before the occurrence of the event (intervention) that is postulated to have caused a change in mean process level.For three of the four models investigated, data should be collected so that the post-intervention record is substantially longer than the pre-intervention record. This is in conflict with the intuitive approach, which would be to collect equal amounts of data before and after the intervention. The threshold (minimum) level of change that can be detected is quite high unless sample sizes of at least 50 and preferably 100 are available; this minimum level is dependent on the complexity of the model required to describe the response of the process mean to the intervention. More complex models tend to require larger sample sizes for the same threshold detectable change level.Uniformity of sampling frequency is a key consideration. Environmental data collection programs have not historically been oriented toward data analysis using time series techniques, thus eliminating a potentially powerful tool from use in many environmental assessment applications.     

NONPARAMETRIC TESTS FOR TREND DETECTION IN WATER QUALITY TIME SERIES1

ABSTRACT: A review of nonparametric tests for trend leads to the conclusion that Mann-Whitney, Spearman, and Kendall tests are the best choice for trend detection in water quality time series. Recently these tests have been adapted to account for dependence and seasonality in such series (Lettenmaier, 1976; Hirsch, et al., 1972; Hirsch and Slack, 1984). For monotonic trends, a procedure allowing to select the pertinent tests considering the characteristics of time series is proposed and the practical limitations of the tests are also brought out. This procedure has been applied to identify the appropriate trend detection test for the time series of nine water quality parameters at Lake Laflamme (Québec). When a time series can be tested with the Mann-Whitney, Kendall, Spearman, or Lettenmaier (1976) test, the number of observations required to detect trends of a given magnitude, for selected significance and power levels can be calculated with the power function of the t test. When the test proposed by Hirsch, et al. (1984), Hirsch and Slack (1984), or Farrell (1980) need to be used, the number of observations can only be estimated approximately from the results of empirical power studies.     

Long‐Term Streamflow Response to Climatic Variability in the Loess Plateau,China1

Abstract: The Loess Plateau region in northwestern China has experienced severe water resource shortages due to the combined impacts of climate and land use changes and water resource exploitation during the past decades. This study was designed to examine the impacts of climatic variability on streamflow characteristics of a 12‐km² watershed near Tianshui City, Gansu Province in northwestern China. Statistic analytical methods including Kendall’s trend test and stepwise regression were used to detect trends in relationship between observed streamflow and climatic variables. Sensitivity analysis based on an evapotranspiration model was used to detect quantitative hydrologic sensitivity to climatic variability. We found that precipitation (P), potential evapotranspiration (PET) and streamflow (Q) were not statistically significantly different (p > 0.05) over the study period between 1982 and 2003. Stepwise regression and sensitivity analysis all indicated that P was more influential than PET in affecting annual streamflow, but the similar relationship existed at the monthly scale. The sensitivity of streamflow response to variations of P and PET increased slightly with the increase in watershed dryness (PET/P) as well as the increase in runoff ratio (Q/P). This study concluded that future changes in climate, precipitation in particular, will significantly impact water resources in the Loess Plateau region an area that is already experiencing a decreasing trend in water yield.     

Uncertainty Assessment for Management of Soil Contaminants with Sparse Data

In order for soil resources to be sustainably managed, it is necessary to have reliable, valid data on the spatial distribution of their environmental impact. However, in practice, one often has to cope with spatial interpolation achieved from few data that show a skewed distribution and uncertain information about soil contamination. We present a case study with 76 soil samples taken from a site of 15 square km in order to assess the usability of information gleaned from sparse data. The soil was contaminated with cadmium predominantly as a result of airborne emissions from a metal smelter. The spatial interpolation applies lognormal anisotropic kriging and conditional simulation for log-transformed data. The uncertainty of cadmium concentration acquired through data sampling, sample preparation, analytical measurement, and interpolation is factor 2 within 68.3 % confidence. Uncertainty predominantly results from the spatial interpolation necessitated by low sampling density and spatial heterogeneity. The interpolation data are shown in maps presenting likelihoods of exceeding threshold values as a result of a lognormal probability distribution. Although the results are not deterministic, this procedure yields a quantified and transparent estimation of the contamination, which can be used to delineate areas for soil improvement, remediation, or restricted area use, based on the decision-makers probability safety requirement.     

Application of Multiattribute Decision-Making Methods for the Determination of Relative Significance Factor of Impact Categories

A relative significance factor (f _i ) of an impact category is the external weight of the impact category. The objective of this study is to propose a systematic and easy-to-use method for the determination of f _i . Multiattribute decision-making (MADM) methods including the analytical hierarchy process (AHP), the rank-order centroid method, and the fuzzy method were evaluated for this purpose. The results and practical aspects of using the three methods are compared. Each method shows the same trend, with minor differences in the value of f _i . Thus, all three methods can be applied to the determination of f _i . The rank order centroid method reduces the number of pairwise comparisons by placing the alternatives in order, although it has inherent weakness over the fuzzy method in expressing the degree of vagueness associated with assigning weights to criteria and alternatives. The rank order centroid method is considered a practical method for the determination of f _i because it is easier and simpler to use compared to the AHP and the fuzzy method.     

Design of a representative and cost-effective sampling programs for industrial wastewater with examples from bleached kraft pulp and paper mills

The diagram constructed for selection of sampling methods indicates that, for a systematic error, E ≤ 13%, grab sampling (GS) may be used to characterize effluents with variation coefficient of flow ≤ 120% and of contaminant concentrations ≤ 10%. For the whole studied range of variation coefficient of contaminant concentrations (2–82%), time-proportional compositing (TC) method may be applied with E ≤ 10% for effluents characterized by variation coefficients in flow < 90%. The more complicated flow-proportional compositing (FC) method is required only for effluents with larger variation coefficients or to produce more precise results. The diagram constructed for selection of sampling frequencies indicates that sequential sampling at intervals of approximately 60 min may be applied with E ≤ 10% for effluents characterized by variation coefficients ≤ 30%. Practical application of the diagrams, constructed using normal series, was checked against monitoring data from two pulp and paper mills in Vietnam. The two diagrams provided results on sampling methods and frequencies in good agreement with those obtained from actual monitoring data with percentages of agreement cases of 80 and 75%, respectively. The approach was applied in design of a monitoring program at the Bai Bang integrated pulp and paper mill in Vietnam.     

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.     

Escherichia coli Concentrations in Urban Watersheds Exhibit Diurnal Sag: Implications for Water‐Quality Monitoring and Assessment

The variability of indicator bacteria over a fine resolution time scale on the order of minutes has yet to be fully understood. In this study, we collected more than 700 Escherichia coli samples at a 10‐ and 30‐min resolution in an urban watershed in Houston. A Bacteria Diurnal Sag (BDS) marked with daytime exponential decay followed by an exponential nighttime regeneration was observed. This pattern was observed during all sampled events but varied depending on other variables. The concentrations during a 24‐h period varied 1 to 5 orders of magnitude and the fecal load was at least 10 times lower than what would be obtained using a single morning E. coli measurement, the typical sampling scheme in most monitoring programs. Decay rates, ranging from 3.67 to 24.7/day, decreased E. coli concentrations to below the water‐quality standards from 14:00 to 18:00 h and were strongly influenced by water temperatures and solar radiation intensities. Rapid regeneration occurred on the order of 9.41 to 64.1/day allowing E. coli concentrations to return to their pre‐decay levels. The data indicated that four to six samples taken between 06:00 and 18:00 h may be sufficient to define the BDS depending on stream conditions, and that a threshold concentration of approximately 100 MPN/dl (most probable number in a deciliter) existed for the studied urban watershed. These findings have significant implications for water‐quality monitoring, regulation, and compliance.     

Quality of rainwater harvesting for rural communities of Delta State,Nigeria

This paper assess the level of potability of rainwater samples harvested from catchments roofs in 6 rural communities of Delta State, Nigeria to achieve this goal a stratified sampling technique was adopted in the establishment of 90 sterilized cans into the 3 senatorial districts of Delta; on the basis of one can for thatch, aluminium, asbestos and corrugated iron sheets, and open surfaces. Six rural communities each were chosen from the three senatorial districts, making a total of 18 rural communities that were chosen for the study. The harvested rainwater samples were analysed with the most appropriate equipment and analytical techniques as recommended by World Health Organisation (WHO) and federal ministry of environment in Nigeria. Kruskal—wallis H’test statistical techniques was employed to ascertain whether differences exist amongst the rainwater samples collected from thatch, aluminium, asbestos and corrugated iron roofing sheets, and open surfaces. The result revealed that most of physiochemical and biological characteristics of rainwater samples were generally below the WHO threshold, as such the rainwater characteristics showed satisfactory concentration in these rural communities. Thus, the rainwater from these rural communities should be harvested, stored for human consumption and for other uses by the inhabitants. But treatment is needed in terms of their pH, TSS, Fe and colour. Similarly, significant differences exist amongst the rainwater samples collected from the 5 roofing types, most especially low quality of rainwater were observed in thatch and asbestos roofing sheets. Thus, rainwater from these sources should be purified before consumption.     

Using electromagnetic induction technology to predict volatile fatty acid, source area differences

Subsurface measures have been adapted to identify manure accumulation on feedlot surfaces. Understanding where manure accumulates can be useful to develop management practices that mitigate air emissions from manure, such as odor or greenhouse gases. Objectives were to determine if electromagnetic induction could be used to predict differences in volatile fatty acids (VFA) and other volatiles produced in vitro from feedlot surface material following a simulated rain event. Twenty soil samples per pen were collected from eight pens with cattle fed two different diets using a predictive sampling approach. These samples were incubated at room temperature for 3 d to determine fermentation products formed. Fermentation products were categorized into acetate, straight-, branched-chained, and total VFAs. These data were used to develop calibration prediction models on the basis of properties measured by electromagnetic induction (EMI). Diet had no significant effect on mean volatile solids (VS) concentration of accumulated manure. However, manure from cattle fed a corn (Zea mays L.)-based diet had significantly ( P ≤ 0.1) greater mean straight-chained and total VFA generation than pens where wet distillers grain with solubles (WDGS) were fed. Alternately, pens with cattle fed a WDGS-based diet had significantly (P ≤ 0.05) greater branched-chained VFAs than pens with cattle fed a corn-based diet. Many branched-chain VFAs have a lower odor threshold than straight-chained VFAs; therefore, emissions from WDGS-based diet manure would probably have a lower odor threshold. We concluded that diets can affect the types and quantities of VFAs produced following a rain event. Understanding odorant accumulation patterns and the ability to predict generation can be used to develop precision management practices to mitigate odor emissions.     

EVALUATION OF AN INDUCED INFILTRATION MODEL AS APPLIED TO GLACIAL AQUIFER SYSTEMS1

ABSTRACT: Numerical models were used to examine the limitations of the assumptions used in an analytical induced infiltration model. The assumptions tested included negligible streambed effects, negligible areal recharge, two-dimensional ground water flow, fully penetrating rivers and wells, and constant surface water stage. For situations that deviate from the underlying assumptions, the analytical model becomes a less reliable predictor of induced infiltration. The numerical experiments show that streambed effects cannot be neglected if the streambed conductivity is more than one order of magnitude lower than the aquifer hydraulic conductivity. Areal recharge cannot be neglected if the ground water basin receives more than 5 in/yr of areal recharge. Three-dimensional flow effects due to well partial penetration cannot be neglected if the ratio of horizontal hydraulic conductivity to vertical hydraulic conductivity (K_h/K_u) is greater than 10. Surface water elevation fluctuations can significantly influence the induced infiltration rate, depending on the degree of fluctuations and the ground water hydraulic gradient.     

Ambient monitoring of asbestos in selected Italian living areas

This paper presents the results of an intensive monitoring activity of the particulate, fall-out and soil of selected living areas in Italy with the aim to detect the asbestos concentration in air and subsequent risk of exposure for the population in ambient living environments, and to assess the nature of the other mineral phases composing the particulate matrix. Some areas were sorted out because of the presence of asbestos containing materials on site whereas others were used as blank spots in the attempt to detect the background environmental concentration of asbestos in air. Because the concentration of asbestos in ambient environments is presumably very low, and it is well known that conventional low–medium flow sampling systems with filters of small diameter (25 mm) may collect only a very small fraction of particulate over a short period, for the first time here, an intense monitoring activity was conducted with a high flow sampling system. The high flow system requires the use of large cellulose filters with the advantage that, increasing the amount of collected dust, the probability to collect asbestos fibers increases. Both the protocol of monitoring and analysis are novel and prompted by the need to increase the sensitivity towards the small number of expected fibers. With this goal, the collection of fall-out samples (the particulate falling into a collector filled with distilled water during the monitoring shift) and soil samples was also accomplished. The analytical protocol of the matrix particulate included preliminary X-ray powder diffraction (XRPD), optical microscopy and quantitative electron microscopy (SEM and TEM). Correlations with climatic trends and PM10 concentration data were also attempted.The surprising outcome of this work is that, despite the nature of the investigated site, the amount of dispersed asbestos fibers is very low and invariably lower than the theoretical method detection limits of the SEM and TEM techniques for identification and counting of asbestos fibers. The results are compared to the literature data worldwide and an updated model for asbestos fibers dispersion in ambient environments is proposed.     

Assessment of the use of selected rodents in ecological monitoring

Rodents can be useful in detecting environmental impacts because they are easy to study (easy to capture and handle), they can occur in densities adequate for statistical analysis, and they are ecologically important. In this study the usefulness of rodent populations for ecological monitoring was investigated by examining the effect of variation on the possibility of detecting differences among populations of rodents on 10 trapping grids. The effects of sampling frequencies and dispersal on detecting differences in population parameters among grids was also investigated, as was the possibility of inferring population parameters from correlations with habitat data. Statistically significant differences as small as 4.3Peromyscus maniculatus/ha were detected between grids. Of 10 populations, this comprised 12% of the highest-density population and 44% of the lowest-density population. Smaller and more differences among grids were found by examining only animals surviving from previous months. Dispersal confounds detection of direct impacts to populations, especially during the breeding season. Infrequent sampling fails to detect impacts that occur between sampling periods and will indicate impacts when observed changes result from natural variation. Correlations between population parameters and habitat variables exist but should only be used in predicting, not measuring, impacts. It is concluded that some rodent populations can be used in ecological monitoring. However, intensive sampling is required to account for variation and dispersal.     

Variations in the chemical properties of landfill leachate

Landfill leachates were collected and their chemical properties analyzed once every two months over a ten-month period from the Gin Drinkers' Bay (GDB) and Junk Bay (JB) landfills. The contents of solids, and inorganic and organic components fluctuated considerably with time. In general, the chemical properties of the two leachates correlated negatively (P<0.05) with the amounts of rainfall prior to the sampling periods. However, magnesium and pH of the leachates remained relatively constant with respect to sampling time. The JB leachate contained higher average contents of solids and inorganic and organic matter than those of GDB with the exception of trace metals. Trace metals were present in the two leachates in trace quantities (<1.0 mg/liter). The concentrations of average ammoniacal nitrogen were 1040 and 549 mg/liter, while chemical oxygen demand (COD) values were 767 and 695 mg/liter for JB and GDB leachates, respectively. These results suggest that the leachates need further treatment before they can be discharged to the coastal waters.     

Adequacy of Visually Classified Particle Count Statistics From Regional Stream Habitat Surveys1

Abstract: Streamlined sampling procedures must be used to achieve a sufficient sample size with limited resources in studies undertaken to evaluate habitat status and potential management‐related habitat degradation at a regional scale. At the same time, these sampling procedures must achieve sufficient precision to answer science and policy‐relevant questions with an acceptable and statistically quantifiable level of uncertainty. In this paper, we examine precision and sources of error in streambed substrate characterization using data from the Environmental Monitoring and Assessment Program (EMAP) of the U.S. Environmental Protection Agency, which uses a modified “pebble count” method in which particle sizes are visually estimated rather than measured. While the coarse (2?) size classes used in EMAP have little effect on the precision of estimated geometric mean (D_gm) or median (D₅₀) particle diameter, variable classification bias among observers can contribute as much as 0.3?, or about 15‐20%, to the root‐mean‐square error (RMSE) of D_gm or D₅₀ estimates. D_gm and D₅₀ estimates based on EMAP data are nearly equal when fine sediments (<2 mm) are excluded, but otherwise can differ by up to a factor of 2 or more, with D_gm < D₅₀ for gravel‐bed streams. The RMSE of reach‐scale particle size estimates based on visually classified particle count data from EMAP surveys, including variability associated with reoccupying unmarked sample reaches during revisits, is up to five to seven times higher than that reported for traditional measured pebble counts by multiple observers at a plot scale. Nonetheless, a variance partitioning analysis shows that the ratio of among site to revisit variance for several EMAP substrate metrics exceeds 8 for many potential regions of interest, suggesting that the data have adequate precision to be useful in regional assessments of channel morphology, habitat quality, or ecological condition.