Revising river water quality monitoring networks using discrete entropy theory: the Jajrood River experience

This paper aims at evaluating and revising the spatial and temporal sampling frequencies of the water quality monitoring system of the Jajrood River in the Northern part of Tehran, Iran. This important river system supplies 23% of domestic water demand of the Tehran metropolitan area with population of more than 10 million people. In the proposed methodology, by developing a model for calculating a discrete version of pair-wise spatial information transfer indices (SITIs) for each pair of potential monitoring stations, the pair-wise SITI matrices for all water quality variables are formed. Also, using a similar model, the discrete temporal information transfer indices (TITIs) using the data of the existing monitoring stations are calculated. Then, the curves of the pair-wise SITI versus distance between monitoring stations and TITI versus time lags for all water quality variables are derived. Then, using a group pair-wise comparison matrix, the relative weights of the water quality variables are calculated. In this paper, a micro-genetic-algorithm-based optimization model with the objective of minimizing a weighted average spatial and temporal ITI is developed and for a pre-defined total number of stations, the best combination of monitoring stations is selected. The results show that the existing monitoring system of the Jajrood River should be partially strengthened and in some cases the sampling frequencies should be increased. Based on the results, the proposed approach can be used as an effective tool for evaluating, revising, or redesigning the existing river water quality monitoring systems.     

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.     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.     

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.     

A water quality monitoring network design using fuzzy theory and multiple criteria analysis

A proper water quality monitoring design is required in a watershed, particularly in a water resource protected area. As numerous factors can influence the water quality monitoring design, this study applies multiple criteria analysis to evaluate the suitability of the water quality monitoring design in the Taipei Water Resource Domain (TWRD) in northern Taiwan. Seven criteria, which comprise percentage of farmland area, percentage of built-up area, amount of non-point source pollution, green cover ratio, landslide area ratio, ratio of over-utilization on hillsides, and density of water quality monitoring stations, are selected in the multiple criteria analysis. The criteria are normalized and weighted. The weighted method is applied to score the subbasins. The density of water quality stations needs to be increased in priority in the subbasins with a higher score. The fuzzy theory is utilized to prioritize the need for a higher density of water quality monitoring stations. The results show that the need for more water quality stations in subbasin 2 in the Bei-Shih Creek Basin is much higher than those in the other subbasins. Furthermore, the existing water quality station in subbasin 2 requires maintenance. It is recommended that new water quality stations be built in subbasin 2.     

Temporal and spatial trends in water quality of Lake Taihu,China: analysis from a north to mid-lake transect, 1991–2011

Interpretations of state and trends in lake water quality are generally based on measurements from one or more stations that are considered representative of the response of the lake ecosystem. The objective of this study is to examine how these interpretations may be influenced by station location in a large lake. We addressed this by analyzing trends in water quality variables collected monthly from eight monitoring stations along a transect from the central lake to the north in Lake Taihu (area about 2,338 km²), China, from October 1991 to December 2011. The parameters examined included chlorophyll a (Chl a), total nitrogen (TN), and total phosphorus (TP) concentrations, and Secchi disk depth (SD). The individual variables were increasingly poorly correlated among stations along the transect from the central lake to the north, particularly for Chl a and TP. The timing of peaks in individual variables was also dependent on station location, with spectral analysis revealing a peak at annual frequency for the central lake station but absence of, or much reduced signal, at this frequency for the near-shore northern station. Percentage annual change values for each of the four variables also varied with station and indicated general improvement in water quality at northern stations, particularly for TN, but little change or decline at central lake stations. Sediment resuspension and tributary nutrient loads were considered to be responsible for some of the variability among stations. Our results indicate that temporal trends in water quality may be station specific in large lakes and that calculated whole-lake trophic status trends or responses to management actions may be specific to the station(s) selected for monitoring and analysis. These results have important implications for efficient design of monitoring programs that are intended to integrate the natural spatial variability of large lakes.     

Developing an environmental water quality monitoring program for Haraz River in Northern Iran

Water quality management plans are an indispensable strategy for conservation and utilization of water resources in a sustainable manner. One common industrial use of water is aquaculture. The present study is an attempt to use statistical analyses in order to prepare an environmental water quality monitoring program for Haraz River, in Northern Iran. For this purpose, the analysis of a total number of 18 physicochemical parameters was performed at 15 stations during a 1-year sampling period. According to the results of the multivariate statistical methods, the optimal monitoring would be possible by only 3 stations and 12 parameters, including NH₃, EC, BOD, TSS, DO, PO₄, NO₃, TDS, temperature, turbidity, coliform, and discharge. In other words, newly designed network, with a total number of 36 measurements (3 stations × 12 parameters = 36 parameters), could achieve exactly the same performance as the former network, designed based on 234 measurements (13 stations × 18 parameters = 234 parameters). Based on the results of cluster, principal component, and factor analyses, the stations were divided into three groups of high pollution (HP), medium pollution (MP), and low pollution (LP). By clustering the stations, it would be possible to track the water quality of Haraz River, only by one station at each cluster, which facilitates rapid assessment of the water quality in the river basin. Emphasizing on three main axes of monitoring program, including measurement parameters, sampling frequency, and spatial pattern of sampling points, the water quality monitoring program was optimized for the river basin based on natural conditions of the study area, monitoring objectives, and required financial resources (a total annual cost of about US $2625, excluding the overhead costs).     

河流水质自动监测站选址适宜性评价

为建立和量化适于河流水质自动监测站选址的评价方法体系,提出了河流水质自动监测站选址一致性、可行性和适宜性评价问题,并建立了选址可行性和适宜性评价2套指标体系。以自动站选址与手工断面位置不一致为前提,利用累乘指数判断选址可行性,在可行的基础上利用模糊综合评价进一步分析选址的适宜性。应用案例显示,罗汉大桥断面水质自动站选址于手工断面下游150 m处是可行的,并且此选址高度适宜,在具有水质代表性的同时兼顾成本和运维管理需求。     

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.     

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.     

Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters

The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.     

Development of the microbial communities in lake donghu in relation to water quality

There is increasing recognition that protozoa is very useful in monitoring and evaluating water ecological healthy and quality. In order to study the relationship between structure and function of protozoan communities and water qualities, six sampling stations were set on Lake Donghu, a hypereutrophic subtropical Chinese lake. Microbial communities and protists sampling from the six stations was conducted by PFU (Polyurethane foam unit) method. Species number (S), diversity index (DI), percentage of phytomastigophra, community pollution value (CPV), community similarity and heterophy index (HI) were mensurated. The measured indicators of water quality included total phosphorus (TP), dissolved oxygen (DO), Chemical oxygen demand (COD), NH(4)(+), NO(2)(-) and NO(3)(-). Every month water samples from stations I, II, III, IV were chemically analyzed for a whole year, Among the chemically analyzed stations, station I was the most heavily polluted, station II was the next, stations III and IV had similar pollution degrees. The variable tendencies of COD, TP, NH(3), NO(2)(-), NO(3)(-), and DO during the year was approximately coincident among the six stations. Analysis from the community parameters showed that the pollution of station 0 was much more serious than others, and station V was the most slight. Of the community parameters, CPV and HI were sensitive in reflecting the variables of the water quality. Community similarity index was also sensitive in dividing water qualities and the water quality status of different stations could be correctly classified by the cluster analysis. DI could reflect the tendency of water quality gradient, species number and percentage of Phytomastigophora was not obvious in indicating the water quality gradient.     

Distribution of heavy metals in water and sediments of selected sites of Yamuna river (India)

The concentration of Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn metals in water and sediments of Yamuna river were determined by atomic absorption spectrophotometry in the year 1981. The data showed that there was considerable variation in the concentration of elements from one sampling station to the other which may be due to the variation in the quality of industrial and sewage wasters being added to the river at different sampling stations. The sediment samples collected from different sampling stations were also analysed for calcium carbonate, organic matter, potassium, and phosphorus.     

基于改进的多目标决策的水环境质量综合评价

在对水环境质量综合评价中,多目标决策-理想区间法解决了水环境质量评价标准是区间而非点的缺陷。但是在计算监测点到各理想区间向量的距离时,各水环境质量指标权重直接影响综合评价的结果,通常的确定方法是简单的假设各水环境质量指标的权重相等,这与实际情况相悖。为了解决这一问题,提出了将超标法用于多目标决策法中,利用超标法确定各水环境质量指标的权重,然后将其应用于多目标决策-理想区间法来分析水环境质量等级。并将改进后的多目标决策-理想区间法应用于珠江口及邻近海域的水环境中。基于超标法确定权重的多目标决策-理想区间法与聚类分析相比更有效,与等权重的多目标决策-理想区间法相比,更能体现水环境的污染状况,可应用于各种环境因子的综合评价中。     

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.     

Spatiotemporal classification of environmental monitoring data in the Yeongsan River basin, Korea, using self-organizing maps

Environmental monitoring data for planning, implementing and evaluating the Total Maximum Daily Loads (TMDL) management system have been measured at about 8-day intervals in a number of rivers in Korea since 2004. In the present study, water quality parameters such as Suspended Solids (SS), Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP) and the corresponding runoff were collected from six stations in the Yeongsan River basin for six years and transformed into monthly mean values. With the primary objective to understand spatiotemporal characteristics of the data, a methodologically systematic application of a Self-Organizing Map (SOM) was made. The SOM application classified the environmental monitoring data into nine clusters showing exclusively distinguishable patterns. Data frequency at each station on a monthly basis identified the spatiotemporal distribution for the first time in the study area. Consequently, the SOM application provided useful information that the sub-basin containing a metropolitan city is associated with deteriorating water quality and should be monitored and managed carefully during spring and summer for water quality improvement in the river basin.     

新型环境监测仪器户外小型水质自动监测站性能研究

随着中国地表水水质自动监测站建设工作的大力推进,近几年一种体积小、集成度高、功能完备并且直接应用于户外的小型水质自动监测站设备成为研发和应用热点。为了探究目前市场上户外小型水质自动监测站产品的仪器性能和技术特征,笔者选取6种型号的户外小型水质自动监测站进行功能检查和性能测试。结果表明：户外小型水质自动监测站具备采配水、预处理、水质多参数分析、数据传输等功能;不同参数标准溶液的测定结果具有较高的准确度和精密度,不进行任何维护的情况下整个系统能够在户外连续稳定运行一个星期以上。     

Selection of appropriate sampling stations in a lake through mapping

Much valuable information is obtained from water quality measurements and monitoring of lakes around the world. A powerful tool is the use of mapping techniques, as it offers potential use in water quality research. Both remote sensing techniques and traditional water quality monitoring are required to collect data at sampling stations. This study suggests another approach to determine the most appropriate distribution of sampling stations in water reservoirs that will be mapped for water quality parameters. Tests were conducted for the proposed approach for Secchi disc depth (SDD), chlorophyll-a, turbidity and suspended solids parameters in Lake Beysehir, Turkey. Results of analysis are available for a total of 30 sampling stations in August 2006. Ten sampling stations were used to model Lake Beysehir while the others were used for validation of the model. Sampling stations that offered the best representation of the lake for each parameter were determined. Then, the best representative sampling stations for all parameters in the study were determined. Moreover, in order to confirm the accuracy of these re-determined sampling stations, modelling was performed on the results of the analysis of June 2006, and it was found that the values obtained from the re-determined sampling stations were acceptable.     

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.     

Landsat and limnologically derived water quality data: A perspective

Fixed station sampling is the conventional method used to obtain data on the median water quality of reservoirs. A major source of uncertainty associated with this technique is that water quality at the fixed stations may not be representative of the ambient water quality in the reservoir at the time of sampling. This problem is particularly relevant for water quality variables such as chlorophyll, which have a markedly patchy spatial distribution. The use of Landsat reflectance data to estimate median chlorophyll concentrations in Roodeplaat Dam was investigated. A linear polynomial regression model for estimating chlorophyll concentrations from Landsat reflectance data, was firstly calibrated with chlorophyll concentration data obtained by sampling seven fixed stations on the reservoir at the time of the satellite overflight to produce an individual calibration. Secondly, the model was calibrated with a pooled set of sampled data obtained from five separate overflights, to obtain a generalised calibration.It was found that median chlorophyll concentrations determined from Landsat-derived data were similar to median chlorophyll concentrations estimated from fixed station data. However, the range of chlorophyll concentrations in the reservoir estimated from Landsat data was considerably larger than that estimated from fixed station data. Landsat derived estimates of chlorophyll concentrations have the added advantage of providing information on the spatial distribution of chlorophyll in the reservoir.