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.     

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.     

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.     

Uncertainty in watershed response predictions induced by spatial variability of precipitation

Negligence to consider the spatial variability of rainfall could result in serious errors in model outputs. The objective of this study was to examine the uncertainty of both runoff and pollutant transport predictions due to the input errors of rainfall. This study used synthetic data to represent the “true” rainfall pattern, instead of interpolated precipitation. It was conducted on a synthetic case area having a total area of 20 km² with ten subbasins. Each subbasin has one rainfall gauge with synthetic precipitation records. Six rainfall storms with varied spatial distribution were generated. The average rainfall was obtained from all of the ten gauges by the arithmetic average method. The input errors of rainfall were induced by the difference between the actual rainfall pattern and estimated average rainfall. The results show that spatial variability of rainfall can cause uncertainty in modeling outputs of hydrologic, which would be transport to pollutant export predictions, when uniformity of rainfall is assumed. Since rainfall is essential information for predicting watershed responses, it is important to consider the properties of rainfall, particularly spatial rainfall variability, in the application of hydrologic and water quality models.     

Characterizing Small Subbasins: A Case Study from Coastal Oregon

A fine-grained statisticaly robust probability sample of stream segments is used to compare two small (20,000 hectare) subbasins of the Tillamook watershed, north coastal Oregon. The two subbasins are matched with respect to several variables [size coastal climates], but vary in terms of geology and consequently land use. A total of 67 wadeable + non-wadeable sizes were identified for sampling in the two subbasins (combined) over two field seasons from a sampling universe consisting of the River Reach File 3 (blue lines on 1:100,000 maps). Target variables include an extensive array of physical habitat endpoints, selected water chemistry endpoints, species composition, and relative abundance of both benthic macroinvertebrates and fish. Field protocols generally followed those of the U.S. EPA's Environmental Monitoring and Assessment Program (EMAP).Eleven fish species were encountered, a typically low number for coastal Oregon streams. Exploratory analysis using nonmetric multidimensional scaling revealed that 92.4% of the variation in the fish assemblages could be explained with two ordination axes. Environmental factors related to stream size and substate were the most correlated to these axes. Further, stream segments for the two subbasins tended to map in different areas of species space. Therefore, we also give unweighted probability distributions for several of the factors that heavily on these two axes by subbasins, as well as probability distributions for chemical endpoints. Results from the subset of sites sampled during the first year (21 wadeable sites) reveal: 1) differences between samples from the two subbasins relates to dream size and substrate composition that are consistent with known differences in geology and land use, 2) unexpectedly minor differences between samples from the two subbasins for stream temperature, canopy cover, and dissolved oxygen, 3) differences between samples from the two subbasins for total P, and total N, possibly related to land use, and 4) unexpected differences in samples from the two subbasins for conductivity, probably related to geological factors. Sample size for each subbasin is low and therefore our samples cannot be taken to necessarily characterize either subbasin. However, our findings are consistent with a comprehensive assessment that had been previously produced for one of the two subbasins.All field work was completed in 8 weeks 3-person field crew. We conclude that rapid assessment protocols, based on probability samples at this level of resolution, can be a cost-effective approach to watershed analysis. This approach should be seen as a complement to, rather than a replacement for, systematic surveys that produced finer scale, reach specific information on factors such as channel complexity and cover relevant to in-stream restoration planning.     

Methodology for designing air quality monitoring networks: I. Theoretical aspects

An objective methodology is presented for determining the number and disposition of ambient air quality stations in a monitoring network for the primary purpose of compliance with air quality standards. The methodolgy utilizes a data base with real or simulated data from an air quality dispersion model for application with a two-step process for ascertaining the optimal monitoring network. In the first step, the air quality patterns in the data base are collapsed into a single composite pattern through a figure-of-merit (FOM) concept. The most desirable locations are ranked and identified using the resultant FOM fields. In the second step the network configuration is determined on the basis of the concept of spheres of influence (SOI) developed from cutoff values of spatial correlation coefficients between potential monitoring sites and adjacent locations. The minimum number of required stations is then determined by deletion of lower-ranked stations whose SOIs overlap. The criteria can be set to provide coverage of less than some fixed, user-provided percentage of the coverage of tha SOIs of the higher ranked stations and for some desired level of minimum detection capability of concentration fluctuations.The methodology is applied in a companion paper (McElroy et al., 1986) to the Las Vegas, Nevada, metropolitan area for the pollutant carbon monoxide.Although the research described in this article has been funded wholly or in part by the United States Environmental Protection Agency through Contract No. 68-03-2446 to Systems Applications, Inc., it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.     

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.     

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.     

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.     

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.     

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.     

美国EPA地表水质监测与评估的点位设计介绍

介绍了美国EPA地表水质监测与评估的点位设计。首先,指导性文件《基本水质监测方案》中的环境监测计划要求建立1个不少于1 000个点位的国家地表水质环境监测网,并提出了点位设计的标准,包括4点基本要求和针对每一类水域的具体要求。其次,另一指导性文件《准备州综合水质评估(305b报告)和电子升级:报告内容的准则》提出了1种新的对水质的综合性评估技术,要求在传统的判断点位设计的基础上增加概率统计点位设计方法。最后,全国一致的概率统计点位设计是相当有效的获知全国范围的水质情况及变化趋势的方法,EPA完全支持通过这种概率统计点位设计的方法来评估更多的水质状况。概率统计点位设计是EPA地表水质监测与评估的点位设计的发展趋势。     

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.     

主分量分析法在环境空气监测数据分析中的应用

根据西宁市13个环境空气监测站点2013—2017年大气污染物细颗粒物(PM2. 5)、可吸入颗粒物(PM10)、二氧化硫(SO_2)、二氧化氮(NO_2)、臭氧最大8 h平均(O_3-8h)和一氧化碳(CO)的监测数据,采用主分量分析法对西宁市环境空气质量进行了综合评估。结果表明,2013—2017年西宁市大部分环境空气监测站点周边环境空气质量逐渐提升,4个国控站综合得分(F)趋势变化幅度较大,其周边环境空气质量状况改善较为明显;城南新区、湟源县气象局和西钢监测站点周边环境空气质量呈逐年下降趋势,与其附近工业生产有关。     

国家水环境质量监测网络发展历程与展望

阐述了水环境质量监测的定义和目的，介绍了构成国家水环境质量监测网络的6个子网，即地表水环境质量监测网、地表水环境质量自动监测网、地下水环境质量监测网、饮用水源地环境质量监测网、水污染防治专项规划水体环境质量监测网和锰三角地区水环境质量监测网的发展历程与现状。指出了目前该网络存在的不足，提出建立水环境质量监测网络设计技术体系、扩大监测网覆盖面、扩展监测项目等建议。     

滨海新区地表水水质评价与污染源分析

滨海新区在大力发展工业的同时,面临水资源紧缺与水环境恶化等问题,基于2020年至2021年滨海新区内15个监测站位的丰水期、枯水期实测数据,通过改进型加拿大水质指数模型对滨海新区地表水进行水质评价,在水质评价的基础上,利用相关性分析与绝对主成分-多元线性回归模型分析影响地表水水质状况的污染源。15个水质监测站位水质评价结果表明：丰水期水质指数为32.27～82.80,良好水质站位1个,中等水质站位6个,较差水质站位7个,差等水质站位1个;枯水期水质指数为47.28～81.36,良好水质站位1个,中等水质站位12个,较差水质站位2个。污染源分析结果表明：丰水期中,污染源为生活污水、农业面源污染、养殖尾水点源污染;枯水期中,主要污染源为工业废水、生活污水、养殖尾水面源污染。     

水质自动监测站的运行管理与水质预警

水质自动监测站在环境管理中发挥着重要的作用,结合东台市环境监测站水质自动监测站的运行实践,客观地分析了水站运行中的存在问题,提出建立科学的管理方式,确保运行经费的投入,建立畅通的信息响应和预警机制,加强基层站对水质自动监测数据的应用以及上下游信息共享等建议。     

Siting analyses for water quality sampling in a catchment

Pollution loads discharged from upstream development or human activities significantly degrade the water quality of a reservoir. The design of an appropriate water quality sampling network is therefore important for detecting potential pollution events and monitoring pollution trends. However, under a limited budgetary constraint, how to site an appropriate number of sampling stations is a challenging task. A previous study proposed a method applying the simulated annealing algorithm to design the sampling network based on three cost factors including the number of reaches, bank length, and subcatchment area. However, these factors are not directly related to the distribution of possible pollution. Thus, this study modified the method by considering three additional factors, i.e. total phosphorus, nitrogen, and sediment loads. The larger the possible load, the higher the probability of a pollution event may occur. The study area was the Derchi reservoir catchment in Taiwan. Pollution loads were derived from the AGNPS model with rainfall intensity estimated using the Thiessen method. Analyses for a network with various numbers of sampling sites were implemented. The results obtained based on varied cost factors were compared and discussed. With the three additional factors, the chosen sampling network is expected to properly detect pollution events and monitor pollution distribution and temporal trends.     

Evaluation of violations in water quality standards in the monitoring network of São Francisco River basin,the third largest in Brazil

The São Francisco River is the largest river located entirely within Brazil, and water scarcity problems have been a major concern of Brazilian society and government. Water quality issues are also a concern and have worsened with the recent intensification of urbanization and industrialization. In this study, violations to water quality standards established by local legislation were calculated as a percentage for 26 selected parameters over a monitoring period of 14 years. The violation percentages were analyzed spatially using the Kruskal-Wallis test, followed by multiple comparison analysis. Temporal analysis was performed using the Mann-Kendall test and Spearman correlation. Some parameters could be identified as cause for concern due to high violation levels, such as the fecal coliform indicator (FCI) and phosphorus—both related to domestic and effluent disposal without treatment or with insufficient treatment—and color, turbidity, manganese, and total suspended solids—which can be affected by erosive processes of natural and anthropogenic causes. The study found that these violations are concentrated in the most urbanized and industrialized areas of the basin. Some metallic parameters, such as iron and arsenic violations, may be related to mining activities in the rich soil of the Iron Quadrangle area located within the Minas Gerais State. Trend analysis results indicated that most monitoring stations did not have significant modification (elevation or reduction) trends over time, which, together with the high violation percentages, might indicate the maintenance of a scenario of constant pressure upon water resources, in particular in those more urbanized areas.