Design of River Water Quality Monitoring Networks: A Case Study

Karoon River, from Gotvand Dam to Persian Gulf with more than 450 km in length and an annual discharge of 11,891 million cubic meters, is the largest river in Iran. Increasing water withdrawal from and wastewater discharge to the river has endangered the aquatic life of this important ecosystem. Furthermore, the drinking and in-stream water quality standards have been violated in many instances. In this paper, a river water quality monitoring network is designed, including determination of sampling frequencies as well as location of water quality monitoring stations. In this regard, two models are developed. The first model is a Genetic Algorithm-based optimization model and the second one is a combination of Kriging method and Analytical Hierarchy Process. The temporal variation of the concentration of water quality variables along Karoon and Dez Rivers are evaluated and the main water quality indicators are selected. Then, thirty five stations are selected and the application of Entropy Theory in calculating the sampling frequency is demonstrated. The results show the significant value of the proposed methodology in the design of monitoring network.     

Phase I of the Kissimmee River restoration project, Florida, USA: Impacts of construction on water quality

Phase I of the Kissimmee River restoration project included backfilling of 12 km of canal and restoring flow through 24 km of continuous river channel. We quantified the effects of construction activities on four water quality parameters (turbidity, total phosphorus flow-weighted concentration, total phosphorus load and dissolved oxygen concentration). Data were collected at stations upstream and downstream of the construction and at four stations within the construction zone to determine if canal backfilling and construction of 2.4 km of new river channel would negatively impact local and downstream water quality. Turbidity levels at the downstream station were elevated for approximately 2 weeks during the one and a half year construction period, but never exceeded the Florida Department of Environmental Protection construction permit criteria. Turbidity levels at stations within the construction zone were high at certain times. Flow-weighted concentration of total phosphorus at the downstream station was slightly higher than the upstream station during construction, but low discharge limited downstream transport of phosphorus. Total phosphorus loads at the upstream and downstream stations were similar and loading to Lake Okeechobee was not significantly affected by construction. Mean water column dissolved oxygen concentrations at all sampling stations were similar during construction.     

Surface Water Quality Assessment by Environmetric Methods

This environmetric study deals with the interpretation of river water monitoring data from the basin of the Buyuk Menderes River and its tributaries in Turkey. Eleven variables were measured to estimate water quality at 17 sampling sites. Factor analysis was applied to explain the correlations between the observations in terms of underlying factors. Results revealed that, water quality was strongly affected from agricultural uses. Cluster analysis was used to classify stations with similar properties and results distinguished three groups of stations. Water quality at downstream of the river was quite different from the other part. It is recommended to involve the environmetric data treatment as a substantial procedure in assessment of water quality data.     

Calculating of river water quality sampling frequency by the analytic hierarchy process (AHP)

River water quality sampling frequency is an important aspect of the river water quality monitoring network. A suitable sampling frequency for each station as well as for the whole network will provide a measure of the real water quality status for the water quality managers as well as the decision makers. The analytic hierarchy process (AHP) is an effective method for decision analysis and calculation of weighting factors based on multiple criteria to solve complicated problems. This study introduces a new procedure to design river water quality sampling frequency by applying the AHP. We introduce and combine weighting factors of variables with the relative weights of stations to select the sampling frequency for each station, monthly and yearly. The new procedure was applied for Jingmei and Xindian rivers, Taipei, Taiwan. The results showed that sampling frequency should be increased at high weighted stations while decreased at low weighted stations. In addition, a detailed monitoring plan for each station and each month could be scheduled from the output results. Finally, the study showed that the AHP is a suitable method to design a system for sampling frequency as it could combine multiple weights and multiple levels for stations and variables to calculate a final weight for stations, variables, and months.     

Assessing temporal representativeness of water quality monitoring data

The effectiveness of different monitoring methods in detecting temporal changes in water quality depends on the achievable sampling intervals, and how these relate to the extent of temporal variation. However, water quality sampling frequencies are rarely adjusted to the actual variation of the monitoring area. Manual sampling, for example, is often limited by the level of funding and not by the optimal timing to take samples. Restrictions in monitoring methods therefore often determine their ability to estimate the true mean and variance values for a certain time period or season. Consequently, we estimated how different sampling intervals determine the mean and standard deviation in a specific monitoring area by using high frequency data from in situ automated monitoring stations. Raw fluorescence measurements of chlorophyll a for three automated monitoring stations were calibrated by using phycocyanin fluorescence measurements and chlorophyll a analyzed from manual water samples in a laboratory. A moving block bootstrap simulation was then used to estimate the standard errors of the mean and standard deviations for different sample sizes. Our results showed that in a temperate, meso-eutrophic lake, relatively high errors in seasonal statistics can be expected from monthly sampling. Moreover, weekly sampling yielded relatively small accuracy benefits compared to a fortnightly sampling. The presented method for temporal representation analysis can be used as a tool in sampling design by adjusting the sampling interval to suit the actual temporal variation in the monitoring area, in addition to being used for estimating the usefulness of previously collected data.     

Design of on-line river water quality monitoring systems using the entropy theory: a case study

The design of a water quality monitoring network is considered as the main component of water quality management including selection of the water quality variables, location of sampling stations and determination of sampling frequencies. In this study, an entropy-based approach is presented for design of an on-line water quality monitoring network for the Karoon River, which is the largest and the most important river in Iran. In the proposed algorithm of design, the number and location of sampling sites and sampling frequencies are determined by minimizing the redundant information, which is quantified using the entropy theory. A water quality simulation model is also used to generate the time series of the concentration of water quality variables at some potential sites along the river. As several water quality variables are usually considered in the design of water quality monitoring networks, the pair-wise comparison is used to combine the spatial and temporal frequencies calculated for each water quality variable. After selecting the sampling frequencies, different components of a comprehensive monitoring system such as data acquisition, transmission and processing are designed for the study area, and technical characteristics of the on-line and off-line monitoring equipment are presented. Finally, the assessment for the human resources needs, as well as training and quality assurance programs are presented considering the existing resources in the study area. The results show that the proposed approach can be effectively used for the optimal design of the river monitoring systems.     

A study of the heavy metal concentrations of the Singapore River

The concentrations of lead, cadmium, copper, zinc, iron, and mercury in the water, sediment and biota of the Singapore River were determined. The concentration of the various metals in water showed significant variation at different sampling times and there was enrichment of lead content. The spatial patterns of metal distribution in the sediment could be due to the different pollution sources such as exhaust emission from boats and other environmental variables such as clay content of sediment or tide level. In the biota, higher amounts of metals were found in species inhabiting the river bed while organisms of higher trophic level such as free-swimming fishes and crabs accumulated lower amounts. In general, the flesh of fishes and crabs had the least content of metals compared to other tissues. The Concentration of various metals in bivalve, Mytilopsis sallei, which were found extensively in the river did not reflect the pollution distribution.     

Monitoring nutrient transport in large rivers

The problem of estimating nutrient transport in large rivers and the uncertainty of such load estimates was studied both empirically and theoretically. In the empirical part of the study, time series of data from the Rhine, Meuse, Vistula and Oder Rivers were examined. The results of this data analysis justify the use of linear interpolation to estimate concentrations prevailing between sampling occasions. A special study of the spatial variation of concentrations within different cross-sections of the Vistula river showed that such variation can contribute substantially to the uncertainty of load estimates. In general, however, sampling at one point in the cross-section did not result in biased load estimates. In the theoretical part of the study, simple ARMA (autoregressive-moving average) models were used to derive generally applicable formulas for the expected mean square error of load estimates based on serially dependent concentration data. These formulas were then used to estimate the uncertainty of calculated nutrient loads in the Rhine and the Vistula, respectively.     

Design of sampling locations for river water quality monitoring considering seasonal variation of point and diffuse pollution loads

The design of a water quality monitoring network (WQMN) is a complicated decision-making process because each sampling involves high installation, operational, and maintenance costs. Therefore, data with the highest information content should be collected. The effect of seasonal variation in point and diffuse pollution loadings on river water quality may have a significant impact on the optimal selection of sampling locations, but this possible effect has never been addressed in the evaluation and design of monitoring networks. The present study proposes a systematic approach for siting an optimal number and location of river water quality sampling stations based on seasonal or monsoonal variations in both point and diffuse pollution loadings. The proposed approach conceptualizes water quality monitoring as a two-stage process; the first stage of which is to consider all potential water quality sampling sites, selected based on the existing guidelines or frameworks, and the locations of both point and diffuse pollution sources. The monitoring at all sampling sites thus identified should be continued for an adequate period of time to account for the effect of the monsoon season. In the second stage, the monitoring network is then designed separately for monsoon and non-monsoon periods by optimizing the number and locations of sampling sites, using a modified Sanders approach. The impacts of human interventions on the design of the sampling net are quantified geospatially by estimating diffuse pollution loads and verified with land use map. To demonstrate the proposed methodology, the Kali River basin in the western Uttar Pradesh state of India was selected as a study area. The final design suggests consequential pre- and post-monsoonal changes in the location and priority of water quality monitoring stations based on the seasonal variation of point and diffuse pollution loadings.     

Heavy metal contamination in the Delhi segment of Yamuna basin

Concentration of heavy metals (Cd, Ni, Zn, Fe, Cu, Mn, Pb, Cr, Hg and As) in the waters of River Yamuna and in the soil of agricultural fields along its course in Delhi are reported from 13 sites, spread through the Delhi stretch of Yamuna, starting from the Wazirabad barrage till the Okhla barrage. Varying concentration of heavy metals was found. Peaks were observed in samples collected downstream of Wazirabad and Okhla barrage, indicating the anthropogenic nature of the contamination. The Wazirabad section of the river receives wastewater from Najafgarh and its supplementary drains, whereas the Shahdara drain releases its pollution load upstream of the Okhla barrage. Average heavy metal concentration at different locations in the river water varied in the order of Fe>Cr>Mn>Zn>Pb>Cu>Ni>Hg>As>Cd. The river basin soil shows higher level of contamination with lesser variation than the water samples among sampling locations, thereby suggesting deposition over long periods of time through the processes of adsorption and absorption. The average heavy metal concentration at different locations in soil varied in the order of Fe>Mn>Zn>Cr>Pb>Ni>Hg>Cu>As>Cd.     

Water quality in Lis river, Portugal

In the past 30?years, the Lis river basin has been subjected to constant ecological disasters mainly due to piggery untreated wastewater discharges. The aim of this study was to evaluate the effect of existing domestic, agricultural, and industrial activities on the water quality, and to propose a watershed plan to protect and manage surface water resources within the Lis river basin. For this purpose, 16 monitoring stations have been strategically selected along the Lis river stretch and its main tributaries to evaluate the water quality in six different sampling periods (2003–2006). All samples were characterized in terms of organic material, nutrients, chlorophyll, and pathogenic bacteria. Generally, the Lis river presents poor water quality, according to environmental quality standards for surface water, principally in terms of dissolved oxygen, biochemical oxygen demand, total nitrogen, and fecal coliform, which can be associated mainly with the contamination source from pig-breeding farms.     

Short-term accumulative signatures of heavy metals in river bed sediments in the industrial area, Tehran, Iran

In modern civilization, numerous anthropogenic activities release a variety of pollutants into the environment and with anomalous enrichment of heavy metals it causes surface and subsurface contamination. The aquatic sediments provide pertinent tools for the quality assessment of urban and industrial environments in large cities. The present study reveals short-term accumulative trends of heavy metals (Co, Cd, and Pb) in the sand and silt dominated riverbed sediments from Chitgar industrial area (Tehran, Iran) between the period of May 2007 and May 2008. Lead demonstrates highest concentration in residential areas, cadmium in and around industrial areas, whereas cobalt shows least variability. Geo-accumulation index implies moderately to highly polluted sediments with respect to Cd and Pb. With few exceptions, all three metals at different sampling stations display short-term increasing trends, independent of seasonal variability with urban and industrial distends along the river being the chief sources of contamination.     

基于在线自动监测的钦州湾海域水质参数周年时空变化特征

通过分析位于钦州湾的2个海水水质自动监测站2009-2010年的自动监测数据，发现钦州湾水温、盐度、溶解氧季节变化明显，海水表层水温变化是引起钦州湾溶解氧含量变动的主要原因；钦州湾海水表层盐度及pH值主要受钦江、茅岭江径流及潮汐涨落的影响；处于河口区域，受大陆径流影响显著的海域使用海水水质标准来评价有欠妥当。     

A cost-precision model for marine environmental monitoring,based on time-integrated averages

Ongoing marine monitoring programs are seldom designed to detect changes in the environment between different years, mainly due to the high number of samples required for a sufficient statistical precision. We here show that pooling over time (time integration) of seasonal measurements provides an efficient method of reducing variability, thereby improving the precision and power in detecting inter-annual differences. Such data from weekly environmental sensor profiles at 21 stations in the northern Bothnian Sea was used in a cost-precision spatio-temporal allocation model. Time-integrated averages for six different variables over 6 months from a rather heterogeneous area showed low variability between stations (coefficient of variation, CV, range of 0.6–12.4%) compared to variability between stations in a single day (CV range 2.4–88.6%), or variability over time for a single station (CV range 0.4–110.7%). Reduced sampling frequency from weekly to approximately monthly sampling did not change the results markedly, whereas lower frequency differed more from results with weekly sampling. With monthly sampling, high precision and power of estimates could therefore be achieved with a low number of stations. With input of cost factors like ship time, labor, and analyses, the model can predict the cost for a given required precision in the time-integrated average of each variable by optimizing sampling allocation. A following power analysis can provide information on minimum sample size to detect differences between years with a required power. Alternatively, the model can predict the precision of annual means for the included variables when the program has a pre-defined budget. Use of time-integrated results from sampling stations with different areal coverage and environmental heterogeneity can thus be an efficient strategy to detect environmental differences between single years, as well as a long-term temporal trend. Use of the presented allocation model will then help to minimize the cost and effort of a monitoring program.     

Assessment and occurrence of various heavy metals in surface water of Ganga river around Kolkata: a study for toxicity and ecological impact

A study was conducted during November, 2005–October, 2006 to evaluate the surface water quality of river Ganga around Kolkata. The samples were analyzed for a number of physico-chemical parameters using standard laboratory procedures and giving prime thrust to determine the heavy metal concentrations (Fe, Mn, Cu, Zn, Pb, Cd, Cr, and Ni) of surface water at four different locations of the river Ganga around Kolkata from two points (middle of the river stream and a discharge point) at each location. Out of 96 samples analyzed, Fe, Mn, Cu, Zn, and Ni were detected in 71, 47, 38, 60, and 45 samples in the concentrations ranging from 0.013 to 5.49, 0.022 to 1.78, 0.003 to 0.033, 0.005 to 0.293, and 0.045 to 0.24 mg L^???1, respectively. Cd and Pb were detected in six and 21 samples in the range of 0.005 to 0.006 and 0.05 to 0.53 mg L^???1, respectively. But Cr was not detected in any of the samples analyzed. The metals exhibited no significant variation with respect to sampling locations as well as discharge points. However, the concentration of those metals varied with season, being higher in rainy and lower in winter season.     

Ecological study of river Suswa: modeling DO and BOD

In this paper limnological status of river Suswa was observed for a period of two years. A water quality Beck modified Khanna Bhutiani model (BMKB model) was developed to calculate DO (dissolved Oxygen) and BOD (biochemical oxygen demand). The model was developed to calculate DO and BOD by using DO/BOD of same place and upstream in previous season which results in Single output. This model gives the seasonal value on the basis of previously taken upstream and downstream observations/concentrations of DO and BOD. The model was calibrated and verified for the water quality data (Physico-chemical data) of samples collected from river Suswa in different seasons. The model gave good agreement between data observed by it and the data observed manually, thus substantiating the validity of the model. Only minor differences were observed in physical, chemical and heavy metals of all the four sampling stations during the course of study.     

地表水自动与常规监测评价结果一致性对比分析

选择分布在不同流域的15个与自动监测站位置一致性较好的断面,对其进行为期1年的“同时同点位”对比监测。分析数据发现:由于采样时间和位置的偏差,自动监测月均值与常规手工监测数据的可比性并不理想。采用以下4种方法评价水质:自动5项、手动5项、手动21项、自动5项+手动16项。比较第1和第2种方法,水质评价类别相同与变化一类(发生一个水质类别变化)的占比之和在85%左右;比较第1和第3种方法,类别相同与变化一类的占比之和在80%左右;比较第3和第4种方法,类别相同与变化一类的占比之和接近90%,因此该组合是更合理的地表水水质评价方法。     

Effect of sampling effort and sampling frequency on the composition of the planktonic crustacean assemblage: a case study of the river Danube

Although numerous studies have focused on the seasonal dynamics of riverine zooplankton, little is known about its short-term variation. In order to examine the effects of sampling frequency and sampling effort, microcrustacean samples were collected at daily intervals between 13 June and 21 July of 2007 in a parapotamal side arm of the river Danube, Hungary. Samples were also taken at biweekly intervals from November 2006 to May 2008. After presenting the community dynamics, the effect of sampling effort was evaluated with two different methods; the minimal sample size was also estimated. We introduced a single index (potential dynamic information loss; to determine the potential loss of information when sampling frequency is reduced. The formula was calculated for the total abundance, densities of the dominant taxa, adult/larva ratios of copepods and for two different diversity measures. Results suggest that abundances may experience notable fluctuations even within 1 week, as do diversities and adult/larva ratios.     

Organochlorine pesticide residues in Songkla Lake

The water quality of Songkla Lake for organochlorine (OC) pesticide contamination was studied from chosen sampling sites (stations) using the lakes geographic data and pollution sources. The water samples were collected monthly from 13 stations in Songkla Lake during September 1991–November 1992. The OC pesticide residues found were Heptachlor, Heptachlor Epoxide, DDD, DDE, DDT and Aldrin in the range 0–0.5690 ppm. This study showed that DDT and its metabolite products (DDD and DDE) dominated OC pesticide residues in the lake. The concentration of OC residues also depended on the season, i.e. at some sampling stations the concentration of OC residues in the dry season (July–September) were higher than in the wet season (October–January).     

Tracking sewage derived contamination in riverine settings by analysis of synthetic surfactants

A study has been made of the presence and reactivity of the most commonly used surfactants, both anionic (linear alkylbenzene sulfonates, LAS, and alkyl ethoxysulfates, AES) and non-ionic (alcohol polyethoxylates, AEOs, and nonylphenol polyethoxylates, NPEOs), in water and surface sediments from the middle stretch of the Guadalete River in SW Spain (12 stations). Average values were between 0.1 and 3.7 mg kg(-1) in sediment, and between 0.2 and 37 μg L(-1) in water. The sorption of surfactants was dominated by hydrophobic mechanisms, so those homologues having longer alkyl chains (e.g. C(18)AEO) showed higher relative percentages and concentrations in sediments compared with water. Local and sharply higher concentrations of these compounds were observed at three sampling stations (7, 9 and 12), indicating the occurrence of wastewater discharges into the river. By analysing the distributions of different surfactant homologues and their metabolites we were able to distinguish between sewage contamination from sources discharging treated and untreated wastewaters. Upstream (stations 1-2), LAS concentrations were below 30 μg L(-1) and the composition of their degradation intermediates (sulfophenyl carboxylic acids, SPCs) (160 μg L(-1)) was dominated by short-chain homologues (C(6)-C(9)SPCs), indicating that the degradation of this surfactant is at an advanced stage. The highest concentration (487 μg L(-1)) of SPCs was detected near the effluent outlet of a sewage treatment plant (STP) (station 12). Sampling stations (7 and 9) affected by untreated wastewater discharges were the only ones showing the presence of the most reactive and biodegradable SPC isomers and homologues (e.g. C(11)SPC). Here, LAS reached the highest concentration values measured (>2 mg L(-1)), and showed a homologue distribution closer to that of commercial mixtures than LAS found at the other stations.