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.     

A Water Quality Monitoring Network Design Methodology for the Selection of Critical Sampling Points: Part I

The principal instrument to temporally and spatially manage water resources is a water quality monitoring network. However, to date in most cases, there is a clear absence of a concise strategy or methodology for designing monitoring networks, especially when deciding upon the placement of sampling stations. Since water quality monitoring networks can be quite costly, it is very important to properly design the monitoring network so that maximum information extraction can be accomplished, which in turn is vital when informing decision-makers. This paper presents the development of a methodology for identifying the critical sampling locations within a watershed. Hence, it embodies the spatial component in the design of a water quality monitoring network by designating the critical stream locations that should ideally be sampled. For illustration purposes, the methodology focuses on a single contaminant, namely total phosphorus, and is applicable to small, upland, predominantly agricultural-forested watersheds. It takes a number of hydrologic, topographic, soils, vegetative, and land use factors into account. In addition, it includes an economic as well as logistical component in order to approximate the number of sampling points required for a given budget and to only consider the logistically accessible stream reaches in the analysis, respectively. The methodology utilizes a geographic information system (GIS), hydrologic simulation model, and fuzzy logic.     

Uncertainty based optimal monitoring network design for a chlorinated hydrocarbon contaminated site

An application of a newly developed optimal monitoring network for the delineation of contaminants in groundwater is demonstrated in this study. Designing a monitoring network in an optimal manner helps to delineate the contaminant plume with a minimum number of monitoring wells at optimal locations at a contaminated site. The basic principle used in this study is that the wells are installed where the measurement uncertainties are minimum at the potential monitoring locations. The development of the optimal monitoring network is based on the utilization of contaminant concentration data from an existing initial arbitrary monitoring network. The concentrations at the locations that were not sampled in the study area are estimated using geostatistical tools. The uncertainty in estimating the contaminant concentrations at such locations is used as design criteria for the optimal monitoring network. The uncertainty in the study area was quantified by using the concentration estimation variances at all the potential monitoring locations. The objective function for the monitoring network design minimizes the spatial concentration estimation variances at all potential monitoring well locations where a monitoring well is not to be installed as per the design criteria. In the proposed methodology, the optimal monitoring network is designed for the current management period and the contaminant concentration data estimated at the potential observation locations are then used as the input to the network design model. The optimal monitoring network is designed for the consideration of two different cases by assuming different initial arbitrary existing data. Three different scenarios depending on the limit of the maximum number of monitoring wells that can be allowed at any period are considered for each case. In order to estimate the efficiency of the developed optimal monitoring networks, mass estimation errors are compared for all the three different scenarios of the two different cases. The developed methodology is useful in coming up with an optimal number of monitoring wells within the budgetary limitations. The methodology also addresses the issue of redundancy, as it refines the existing monitoring network without losing much information of the network. The concept of uncertainty-based network design model is useful in various stages of a potentially contaminated site management such as delineation of contaminant plume and long-term monitoring of the remediation process.     

Critical Sampling Points Methodology: Case Studies of Geographically Diverse Watersheds

Only with a properly designed water quality monitoring network can data be collected that can lead to accurate information extraction. One of the main components of water quality monitoring network design is the allocation of sampling locations. For this purpose, a design methodology, called critical sampling points (CSP), has been developed for the determination of the critical sampling locations in small, rural watersheds with regard to total phosphorus (TP) load pollution. It considers hydrologic, topographic, soil, vegetative, and land use factors. The objective of the monitoring network design in this methodology is to identify the stream locations which receive the greatest TP loads from the upstream portions of a watershed. The CSP methodology has been translated into a model, called water quality monitoring station analysis (WQMSA), which integrates a geographic information system (GIS) for the handling of the spatial aspect of the data, a hydrologic/water quality simulation model for TP load estimation, and fuzzy logic for improved input data representation. In addition, the methodology was purposely designed to be useful in diverse rural watersheds, independent of geographic location. Three watershed case studies in Pennsylvania, Amazonian Ecuador, and central Chile were examined. Each case study offered a different degree of data availability. It was demonstrated that the developed methodology could be successfully used in all three case studies. The case studies suggest that the CSP methodology, in form of the WQMSA model, has potential in applications world-wide.     

基于颗粒物光量子雷达的颗粒物排放实时溯源及应用

在大气污染治理中,传统探测方式在局地大气颗粒物排放源的精准定位和实时溯源方面还有所不足。自主研发的1 550 nm波长颗粒物光量子雷达,具备探测效率高、人眼安全等特点,360°水平扫描一周仅需8.5 min。基于该雷达水平扫描监测,结合迭代拼接法和新发展的颗粒物示踪系数及污染源定位方法,可准确识别并定位出当地的污染排放源位置。对于部分污染排放定位溯源案例,结合多图展现并分析了颗粒物排放、扩散、传输、消散过程中的烟羽变化,并结合卫星图像确认了相应工业生产和建筑扬尘等典型颗粒物排放源。地面监测数据分析了部分污染源对监测站点颗粒物浓度的影响。该雷达通过低仰角、可重复性的快速扫描,结合符合颗粒物扩散规律的分析过程,在颗粒物污染实时溯源定位方面展现了极高的准确性。     

面向水源保护与污染监控的广东地下水环境监测网研究

通过系统整理分析自然资源、水利、生态环境等部门已有地下水监测网,针对广东地下水监测存在的问题和未来地下水环境管理需求,提出较大空间尺度和水质监控的地下水环境监测网建设框架及广东省"三层七级"共237个网点的层级化地下水环境监测网建设方案,并与水文地质单元、浅层地下水功能区划进行了空间叠加分析。结果表明,广东省三大部门监测网在空间上分布总体较为分散,相互补充性好,提出的监测网方案总体上与广东省地下水本底条件、地下水资源开发利用现状、地下水环境功能分区、重点污染源空间分布特征等相匹配,契合地下水饮用水源保护和重点污染源监控两大管理需求,构建的地下水环境监测网框架可为其他地区提供参考,提出的地下水环境监测网建设方案可为广东省地下水环境管理和污染防控提供决策支持。     

Spatial�Ctemporal assessment and redesign of groundwater quality monitoring network: a case study

Assessment of groundwater quality monitoring networks requires methods to determine the potential efficiency and cost-effectiveness of the current monitoring programs. To this end, the concept of entropy has been considered as a promising method in previous studies since it quantitatively measures the information produced by a network. In this study, the measure of transinformation in the discrete entropy theory and the transinformation?Cdistance (T?CD) curves, which are used frequently by other researchers, are used to quantify the efficiency of a monitoring network. This paper introduces a new approach to decrease dispersion in results by performing cluster analysis that uses fuzzy equivalence relations. As a result, the sampling (temporal) frequency determination method also recommends the future sampling frequencies for each location based on certain criteria such as direction, magnitude, correlation with neighboring stations, and uncertainty of the concentration trend derived from representative historical concentration data. The proposed methodology is applied to groundwater resources in the Tehran?CKaradj aquifer, Tehran, Iran.     

Groundwater monitoring plans at small-scale sites--an innovative spatial and temporal methodology

An innovative methodology for improving existing groundwater monitoring plans at small-scale sites is presented. The methodology consists of three stand-alone methods: a spatial redundancy reduction method, a well-siting method for adding new sampling locations, and a sampling frequency determination method. The spatial redundancy reduction method eliminates redundant wells through an optimization process that minimizes the errors in plume delineation and the average plume concentration estimation. The well-siting method locates possible new sampling points for an inadequately delineated plume via regression analysis of plume centerline concentrations and estimation of plume dispersivity values. The sampling frequency determination method recommends the future frequency of sampling for each sampling location based on the direction, magnitude, and uncertainty of the concentration trend derived from representative historical concentration data. Although the methodology is designed for small-scale sites, it can be easily adopted for large-scale site applications. The proposed methodology is applied to a small petroleum hydrocarbon-contaminated site with a network of 12 monitoring wells to demonstrate its effectiveness and validity.     

Methodology for designing air quality monitoring networks: II. Application to Las Vegas,Nevada, for carbon monoxide

An objective methodology presented in a companion paper (Liu et al., 1986) for determining the optimum number and disposition of ambient air quality stations in a monitoring network for carbon monoxide is applied to the Las Vegas, Nevada, area. The methodology utilizes an air quality simulation model to produce temporally-varying air quality patterns for each of a limited number of meteorological scenarios representative of the region of interest. These air quality patterns in turn serve as the data base in a two-step procedure for the identification and ranking of the most desirable monitoring locations (step 1) and the removal of redundancies in spatial coverage among the desired locations (step 2.)The performance of the air quality simulation model, a key element in the design methodology, was evaluated in the Las Vegas area in a special field measurement program. In the Las Vegas demonstration for carbon monoxide, 19 stations covering concentration maxima and 3 stations covering background concentrations in rural areas were identified and ranked. A 10-station network, for example, consisting of 7 stations for peak average concentrations and 3 stations for background concentrations, was selected for a desired minimum detection capability of 50% of concentration variations. Networks with fewer stations would be selected if smaller minimum detection capabilities of concentration variations are acceptable, and vice versa. Background stations could, of course, be deleted for networks with the sole purpose of discerning peak concentrations.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 Application, 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.     

A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations

There are several deficiencies in the statistical approaches proposed in the literature for the assessment and redesign of surface water-quality-monitoring locations. These deficiencies vary from one approach to another, but generally include: (i) ignoring the attributes of the basin being monitored; (ii) handling multivariate water quality data sequentially rather than simultaneously; (iii) focusing mainly on locations to be discontinued; and (iv) ignoring the reconstitution of information at discontinued locations. In this paper, a methodology that overcomes these deficiencies is proposed. In the proposed methodology, the basin being monitored is divided into sub-basins, and a hybrid-cluster analysis is employed to identify groups of sub-basins with similar attributes. A stratified optimum sampling strategy is then employed to identify the optimum number of monitoring locations at each of the sub-basin groups. An aggregate information index is employed to identify the optimal combination of locations to be discontinued. The proposed approach is applied for the assessment and redesign of the Nile Delta drainage water quality monitoring locations in Egypt. Results indicate that the proposed methodology allows the identification of (i) the optimal combination of locations to be discontinued, (ii) the locations to be continuously measured and (iii) the sub-basins where monitoring locations should be added. To reconstitute information about the water quality variables at discontinued locations, regression, artificial neural network (ANN) and maintenance of variance extension (MOVE) techniques are employed. The MOVE record extension technique is shown to result in a better performance than regression or ANN for the estimation of information about water quality variables at discontinued locations.     

Site location optimization of regional air quality monitoring network in China: methodology and case study

Regional air quality monitoring networks (RAQMN) are urgently needed in China due to increasing regional air pollution in city clusters, arising from rapid economic development in recent decades. This paper proposes a methodological framework for site location optimization in designing a RAQMN adapting to air quality management practice in China. The framework utilizes synthetic assessment concentrations developed from simulated data from a regional air quality model in order to simplify the optimal process and to reduce costs. On the basis of analyzing various constraints such as cost and budget, terrain conditions, administrative district, population density and spatial coverage, the framework takes the maximum approximate degree as an optimization objective to achieve site location optimization of a RAQMN. An expert judgment approach was incorporated into the framework to help adjust initial optimization results in order to make the network more practical and representative. A case study was used to demonstrate the application of the framework, indicating that it is feasible to conduct site optimization for a RAQMN design in China. The effects of different combinations of primary and secondary pollutants on site location optimization were investigated. It is suggested that the network design considering both primary and secondary pollutants could better represent regional pollution characteristics and more extensively reflect temporal and spatial variations of regional air quality. The work shown in this study can be used as a reference to guide site location optimization of a RAQMN design in China or other regions of the world.     

Using the polychaete Arenicola marina to determine toxicity and bioaccumulation of PAHS bound to sediments

Transportation system has contributed significantly to the development of human civilization; on the other hand it has an enormous impact on the ambient air quality in several ways. In this paper the air and noise pollution at selected sites along three sections of National Highway was monitored. Pakistan National Highway Authority has started a Highway Improvement program for rehabilitations and maintenance of National highways to improve the traffic flows, and would ultimately improve the air quality along highways. The ambient air quality and noise level was monitored at nine different locations along these sections of highways to quantify the air pollution. The duration of monitoring at individual location was 72 h. The most of the sampling points were near the urban or village population, schools or hospitals, in order to quantify the air pollution at most affected locations along these roads. A database consisting of information regarding the source of emission, local metrology and air quality may be created to assess the profile of air quality in the area.     

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.     

区域规划环评中大气环境监测点位布设研究

探讨了大气环境监测点位的布设方法,在区域规划环境影响评价布设大气监测点位时,应综合考虑开发区的功能区划分、区内产业分布及环境敏感点分布等情况;结合规划区内外现状及规划实施后重点污染源的位置及排放高度,根据区域污染气象条件,采用Gauss模式预测最大浓度落地点,并以此作为区域大气环境监测点的布设依据.对某区域开发规划案例进行了大气环境监测点位布设研究,通过实践,该布设方法不仅可以反映区域大气环境质量现状的空间分布特征,而且可以为区域大气环境预测提供良好的数据支持,为优化区域规划提供依据;同时,对规划后的污染源最大浓度落地点的监测,可以为单个项目的环境预测提供背景值,起到简化入区建设项目环评的作用.     

国家污染源监测数据管理系统构建

针对全国污染源监测数据管理和应用需求，设计了一套污染源监测数据指标集，分析了污染源排放达标评价对象及评价结果表征方法，突破了建立电子化排放标准库、数据录入全过程多层次质量控制等关键技术，并在需求分析、功能设计和技术方案选择的基础上，开发了覆盖国家、省、市3级应用的污染源监测数据管理信息软件平台，取得了很好的应用效果。     

Representative locations from time series of soil water content using time stability and wavelet analysis

The concept of time stability has been widely used in the design and assessment of monitoring networks of soil moisture, as well as in hydrological studies, because it is as a technique that allows identifying of particular locations having the property of representing mean values of soil moisture in the field. In this work, we assess the effect of time stability calculations as new information is added and how time stability calculations are affected at shorter periods, subsampled from the original time series, containing different amounts of precipitation. In doing so, we defined two experiments to explore the time stability behavior. The first experiment sequentially adds new data to the previous time series to investigate the long-term influence of new data in the results. The second experiment applies a windowing approach, taking sequential subsamples from the entire time series to investigate the influence of short-term changes associated with the precipitation in each window. Our results from an operating network (seven monitoring points equipped with four sensors each in a 2-ha blueberry field) show that as information is added to the time series, there are changes in the location of the most stable point (MSP), and that taking the moving 21-day windows, it is clear that most of the variability of soil water content changes is associated with both the amount and intensity of rainfall. The changes of the MSP over each window depend on the amount of water entering the soil and the previous state of the soil water content. For our case study, the upper strata are proxies for hourly to daily changes in soil water content, while the deeper strata are proxies for medium-range stored water. Thus, different locations and depths are representative of processes at different time scales. This situation must be taken into account when water management depends on soil water content values from fixed locations.     

基于3S技术的桂林市南溪河污染现状调查

城区小流域常是水污染较重的区域,又是污染源密集的地方,其非点源污染的监测与评估,需要实用方法。本调查基于3S技术,开展流域的监测与评价,包括空间定位的精度控制、非点源的遥感分类解译、采用排污系数对非点源污染评估、对污染源及污水管网做GIS空间分析。结合水质监测进行污径比和水环境容量的评价。重点讨论了城区人口解译方法和污染源评估方法,探讨典型城区非点源污染监测的思路。     

Tailoring groundwater quality monitoring to vulnerability: a GIS procedure for network design

Monitoring networks aiming to assess the state of groundwater quality and detect or predict changes could increase in efficiency when fitted to vulnerability and pollution risk assessment. The main purpose of this paper is to describe a methodology aiming at integrating aquifers vulnerability and actual levels of groundwater pollution in the monitoring network design. In this study carried out in a pilot area in central Italy, several factors such as hydrogeological setting, groundwater vulnerability, and natural and anthropogenic contamination levels were analyzed and used in designing a network tailored to the monitoring objectives, namely, surveying the evolution of groundwater quality relating to natural conditions as well as to polluting processes active in the area. Due to the absence of an aquifer vulnerability map for the whole area, a proxi evaluation of it was performed through a geographic information system (GIS) methodology, leading to the so called “susceptibility to groundwater quality degradation”. The latter was used as a basis for the network density assessment, while water points were ranked by several factors including discharge, actual contamination levels, maintenance conditions, and accessibility for periodical sampling in order to select the most appropriate to the network. Two different GIS procedures were implemented which combine vulnerability conditions and water points suitability, producing two slightly different networks of 50 monitoring points selected out of the 121 candidate wells and springs. The results are compared with a “manual” selection of the points. The applied GIS procedures resulted capable to select the requested number of water points from the initial set, evaluating the most confident ones and an appropriate density. Moreover, it is worth underlining that the second procedure (point distance analysis [PDA]) is technically faster and simpler to be performed than the first one (GRID?+?PDA).     

浅析污染源监督监测工作的问题和对策

从监测数据应用的角度出发,分析了当前污染源监督监测工作存在的问题。提出,应明确环境监测法律地位,加强监测能力建设;及时调整工作思路,加强污染源监督监测力度;理顺污染源在线监测系统的投入和运营机制,加快污染源在线监控技术在监督监测中的应用;快信息技术在环境监测领域的推广和应用,提高污染源评价水平。     

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.