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.     

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.     

An intergrated waste survey and environmental effects of COGIDO, a bleached pulp and paper mill in Vietnam, on the receiving waterbody

An integrated investigation on wastewater characterization and the environmental effects from the COGIDO pulp and paper mill in Bien Hoa Industrial Estate, Vietnam, a chlorine bleached soda integrated pulp and paper mill operating without a chemical recovery system, on the receiving water body was conducted during the rainy and dry seasons in 1993 and 1995. The pollution load from the mill was very high in terms of BOD, COD and SS (COD_m: 58.7 t/d; BOD: 33.3 t/d and SS: 25.1 t/d). The effluent toxicity was determined using four toxicity tests: the green micro-alga, Selenastrum capricornutum, Microtox (marine bacteria: Photobacterium phosphoreum), the duckweed, Lemna aequinoctialis, and fish (silver barb: Puntius gonionotus, and Tilapia: Tilapia nilotica). Selenastrum capricornutum was the most sensitive among the tested organisms. The mill toxicity emission rate (TER) was as high as 338 610 (Selenastrum test). The bleaching-pulp and semi-chemical pulp plants which contributed the largest pollution load to the total COGIDO effluent, therefore, were targeted for abatement measures. Physico-chemical parameters as well as qualitative and quantitative aquatic organism composition for the river water were established. The BOD₅ and COD values exceeded the potable surface water standard by a factor of 2 to 4. The species diversity and abundance of the phytoplankton, zooplankton and zoobenthos were found to be lower (20–40%) than that of unpolluted rivers in Vietnam, whereas pollution-indicator species increased up to four times during the dry season 1995.     

Water quality monitoring—Some practical sampling frequency considerations

Water quality monitoring involves sampling a population, water quality, that is changing over time. Sample statistics (e.g., sample mean) computed from data collected by a monitoring network can be affected by three general factors: (1) random changes due to storms, rainfall, etc.; (2) seasonal changes in temperature, rainfall, etc.; and (3) serial correlation or duplication in information from sample to sample. (Closely spaced samples will tend to give similar information).In general, these effects have been noted, but their specific effects on water quality monitoring network design have not been well defined quantitatively. The purpose of this paper is to examine these effects with a specific data set and draw conclusions relative to sampling frequency determinations in network design.The design criterion adopted for this study of effects due to the above factors is the width of confidence intervals about annual sample geometric means of water quality variables. The data base for the study consisted of a daily record of 5 water quality variables at 9 monitoring stations in Illinois for a period of 1 year.Three general regions of frequencies were identified: (1) greater than approximately 30 samples per year where serial correlation plays a dominant role; (2) between approximately 10 and 30 samples per year where the effects of seasonal variation and serial correlation tended to cancel each other out; and (3) less than approximately 10 samples per year where seasonal variation plays a dominant role. In region 2, either seasonal variation and serial correlation should both be considered or both ignored. To consider only seasonal variation introduces more error than ignoring it. These results are network averages (over variables and stations) from one network, thus results for individual variables may deviate considerably from the average and from those for other networks.Financial support for this study was provided, in part, by the U.S. Environmental Protection Agency, grant number R805759-01-0.     

Network design for water quality monitoring of surface freshwaters: a review

To date, many water quality monitoring networks for surface freshwaters have been rather haphazardly designed without a consistent or logical design strategy. Moreover, design practices in recent years indicate a need for cost-effective and logistically adaptable network design approaches. There are many variables that need to be included in a comprehensive yet practical monitoring network: a holistic appraisal of the monitoring objectives, representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples. In order to investigate the factors which affect the development of an effective water quality monitoring network design methodology, a review of past and current approaches is presented.     

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.     

Phytoremediation of dairy effluent by constructed wetland technology

Constructed wetlands are artificial wastewater treatment systems consisting of shallow ponds or channels which have been planted with aquatic plants and which rely upon natural microbial, biological, physical and chemical process to treat wastewater and are gaining acceptance in the recent years as a viable option for the treatment of industrial effluents and removal of toxic components. In this study, an attempt was made to compare the efficiency of aquatic macrophytes like Typha sp., Eichhornia sp., Salvinia sp., Pistia sp., Azolla sp. and Lemna sp. to treat the effluents from dairy factory, under laboratory conditions in constructed wetlands. The biological oxygen demand and chemical oxygen demand of dairy effluent were reduced up to 65.4–83.07% and 70.4–85.3%, respectively, after treatment with constructed wetland technology.     

Assessing watershed transport of atrazine and nitrate to evaluate conservation practice effects and advise future monitoring strategies

Continued public support for U.S. taxpayer funded programs aimed at reducing agricultural pollutants depends on clear demonstrations of water quality improvements. The objective of this research was to determine if implementation of agricultural best management practices (BMPs) in the Goodwater Creek Experimental Watershed (GCEW) resulted in changes to atrazine and nitrate (NO₃–N) loads during storm events. An additional objective was to estimate future monitoring periods necessary to detect a 5, 10, 20, and 25% reduction in atrazine and NO₃–N event load. The GCEW is a 73 km² watershed located in northcentral Missouri, USA. Linear regressions and Akaike Information Criteria were used to determine if reductions in atrazine and NO₃–N event loads occurred as BMPs were implemented. No effects due to any BMP type were indicated for the period of record. Further investigation of event sampling from the long-term GCEW monitoring program indicated errors in atrazine load calculations may be possible due to pre-existing minimum threshold levels used to trigger autosampling and sample compositing. Variation of event loads was better explained by linear regressions for NO₃–N than for atrazine. Decommissioning of upstream monitoring stations during the study period represented a missed opportunity to further explain variation of event loads at the watershed outlet. Atrazine requires approximately twice the monitoring period relative to NO₃–N to detect future reductions in event load. Appropriate matching of pollutant transport mechanisms with autosampling protocols remains a critical information need when setting up or adapting watershed monitoring networks aimed at detecting watershed-scale BMP effects.     

Optimal water quality monitoring network design for river systems

Typical tasks of a river monitoring network design include the selection of the water quality parameters, selection of sampling and measurement methods for these parameters, identification of the locations of sampling stations and determination of the sampling frequencies. These primary design considerations may require a variety of objectives, constraints and solutions. In this study we focus on the optimal river water quality monitoring network design aspect of the overall monitoring program and propose a novel methodology for the analysis of this problem. In the proposed analysis, the locations of sampling sites are determined such that the contaminant detection time is minimized for the river network while achieving maximum reliability for the monitoring system performance. Altamaha river system in the State of Georgia, USA is chosen as an example to demonstrate the proposed methodology. The results show that the proposed model can be effectively used for the optimal design of monitoring networks in river systems.     

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.     

Changing effluent chemistry affect survival,growth and physiological function of <Emphasis Type="Italic">Acacia nilotica</Emphasis> seedlings in northwestern region of India

Recycling and conservation efforts for water are the need of the day because of the lack of new water sources and the ever-increasing demand for drinking water. Seedlings of Acacia nilotica L. were irrigated with: canal water (T₁, control); municipal effluent (T₂); textile effluent (T₃); steel effluent (T₄); textile + municipal effluent in 1:1 ratio (T₅); steel + municipal effluent in 1:2 ratio (T₆); steel + textile in 1:2 ratio (T₈) and steel + municipal + textile in 1:2:2 ratio (T₇) with views to observe effluents effect on the seedlings and its adaptability and to recommend safe disposal of these effluents. Seedlings in T₆, T₇ and T₈ showed 50% lesser height and collar diameter than those in control. Seedlings in T₂ attained greatest height, collar diameter, numbers of branches and produced 140 g dry biomass seedling⁻¹. Highest concentration of manganese (Mn), iron (Fe), copper (Cu) and zinc (Zn) and lowest concentration of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg) in the seedlings of T₄, T₆, T₇ and T₈ resulted in nutritional imbalance, mineral toxicity and reduction in photosynthetic (Pn) and transpiration (E) rates and caused seedling mortality. Seedlings of T₃ had highest sodium concentration and low concentration of Ca, Mg and micronutrients resulting in nutritional imbalance, augmented chlorosis and reduced gas exchange and biomass by half as compared to control. Increased growth, Pn and E and biomass in seedlings of T₅ over T₃ and survival period in T₆, T₇ and T₈ seedlings suggested a beneficial effect of effluents mixing. Unscientific disposal should be avoided and toxic concentration of metal ions␣may be reduced for long-term application and harmless disposal of effluents in afforestation and urban development.     

Application of SPARROW Modeling to Understanding Contaminant Fate and Transport from Uplands to Streams

Understanding spatial variability in contaminant fate and transport is critical to efficient regional water‐quality restoration. An approach to capitalize on previously calibrated spatially referenced regression (SPARROW) models to improve the understanding of contaminant fate and transport was developed and applied to the case of nitrogen in the 166,000 km² Chesapeake Bay watershed. A continuous function of four hydrogeologic, soil, and other landscape properties significant (α = 0.10) to nitrogen transport from uplands to streams was evaluated and compared among each of the more than 80,000 individual catchments (mean area, 2.1 km²) in the watershed. Budgets (including inputs, losses or net change in storage in uplands and stream corridors, and delivery to tidal waters) were also estimated for nitrogen applied to these catchments from selected upland sources. Most (81%) of such inputs are removed, retained, or otherwise processed in uplands rather than transported to surface waters. Combining SPARROW results with previous budget estimates suggests 55% of this processing is attributable to denitrification, 23% to crop or timber harvest, and 6% to volatilization. Remaining upland inputs represent a net annual increase in landscape storage in soils or biomass exceeding 10 kg per hectare in some areas. Such insights are important for planning watershed restoration and for improving future watershed models.     

Synthesis and application of insect attractants in Vietnam

Detrimental effects of synthetic pesticides on health, environment and organisms have necessitated the exploration of alternative strategies for insect control. The insect attractants represent an important link within these systems. In Vietnam, since 1970, methyleugenol and its analogues have been synthesized for mass trapping of the fruitfly Daccus dorsalis Hendel. This chemical reduced the damage on the oranges of many plantations in our country. In the period 1978–1980, for the first time some selected types of pheromones were tested. The trials verified and provided evidence of the occurrence of six species of moth in southeast Vietnam: Archips micaceanus, Archips seminubilus, Cadra caustella, Spodoptera exigua, Chysodeixis eriosoma and Parapoynx sp. The last decade has seen intense activity in the elaboration and application of some complex systems of fighting plant pests. Pheromones of moth and weevils have been prepared in the Institute of Agrochemistry and the Institute of Tropical Biology NCST: Ostrinia nubilalis Hbn, Heliothis armigera Hbn, Plutella xylostella Curt, Adoxophyes sp, Lyonetia clerckella, Trogoderma granarium, Diabrotica virgifera virgifera, Diabrotica undecimpunctata, Blattela germanica, Diprion, Neodiprion, Scolytus multistriatus, Scolytus scolytus, Lasioderma sericorne, Tribolium cofusum. Some synthetic aspects of these pheromones are described. The use of pheromone traps for monitoring and mass trapping the Scolytus multistriatus, Tribolium confusum, Plutella xylostella Curt, Heliothis armigera Hbn, Cylas formicarius elegantulus will be discussed.     

Biomass use in chemical and mechanical pulping with biomass-based energy supply

The pulp and paper industry is energy intensive and consumes large amounts of wood. Biomass is a limited resource and its efficient use is therefore important. In this study, the total amount of biomass used for pulp and for energy is estimated for the production of several woodfree (containing only chemical pulp) and mechanical (containing mechanical pulp) printing paper products, under Swedish conditions. Chemical pulp mills today are largely self-sufficient in energy while mechanical pulp mills depend on large amounts of external electricity. Technically, all energy used in pulp- and papermaking can be biomass based. Here, we assume that all energy used, including external electricity and motor fuels, is based on forest biomass. The whole cradle-to-gate chain is included in the analyses. The results indicate that the total amount of biomass required per tonne paper is slightly lower for woodfree than for mechanical paper. For the biomass use per paper area, the paper grammage is decisive. If the grammage can be lowered by increasing the proportion of mechanical pulp, this may lower the biomass use per paper area, despite the higher biomass use per unit mass in mechanical paper. In the production of woodfree paper, energy recovery from residues in the mill accounts for most of the biomass use, while external electricity production accounts for the largest part for mechanical paper. Motor fuel production accounts for 5–7% of the biomass use. The biomass contained in the final paper product is 21–42% of the total biomass use, indicating that waste paper recovery is important. The biomass use was found to be about 15–17% lower for modelled, modern mills compared with mills representative of today's average technology.     

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.     

Relative Influence of Streamflows in Assessing Temporal Variability in Stream Habitat1

Abstract: The effects of streamflows on temporal variation in stream habitat were analyzed from the data collected 6‐11 years apart at 38 sites across the United States. Multiple linear regression was used to assess the variation in habitat caused by streamflow at the time of sampling and high flows between sampling. In addition to flow variables, the model also contained geomorphic and land use factors. The regression model was statistically significant (p < 0.05; R² = 0.31‐0.46) for 5 of 14 habitat variables: mean wetted stream depth, mean bankfull depth, mean wetted stream width, coefficient of variation of wetted stream width, and the percent frequency of bank erosion. High flows between samples accounted for about 16% of the total variation in the frequency of bank erosion. Streamflow at the time of sampling was the main source of variation in mean stream depth and contributed to the variation in mean stream width and the frequency of bank erosion. Urban land use (population change) accounted for over 20% of the total variation in mean bankfull depth, 15% of the total variation in the coefficient of variation of stream width, and about 10% of the variation in mean stream width.     

Optimizing Liquid Effluent Monitoring at a Large Nuclear Complex

Effluent monitoring typically requires a large number of analytes and samples during the initial or startup phase of a facility. Once a baseline is established, the analyte list and sampling frequency may be reduced. Although there is a large body of literature relevant to the initial design, few, if any, published papers exist on updating established effluent monitoring programs. This paper statistically evaluates four years of baseline data to optimize the liquid effluent monitoring efficiency of a centralized waste treatment and disposal facility at a large defense nuclear complex. Specific objectives were to: (1) assess temporal variability in analyte concentrations, (2) determine operational factors contributing to waste stream variability, (3) assess the probability of exceeding permit limits, and (4) streamline the sampling and analysis regime. Results indicated that the probability of exceeding permit limits was one in a million under normal facility operating conditions, sampling frequency could be reduced, and several analytes could be eliminated. Furthermore, indicators such as gross alpha and gross beta measurements could be used in lieu of more expensive specific isotopic analyses (radium, cesium-137, and strontium-90) for routine monitoring. Study results were used by the state regulatory agency to modify monitoring requirements for a new discharge permit, resulting in an annual cost savings of US $223,000. This case study demonstrates that statistical evaluation of effluent contaminant variability coupled with process knowledge can help plant managers and regulators streamline analyte lists and sampling frequencies based on detection history and environmental risk.     

Factors affecting nitrate distribution in shallow groundwater under a beef farm in South Eastern Ireland

Groundwater contamination was characterised using a methodology which combines shallow groundwater geochemistry data from 17 piezometers over a 2 yr period in a statistical framework and hydrogeological techniques. Nitrate–N (NO₃-N) contaminant mass flux was calculated across three control planes (rows of piezometers) in six isolated plots. Results showed natural attenuation occurs on site although the method does not directly differentiate between dilution and denitrification. It was further investigated whether NO₃-N concentration in shallow groundwater (<5 m below ground level) generated from an agricultural point source on a 4.2 ha site on a beef farm in SE Ireland could be predicted from saturated hydraulic conductivity (K_sat) measurements, ground elevation (m Above Ordnance Datum), elevation of groundwater sampling (screen opening interval) (m AOD) and distance from a dirty water point pollution source. Tobit regression, using a background concentration threshold of 2.6 mg NO₃-N L⁻¹ showed, when assessed individually in a step wise procedure, K_sat was significantly related to groundwater NO₃-N concentration. Distance of the point dirty water pollution source becomes significant when included with K_sat in the model. The model relationships show areas with higher K_sat values have less time for denitrification to occur, whereas lower K_sat values allow denitrification to occur. Areas with higher permeability transport greater NO₃-N fluxes to ground and surface waters. When the distribution of Cl⁻ was examined by the model, K_sat and ground elevation had the most explanatory power but K_sat was not significant pointing to dilution having an effect. Areas with low NO₃ concentration and unaffected Cl⁻ concentration points to denitrification, low NO₃ concentration and low Cl⁻ chloride concentration points to dilution and combining these findings allows areas of denitrification and dilution to be inferred. The effect of denitrification is further supported as mean groundwater NO₃-N was significantly (P < 0.05) related to groundwater N₂/Ar ratio, redox potential (Eh), dissolved O₂ and N₂ and was close to being significant with N₂O (P = 0.08). Calculating contaminant mass flux across more than one control plane is a useful tool to monitor natural attenuation. This tool allows the identification of hot spot areas where intervention other than natural attenuation may be needed to protect receptors.     

Field Evaluation of DRAINMOD 5.1 Under a Cold Climate: Simulation of Daily Midspan Water Table Depths and Drain Outflows1

Abstract: The hydrologic performance of DRAINMOD 5.1 was assessed for the southern Quebec region considering freezing/thawing conditions. A tile drained agricultural field in the Pike River watershed was instrumented to measure tile drainage volumes. The model was calibrated using water table depth and subsurface flow data over a two‐year period, while another two‐year dataset served to validate the model. DRAINMOD 5.1 accurately simulated the timing and magnitude of subsurface drainage events. The model also simulated the pattern of water table fluctuations with a good degree of accuracy. The R² between the observed and simulated daily WTD for calibration was >0.78, and that for validation was 0.93. The corresponding coefficients of efficiency (E) were >0.74 and 0.31. The R² and E values for calibration/validation of subsurface flow were 0.73/0.48 and 0.72/0.40, respectively. DRAINMOD simulated monthly subsurface flow quite accurately (E > 0.82 and R² > 0.84). The model precisely simulated daily/monthly drain flow over the entire year, including the winter months. Thus DRAINMOD 5.1 performed well in simulating the hydrology of a cold region.