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。     

长江水环境质量监测网络运行体系初步构建

为精准、客观、全面评价长江水环境质量和支撑长江大保护,通过研究制定一系列管理制度和技术规范,以优化调整的水环境质量监测网络为基础,建立了涉及管理制度、监测技术、质量控制和数据审核等方面的水质自动监测与采测分离手工监测相结合的网络运行机制。研究自动与手工监测的总磷前处理方式,实现了自动与手工监测数据的匹配和融合,并将融合数据应用于长江水环境质量评价、预警、考核与排名,实现了长江水环境质量监测网络的业务化运行。     

江苏省设区市生态环境监测监控规划关键问题研究

生态环境监测是生态文明建设的重要支撑。在设区市级环境监测监控能力普遍较弱、生态环境保护压力巨大的双重背景下,编制设区市生态环境监测监控规划具有重要意义。在调查了江苏省部分设区市环境监测监控规划的基础上,总结了规划编制在监测监控网络建设、监测监控能力建设、质量管理、大数据应用建设、人才队伍建设等方面的主要内容,针对规划中普遍存在的组织架构不清晰、特色发展定位不明确、环境监测监控融合发展谋划不足、项目建设可行性论证不够等关键问题,提出应理顺组织架构、明确特色发展定位、加强环境监测监控一体化发展谋划、加强项目建设可行性论证等对策建议,以期为今后的规划编制工作提供相关借鉴。     

新疆水环境质量监测现状、问题及对策

水环境质量监测是环境质量监测的重要组成部分，其任务是说清区域水环境质量现状、问题及变化趋势，为环境管理决策提供依据。本文简要介绍了新疆环保系统的水环境质量监测工作现状及存在问题，并提出了相应的对策建议，以期为进一步改进新疆水环境质量监测与管理工作提供参考。     

辽河干流水环境质量监测网络优化研究

通过构建适宜度方法对水环境质量监测网络优化方法进行定量筛选,并以辽河干流为研究区进行水环境监测网络优化方法的筛选、应用和优化结果验证。结果表明,通过适宜度方法的定量筛选,最优分割法更适宜于辽河干流水环境监测网络的优化,优化后辽河干流水环境监测网络由8个断面优化为4个断面。采用T检验和F检验对优化结果验证,优化后的监测网络能很好地代表原监测网络,且相邻断面监测数据相关率降低,监测网络合理性得到提高。     

流域水环境监测质量管理系统设计与实现

目前的水环境监测工作需要建立统一的水环境监测质量管理系统,这对于各级、各地水环境监测质量控制信息的规范化录入和分级汇总统计、信息共享具有重要的意义.在分析目前水环境监测质量管理存在问题的基础上,基于网络服务、地理信息等技术,设计实现了水环境监测质量管理系统.利用该系统,各级、各地水环境监测质量管理部门能够进行监测机构、持证人员、监测项目、仪器设备等信息的录入和定期维护,同时共享监测方法、政策法规、标准规范、标准物质等信息.同时上级管理部门能够查看、统计所辖部门的水环境监测质量控制信息,从而为流域水环境突发事件应急资源调配、辅助决策等提供信息支撑.     

开展水质手工监测质量核查工作的思考

水环境质量监测数据是客观评价水质状况、反映水污染防治成效、实施水环境管理与决策的基本依据。提高水环境监测数据质量，是建立科学制定水生态环境治理政策的重要前提，是实现生态环境治理体系和治理能力现代化的内在需要，也是深入打好碧水保卫战、提高政府公信力、维护公众环境权益的有力保障。然而，目前新疆水环境质量监测工作尚存在许多亟待完善的问题，监测数据失真现象时有发生，导致监测结果难以客观真实反映新疆水环境质量实际状况。为了加强水环境质量监测的监督管理，本文分析了新疆水环境质量监测工作存在的问题以及开展水质手工监测质量核查工作的必要性，并对如何开展水质手工监测质量核查进行了深入探讨。     

日本水环境质量监测管理概述

伴随着日本经济的高速发展,其水环境污染问题十分严峻,防治水污染成为日本政府在20—21世纪的重要工作之一。经过几十年的努力,日本水污染治理取得长足进展。目前日本水环境监测已经形成由水和土壤等方面组成的水循环监测体系,包括地表水、近海、湖泊、地下水和土壤等。在日本的重要环保法律法规中均有涉及水环境监测工作内容的明确法律条文,国家行政机关、地方政府和公立的科研单位在具体实施水环境质量监测过程中的职责和义务不同,水环境质量监测管理的国家行政机关以环境省为主,地方政府根据环境省制定的水环境质量标准、监测技术方法及规范,制定所辖地域的监测方案并实施监测,公立的环境科研机构在环境质量监测工作中起到重要的支撑作用。笔者概述了日本开展水环境质量监测的法律依据和监测管理情况等。     

太湖梅梁湾水环境监控预警体系研究

从水质预警站、实验室深度分析和蓝藻遥感监测等技术集成，监控预警模型构建，监控预警体系建立，应急响应工作 机制等方面介绍了太湖梅梁湾水环境监控预警系统的研究，为太湖流域水环境监控预警提供示范。     

京津冀协同发展背景下地表水环境监测路径研究

在京津冀协同发展与环境监测体制改革新形势下,结合京津冀区域海河流域特点,从监测网络建设、技术指标体系构成、新技术应用和区域合作等方面,分析了该区域地表水环境质量监测现状、面临的新形势与新任务,提出了进一步整合优化区域水环境监测网络,加快监测技术体系尤其是质量保证体系和评价体系的建设,提高监测工作规范化、标准化程度和监测数据质量等建议。     

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.     

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).     

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.     

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).     

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.     

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.     

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin,Brazil

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008–2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.     

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.     

Application of water quality indices and analysis of the surface water quality monitoring network in semiarid North-Central Chile

Surface water quality has increasing importance worldwide and is particularly relevant in the semiarid North-Central Chile, where agriculture and mining activities are imposing heavy pressure on limited water resources. The current study presents the application of a water quality index in four watersheds of the 29°-33°S realm for the period 1999-2008, based on the Canadian Council of Ministers for the Environment approach and the Chilean regulation for irrigation water quality. In addition, two modifications to the index are tested and a comprehensive characterization of the existing monitoring network is performed through cluster analysis. The basins studied show fairly good water quality in the overall, specially the Limarí basin. On the other hand, the lower index values were obtained for the headwaters of Elqui, associated with the El Indio mining district. The first modification of the indicator (i.e., to consider parameters differentially according to their effect on human health or the environment) did not produce major differences with respect to the original index, given the generally good water quality. The second modification (i.e., to consider as threshold values the more restrictive figures derived from a set of regulations) yielded important differences in the indicator values. Finally, an adequate characterization of the monitoring network was obtained. The results presented spatial coherence and the information can be used as a basis for the optimization of the monitoring network if required.