Development and Evaluation of a Regulatory Model for Pesticides in Flooded Applications

The pesticides in flooded applications model (PFAM) is a regulatory model for government agencies and others interested in estimating water concentrations of pesticides used in flooded agriculture applications such as rice paddies and cranberries bogs. PFAM was designed around the specific parameters that are typically available for a pesticide risk assessment, thereby simplifying the model and allowing the user to concentrate on only the most relevant model inputs. The model considers the fate properties of pesticides and allows for the specifications of typical flooded agriculture management practices such as scheduled water releases and refills. It also allows for natural water-level fluctuations resulting from precipitation and evapotranspiration. Model quality assurance requirements for regulatory models aimed at protecting the public are that the models err on the high side of measured data and at the same time should not cause undue burden to stakeholders by being overly conservative. For the studies herein, PFAM did tend to err on the high side of the data yet provided more realistic estimates than the currently used methods, which thereby reduced stakeholder burden. As is also important for a regulatory model, PFAM is nonproprietary and freely available.     

Impact of phosphorus load reduction on water quality in a stratified reservoir-eutrophication modeling study

Monitoring data collected from the Mingder Reservoir in Taiwan indicate that the water quality is between mesotrophic and eutrophic. Chlorophyll a concentration is higher in the summer and anoxic conditions occur in the bottom. The data also reveal that a pronounced vertical thermal gradient in summer and vertical mixing the end of fall. A vertical two-dimensional, laterally averaged hydrodynamic and water quality model (CE-QUAL-W2) was adopted to simulate the water surface elevation, water temperature, and water quality conditions in the water column. The modeling effort was supported with monitoring data collected in the field for a 2-year period in the reservoir. The hydrodynamic model reproduced the time series water surface elevation. Spatial and temporal distributions of temperature in the water column of the reservoir were also well reproduced by the hydrodynamic model. Model-calculated concentrations of key water quality constituents such as nutrients, dissolved oxygen, and algal biomass matched the measured values closely in the reservoir. The calibrated model was then applied to simulate water quality response to various nutrient reduction scenarios. Results of the model scenario runs reveal that a 20% and 80% reduction of the phosphorus loads will improve the water quality from eutrophic to mesotrophic and oligotrophic conditions, respectively. The modeling effort has yielded valuable information that can be used by decision makers for the evaluation of different management strategies of reducing watershed nutrient loads.     

Assessment of water quality along a recreational section of the Damour River in Lebanon using the water quality index

Considering that water is becoming progressively scarce, monitoring water quality of rivers is a subject of ongoing concern and research. It is very intricate to accurately express water quality as water quantity due to the various variables influencing it. A water quality index which integrates several variables in a specific value may be used as a management tool in water quality assessment. Moreover, this index may facilitate communication with the public and decision makers. The main objectives of this research project are to evaluate the water quality index along a recreational section of a relatively small Mediterranean river in Southern Lebanon and to characterize the spatial and temporal variability. Accordingly, an assessment was conducted at the end of the dry season for a period of 5 years from 2005 to 2009. The estimated water quality index classified the average water quality over a 5-year period at the various sites as good. Results revealed that water quality of the Damour River is generally affected by the anthropogenic activities taking place along its watershed. The best quality was found in the upper sites and the worst at the estuary. The presence of fecal coliform bacteria in very high levels may indicate potential health risks to swimmers. This study can be used to support the evaluation of management, regulatory, and monitoring decisions.     

Toward a Practical Method for Setting Screening-Level, Ecological Risk-Based Water Temperature Criteria and Monitoring Compliance

We integrated basic concepts from fisheries science and toxicological risk assessment to form a potential method for setting screening-level, risk-based, site-specific water quality objectives for temperature. In summary, the proposed approach: (a) uses temperature impacts upon specific growth as a measure of chronic (cumulative) temperature effects; (b) explicitly incorporates the consequences of both magnitude and cumulative duration of exposures; (c) adjusts the result for local watershed conditions, reducing the likelihood that naturally warm systems are identified as thermally polluted while helping to ensure that naturally cool systems are closely monitored for ecologically harmful changes in thermal regime; and (d) expresses the net result both graphically and as a risk quotient, RQ, closely analogous to that used in toxicological risk assessments. The latter yields a site-specific, risk-based water quality objective and may serve as a straightforward decision rule for environmental managers. The method was applied to historical data from a small British Columbia stream subject to increasing urban development pressures. We also illustrate how the technique might be used to explore potential climatic change impacts, using coupled general circulation model predictions in conjunction with empirical downscaling. Overall, the method and results are presented as an introduction and illustration of concept, intended as a step toward the development of a logistically feasible risk-based approach to establishing screening-level, site-specific water temperature objectives, and monitoring compliance, in the context of large-scale, many-site, environmental monitoring networks. With further work, the technique offers potential to fill the gap between the temperature threshold-based targets typically specified in regulatory guidelines, which may be hydroecologically unrealistic, and detailed biophysical modelling, which typically is logistically infeasible in a day-to-day environmental monitoring and management context.     

Sensitivity analysis of water quality for Delhi stretch of the River Yamuna,India

Simulation models are used to aid the decision makers about water pollution control and management in river systems. However, uncertainty of model parameters affects the model predictions and hence the pollution control decision. Therefore, it often is necessary to identify the model parameters that significantly affect the model output uncertainty prior to or as a supplement to model application to water pollution control and planning problems. In this study, sensitivity analysis, as a tool for uncertainty analysis was carried out to assess the sensitivity of water quality to (a) model parameters (b) pollution abatement measures such as wastewater treatment, waste discharge and flow augmentation from upstream reservoir. In addition, sensitivity analysis for the “best practical solution” was carried out to help the decision makers in choosing an appropriate option. The Delhi stretch of the river Yamuna was considered as a case study. The QUAL2E model is used for water quality simulation. The results obtained indicate that parameters K ₁ (deoxygenation constant) and K ₃ (settling oxygen demand), which is the rate of biochemical decomposition of organic matter and rate of BOD removal by settling, respectively, are the most sensitive parameters for the considered river stretch. Different combinations of variations in K ₁ and K ₂ also revealed similar results for better understanding of inter-dependability of K ₁ and K ₂. Also, among the pollution abatement methods, the change (perturbation) in wastewater treatment level at primary, secondary, tertiary, and advanced has the greatest effect on the uncertainty of the simulated dissolved oxygen and biochemical oxygen demand concentrations.     

Principal response curves technique for the analysis of multivariate biomonitoring time series

Although chemical and biological monitoring is often used to evaluate the quality of surface waters for regulatory purposes and/or to evaluate environmental status and trends, the resulting biological and chemical data sets are large and difficult to evaluate. Multivariate techniques have long been used to analyse complex data sets. This paper discusses the methods currently in use and introduces the principal response curves method, which overcomes the problem of cluttered graphical results representation that is a great drawback of most conventional methods. To illustrate this, two example data sets are analysed using two ordination techniques, principal component analysis and principal response curves. Whereas PCA results in a difficult-to-interpret diagram, principal response curves related methods are able to show changes in community composition in a diagram that is easy to read. The principal response curves method is used to show trends over time with an internal reference (overall mean or reference year) or external reference (e.g. preferred water quality or reference site). Advantages and disadvantages of both methods are discussed and illustrated.     

The Modeling Policy-Maker. On Decision Support Systems in Water Management

Computer models play an important role in modern water management as decision supporting tools to assess effects of possible measures in water systems. An important aspect in building these models is the selection of elements of the real world that should be incorporated in the model. For decision support tools, this selection depends on the policy measures and the effects to be evaluated. As some of these selections are strategic decisions, the policy-maker should be involved in the modeling process. In practice this is often not the case. Decisions, including the strategic ones, are usually all made by the modeling expert. This often leads to the situation that promising measures are not evaluated and sub optimal decisions are taken. This article focuses on the role which the policy-maker and the modeling expert should play in the modeling process. We formulate recommendations with respect to their communication by analysing the gap between this ideal situation and the day to day reality.     

A two-stage DEA approach for environmental efficiency measurement

The slacks-based measure (SBM) model based on the constant returns to scale has achieved some good results in addressing the undesirable outputs, such as waste water and water gas, in measuring environmental efficiency. However, the traditional SBM model cannot deal with the scenario in which desirable outputs are constant. Based on the axiomatic theory of productivity, this paper carries out a systematic research on the SBM model considering undesirable outputs, and further expands the SBM model from the perspective of network analysis. The new model can not only perform efficiency evaluation considering undesirable outputs, but also calculate desirable and undesirable outputs separately. The latter advantage successfully solves the "dependence" problem of outputs, that is, we can not increase the desirable outputs without producing any undesirable outputs. The following illustration shows that the efficiency values obtained by two-stage approach are smaller than those obtained by the traditional SBM model. Our approach provides a more profound analysis on how to improve environmental efficiency of the decision making units.     

A fuzzy multi-stakeholder multi-criteria methodology for water allocation and reuse in metropolitan areas

In this paper, a fuzzy decision making methodology is proposed to find a socially optimal scenario for allocating effluent of wastewater treatment plants and urban and suburban runoffs to agricultural regions and recharging aquifers. The presented methodology named modified fuzzy social choice (MFSC) considers multi-stakeholder multi-criteria problems under uncertainties inherent in a decision making process utilizing a fuzzy ranking method and the fuzzy social choice (FSC) theory. A set of water and wastewater allocation scenarios are proposed for water quantity and quality management of the study area, while six main stakeholders with conflicting utilities and different negotiation powers are involved. The proposed methodology is applied to Tehran metropolitan area, the capital city of Iran with the population of about 8 million people, to examine its applicability and effectiveness. The results shows that using fuzzy multi-stakeholder multi-criteria decision making method considering equal and different negotiation powers can lead to different outcomes. Based on the results, the MFSC method, which considers a number of decision makers having different negotiation powers, degrees of importance of decision making criteria, and some important uncertainties, performs more promising in real water resources management problems.     

Linking on-farm dairy management practices to storm-flow fecal coliform loading for California coastal watersheds

How and where to improve water quality within an agricultural watershed requires data at a spatial scale that corresponds with individual management decision units on an agricultural operation. This is particularly true in the context of water quality regulations, such as Total Maximum Daily Loads (TMDLs), that identify agriculture as one source of non-point source pollution through larger tributary watershed scale and above and below water quality investigations. We have conducted a systems approach study of 10 coastal dairies and ranches to document fecal coliform concentration and loading to surface waters at the management decision unit scale. Water quality samples were collected on a storm event basis from loading units that included: manure management systems; gutters; storm drains; pastures; and corrals and lots. In addition, in-stream samples were collected above and below the dairy facilities and from a control watershed, managed for light grazing and without a dairy facility or human residence and corresponding septic system. Samples were analyzed for fecal coliform concentration by membrane filtration. Instantaneous discharge was measured for each collected sample. Storm runoff was also calculated using the curve number method (SCS, 1985). Results for a representative dairy as well as the entire 10 dairy data set are presented. Fecal coliform concentrations demonstrate high variability both within and between loading units. Fecal coliform concentrations for pastures range from 206 to 2,288,888 cfu/100 ml and for lots from 1,933 to 166,105,000 cfu/100 ml. Mean concentrations for pastures and lots are 121,298 (SE=62,222) and 3,155,584 (SE=1,902,713) cfu/100 ml, respectively. Fecal coliform load from units of concentrated animals and manure are significantly more than units such as pastures while storm flow amounts were significantly less. Compared with results from earlier tributary scale studies in the watershed, this systems approach has generatedwater quality data that is beneficial for management decisions because of its scale and representation of current management activities. These results are facilitating on-farm changes through the cooperative efforts of dairy managers, regulatory agency staff, and sources of technical and financial assistance.     

决策树模型在水环境监测网络中选取代表性样点的应用

地表水体中的硝酸盐污染已经成为全球关注的热点环境问题之一。现今,国内外均建立了相关的监测网络对地表水体的水质实施长期监测,但是却导致大量的监测数据累积,给后续的科学研究工作带来了不便,尤其是在庞大的监测网络中如何选取有代表性样点的研究点则成为急需解决的问题之一。以比利时弗拉芒地区地表水的长期监测物理化学指标为例,利用决策树模型评估地表水样点的硝酸盐污染来源专家分类的有效性,为点位优化提供理论依据。原有监测点位的污染源专家分类和模型输出的可匹配率为80%,优化后监测点位从原有47个点降低到30个点,提高了监测工作效率。     

湖泊富营养化机理模型研究进展

湖泊富营养化机理模型是模拟和预测水质参数变化趋势和水体富营养化状态的有效工具,可为水环境污染预防和治理提供数据支撑与科学依据。在回顾湖泊富营养化机理模型分类及发展的基础上,重点分析和总结了CAEDYM模型、PCLake模型、AQUATOX模型和WASP模型等生态动力学模型研究热点,探讨了各个模型的适用性与局限性;并进一步从湖泊富营养化影响机制探究和水质水环境管理保护决策服务两方面梳理了富营养化模型的应用现状,指出了富营养化机理模型当前存在的问题与发展方向,旨在为模型研究和应用提供参考。     

江苏省太湖应急防控形势及对策体系研究

对2008年-2010年来太湖水质状况、蓝藻暴发状况及影响因素、湖泛发生状况及成因、蓝藻生长对湖体水质的影响、蓝藻与湖泛对饮用水安全影响进行了研究.简述了环保、建设、水利、气象、中科院南京地理与湖泊研究所等部门和单位,在监测预警、供水保障、调水引流、打捞蓝藻、生态清淤、控源截污、人工增雨、统筹协调等方面团结协作、多措并...     

Modelling the Effect of Weather Conditions on Cyanobacterial Bloom Outbreaks in Lake Dianchi: a Rough Decision-Adjusted Logistic Regression Model

Lake Dianchi, one of the main water sources for Kunming, China, experiences severe cyanobacterial blooms due to rapid urbanization and local industrial development. Scientific interest in the mechanisms that cause blooms has been increasing. An integrated model combining rough set theory with binary logistic regression was used to examine the correlation between weather conditions and cyanobacterial blooms in Lake Dianchi based on daily monitoring data. The binary logistic regression yielded quantitative correlations between cyanobacterial blooms and the assessed meteorological variables, including temperature, wind velocity, and wind direction. The rough decision process connected the weather conditions and cyanobacterial blooms, which were used to verify the binary regression model results. It was shown that by comparing the methods, the rough decision-adjusted binary logistic regression model significantly improved model accuracy. The integrated model of cyanobacterial blooms in Lake Dianchi may inform decision-makers at local water purification plants of the water quality in the lake and assist them in making more cost-effective decisions.     

An expert system for water quality modelling

The RAISON-micro (Regional Analysis by Intelligent System ON a micro-computer) expert system is being used to predict the effects of mine effluents on receiving waters in Ontario. The potential of this system to assist regulatory agencies and mining industries to define more acceptable effluent limits was shown in an initial study. This system has been further developed so that the expert system helps the model user choose the most appropriate model for a particular application from a hierarchy of models. The system currently contains seven models which range from steady state to time dependent models, for both conservative and nonconservative substances in rivers and lakes. The menu driven expert system prompts the model user for information such as the nature of the receiving water system, the type of effluent being considered, and the range of background data available for use as input to the models. The system can also be used to determine the nature of the environmental conditions at the site which are not available in the textual information database, such as the components of river flow. Applications of the water quality expert system are presented for representative mine sites in the Timmins area of Ontario.     

Assessing the Relative Importance of Spatial Variability in Emissions Versus Landscape Properties in Fate Models for Environmental Exposure Assessment of Chemicals

Multimedia mass balance models differ in their treatment of spatial resolution from single boxes representing an entire region to multiple interconnected boxes with varying landscape properties and emission intensities. Here, model experiments were conducted to determine the relative importance of these two main factors that cause spatial variation in environmental chemical concentrations: spatial patterns in emission intensities and spatial differences in environmental conditions. In the model, experiments emissions were always to the air compartment. It was concluded that variation in emissions is in most cases the dominant source of variation in environmental concentrations. It was found, however, that variability in environmental conditions can strongly influence predicted concentrations in some cases, if the receptor compartments of interest are soil or water—for water concentrations particularly if a chemical has a high octanol–air partition coefficient (K _oa). This information will help to determine the required level of spatial detail that suffices for a specific regulatory purpose.     

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。     

A multi-variate methodology for analyzing pre-existing lake water quality data

Environmental agencies are given the task of monitoring water quality in rivers, lakes, and other bodies of water, for the purpose of comparing the results with regulatory standards. Monitoring follows requirements set by regulations, and data are collected in a systematic way for the intended purpose. Monitoring enables agencies to determine whether water bodies are polluted. Much effort is spent per monitoring event, resulting in hundreds of data points typically used solely for comparison with regulatory standards and then stored for little further use. This paper devises a data analysis methodology that can make use of the pre-existing datasets to extract more useful information on water quality trends, without new sample collection and analysis. In this paper, measured lake water quality data are subjected to statistical analyses including Principal Component Analysis (PCA) to deduce changes in water quality spatially and temporally over several years. It was found that the lake as a whole changed temporally by season, rather than spatially. Storm events caused the greatest shifts in water quality, though the shifts were fairly consistent across sampling stations. This methodology can be applied to similar datasets, especially with the recent emphasis by the U.S. EPA on protection of lakes as water sources. Water quality managers using these techniques may be able to lower their monitoring costs by eliminating redundant water quality parameters found in this analysis.     

Application of a Life Cycle Simulation Model to Evaluate Impacts of Water Management and Conservation Actions on an Endangered Population of Chinook Salmon

Fisheries and water resource managers are challenged to maintain stable or increasing populations of Chinook salmon in the face of increasing demand on the water resources and habitats that salmon depend on to complete their life cycle. Alternative management plans are often selected using professional opinion or piecemeal observations in place of integrated quantitative information that could reduce uncertainty in the effects of management plans on population dynamics. We developed a stochastic life cycle simulation model for an endangered population of winter-run Chinook salmon in the Sacramento River, California, USA with the goal of providing managers a tool for more effective decision making and demonstrating the utility of life cycle models for resource management. Sensitivity analysis revealed that the input parameters that influenced variation in salmon escapement were dependent on which age class was examined and their interactions with other inputs (egg mortality, Delta survival, ocean survival). Certain parameters (river migration survival, harvest) that were hypothesized to be important drivers of population dynamics were not identified in sensitivity analysis; however, there was a large amount of uncertainty in the value of these inputs and their error distributions. Thus, the model also was useful in identifying future research directions. Simulation of variation in environmental inputs indicated that escapement was significantly influenced by a 10% change in temperature whereas larger changes in other inputs would be required to influence escapement. The model presented provides an effective demonstration of the utility of life cycle simulation models for decision making and provides fisheries and water managers in the Sacramento system with a quantitative tool to compare the impact of different resource use scenarios.     

A systems approach to modeling Community-Based Environmental Monitoring: a case of participatory water quality monitoring in rural Mexico

Community-Based Environmental Monitoring (CBM) is a social practice that makes a valuable contribution to environmental management and construction of active societies for sustainable future. However, its documentation and analysis show deficiencies that hinder contrast and comparison of processes and effects. Based on systems approach, this article presents a model of CBM to orient assessment of programs, with heuristic or practical goals. In a focal level, the model comprises three components, the social subject, the object of monitoring, and the means of action, and five processes, data management, social learning, assimilation/decision making, direct action, and linking. Emergent properties were also identified in the focal and suprafocal levels considering community self-organization, response capacity, and autonomy for environmental management. The model was applied to the assessment of a CBM program of water quality implemented in rural areas in Mexico. Attributes and variables (indicators) for components, processes, and emergent properties were selected to measure changes that emerged since the program implementation. The assessment of the first 3 years (2010–2012) detected changes that indicated movement towards the expected results, but it revealed also the need to adjust the intervention strategy and procedures. Components and processes of the model reflected relevant aspects of the CBM in real world. The component called means of action as a key element to transit “from the data to the action.” The CBM model offered a conceptual framework with advantages to understand CBM as a socioecological event and to strengthen its implementation under different conditions and contexts.