Improving real-time forecasting of water quality indicators with combination of process-based models and data assimilation technique

Water quality indicators can be used to characterize the status and quantify and qualify the change of aquatic ecosystems under different disturbance regimes. Although many studies have been done to develop and assess indicators and discuss interactions among them, few studies have focused on how to improve the predicted indicators and explore their variations in receiving water bodies. Accurate and effective predictions of ecological indictors are critical to better understand changes of water quality in aquatic ecosystems, especially for the real-time forecasting. Process-based water quality models can predict the spatiotemporal variations of the water quality indicators and provide useful information for policy-makers on sound management of water resources. Given their inherent constraints, however, such process models alone cannot actually guarantee perfect results since water quality models generally have a large number of parameters and involve many processes which are too complex to be efficiently calibrated. To overcome these limitations and explore a fast and efficient forecasting method for the change of water quality indictors, we proposed a new framework which combines the process-based models and data assimilation technique. Unlike most traditional approaches in which only the model parameters or initial conditions are updated or corrected and the models are run online, this framework allows the information extracted from observations and outputs of process models to be directly used in a data-driven local/modified local model. The results from the data-driven model are then assimilated into the original process model to further improve its forecasting ability. This approach can be efficiently run offline to directly correct and update the output of water quality models. We applied this framework in a real case study in Singapore. Two of the water quality indicators, namely salinity and oxygen were selected and tested against the observations, suggesting that a good performance of improving the model results and reducing computation time can be obtained. This approach is simple and efficient, especially suitable for real-time forecasting systems. Thus, it can enhance forecasting of water quality indictors and thereby facilitate the effective management of water resources.     

Diverse water quality responses to extreme climate events: an introduction

We synthesize and summarize main findings from a special issue examining the origins, evolution, and resilience of diverse water quality responses to extreme climate events resulting from a Chapman Conference of the American Geophysical Union (AGU). Origins refer to sequences of interactive disturbances and antecedent conditions that influence diversification of water quality responses to extreme events. Evolution refers to the amplification, intensification, and persistence of water quality signals across space and time in watersheds. Resilience refers to strategies for managing and minimizing extreme water quality impacts and ecosystem recovery. The contributions of this special issue, taken together, highlight the following: (1) there is diversification in the origins of water quality responses to extreme climate events based on the intensity, duration, and magnitude of the event mediated by previous historical conditions; (2) interactions between climate variability and watershed disturbances (e.g., channelization of river networks, land use change, and deforestation) amplify water quality ‘pulses,’ which can manifest as large changes in chemical concentrations and fluxes over relatively short time periods. In the context of the evolution of water quality responses, results highlight: (3) there are high intensity and long-term climate events, which can generate unique sequences in water quality, which have differential impacts on persistence of water quality problems and ecosystem recovery rates; and (4) ‘chemical cocktails’ or novel mixtures of elements and compounds are transported and transformed during extreme climate events. The main findings regarding resilience to extreme climate events are that: (5) river restoration strategies for reducing pollution from extreme events can be improved by preserving and restoring floodplains, wetlands, and oxbow ponds, which enhance hydrologic and biogeochemical retention, and lengthen the distribution of hydrologic residence times; and (6) the biogeochemical capacity for stream and river ecosystems to retain and transform pollution from landscapes can become “saturated” during floods unless watershed pollution sources are reduced. Finally, the unpredictable occurrence of extreme climate events argues for wider deployment of high-frequency, in situ sensors for monitoring, managing, and modeling diverse water quality responses. These sensors can be used to develop robust proxies for chemical cocktails, detect water quality violations following extreme climate events, and effectively trace the trajectory of water quality recovery in response to managing ecosystem resilience.     

The importance of validated ecological indicators for manure regulations in the Netherlands

The termination of the EU milk quota system on April 1, 2015 is leading to an increase in manure production in the Netherlands. Rather than focus on the quality of water and nature, of which at least the water quality has strongly improved during the last decades, discussions appear to center on strengthening proxy measures that are already being used and which are only remotely related to the quality issue. The quality of water and nature is determined for ground- and surface water by first measuring their N and P content and for nature areas the N deposition. When these values are higher than threshold values determined by ecologists, quality is inadequate and measures are needed. When values are lower, quality is adequate. Three basic problems need to be addressed: (i) threshold values are in practice considered to be permanent while they should be dynamic reflecting a learning process when comparing measurements of N and P values on the one hand and a simultaneous ecological characterization on the other. This requires more cooperation between soil scientists, hydrologists and ecologists. Dynamic characterization may well lead to locally different threshold values. (ii) many measurements of water quality are being made but hardly any measurements of N deposition on nature areas. Such measurements are needed to allow judgements as to the effect of agricultural practices on nature quality. (iii) The necessary further improvement in water and nature quality, as far as it is affected by agricultural practices, can only be achieved when farmers are fully committed and engaged. The current top-down regulations with a “command-and-control” character, while effective in the 1990s, cannot serve this purpose in the information age, the more so since farmers are increasingly well educated and ask too many questions that are not being answered. The suggestion is made to change the generic character of the legislation (“one size fits all”) to a system where “tailor made” management systems are designed for individual farms,considering environmental conditions in the area where the farm occurs. Researchers and farmers can work together in a joint-learning mode to develop such designs that can be recognized by certificates with a legal status. In any case, the proportionality principle needs to be considered assuring that the severity of measures taken are in balance with societal effects.     

A method to prioritize and monitor wetland restoration for water-quality improvement

Wetland restoration can improve water quality by reducing concentrations of sediment, total phosphorus, and nitrate in runoff. Managers need a simple method to choose among many possible restoration sites, particularly in large agricultural basins covering thousands of square kilometers. The purpose of this paper is to outline a method for prioritizing and monitoring wetland restoration sites in light of the factors that affect water-quality improvement by wetlands. These factors are categorized as loading factors, path factors, and process factors. The method for prioritizing wetland restoration sites depends primarily on assessing the potential effectiveness of the wetland for improving water quality. Three types of effectiveness are considered: problem effectiveness (is the site in an area with known water-quality problems?), function effectiveness (is the site likely to improve water quality more or less than other sites?), and information effectiveness (does the site fit within an overall research plan to gain information on how wetlands improve water quality?). The variables of hydraulic residence time, hydraulic flux, and wetland area, volume, and average depth are combined into a single variable termed and used as a proxy for estimating the relative function effectiveness of potential restoration sites. Monitoring restoration sites is targeted at establishing a minimum data set that can be collected consistently at different sites over time, and that can be used for inter-site comparison with simple statistical techniques. The Minnesota River Basin is used as an example throughout to demonstrate the types of data that are available to plan wetland restoration. While this paper focuses on the water-quality benefits, wetland restoration should be a multi-disciplinary effort to integrate other benefits of restoration, such as improvement of wildlife habitat and flood abatement.     

Looking Upstream: Findings from Focus Groups on Public Perceptions of Source Water Quality in British Columbia,Canada

In association with the development of new microbial tests for source water quality (SWQ), focus groups with members of the public were conducted to gain insight into their perceptions of SWQ, behaviours and contaminants they think pose the greatest threat to its quality, and what/how they want to know about SWQ. Discussions revealed a low concern about SWQ in general, and in particular about microbial contamination. Participants identified behaviours that threaten SWQ, barriers to changing behaviour and suggestions for inducing change. A strong desire was expressed for water quality information to be interpreted and communicated in terms of how SWQ may impact human health and how their actions should be altered in response to test results. The information can be used to inform communication strategies and possibly impact policies associated with water quality testing and implementation of new tests. More broadly, awareness of the public’s understanding and beliefs about source water can be used in working with the public to adopt water-friendly behaviours, influence the content and methods of communicating with the public about water issues and water quality, and could contribute to the direction of future research and investment into water technologies to align with the public’s priorities.     

Interacting Coastal Based Ecosystem Services: Recreation and Water Quality in Puget Sound,WA

Coastal recreation and water quality are major contributors to human well-being in coastal regions. They can also interact, creating opportunities for ecosystem based management, ecological restoration, and water quality improvement that can positively affect people and the environment. Yet the effect of environmental quality on human behavior is often poorly quantified, but commonly assumed in coastal ecosystem service studies. To clarify this effect we investigate a water quality dataset for evidence that environmental condition partially explains variation in recreational visitation, our indicator of human behavior. In Puget Sound, WA, we investigate variation in visitation in both visitation rate and fixed effects (FE) models. The visitation rate model relates the differences in annual recreational visitation among parks to environmental conditions, park characteristics, travel cost, and recreational demand. In our FE model we control for all time-invariant unobserved variables and compare monthly variation at the park level to determine how water quality affects visitation during the summer season. The results of our first model illustrate how visitation relates to various amenities and costs. In the FE analysis, monthly visitation was negatively related to water quality while controlling for monthly visitation trends. This indicates people are responding to changes in water quality, and an improvement would yield an increase in the value of recreation. Together, these results could help in prioritizing water quality improvements, could assist the creation of new parks or the modification of existing recreational infrastructure, and provide quantitative estimates for the expected benefits from potential changes in recreational visitation and water quality improvements. Our results also provide an example of how recreational visitation can be quantified and used in ecosystem service assessments.     

大亚湾水质遥感监测指标分析

我国沿海经济高速发展,对近海岸水质环境影响极大。传统的近海岸水质监测手段不仅成本大,而且空间信息有限,难以对相关海域进行全面、准确的监测与评价;利用遥感的手段进行近海岸水质监测可克服这些局限。利用遥感进行水质评价,需要建立相应的指标体系。论文以大亚湾为例,分析了大亚湾的水质环境现状,讨论了具有光学敏感性或热敏感性的水质因子特性,指出水温、悬浮物及叶绿素是大亚湾水质遥感监测与评价的首选指标。讨论了悬浮物、叶绿素的污染表征物特征,以及在近海岸、湖泊及河流水质研究中的重要指示意义,同时建议将叶绿素作为常规监测指标纳入我国海水水质评价体系。     

Limnological research can improve and reduce the cost of monitoring and control of water quality

An evaluation of the programmes for control and monitoring of water quality in Sweden has demonstrated many short-comings. This paper discusses how improvements can be achieved by using new limnological knowledge.High-frequency sampling and analysis of mixed samples gives reliable average values with reduced costs. Strong correlations between, for instance, summer average values and summer maximum values, can be used for predicting the worst possible situation, which would be difficult to analyse by low-frequency sampling. Phosphorus load and lake response relationships are valuable tools for lake management and for establishing water quality criteria in physical planning. Future control may be further improved if limnological research gives better information on relationships between structure and function of aquatic ecosystems in relation to the form and size of the water body, water flushing rate, inputs from watershed and air space, etc.     

土壤质量与土壤质量指标及其评价

土壤作为一种重要的自然资源可以为人类生产食物和纤维,并维持地球生态系统.土壤也是植物生长的媒介、水、热和化合物的源、水分的过滤器和废物分解的生物介质.土壤与水、气和植物互作并抑制环境的波动.土壤可以调节很多控制水气质量和促进植物生长的生态过程.土壤质量概念的引入使我们更全面地理解土壤,也有助于合理地使用和分配劳力、能源、财政和其它投入.土壤质量也提供了一个通用的概念使得专业人员、生产者和公众明白土壤的重要性.此外,它也是一个评价管理措施和土地利用变化对土壤影响的评价工具.土壤质量由土壤的物理、化学和生物性质组成,MDS已被科学家们提出用于土壤质量评价.国际上比较常用的评价方法主要有多变量指标克立格法、土壤质量动力学方法、土壤质量综合评分法和土壤相对质量法.人类对土地不和谐地利用和管理可以导致全球生物地球化学循环发生改变和加快土壤性质变化的速度,当前世界各地土壤退化相当严重,已日益威胁到人类赖以生存的土地资源.在探讨相关概念的基础上综述了近年来土地利用变化对土壤理化质量和生物质量的影响进展,以引起国内外学者对土地利用变化对土壤质量影响研究的重视,从而为探讨土地利用对土壤质量影响的机理和规律以及退化土地的恢复和区域土地资源管理以及土地的持续利提供理论依据.土壤质量未来的研究应该集中在土壤质量指标与评价方法;土壤质量变化的发生条件、过程、影响因素及其作用机理与时空规律性;尺度问题的研究;土壤质量保持与提高的途径及其关键技术研究.     

飞来峡水库水质现状及其向广州供水能力的探讨

水库供水(特别是对城市的供水)已成为缓解全球水资源供给不足的重要途径。于2001年至2003年的丰水期和枯水期调查分析了新建河流型水库-飞来峡水库的水质、浮游植物群落特征和营养状态。结果表明飞来峡水库水质良好,多数水质指标为地表水Ⅱ水质标准,其营养盐浓度、浮游植物的密度均较低,属于贫中营养。从近几年的水质变化来看,建库后,水质改善明显。通过对广州市饮用水源水水质现状及存在问题的分析,从水质和水量两方面探讨了飞来峡水水库作为广州优质水源地的优势。由于来水量大,水库水质净化能力强,飞来峡水库水质和水量均有保证,可作为广州市重要水源地之一。但今后,在流域管理和水土保持工作更应重视和加强。     

河流水质的景观组分阈值研究进展

土地利用/覆被变化产生的区域生态环境负面效应已引起国内外研究者的广泛关注,其中,河流水质对景观组分变化的响应已在区域及更大尺度的研究中,成为热点。探讨河流水质的景观组分阈值,可以弥补非点源污染研究在区域尺度上的景观变化影响水质问题研究中的不足,而这是当前流域水环境管理及土地利用规划与管理的主要依据之一。从景观组分指数与水质指标出发,分析了当前研究的常用指标,认为:具有明确物理意义的景观组分指数,如不透水表面指数、植被指数等,受到水质的景观组分阈值研究的青睐;在水质指标中,水化学指标应用最为广泛,同时,表征水生生态系统条件的如生物类指标、综合生物类与非生物类指标,也逐渐受到重视,方兴未艾。尽管河流水质的景观组分阈值是当前的研究重点,但在区域以及更大尺度上,阈值的差异较大。在今后的研究中,水质退化的景观组分阈值还需在研究尺度、水质指标及阈值标准等问题上进一步深化,而景观格局指数的应用将会促进对水质退化受景观组分空间配置影响的研究。对水质的景观组分阈值研究进行综述,可以为区域尺度上开展水质保护、流域水环境管理及土地利用规划提供前沿信息。     

Development and Applications of Five New Water Quality Indices

Two indices, P₁ and I, employing ranked data and following the beta distribution, are described. These indices, which are true statistical measures of water quality, can be used with any set of parameters. Further, these indices correlate highly with biological and subjective-engineering assessments of water quality. Three indices, employing raw data and based on the chi-square distribution, are described. Two of these, B₁ and B₂, do not have sufficient discrimination to serve as general measures of water quality, although they have use in specific circumstances. The index C has been found to be a measure of excessive variability (at a station), and can be used to quantitatively compare the (data) variability among stations. The five indices described here are evaluated against a set of operational criteria which a mathematically sound index should meet.     

Rationale and Procedures for Using the Tissue-Residue Approach for Toxicity Assessment and Determination of Tissue,Water, and Sediment Quality Guidelines for Aquatic Organisms

This article describes a set of procedures for developing tissue, water, and sediment quality guidelines for the protection of aquatic life by using the tissue-residue approach (TRA) for toxicity assessment. The TRA, which includes aspects of the Critical Body Residue (CBR) approach, associates tissue concentrations of chemicals with adverse biological effects in a dose-response fashion that can be used to determine CBRs. These CBRs can then be used to develop tissue quality guidelines (TQGs), which may be translated into water or sediment guidelines with bioaccumulation factors. Not all toxicants are amenable to this type of analysis; however, some appear to exhibit relatively consistent results that can likely be applied in a regulatory framework. By examining tissue residues, variations in toxicokinetics (temporal aspects of accumulation, biotransformation, and internal distribution) are greatly reduced allowing a greater focus on toxicodynamics (action and potency) of the toxicants. The strongest feature of this approach is causality; hence, guidelines based on tissue concentrations are based on data demonstrating a causal relationship between the acquired dose and the biological effect. Because the TRA has utility for assessing the toxicity of contaminant mixtures, an approach is presented here using toxic unit values that can be used to assess the likelihood of observing toxic effects based on tissue residues.     

A simple trickle chamber for rearing aquatic invertebrates

A chamber for laboratory rearing of aquatic invertebrates is described. The animals are reared in plastic dishes, through which a recirculating water volume is passed. The design ensures identical water quality in a high number of parallels. The chamber is constructed for rearing the freshwater amphipod Gammarus pulex, but can be used in studies of growth, reproduction etc. of other aquatic invertebrates as well.     

不同地貌条件下景观对河流水质的影响差异

景观对河流水质的影响在不同地区、不同空间尺度上存在差异。以赤水河流域为研究对象,根据地貌特征将研究区分为喀斯特地貌和非喀斯特地貌,在划分的29个子流域内采集测试水质数据,所选用的水质指标有溶解氧(DO)、电导率(EC)、总氮(TN)和总磷(TP),运用空间分析及数理统计方法,分析流域内不同地貌区景观之间的差异,探究不同空间尺度上景观与水质指标之间的关系。结果表明:(1)流域内景观组成以林地和灌草为主,建设用地和耕地次之,景观组成在不同地貌区各空间尺度上存在差异。建设用地和耕地对水质具有负面影响,且在碳酸盐岩地区更显著;林地对水质具有正面影响;灌草对水质的影响相对复杂。(2)流域内水质表现为碳酸盐岩地区优于碎屑岩地区。景观破碎化指数与总氮(TN)、总磷(TP)呈正相关,是水质变化的重要影响因素;景观聚集度指数与溶解氧(DO)呈正相关;景观破碎化指数和景观聚集度指数与电导率(EC)的关系在两个地区呈相反的结果。(3)不同地貌区景观对河流水质具有不同程度的影响。在两个地区,景观组成对河流水质解释能力最大空间尺度均为河岸带尺度,解释率分别为53.4%和59.1%;景观格局对河流水质解释能力最大...     

纤毛原生动物研究的经济意义

纤毛原生动物与人们日常生活息息相关,具有重要的科学研究意义和社会经济价值。纤毛原生动物不仅可以监测与净化水体,维持反刍动物瘤胃的内环境稳定,促进土壤生态系统的平衡,还可以作为海洋抗菌活性物质及遗传学研究的材料。通过将其在以上各方面的应用价值进行初步的探讨性总结,以期得到人们更多的重视。     

Application of an unsupervised artificial neural network technique to multivariant surface water quality data

Surface water contamination from agricultural and urban runoff and wastewater discharges from industrial and municipal activities is of major concern to people worldwide. Classical models can be insufficient to visualise the results because the water quality variables used to describe dynamic pollution sources are complex, multivariable, and nonlinearly related. Artificial intelligence techniques with the ability to analyse multivariant water quality data by means of a sophisticated visualisation capacity can offer an alternative to current models. In this study, the Kohonen self-organising feature maps (SOM) neural network was initially applied to analyse the complex nonlinear relationships among multivariable surface water quality variables using the component planes of the variables to determine the complex behaviour of water quality parameters. The dependencies between water quality variables were extracted and interpreted using the pattern analysis visualised in component planes. For further investigation, the k-means clustering algorithm was used to determine the optimal number of clusters by partitioning the maps and utilising the Davies–Bouldin clustering index, leading to seven groups or clusters corresponding to water quality variables. The results reveal that the concentrations of Na, K, Cl, NH₄-N, NO₂-N, o-PO₄, component planes of organic matter (pV), and dissolved oxygen (DO) were significantly affected by seasonal changes, and that the SOM technique is an efficient tool with which to analyse and determine the complex behaviour of multidimensional surface water quality data. These results suggest that this technique could also be applied to other environmentally sensitive areas such as air and groundwater pollution.     

Water Resources in Life-Cycle Impact Assessment: Considerations in Choosing Category Indicators

Water is one of many resources, wastes, and pollutants considered in life-cycle assessment (LCA). The widely used indicator for water resources, the total input of water used, is not adequate to assess water resources from a sustainability perspective. More detailed indicators are proposed for water resources in two areas essential to water sustainability: water quantity and water quality. The governing principles for a consideration of water quantity are that (1) the water sources or LCA inputs are renewable and sustainable and (2) the volume of water released or LCA outputs are returned to humans or ecosystems for further use downstream. The governing principle for a consideration of water quality is that the utility of the returned water is not impaired for either humans or ecosystems downstream. Water quantity indicators are defined for water use, consumption, and depletion to reveal the sustainable or nonsustainable nature of the sources. A flexible set of water quality indicators for various factors that may impair water quality are then discussed, including the LCA study choices, technical challenges, and trade-offs involved with such indicators. Indicator selection from this set involves the underlying concern or endpoint represented by the indicator and the level and accuracy of decision-making information that the indicator must provide. With significant differences in emissions among systems studied using LCA and different purposes of the LCA studies themselves, a single, default set of water quality indicators applicable to all systems studied with LCA is problematic. The proposed water quantity and quality indicators for LCA studies are also intended to be compatible with environmental management and reporting systems so that data needs are not duplicated and interpretation for one does not contradict or sow confusion for the other.