Information theoretic perspective on coastal water-quality monitoring and management near an offshore industrial park

A semi-continuous water-quality monitoring system was installed in Yunlin Offshore Industrial Park (YOIP), the largest industrial park in Taiwan, in 2007 to provide real-time water-quality information such as pH, water depth, dissolved oxygen, temperature, turbidity, conductivity, and chlorophyll. To interpret the large quantities of high-frequency data generated by this system, information theory was applied for data analysis and extraction of useful information for further coastal water-quality management. Information theory is a branch of applied mathematics that involves the quantification of information. Shannon entropy is a key measure of information that was calculated in this study to reveal the inherent uncertainty of water-quality information. The applicability of Shannon entropy for signaling possible coastal pollution events in the YOIP was explored and results showed that it provides new insight into the inherent uncertainty or randomness of the original data. Specially, when Shannon entropy was high, multiple instable readings were observed for turbidity and salinity. This indicates that Shannon entropy may be a useful new tool for exploratory data analysis. It can be used as a supplementary indicator along with the original environmental data to signify some episodes of water-quality degradation.     

DO-BOD modeling of River Yamuna for national capital territory, India using STREAM II, a 2D water quality model

The study illustrates the utility of STREAM II as a modeling package to determine the pollution load due to organic matter in the River Yamuna during its course through the National Capital Territory that is Delhi, India. The study was done for a period from 1995–2005. Model simulates the dissolved oxygen and biochemical oxygen demand parameters in a two-dimensional fashion by performing the numerical solution to a set of differential equations representing aquatic life with the help of Crank–Nicholson finite difference method. The model was simulated and calibrated through the field water-quality primary data and the secondary data which were taken from Central Pollution Control Board. The main reasons for the high river pollution is increasing population of Delhi and other states, leading to generation of huge amounts of domestic sewage into the river Yamuna. The model gave a good agreement between calibrated and observed data, thus, actualizing the validity of the model. However, discrepancies noticed during model calibrations were attributed to the assumptions adopted in the model formulation and to lack of field data.     

Monitoring sediment oxygen demand for assessment of dissolved oxygen distribution in river

Sediment oxygen demand (SOD) has become an integral part of modeling dissolved oxygen (DO) within surface water bodies. Because very few data on SOD are available, it is common for modeler to take SOD values from literature for use within DO models. SOD is such an important parameter in modeling DO that this approach may lead to erroneous results. This paper reported on developing an approach for monitoring sediment oxygen demand conducted with undisturbed sediment core samples, where the measured results were incorporated into a water quality model for simulating and assessing dissolved oxygen distribution in the Xindian River of northern Taiwan. The measured results indicate that a higher freshwater discharge results in a lower SOD. Throughout a 1-year observation in 2004, the measured SOD ranged from 0.367 to 1.246 g/m(2)/day at the temperature of 20°C. The mean values of the measured SOD at each station were adopted in a vertical two-dimensional water quality model to simulate the DO distribution along the Xindian River. The simulating results accurately depict the field-measured DO distribution during the low and high flow conditions. Model sensitivity analyses were also conducted with increasing and decreasing SOD values for the low and high flow conditions and revealed that SOD had a significant impact on the DO distribution along the Xindian River. The present work combined with field measurements and numerical simulation should assist in river water quality management.     

Strategies to optimize monitoring schemes of recreational waters from Salta,Argentina: a multivariate approach

Several recreational surface waters in Salta, Argentina, were selected to assess their quality. Seventy percent of the measurements exceeded at least one of the limits established by international legislation becoming unsuitable for their use. To interpret results of complex data, multivariate techniques were applied. Arenales River, due to the variability observed in the data, was divided in two: upstream and downstream representing low and high pollution sites, respectively, and cluster analysis supported that differentiation. Arenales River downstream and Campo Alegre Reservoir were the most different environments, and Vaqueros and La Caldera rivers were the most similar. Canonical correlation analysis allowed exploration of correlations between physicochemical and microbiological variables except in both parts of Arenales River, and principal component analysis allowed finding relationships among the nine measured variables in all aquatic environments. Variable’s loadings showed that Arenales River downstream was impacted by industrial and domestic activities, Arenales River upstream was affected by agricultural activities, Campo Alegre Reservoir was disturbed by anthropogenic and ecological effects, and La Caldera and Vaqueros rivers were influenced by recreational activities. Discriminant analysis allowed identification of subgroup of variables responsible for seasonal and spatial variations. Enterococcus, dissolved oxygen, conductivity, E. coli, pH, and fecal coliforms are sufficient to spatially describe the quality of the aquatic environments. Regarding seasonal variations, dissolved oxygen, conductivity, fecal coliforms, and pH can be used to describe water quality during dry season, while dissolved oxygen, conductivity, total coliforms, E. coli, and Enterococcus during wet season. Thus, the use of multivariate techniques allowed optimizing monitoring tasks and minimizing costs involved.     

Temporal and spatial variability in water quality of wetlands in the Minneapolis/St. Paul,MN metropolitan area: Implications for monitoring strategies and designs

Temporal and spatial variability in wetland water-quality variables were examined for twenty-one wetlands in the Minneapolis/St. Paul metropolitan area and eighteen wetlands in adjacent Wright County. Wetland water quality was significantly affected by contact with the sediment (surface water vs. groundwater), season, degree of hydrologic isolation, wetland class, and predominant land-use in the surrounding watershed (p<0.05). Between years, only nitrate and particulate nitrogen concentrations varied significantly in Wright County wetland surface waters. For eight water-quality variables, the power of a paired before-and-after comparison design was greater than the power of a completely randomized design. The reverse was true for four other water-quality variables. The power of statistical tests for different classes of water-quality variables could be ranked according to the predominant factors influencing these: climate factors>edaphic factors>detritivory>land-use factors>biotic-redox or other multiple factors.For two wetlands sampled intensively, soluble reactive phosphate and total dissolved phosphorus were the most spatially variable (c.v.=76–249%), while temperature, color, dissolved organic carbon, and DO were least variable (c.v.=6–43%). Geostatistical analyses demonstrated that the average distance across which water-quality variables were spatially correlated (variogram range) was 61–112% of the mean radius of each wetland. Within the shallower of the two wetlands, nitrogen speciation was explained as a function of dissolved oxygen, while deeper marsh water-quality variables were explained as a function of water depth or distance from the wetland edge. Compositing water-quality samples produced unbiased estimates of individual sample means for all water quality variables examined except for ammonium.     

Water quality of potential reference lakes in the Arkansas Valley and Ouachita Mountain ecoregions,Arkansas

This report describes a study to identify reference lakes in two lake classifications common to parts of two level III ecoregions in western Arkansas—the Arkansas Valley and Ouachita Mountains. Fifty-two lakes were considered. A screening process that relied on land-use data was followed by reconnaissance water-quality sampling, and two lakes from each ecoregion were selected for intensive water-quality sampling. Our data suggest that Spring Lake is a suitable reference lake for the Arkansas Valley and that Hot Springs Lake is a suitable reference lake for the Ouachita Mountains. Concentrations for five nutrient constituents—orthophosphorus, total phosphorus, total kjeldahl nitrogen, total nitrogen, and total organic carbon—were lower at Spring Lake on all nine sampling occasions and transparency measurements at Spring Lake were significantly deeper than measurements at Cove Lake. For the Ouachita Mountains ecoregion, water quality at Hot Springs Lake slightly exceeded that of Lake Winona. The most apparent water-quality differences for the two lakes were related to transparency and total organic carbon concentrations, which were deeper and lower at Hot Springs Lake, respectively. Our results indicate that when nutrient concentrations are low, transparency may be more valuable for differentiating between lake water quality than chemical constituents that have been useful for distinguishing between water-quality conditions in mesotrophic and eutrophic settings. For example, in this oligotrophic setting, concentrations for chlorophyll a can be less than 5 μg/L and diurnal variability that is typically associated with dissolved oxygen in more productive settings was not evident.     

Application of physicochemical data for water-quality assessment of watercourses in the Gdansk Municipality (South Baltic coast)

The paper presents water-quality evaluation based on an 8-year monitoring programme in the Gdansk Municipality region, on the Southern coast of the Baltic Sea. The studies were carried out from 2000 to 2007 by surface water analysis at 15 various sites within eight watercourses. Sampling sites included rather urbanized or developed lands, farming fields and non-polluted city recreational areas such as parks and forests. Most of the watercourses were sampled monthly at two locations, one within the upper course of the watercourse and the other near its mouth. In all samples, eight parameters of water quality were determined: total suspended solids, dissolved oxygen, water temperature, oxygen saturation, 5-day biochemical oxygen demand, chemical oxygen demand, total phosphorus and total nitrogen concentration. Interpretation of the obtained results revealed that examination of those basic physicochemical parameters permits to discriminate initially watercourses with respect to level of water contamination. During the research, a large dataset was obtained and it was described by both basic statistical parameters and chemometric method of cluster analysis. The paper presents relations between analysed parameters and influence of land exploitation mode on water quality and describes variation of the results both in space and time.     

A Three-Dimensional Water Quality Model of Chicago Area Waterway System (CAWS)

As outfalls from various water reclamation plants, pumping stations, and combined sewer overflow outfalls discharge into the Chicago Area Waterway System (CAWS), an enhanced understanding of the final fate of crucial water quality state variables is of utmost importance. This paper reports the development and application of a 3D water quality model for a modified CAWS combined with the hydrodynamic kernel of Environmental Fluid Dynamics Code (EFDC). The modified CAWS is used to demonstrate the usefulness of the model while eliminating complications beyond the scope of this initial effort. The water quality model developed and presented in this research is a simplistic dissolved oxygen (DO)—biochemical oxygen demand model with the facility to account for the interaction between the water column and the bed. The aforementioned model is applied for the month of May 2009. The results from the hydrodynamic (EFDC) and water quality model is validated with the help of the observed data obtained from United States Geological Survey gaging stations and Metropolitan Water Reclamation District of Greater Chicago monitoring stations present inside the modeled domain. The 3D modeling captured the hydrodynamic and water-quality processes in CAWS in a satisfactory manner. Furthermore, modeling results showed and proved the interdependence of water quality characteristics in Bubbly Creek and CAWS with the effluent concentration from Racine Avenue Pumping Station situated at the head of Bubbly Creek, South Fork of South Branch of Chicago River.     

A Three-Dimensional, Integrated Seasonal Separate Advection–Diffusion Model (ISSADM) to Predict Water Quality Patterns in the Chahnimeh Reservoir

Seasonal rivers are the main sources of discharge for many lakes and reservoirs. These rivers can deliver pollutants into these water bodies, especially during large events. The fate and distribution of these pollutants within lakes is difficult to predict. Here, a three-dimensional, finite-volume model for predicting lake water quality is used to account for internal advection and diffusion, including the impacts of the inflowing rivers on the velocity field. We used parsimonious sub-models for the source/sink terms for temperature, dissolved oxygen, ammonia nitrogen, phosphorous, phytoplankton, and zooplankton concentrations and tested the model predictions against field measurements from the Chahnimeh Reservoir in Iran. The modeled water quality parameters were in good agreement with the measured values. Results were notably poorer when the three-dimensionality of the model was removed. This study suggests that properly simulating three-dimensional advection is important to properly predict the distribution of pollutants within some lakes and reservoirs and that this model may be directly applicable to systems similar to Chahnimeh Reservoir.     

Near-field loading dynamics of total phosphorus and short-term water quality variations at a rainbow trout cage farm in Lake Huron

Aquatic total phosphorus (Tot-P) is measured at fish-cages in Lake Huron for environmental regulatory compliance. An improved understanding of how Tot-P is manifested in the near-field (相似文献   

Assessment of water quality of Rawal Lake by long-time monitoring

Water quality of rivers, natural lakes, and reservoirs in developing countries is being degraded because of the contaminated inflows. There is a serious need for appropriate water quality monitoring for future planning and management of clean water resources. Quality of water in Rawal Lake Pakistan has been investigated in this paper. Flows from the upstream of Rawal Lake and its surrounding villages are highly polluted. Lake water quality parameters like pH, turbidity, alkalinity, calcium, nitrite, sulfate, biological oxygen dissolved, dissolved oxygen, chloride, total dissolved solids (TDS), and coliforms were investigated. Samples of water from different locations of Korang River were collected and tested. Most of the data was collected by field sampling and field visits. However, long-term information was taken from different departments. Statistical parameters (standard deviation, maximum, minimum, mean, mode, kurtosis, skew, and Euclidean distance) of variables were determined. A distinct parameter based on the difference of the maximum value the variable and maximum allowable value of that variable defined by World Health Organization was used for analysis. Grouping and clustering of elements was made on the basis of this parameter. Trend of increasing or decreasing of values of variables over a long time was also taken into account for grouping the variables. It was concluded that the concentration of seven contaminants was higher as compared to the permissible limits under environmental standards. These variables need immediate attention. The environmentally bad conditions of Rawal Lake can only be rectified by appropriate lake environmental supervision, watershed management, and implementation of environmental legislation.     

Sensitivity analysis of water quality for Delhi stretch of the River Yamuna,India

Simulation models are used to aid the decision makers about water pollution control and management in river systems. However, uncertainty of model parameters affects the model predictions and hence the pollution control decision. Therefore, it often is necessary to identify the model parameters that significantly affect the model output uncertainty prior to or as a supplement to model application to water pollution control and planning problems. In this study, sensitivity analysis, as a tool for uncertainty analysis was carried out to assess the sensitivity of water quality to (a) model parameters (b) pollution abatement measures such as wastewater treatment, waste discharge and flow augmentation from upstream reservoir. In addition, sensitivity analysis for the “best practical solution” was carried out to help the decision makers in choosing an appropriate option. The Delhi stretch of the river Yamuna was considered as a case study. The QUAL2E model is used for water quality simulation. The results obtained indicate that parameters K ₁ (deoxygenation constant) and K ₃ (settling oxygen demand), which is the rate of biochemical decomposition of organic matter and rate of BOD removal by settling, respectively, are the most sensitive parameters for the considered river stretch. Different combinations of variations in K ₁ and K ₂ also revealed similar results for better understanding of inter-dependability of K ₁ and K ₂. Also, among the pollution abatement methods, the change (perturbation) in wastewater treatment level at primary, secondary, tertiary, and advanced has the greatest effect on the uncertainty of the simulated dissolved oxygen and biochemical oxygen demand concentrations.     

Modeling the effect of land use/land cover on nitrogen,phosphorous and dissolved oxygen loads in the Velhas River using the concept of exclusive contribution area

Non-point source water pollution is a major problem in most parts of the world, but is also very difficult to quantify and control since it is not easily separated from point sources and can theoretically originate from the whole watershed. In this article, we evaluate the relationship between land use and land cover and four water pollution parameters in a watershed in Southeast Brazil. The four parameters are nitrate, total ammonia nitrogen, total phosphorous, and dissolved oxygen. To help concentrate on non-point source pollution, only data from the wet seasons of the time period (2001–2013) were analysed, based on the fact that precipitation causes runoff which is the main cause of diffuse pollution. The parameters measured were transformed into loads, which were in turn associated with an exclusive contribution area, so that every measuring station could be considered independent. Analyses were also performed on riparian zones of different widths to verify if the effect of the land cover on the water quality of the stream decreases with the increased distance. Pearson correlation coefficients indicate that urban areas and agriculture/pasture tend to worsen water quality (source). Conversely, forest and riparian areas have a reducing effect on pollution (sink). The best results were obtained for total ammonia nitrogen and dissolved oxygen using the whole exclusive contribution areas with determination coefficients better than R²≈0.8. Nitrate and total phosphorous did not produce valid models. We suspect that the transformation delay from total ammonia nitrogen to nitrate might be an important factor for the poor result for this parameter. For phosphorous, we think that the phosphorous sink in the bottom sediment might be the most limiting factor explaining the failure of our models.     

中俄跨界水体水质联合监测数据可比性研究

中俄跨界水体水质联合监测已经连续开展了11 a,积累了大量的监测数据。笔者针对双方实际监测数据,选用相关性分析和t检验等统计学方法,分析了中俄双方联合监测数据可比性。研究结果表明:p H、溶解氧、高锰酸盐指数和化学需氧量的相对偏差统计容许限基本满足中国标准建议值;氨氮和铁2个指标高于中国标准建议值;锰的数据差异最大。建议中俄双方针对溶解氧使用便携式溶解氧仪进行原位监测;重点对氨氮、铁和锰开展技术交流,设计相关实验,从样品采集、保存、运输、前处理和实验室分析等各环节查找双方差异。     

Evaluation of sampling strategies to characterize dissolved oxygen conditions in northern Gulf of Mexico estuaries

Dissolved oxygen was continuously monitored in eight sites of northern Gulf of Mexico estuaries in August, 1990. Monte Carlo analyses on subsamples of the data were used to evaluate several commonly used monitoring strategies. Monitoring strategies which involve single point sampling of dissolved oxygen may often misclassify an estuary as having good water quality. In the case of shallow, often well-mixed estuaries that experience diurnal cycles, such monitoring often does not occur at night, during the time of lowest dissolved oxygen concentration. Our objective was to determine the minimum sampling effort required to correctly classify a site in terms of the observed frequency of hypoxia. Tests concluded that the most successful classification strategy used the minimum dissolved oxygen concentration from a continuously sampled 24-hour period.Contribution No. 745, U.S. E.P.A., Environmental Research Lab, Gulf Breeze, FL 32561     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

Evaluation of data quality in Japanese National Forest Inventory

We evaluated the quality of data being collected for the Japanese National Forest Inventory (NFI). The inventory program commenced in 1999 but has not incorporated a quality assurance (QA) program; we sought to determine what effect this was having on the quality of data being collected. Forty-eight plots in four prefectures were measured by operational field teams and then remeasured by a control team that made careful and unhurried measurements. The paired data were evaluated, including diameter, total height, tree count, species richness, and topographic condition. Compared to the control team, all field teams of each prefecture tended to significantly underestimate all of the continuous variables. Most variables had larger variability in the inventory data than has been reported in the published literature. The findings of consistent bias and large variation in the field team measurements call for urgent implementation of a quality assurance program (extensive field training and regular remeasurement) in the Japanese NFI to improve data quality, and this conclusion could be applied to the inventory system of any country that does not include a QA program.     

Atmospheric influences on water quality: a simulation of nutrient loading for the Pearl River Basin, USA

Knowledge of water quality conditions is essential in assessing the health of riverine ecosystems. The goal of this study is to determine the degree to which water quality variables are related to precipitation and air temperature conditions for a segment of the Pearl River Basin near Bogalusa, LA, USA. The AQUATOX ecological fate simulation model is used to estimate daily total nitrogen, total phosphorus, and dissolved oxygen concentrations over a 2-year period. Daily modeled output for each variable was calibrated against reliably measured data to assess the accuracy. Observed data were plotted against simulated data for controlled and perturbed models for validation, and stepwise multiple regression analysis was used to quantify the relationships between the water quality and meteorological variables. Results suggest that daily dissolved oxygen is significantly negatively correlated to concurrent daily mean air temperature with a total explained variance of 0.679 (p?<?0.01), and monthly dissolved oxygen is significantly negatively correlated to monthly mean air temperature with a total explained variance of 0.567 (p?<?0.01). Total mean monthly phosphorus concentration is significantly positively related to the previous month's precipitation with a total explained variance of 0.302 (p?<?0.01). These relationships suggest that atmospheric conditions have a strong influence on water quality in the Pearl Basin. Therefore, environmental planners should expect that future climatic changes are likely to alter water quality.