A Hierarchical Fuzzy Decision Support System for the Environmental Rehabilitation of Lake Koronia,Greece

This article presents the design of a fuzzy decision support system (DSS) for the assessment of alternative strategies proposed for the restoration of Lake Koronia, Greece. Fuzzy estimates for the critical characteristics of the possible strategies, such as feasibility, environmental impact, implementation time, and costs are evaluated and supplied to the fuzzy DSS. Different weighting factors are assigned to the critical characteristics and the proposed strategies are ordered with respect to the system responses. The best strategies are selected and their expected impact on the ecosystem is evaluated with the aid of a fuzzy model of the lake. Sensitivity analysis and simulation results have shown that the proposed fuzzy DSS can serve as a valuable tool for the selection and evaluation of appropriate management actions. Note: This version was published online in June 2005 with the cover date of August 2004.     

A Knowledge-Based Systems Approach to Design of Spatial Decision Support Systems for Environmental Management

/ This paper describes a framework for designing spatial decision support systems for environmental management using a knowledge-based systems approach. An architecture for knowledge-based spatial decision supportsystems (KBSDSS) is presented that integrates knowledge-based systems with geographical information systems (GIS) and other problem-solving techniques. A method based on spatial influence diagrams is developed for representation of environmental problems. The spatial influence diagram provides an interface through which knowledge-based systems techniques can be applied to build capabilities for problem formulation, automated design, and execution of a solution process. In addition to the flexibility and developmental advantages of knowledge-based systems, the KBSDSS incorporates expert knowledge to provide assistance for structuring spatial influence diagrams and executing a solution process that automatically integrates the GIS, data base, knowledge base, and different types of models. The framework is illustrated with a system, known as the Islay Land Use Decision Support System (ILUDSS), designed to assist planners in strategic planning of land use for the development of the island of Islay, off the west coast of Scotland.KEY WORDS: Geographical information systems; Spatial decision support systems; Knowledge-based systems; Spatial influence diagrams; Environmental management     

An Ex Post Evaluation of Ohio’s Great Miami Water Quality Trading Program1

Newburn, David A. and Richard T. Woodward, 2011. An Ex Post Evaluation of Ohio’s Great Miami Water Quality Trading Program. Journal of the American Water Resources Association (JAWRA) 48(1): 156‐169. DOI: 10.1111/j.1752‐1688.2011.00601.x Abstract: Market‐based approaches to address water quality problems have resulted in only limited success, especially in trading programs involving both point and nonpoint sources. We analyze one of the largest point‐nonpoint trading programs – the Great Miami Trading Program in Ohio, administered by the Miami Conservancy District (MCD). Our evaluation focuses on the economic and institutional aspects of the program, including cost effectiveness, efficiency of bidding, transaction costs, trading ratios, and innovation. We use a unique dataset consisting of all bids from agricultural nonpoint sources and interviews of soil and water conservation district (SWCD) agents in the watershed. We find that the MCD’s reliance on county‐level SWCD offices to recruit and advise farmers has been essential to achieve relatively high rates of farmer participation. Additionally, the MCD is able to partly free ride on the administrative costs that SWCD offices receive to assist federal conservation programs, which is helpful to lower costs for a fledgling trading program. However, the involvement of SWCD offices reduced the potential cost savings from the reverse auction structure because some agents were able to learn about the threshold price over the six rounds of bidding and help farmers bid strategically. Overall, the program structure serves as an effective model for future trading programs in other regions that seek to involve agricultural nonpoint sources.     

An Innovative Index for Evaluating Water Quality in Streams

A water quality index expressed as a single number is developed to describe overall water quality conditions using multiple water quality variables. The index consists of water quality variables: dissolved oxygen, specific conductivity, turbidity, total phosphorus, and fecal coliform. The objectives of this study were to describe the preexisting indices and to define a new water quality index that has advantages over these indices. The new index was applied to the Big Lost River Watershed in Idaho, and the results gave a quantitative picture for the water quality situation. If the new water quality index for the impaired water is less than a certain number, remediation—likely in the form of total maximum daily loads or changing the management practices—may be needed. The index can be used to assess water quality for general beneficial uses. Nevertheless, the index cannot be used in making regulatory decisions, indicate water quality for specific beneficial uses, or indicate contamination from trace metals, organic contaminants, and toxic substances.     

Stakeholder Perceptions of Scientists: Lake Tahoe Environmental Policy from 1984 to 2001

What factors explain stakeholders’ perceptions of scientists in environmental politics? Questionnaire data are used to examine stakeholders’ views of scientific experts in the context of Lake Tahoe environmental policy from 1984 to 2001. Stakeholders’ perceptions of scientists have remained the same over time – despite a shift from adversarial to collaborative policymaking and after decades of mounting scientific evidence showing water quality declines. On average, stakeholders perceive scientists with limited influence on Lake Tahoe environmental policy and view them with mixed levels of skepticism. Stakeholders’ evaluation of scientists is best explained by their beliefs about development versus the environment. Stakeholders in favor of more land development express distrust of scientists and negatively evaluate university researchers and consultants. Stakeholders in favor of environmental protection are more likely to trust scientists and positively evaluate university researchers and consultants.     

Water Quality Model Uncertainty Analysis of a Point‐Point Source Phosphorus Trading Program1

Kardos, Josef S. and Christopher C. Obropta, 2011. Water Quality Model Uncertainty Analysis of a Point‐Point Source Phosphorus Trading Program. Journal of the American Water Resources Association (JAWRA) 47(6):1317–1337. DOI: 10.1111/j.1752‐1688.2011.00591.x Abstract: Water quality modeling is a major source of scientific uncertainty in the Total Maximum Daily Load (TMDL) process. The effects of these uncertainties extend to water quality trading programs designed to implement TMDLs. This study examines the effects of water quality model uncertainty on a nutrient trading program. The study builds on previous work to design a phosphorus trading program for the Nontidal Passaic River Basin in New Jersey that would implement the watershed TMDL for total phosphorus (TP). The study identified how water quality model uncertainty affects outcomes of potential trades of TP between wastewater treatment plants. The uncertainty analysis found no evidence to suggest that the outcome of trades between wastewater treatment plants, as compared with command and control regulation, will significantly increase uncertainty in the attainment of dissolved oxygen surface water quality standards, site‐specific chlorophyll a criteria, and reduction targets for diverted TP load at potential hot spots in the watershed. Each simulated trading scenario demonstrated parity with or improvement from the command and control approach at the TMDL critical locations, and low risk of hot spots elsewhere.     

Water Quality in Drinking Water Reservoirs of a Megacity, Istanbul

Providing clean water at relevant quality and quantity is a challenge that regulatory authorities have to face in metropolitan cities that seem to develop at their limits of sustainability. Istanbul strives to face such a challenge for its population of over 10 million, through six surface water resources. Two approaches of classification for the reservoirs are presented, one based on current regulations and an alternative based on a more detailed classification. The results have shown that nutrient control is the primary issue, and one of the reservoirs has already exceeded the limits of being eutrophic, one is at mesotrophic conditions, and the remaining four are at the limit of being eutrophic, indicating the significance of making the correct decision and taking pertinent measures for management and control. It has been observed that the only mesotrophic resource, which also has the best general quality class, has no industry and a very low population density, whereas the one that is already eutrophic is also the one with the lowest quality class, has the highest population density, and has the greatest percentage of urban land use within its watershed.     

A Watershed Approach to Improve Water Quality: Case Study of Clean Water Services’ Tualatin River Program1

Cochran, Bobby and Charles Logue, 2011. A Watershed Approach to Improve Water Quality: Case Study of Clean Water Services’ Tualatin River Program. Journal of the American Water Resources Association (JAWRA) 47(1):29‐38. DOI: 10.1111/j.1752‐1688.2010.00491.x Abstract: Over the last five years, Clean Water Services developed and implemented a program to offset thermal load discharged from its wastewater facilities to the Tualatin River by planting trees to shade streams and augmenting summertime instream flows. The program has overcome challenges facing many of the nation’s water quality trading programs to not only gain consensus on the frameworks needed to authorize trading, but also provide a broad range of ecosystem services. This paper compares the Tualatin case study with some of the commonly cited factors of successful trading programs.     

A Web‐Based Decision Support System for Assessing Regional Water‐Quality Conditions and Management Actions1

Booth, Nathaniel L., Eric J. Everman, I‐Lin Kuo, Lori Sprague, and Lorraine Murphy, 2011. A Web‐Based Decision Support System for Assessing Regional Water‐Quality Conditions and Management Actions. Journal of the American Water Resources Association (JAWRA) 47(5):1136‐1150. DOI: 10.1111/j.1752‐1688.2011.00573.x Abstract: The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water‐quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water‐quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow‐weighted concentration, or load of constituents in water under various land‐use condition, change, or resource management scenarios. A web‐based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water‐quality conditions and to offer sophisticated scenario testing capabilities for research and water‐quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water‐quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000‐scale River Reach File (RF1) and 1:100,000‐scale National Hydrography Dataset (medium‐resolution, NHDPlus) stream networks.     

Development of a Decision Support System for Assessing Farm Animal Welfare in Relation to Husbandry Systems: Strategy and Prototype

Due to increasing empiricalinformation on farm animal welfare since the1960s, the prospects for sound decisionmakingconcerning welfare have improved. This paperdescribes a strategy to develop adecision-making aid, a decision support system,for assessment of farm-animal welfare based onavailable scientific knowledge. Such a decisionsupport system allows many factors to be takeninto account. It is to be developed accordingto the Evolutionary Prototyping Method, inwhich an initial prototype is improved inreiterative updating cycles. This initialprototype has been constructed. It useshierarchical representations to analysescientific statements and statements describingthe housing system. Welfare is assessed fromwhat is known about the biological needs of theanimals, using a welfare model in the form of atree that contains these needs as welfarecomponents. Each state of need is assessedusing welfare relevant attributes of thehousing system and weighting factors.Attributes are measurable properties of thehousing system. Weighting factors are assignedaccording to heuristic rules based on theprinciple of weighting all components(attributes and needs) equally, unless thereare strong reasons to do otherwise. Preliminarytests of the prototype indicate that it may bepossible to perform assessment of farm-animalwelfare in an explicit way and based onempirical findings. The procedure needs to berefined, but its prospects are promising.     

Approaches to Evaluate Water Quality Model Parameter Uncertainty for Adaptive TMDL Implementation1

Abstract: The National Research Council recommended Adaptive Total Maximum Daily Load implementation with the recognition that the predictive uncertainty of water quality models can be high. Quantifying predictive uncertainty provides important information for model selection and decision‐making. We review five methods that have been used with water quality models to evaluate model parameter and predictive uncertainty. These methods (1) Regionalized Sensitivity Analysis, (2) Generalized Likelihood Uncertainty Estimation, (3) Bayesian Monte Carlo, (4) Importance Sampling, and (5) Markov Chain Monte Carlo (MCMC) are based on similar concepts; their development over time was facilitated by the increasing availability of fast, cheap computers. Using a Streeter‐Phelps model as an example we show that, applied consistently, these methods give compatible results. Thus, all of these methods can, in principle, provide useful sets of parameter values that can be used to evaluate model predictive uncertainty, though, in practice, some are quickly limited by the “curse of dimensionality” or may have difficulty evaluating irregularly shaped parameter spaces. Adaptive implementation invites model updating, as new data become available reflecting water‐body responses to pollutant load reductions, and a Bayesian approach using MCMC is particularly handy for that task.     

Water-quality effectiveness of a detention/wetland treatment system and its effect on an urban lake

A newly installed combined detention/wetland stormwater treatment facility upstream from Lake McCarrons, Roseville, Minnesota, was monitored for 21 months to evaluate its effectiveness and the response of the lake to decreased phosphorus loads. The treatment facility consists of a 1.0-ha detention pond that discharges into a series of six constructed wetland “chambers.” Data from snowmelt and rainfall events are presented for several pollutants. Results show good reductions for most pollutants. Discussion on the facets of the system's operation are presented. Data from the lake show very little change in its water quality from three years prior to restoration (1984–1986) to three years following restoration (1987–1989): the lake's phosphorus and chlorophyll has actually increased.