PROBABILISTIC METHODS IN STREAM QUALITY MANAGEMENT1

ABSTRACT. Recent advances in water quality modelling have pointed out the need for stochastic models to simulate the probabilistic nature of water quality. However, often all that is needed is an estimate of the uncertainty in predicting water quality variables. First order analysis is a simple method of providing an estimate in the uncertainty in a deterministic model due to uncertain parameters. The method is applied to the simplified Streeter-Phelps equations for DO and BOD; a more complete Monte Carlo simulation is used to check the accuracy of the results. The first order analysis is found to give accurate estimates of means and variances of DO and BOD up to travel times exceeding the critical time. Uncertainty in travel time and the BOD decay constant are found to be most important for small travel times; uncertainty in the reaeration coefficient dominates near the critical time. Uncertainty in temperature was found to be a negligible source of uncertainty in DO for all travel times.     

INTERPLAY BETWEEN PARAMETER UNCERTAINTY AND MODEL AGGREGATION ERROR1

ABSTRACTS: Modeling error can be divided into two basic components: use of an incorrect model and input parameter uncertainty. Incorrect model usage can be further subdivided into inappropriate model selection and inherent modeling error due to process aggregation. Total modeling error is a culmination of these various modeling error components, with overall optimization requiring reductions in all. A technique, utilizing Monte Carlo analysis, is employed to investigate the relative importance of input parameter uncertainty versus process aggregation error. An expanded form of the Streeter-Phelps dissolved oxygen equation is used to demonstrate the application of this technique. A variety of scenarios are analyzed to illustrate the relative obfuscation of each modeling error component. Under certain circumstances an aggregated model performs better than a more complex model, which perfectly simulates the real system. Alternately, process aggregation error dominates total modeling error for other situations. The ability to differentiate modeling error impact is a function of the desired or imposed model performance level (accuracy tolerance).     

WATER QUALITY MODEL CALIBRATION: A COMPARISON OF INPUT AND OUTPUT ERROR CRITERIA1

ABSTRACT: A common framework for the analysis of water resources systems is the input-parameter-output representation. The system, described by its parameters, is driven by inputs and responds with outputs. To calibrate (estimate the parameters) models of these systems requires data on both inputs and outputs, both of which are subject to random errors. When one is uncertain as to whether the predominant source of error is associated with inputs or outputs, uncertainty also exists as to the correct specification of a calibration criterion. This paper develops and analyzes two alternative least squares criteria for calibrating a numerical water quality model. The first criterion assumes that errors are associated with inputs while the second assumes output errors. Statistical properties of the resulting estimators are examined under conditions of pure input or output error and mixed error conditions from a theoretical perspective and then using simulated results from a series of Monte Carlo experiments.     

Spatial variations of human health risk associated with exposure to chlorination by-products occurring in drinking water

During disinfection, chlorine reacts with organic matter present in drinking water and forms various undesirable chlorinated by-products (CBPs). This paper describes a study of the spatial variability of human health risk (i.e., cancer effects) from CBP exposure through drinking water in a specific region. The region under study involves nine drinking water distribution systems divided into several zones based on their characteristics. The spatial distribution of cancer risk (CR) was estimated using two years of data (2006-2008) on various CBP species. In this analysis, trihalomethanes (THMs) and haloacetic acids (HAAs) served as surrogates for CBPs. Three possible routes of exposure (i.e., via ingestion, inhalation and dermal contact) were considered for each selected compound. The cancer risk assessment involved estimating a unit risk (R(T)) in each zone of the selected distribution systems. A probabilistic analysis based on Monte Carlo simulations was employed. Risk assessment results showed that cancer risk varied between systems, but also within individual systems. As a result, the population of the same region was not exposed to the same risk associated with CBPs in drinking water. Unacceptable levels (i.e., R(T) > 10(-4)) for the estimated CR were determined for several zones in the studied region. This study demonstrates that a spatial-based analysis performed to represent the spatial distribution of risk estimates can be helpful in identifying suitable risk management strategies. Suggestions for improving the risk analysis procedure are also presented.     

汕头地区农业生态系统中有机氯农药的研究

有机氯农药（Organochlorine Pesticides,OCPs）是一类由人工合成的杀虫广谱、毒性较低、残效期长的化学杀虫剂。本文以汕头市为研究区域,探讨了土壤OCPs的残留现状和特征,并对该区的土壤进行了环境质量评价和初步的生态风险评价。结果表明：（1）汕头地区土壤中OCPs的检出率高达99.13％,OCPs残留量的平均值是113.37 ng·g^-1,主要的OCPs污染物为DDTs和硫丹类;南澳县OCPs残留量平均值最高（174.68 ng·g^-1）,其次为龙湖区,濠江区含量平均值最低（69.24 ng·g^-1）;（2）与国内外一些地区土壤中OCPs的残留量对比,本研究区域土壤中的OCPs处于中等污染残留水平;与美国马里兰州标准、纽约州可容许的土壤浓度标准和我国的土壤环境质量标准相比较,OCPs基本没有超标;（3）本研究地区土壤存在较高的生态风险,OCPs可能对环境造成一定的危害,其中生态风险最高的是DDTs,BHCs的生态风险较低。     

Environmental Integrated Assessment via Monte Carlo Simulation with a Case Study of the Mid-Atlantic Region,USA

Environmental integrated assessments are often carried out via the aggregation of a set of environmental indicators. Aggregated indices derived from the same data set can differ substantially depending upon how the indicators are weighted and aggregated, which is often a subjective matter. This article presents a method of generating aggregated environmental indices in an objective manner via Monte Carlo simulation. Rankings derived from the aggregated indices within and between three Monte Carlo simulations were used to evaluate the overall environmental condition of the study area. Other insights, such as the distribution of good or bad values of indicators at a watershed and/or a subregion, were observed in the study.     

OCCURRENCE OF PESTICIDES IN GROUND WATER OF THE OZARK PLATEAUS PROVINCE1

ABSTRACT: Pesticides were detected in ground-water samples collected from 20 springs and nine wells in the Ozark Plateaus Province of Arkansas, Kansas, Missouri, and Oklahoma. From April through September 1993, water samples were collected from 50 shallow domestic wells and 50 springs in the Springfield Plateau and Ozark aquifers and analyzed for 47 pesticides and metabolites. Pesticides were detected in 17 water samples from the Springfield Plateau aquifer and 12 water samples from the Ozark aquifer. Fourteen pesticides were detected, with a maximum of four pesticides detected in any one sample. The most commonly detected pesticides were atrazine (14 detections), prometon (11 detections), and tebuthiuron (seven detections). P, P' DDE, a metabolite of DDT, was detected in water samples from three wells and one spring. The remaining pesticides were detected in three or less samples. The occurrence and distribution of pesticides probably are related to the local land use near a sampling site. Pesticide detections were significantly related to aquifer, site type, and discharge of springs.     

中美水质评价方法比较

国内外的研究都表明,从保护人类、野生动植物和自然生态环境健康角度出发,按照水体自然属性并结合人类对水体的使用和保护要求对水体进行功能划分,制定合理与水体使用功能相适应的水环境质量标准,并采取控制措施使水体水质达到该标准,是既合理、经济,又能有效保护水环境的方法.其关键是如何按照水质标准对水环境质量进行客观准确评价,这既是保护水环境的基础性工作,直接关系到水环境保护和排污控制措施的有效性,也是我国目前急需解决的重要课题.本文首先对美国水环境质量评价方法体系作了概要介绍,然后对我国水环境质量评价现状进行分析,通过对比美国和我国的水环境质量评价方法,对我国水环境质量评价提出了建议和研究方向.     

Water quality modelling of the river Yamuna (India) using QUAL2E-UNCAS

This paper describes the utility of QUAL2E as a modelling package in the evaluation of a water quality improvement programme. In this study, QUAL2E was applied to determine the pollution loads in the river Yamuna during its course through the national capital territory of Delhi, India. The study aimed at examining the influence of different scenarios on river water quality. Four different pollution scenarios were analysed besides the 'business as usual' situation. The study revealed that it was necessary to treat the discharge from drains to the river Yamuna and diversion of a substantial load to the Agra canal for further treatment was also essential. It was also established through this study that maintaining a flow rate of more than 10 m(3)/s in the river could also help preserve the river's water quality. To clearly display the model outcomes and demarcate polluted zones in the river stretch, model results were interfaced with a Geographical Information System (GIS) to produce cartographic outputs. In addition, uncertainty analysis in the form of first-order error analysis and Monte Carlo analysis was performed, to realise the effect of each model parameter on DO and BOD predictions. The uncertainty analysis gave satisfactory results on simulated data.     

QUANTITATIVE METHODS FOR PRELIMINARY DESIGN OF WATER QUALITY SURVEILLANCE SYSTEMS1

ABSTRACT: To assure attainment and maintenance of desired water quality levels in our rivers and streams, systematic monitoring must be performed. A preliminary phase of the design of water quality surveillance systems is the specification of sampling frequencies and station locations throughout the basin; that is, the development of an adequate space/time sampling plan. The purpose of this paper is to present some quantitative methods which have been developed to identify candidate sets of sampling frequencies and station locations, and to establish priorities for implementing the different frequencies and locations. These methods are useful in the cost/effectiveness trade-off analyses in surveillance system design, and are based on the surveillance system objective of pollution abatement in which it is desired to detect violations in state-federal water quality standards. A spatial priority measure is developed which is dependent both on the water quality profile in the stream and on the information obtained from monitoring stations located in other reaches. Also, a temporal sampling priority rating is presented which is a measure of the effectiveness of the surveillance system with respect to its ability to detect the violations in the standards. To illustrate the quantitative methods, the procedures are applied to the Wabash River Basin.