RELIABILITY AND ECONOMIC OPTIMIZATION FOR URBAN RETURN FLOWS MANAGEMENT1

ABSTRACT The reduction of the liability of pollution to urban water resources is considered as one of the common goals of all elements of our society. To approach the challenge with a sense of realism the probabilistic nature of the performance of pollution control facilities as well as environmental responses must not be ignored and cannot be eliminated. Reliability is defined herein as the measure of effectiveness for the attainment of water quality managerial goals. The objective of this paper is to develop an optimization model for the determination of the best pollution control policies for each treatment facility in terms of the minimization of total regional cost requirements, the quality control requirements, and the reliability desired. A chance-constrained quadratic programming technique coupled with parametric analysis is utilized as the basic solution approach. A practical problem based on the situation existing in the San Antonio River Basin Region of Texas was used for the illustration of this application. The implications resulting from the sensitivity analysis of this model will be discussed.     

Methods of Compliance Evaluation for Ocean Outfall Design and Analysis

Sewage discharge from an ocean outfall is subject to water quality standards, which are often stated in probabilistic terms. Monte Carlo simulation (MCS) has been used in the past to evaluate the ability of a designed outfall to meet water quality standards or compliance guidelines associated with sewage discharges. In this study, simpler and less computer-intensive probabilistic methods are considered. The probabilistic methods evaluated are the popular mean first-order second-moment (MFOSM) and the advance first-order second-moment (AFOSM) methods. Available data from the Spaniard's Bay Outfall located on the east coast of Newfoundland, Canada, were used as inputs for a case study. Both methods were compared with results given by MCS. It was found that AFOSM gave a good approximation of the failure probability for total coliform concentration at points remote from the outfall. However, MFOSM was found to be better when considering only the initial dilutions between the discharge point and the surface. Reasons for the different results may be the difference in complexity of the performance function in both cases. This study does not recommend the use of AFOSM for failure analysis in ocean outfall design and analysis because the analysis requires computational efforts similar to MCS. With the advancement of computer technology, simulation techniques, available software, and its flexibility in handling complex situations, MCS is still the best choice for failure analysis of ocean outfalls when data or estimates on the parameters involved are available or can be assumed.     

A two-stage inexact joint-probabilistic programming method for air quality management under uncertainty

A two-stage inexact joint-probabilistic programming (TIJP) method is developed for planning a regional air quality management system with multiple pollutants and multiple sources. The TIJP method incorporates the techniques of two-stage stochastic programming, joint-probabilistic constraint programming and interval mathematical programming, where uncertainties expressed as probability distributions and interval values can be addressed. Moreover, it can not only examine the risk of violating joint-probability constraints, but also account for economic penalties as corrective measures against any infeasibility. The developed TIJP method is applied to a case study of a regional air pollution control problem, where the air quality index (AQI) is introduced for evaluation of the integrated air quality management system associated with multiple pollutants. The joint-probability exists in the environmental constraints for AQI, such that individual probabilistic constraints for each pollutant can be efficiently incorporated within the TIJP model. The results indicate that useful solutions for air quality management practices have been generated; they can help decision makers to identify desired pollution abatement strategies with minimized system cost and maximized environmental efficiency.     

Uncertainty Analysis In Dissolved Oxygen Modeling in Streams

Uncertainty analysis in surface water quality modeling is an important issue. This paper presents a method based on the first-order reliability method (FORM) to assess the exceedance probability of a target dissolved oxygen concentration in a stream, using a Streeter–Phelps prototype model. Basic uncertainty in the input parameters is considered by representing them as random variables with prescribed probability distributions. Results obtained from FORM analysis compared well with those of the Monte Carlo simulation method. The analysis also presents the stochastic sensitivity of the probabilistic outcome in the form of uncertainty importance factors, and shows how they change with changing simulation time. Furthermore, a parametric sensitivity analysis was conducted to show the effect of selection of different probability distribution functions for the three most important parameters on the design point, exceedance probability, and importance factors. Note: This version was published online in June 2005 with the cover date of August 2004.     

A WATER QUALITY‐BASED APPROACH FOR WATERSHED WIDE BMP STRATEGIES1

ABSTRACT: Watershed management strategies generally involve controlling nonpoint source pollution by implementing various best management practices (BMPs). Currently, stormwater management programs in most states use a performance‐based approach to implement onsite BMPs. This approach fails to link the onsite BMP performance directly to receiving water quality benefits, and it does not take into account the combined treatment effects of all the stormwater management practices within a watershed. To address these issues, this paper proposes a water quality‐based BMP planning approach for effective nonpoint source pollution control at a watershed scale. A coupled modeling system consisting of a watershed model (HSPF) and a receiving water quality model (CE‐QUAL‐W2) was developed to establish the linkage between BMP performance and receiving water quality targets. A Monte Carlo simulation approach was utilized to develop alternative BMP strategies at a watershed level. The developed methodology was applied to the Swift Creek Reservoir watershed in Virginia, and the results show that the proposed approach allows for the development of BMP strategies that lead to full compliance with water quality requirements.     

新疆南部T油田废水污染物排放标准的适宜性研究

以新疆南部T油田为例，探讨了区域生态环境敏感性识别、区域生态系统服务功能重要性评价问题，结合T油田开发区内各区块生态环境敏感性和生态系统服务功能重要性的对比分析，提出油田开发区内污水排放执行不同综合排放标准的适宜性分区建议，为油田开发中的污染防治和区域生态环境的保护管理提供了科学依据。     

REGIONAL WATER QUALITY MANAGEMENT BY THE GENERALIZED REDUCED GRADIENT METHOD1

ABSTRACT: A river basin-wide water quality management system is considered. The river receives thermal as well as organic wastes. At-source treatment of these pollutants is imposed to control the basin-wide water quality. The related water quality standards are: the minimum DO concentration, the maximum allowable BOD concentration, the maximum allowable stream temperature, and the allowable rise in stream temperature. The general dynamic mathematical model representing water quality in streams and the thermal effects on BOD and DO concentrations is presented. The model is highly nonlinear in nature. The optimal management problem involving the model is solved by a recently developed nonlinear propgramming technique - the generalized reduced gradient (GRG) method. Comparison of results obtained by the GRG method vs. dynamic programming, and of results using a more realistic mathematical model vs. a simple model are presented. The analysis procedure can be applied to designing new and examining existing water quality programs, and to study the influence of alternate policies and constraints.     

ANALYSIS OF WASTE LOAD ALLOCATION PROCEDURES1

A study was made to analyze and modify procedures used for stream assimilation capacity and point source wasteload allocation calculations. This paper describes the sources and types of information collected and the analysis of alternative computation methods developed during the study. The calculation of stream assimilation capacity or Total Maximum Daily Load (TMDL), will depend upon assumed stream flows, quality standards, reaction rates, and modeling procedures. The “critical conditions” selected for TMDL calculations usually are low flows and warm temperatures. The complexity of water quality models used for TMDL and allocation calculations can range from simple, complete mixing to calibrated and verified mathematical models. A list of 20 wasteload allocation (WLA) methods was developed. Five of these WLA's were applied to an example stream to permit comparisons based on cost, equity, efficient use of stream assimilation capacity, and sensitivity to fundamental stream quality data. Based on insensitivity to data errors and current use by several states, the WLA method of “equal percent treatment” was preferable in the example stream.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

Impacts of Multiple Stresses on Water Demand and Supply Across the Southeastern United States1

Abstract: Assessment of long‐term impacts of projected changes in climate, population, and land use and land cover on regional water resource is critical to the sustainable development of the southeastern United States. The objective of this study was to fully budget annual water availability for water supply (precipitation ? evapotranspiration + groundwater supply + return flow) and demand from commercial, domestic, industrial, irrigation, livestock, mining, and thermoelectric uses. The Water Supply Stress Index and Water Supply Stress Index Ratio were developed to evaluate water stress conditions over time and across the 666 eight‐digit Hydrologic Unit Code basins in the 13 southeastern states. Predictions from two Global Circulation Models (CGC1 and HadCM2Sul), one land use change model, and one human population model, were integrated to project future water supply stress in 2020. We found that population increase greatly stressed water supply in metropolitan areas located in the Piedmont region and Florida. Predicted land use and land cover changes will have little effect on water quantity and water supply‐water demand relationship. In contrast, climate changes had the most pronounced effects on regional water supply and demand, especially in western Texas where water stress was historically highest in the study region. The simulation system developed by this study is useful for water resource planners to address water shortage problems such as those experienced during 2007 in the study region. Future studies should focus on refining the water supply term to include flow exchanges between watersheds and constraints of water quality and environmental flows to water availability for human use.     

CALIBRATION AND APPLICATION OF QUAL-II TO THE LOWER WINOOSKI RIVER1

ABSTRACT: A modified version of the U.S. Environmental Protection Agency's QUAL-II water quality simulation model is calibrated and applied to the Lower Winooski River, Vermont. The river flows through the metropolitan Burlington area and is impacted by several industrial and municipal point sources and by operation of hydropower facilities. Several structural modifications are made in the model to improve water quality simulations in rivers impacted by algal growth; these include the addition of organic nitrogen and organic phosphorus compartments and provision for algal uptake of ammonia and/or nitrate nitrogen. The model is interfaced with statistical programs which facilitate tabulation, display, and analysis of observed and predicted concentrations. The model is calibrated and tested against data from two intensive water quality surveys. Applications demonstrate the factors controlling water quality and sensitivities to point source waste management strategies and flow, as influenced by hydropower operations.     

OPTIMIZING NONPOINT SOURCE CONTROLS IN WATER QUALITY REGULATION1

ABSTRACT: A stochastic programming framework is developed to evaluate the economic implications of reliability criteria and multiple effluent controls on nonpoint source pollution. An integrated watershed simulation model is used to generate probability distributions for agricultural effluents in surface and ground water resulting from agricultural practices. Results from the planning model indicate that reliability and multiple effluent constraints significantly increase the cost of nonpoint controls but the effects vary by control alternative. The analysis indicates that an evaluation of multiple water quality objectives can be an important planning tool for designing nonpoint source controls for innovative programs to promote cost-effective water quality regulation.     

EXPERIENCE WITH THE 303-208-201 STUDY RELATIONSHIPS1

ABSTRACT: The current 201 study by the Bergen County Sewer Authority illustrates possibilities for improving the currently defined relationships between 201, 208 and 303 studies. The Bergen County Sewer Authority serves 115 square miles in northeast New Jersey, providing sewerage service to 507,000 people in 43 municipalities. Its STP discharges to the Hackensack River, a tidal estuary recently classified as Water Quality Limited, and which receives significant non-plant loading. The subject 201 study is concurrent with 208 and 303 planning by NJDEP. Preliminary evaluations show that detailed 201 work can affect the conclusions of 303 and 208 studies, and that a wider (environmental - social as well as economic) interpretation of cost-effectiveness can demand re-examination of prior assumptions and decisions, a task not typically part of 208–303 work. Increased flexibility is needed in applying 303 and 208 recommendations to defining 201 studies and NPDES permit criteria, particularly in analysis of water use objectives, water quality parameters and future flows, loadings and facility costs. Further, perception of alternatives can be clarified by broadening analysis of costs and control and plant strategies. Inclusion of 201 planning at all stages of regional planning can synergistically improve the total planning process.     

Riparian vegetation dynamics and evapotranspiration in the riparian corridor in the delta of the Colorado River, Mexico

Like other great desert rivers, the Colorado River in the United States and Mexico is highly regulated to provide water for human use. No water is officially allotted to support the natural ecosystems in the delta of the river in Mexico. However, precipitation is inherently variable in this watershed, and from 1981-2004, 15% of the mean annual flow of the Lower Colorado River has entered the riparian corridor below the last diversion point for water in Mexico. These flows include flood releases from US dams and much smaller administrative spills released back to the river from irrigators in the US and Mexico. These flows have germinated new cohorts of native cottonwood and willow trees and have established an active aquatic ecosystem in the riparian corridor in Mexico. We used ground and remote-sensing methods to determine the composition and fractional cover of the vegetation in the riparian corridor, its annual water consumption, and the sources of water that support the ecosystem. The study covered the period 2000-2004, a flood year followed by 4 dry years. The riparian corridor occupies 30,000ha between flood control levees in Mexico. Annual evapotranspiration (ET), estimated by Moderate Resolution Imaging Spectrometer (MODIS) satellite imagery calibrated against moisture flux tower data, was about 1.1myr(-1) and was fairly constant throughout the study period despite a paucity of surface flows 2001-2004. Total ET averaged 3.4x10(8)m(3)yr(-1), about 15% of Colorado River water entering Mexico from the US Surface flows could have played only a small part in supporting these high ET losses. We conclude that the riparian ET is supported mainly by the shallow regional aquifer, derived from agricultural return flows, that approaches the surface in the riparian zone. Nevertheless, surface flows are important in germinating cohorts of native trees, in washing salts from the soil and aquifer, and in providing aquatic habitat, thereby enriching the habitat value of the riparian corridor for birds and other wildlife. Conservation and water management strategies to enhance the delta habitats are discussed in light of the findings.     

提高土壤环境管理成效:推进三大环境要素协同治理

经过长期的大气污染和水污染治理实践,各地积累了一定的技术、工程和管理经验,但随着土壤污染问题的日益凸显,三大环境要素质量如何整体提升、确保区域生态系统服务功能稳定持续发挥、满足人民群众对环境产品的需求,成为各级政府推进环境基本公共服务均等化过程中需要正视和亟待破解的一个难题。本文在系统分析当前环境污染以单要素为主线实施治理的总体思路所面临困境的基础上,基于生态系统整体性和区域统筹考量,从治理主体、治理手段、治理过程三个方面,提出推进土壤环境-水环境-大气环境协同治理的基本路径,为国家出台土壤环境管理相关政策措施、促进城镇化过程中区域环境质量整体改善提供参考。     

Uncertainty characterization approaches for risk assessment of DBPs in drinking water: A review

The management of risk from disinfection by-products (DBPs) in drinking water has become a critical issue over the last three decades. The areas of concern for risk management studies include (i) human health risk from DBPs, (ii) disinfection performance, (iii) technical feasibility (maintenance, management and operation) of treatment and disinfection approaches, and (iv) cost. Human health risk assessment is typically considered to be the most important phase of the risk-based decision-making or risk management studies. The factors associated with health risk assessment and other attributes are generally prone to considerable uncertainty. Probabilistic and non-probabilistic approaches have both been employed to characterize uncertainties associated with risk assessment. The probabilistic approaches include sampling-based methods (typically Monte Carlo simulation and stratified sampling) and asymptotic (approximate) reliability analysis (first- and second-order reliability methods). Non-probabilistic approaches include interval analysis, fuzzy set theory and possibility theory. However, it is generally accepted that no single method is suitable for the entire spectrum of problems encountered in uncertainty analyses for risk assessment. Each method has its own set of advantages and limitations. In this paper, the feasibility and limitations of different uncertainty analysis approaches are outlined for risk management studies of drinking water supply systems. The findings assist in the selection of suitable approaches for uncertainty analysis in risk management studies associated with DBPs and human health risk.     

Determining regional water quality patterns and their ecological relationships

A multivariate statistical method for analyzing spatial patterns of water quality in Georgia and Kansas was tested using data in the US Environmental Protection Agency's STORET data system. Water quality data for Georgia and Kansas were organized by watersheds. We evaluated three questions: (a) can distinctive regional water quality patterns be detected and predicted using only a few water quality variables, (b) are regional water quality patterns correlated with terrestrial biotic regions, and (c) are regional water quality patterns correlated with fish distributions? Using existing data, this method can distinguish regions with water quality very different from the average conditions (as in Georgia), but it does not discriminate well between regions that do not have diverse water quality conditions (as in Kansas). Data that are spatially and temporally adequate for representing large regions and for multivariate statistical analysis are available for only a few common water quality parameters. Regional climate, lithology, and biotic regimes all have the potential to affect water quality, and terrestrial biotic regions and fish distributions do compare with regional water quality patterns, especially in a state like Georgia, where watershed characteristics are diverse. Thus, identifiable relationships between watershed characteristics and water quality should allow the development of an integrated landaquatic classification system that would be a valuable tool for resource management. Because geographical distributions of species may be limited by Zoogeographic and environmental factors, the recognition of patterns in fish distributions that correlate with regional water quality patterns could influence management strategies and aid regional assessments.     

对跨界断面考核制度改进的思考:以辽河铁岭段为例

水是生命之源,水资源的重要性不言而喻。行之有效的水环境管理制度对水资源的合理开发和利用意义重大。辽宁省政府于2008年出台跨行政区断面考核制度,该制度对跨界断面水质的管理和保护起到了重要作用。从管理角度来看,一套完善的跨行政区出市断面考核体系对跨界断面河流的水环境保护和水质改善至关重要。本文通过对该制度的详细研究,从管理绩效方面找出了该制度目前仍存在的缺陷与不足,并以辽河流域铁岭段监测断面的水质数据分析为基础,对跨界断面考核制度做出了调整:提出了监测频率由一月监测一次调整为一季度监测一次的建议;在原有的只对考核目标水质得分值计算的基础上加入了对考核目标浓度变化值的考查;以主成分分析法对水质分析的结果为依据,对不同季节的水质考核值做出了相应调整,避免了对所有月份按照统一标准进行考核所带来的不合理之处。     

A MULTIOBJECTIVE MODEL FOR REGIONAL WATER QUALITY MANAGEMENT1

ABSTRACT: Linear programming is the simplest of all the optimization techniques used in regional water quality management studies; but the technique can optimize only one goal. When there are multiple goals with the same or different priorities, goal programming is a useful decisionmaking tool. This paper illustrates the application of goal programming to a regional water quality management problem where the following two goals are considered: (1) minimize the total cost of waste treatment, and (2) maintain the water quality goals (dissolved oxygen) close to the minimum level stated in the stream standards.