Siting and Routing Assessment for Solid Waste Management Under Uncertainty Using the Grey Mini-Max Regret Criterion

Solid waste management (SWM) is at the forefront of environmental concerns in the Lower Rio Grande Valley (LRGV), South Texas. The complexity in SWM drives area decision makers to look for innovative and forward-looking solutions to address various waste management options. In decision analysis, it is not uncommon for decision makers to go by an option that may minimize the maximum regret when some determinant factors are vague, ambiguous, or unclear. This article presents an innovative optimization model using the grey mini-max regret (GMMR) integer programming algorithm to outline an optimal regional coordination of solid waste routing and possible landfill/incinerator construction under an uncertain environment. The LRGV is an ideal location to apply the GMMR model for SWM planning because of its constant urban expansion, dwindling landfill space, and insufficient data availability signifying the planning uncertainty combined with vagueness in decision-making. The results give local decision makers hedged sets of options that consider various forms of systematic and event-based uncertainty. By extending the dimension of decision-making, this may lead to identifying a variety of beneficial solutions with efficient waste routing and facility siting for the time frame of 2005 through 2010 in LRGV. The results show the ability of the GMMR model to open insightful scenario planning that can handle situational and data-driven uncertainty in a way that was previously unavailable. Research findings also indicate that the large capital investment of incineration facilities makes such an option less competitive among municipal options for landfills. It is evident that the investment from a municipal standpoint is out of the question, but possible public–private partnerships may alleviate this obstacle.     

FUZZY DECISION MAKING IN GROUND WATER NITRATE RISK MANAGEMENT1

ABSTRACT: Ground water nitrate contamination is widespread in the United States and especially prevalent in agriculture-intensive areas such as the Midwest. To reduce human health risks (i.e., methemoglobinemia and cancer risks) from nitrates in ground water supplies, several nitrate risk-management strategies can be developed based on acceptable levels of human health risks, the reasonableness of the cost required for risk reduction, and the technical feasibility of nitrate-control methods. However, due to a lack of available information, assessing risk, cost, and technical feasibility contains elements of uncertainty. In this paper, a nitrate risk-management methodology using fuzzy sets in combination with a multicriterion decision-making (MCDM) technique is developed to assist decision makers in evaluating, with uncertain information, possible regulatory actions along with the various nitrate risk-management strategies in order to determine an appropriate strategy. The methodology is illustrated using data from a community with a nitrate water-quality problem.     

Public and Private Compromises in Agricultural Water Management

Agricultural water management is a complex decision-making problem involving multiple criteria of different nature as well as multiple decision agents with different interests. To handle this multiplicity of objectives and interests a pragmatic approach based on compromise programming is proposed in this paper. The methodology is applied to an agricultural water management problem in Tauste, Spain. Public, environmentalist and private decision makers are considered. The approach proposed reveals itself as a pragmatic alternative to other approaches based on aggregate utility functions with very sound theoretical underpinnings but with few possibilities of actually being put into practice.     

An Analytic Network Process approach for siting a municipal solid waste plant in the Metropolitan Area of Valencia (Spain)

In this paper the Analytic Network Process (ANP) is applied to select the best location for the construction of a municipal solid waste (MSW) plant in the Metropolitan area of Valencia (Spain). Selection of the appropriate MSW facility location can be viewed as a complex multicriteria decision-making problem that requires an extensive evaluation process of the potential MSW plant locations and other factors as diverse as economic, technical, legal, social or environmental issues. The decision-making process includes the identification of six candidate MSW plant sites and 21 criteria grouped into clusters for the construction of a network. Two technicians of the Metropolitan Waste Disposal Agency acted as decision makers (DMs).The influences between the elements of the network were identified and analyzed using the ANP multicriteria decision method. Two different ANP models were used: one hierarchy model (that considers AHP as a particular case of ANP) and another network-based model. The results obtained in each model were compared and analyzed. The strengths and weaknesses of ANP as a multicriteria decision analysis tool are also described in the paper. The main findings of this research have proved that ANP is a useful tool to help technicians to make their decision process traceable and reliable. Moreover, this approach helps DMs undertake a sound reflection of the siting problem.     

Fuzzy adaptive management of social and ecological carrying capacities for protected areas

Commonly used methods of evaluating the degree of consistency of protected area ecosystems with social and ecological carrying capacities are likely to result in decision errors. This occurs because such methods do not account for imprecision and uncertainty in inferring the degree of ecosystem consistency from an observed ecosystem indicator. This paper proposes a fuzzy adaptive management approach to determine whether a protected area ecosystem is consistent with ecological and social carrying capacities and, if not, to identify management actions that are most likely to achieve consistency when there is uncertainty about the current degree of consistency and how alternative management actions are likely to influence that consistency. The proposed approach is illustrated using a hypothetical example that uses an ecosystem indicator that reflects combinations of different levels of user satisfaction and conservation of threatened and endangered species. Application of the proposed fuzzy adaptive management approach requires a protected area manager to: (1) identify alternative management actions for achieving ecosystem consistency with social and ecological carrying capacities in each of several management zones in a protected area; (2) randomly assign alternative management actions to management zones; (3) define fuzzy sets for the ecosystem indicator and degree of ecosystem consistency, and fuzzy relations between the ecosystem indicator and the degree of ecosystem consistency; (4) monitor the indicator in each management zone; (5) define fuzzy sets based on the observed indicator in each management zone; and (6) combine the fuzzy sets defined on the observed indicator and the fuzzy relations between the indicator and the degree of ecosystem consistency to reach conclusions about the most likely degree of consistency for alternative management actions in each management zone. The fuzzy adaptive management approach proposed here is advantageous when the benefits of avoiding the decision errors inherent with crisp and stochastic decision rules outweigh the added cost of implementing the approach.     

Interactive two-stage stochastic fuzzy programming for water resources management

In this study, an interactive two-stage stochastic fuzzy programming (ITSFP) approach has been developed through incorporating an interactive fuzzy resolution (IFR) method within an inexact two-stage stochastic programming (ITSP) framework. ITSFP can not only tackle dual uncertainties presented as fuzzy boundary intervals that exist in the objective function and the left- and right-hand sides of constraints, but also permit in-depth analyses of various policy scenarios that are associated with different levels of economic penalties when the promised policy targets are violated. A management problem in terms of water resources allocation has been studied to illustrate applicability of the proposed approach. The results indicate that a set of solutions under different feasibility degrees has been generated for planning the water resources allocation. They can help the decision makers (DMs) to conduct in-depth analyses of tradeoffs between economic efficiency and constraint-violation risk, as well as enable them to identify, in an interactive way, a desired compromise between satisfaction degree of the goal and feasibility of the constraints (i.e., risk of constraint violation).     

SELECTION AND SUSTAINABILITY OF LAND AND WATER RESOURCE MANAGEMENT SYSTEMS1

ABSTRACT: Most spatial decision support systems for natural resource planning and management are limited by their scenario-based (non-behavioral), deterministic (non-stochastic) structure. A spatial decision support system is developed that uses a multiple attribute decision-making model to explain how a property manager selects a land and water resource management system (LWRMS) based on its multiple, stochastic economic and environmental attributes. The decision support system assesses sustainable resource management at the property and watershed scales and identifies the most cost-effective policy for enhancing sustainable resource management. Economic attributes are determined with an economic model and environmental attributes are simulated with an environmental model. Input parameters for both models are generated with a geographic information system. The decision support system is used to rank five LWRMS for a sample of 20 farmers in Missouri's Goodwater Creek watershed and for two hypothetical watershed alliance groups. Results indicate that the average farmer and the two alliance groups would rank the five LWRMS in the same manner. From the viewpoint of the watershed alliance, the most preferred LWRMS for the average farmer in the watershed is sustainable.     

Group decision-making for leakage management strategy of water network

The problem of leakage is complex and requires actions drawn from different aspects of water network management. Inadequate maintenance has serious consequences, both financial and environmental. This paper proposes a group decision-making model based on PROMETHEE V method to aim a leakage management strategy, which takes into account the points of view of four stakeholders, selecting feasible options, and considering the available budget as constraint. Thus, this strategy is the combination of options that will efficiently meet technical, socio-economic and environmental criteria to achieve sustainable development.     

An Interval-Parameter Waste-Load-Allocation Model for River Water Quality Management Under Uncertainty

A simulation-based interval quadratic waste load allocation (IQWLA) model was developed for supporting river water quality management. A multi-segment simulation model was developed to generate water-quality transformation matrices and vectors under steady-state river flow conditions. The established matrices and vectors were then used to establish the water-quality constraints that were included in a water quality management model. Uncertainties associated with water quality parameters, cost functions, and environmental guidelines were described as intervals. The cost functions of wastewater treatment units were expressed in quadratic forms. A water-quality planning problem in the Changsha section of Xiangjiang River in China was used as a study case to demonstrate applicability of the proposed method. The study results demonstrated that IQWLA model could effectively communicate the interval-format uncertainties into optimization process, and generate inexact solutions that contain a spectrum of potential wastewater treatment options. Decision alternatives can be generated by adjusting different combinations of the decision variables within their solution intervals. The results are valuable for supporting local decision makers in generating cost-effective water quality management strategies.     

Multiple attribute evaluation of landscape management

Economic approaches to the valuation of ecological services have several limitations. Some of these limitations can be overcome using the multiple attribute decision-making model developed in this paper. The model postulates that a private or public decision-maker selects a site/landscape management plan based on the biophysical and economic attributes of alternative management plans, the decision-maker’s preferences for attributes, and constraints on the selection of a management plan.Two cases are examined. Case A is a watershed consisting of publicly owned land that is managed at the site, management unit and landscape scales. Management is based on the philosophy of ecosystem management. Case B is a watershed composed of several privately owned units that are managed at the site scale by decision-makers whose primary motivation is economic profit. The preferred management plan in both cases is determined using a two-stage procedure. The first stage uses a stochastic programming model to identify the most efficient management plans for a site/landscape. The second stage determines which efficient management plan for a site/landscape is preferred by maximizing an expected utility function that is additive in the attributes and assumes that the decision-maker is risk neutral.Whether a land-management plan results in strongly or weakly sustainable resource conditions is evaluated. Strong sustainability requires the probability of exceeding the minimum acceptable value of an attribute to be greater than or equal to a pre-determined reliability level for each attribute. Weak sustainability requires the same condition except that it applies to a composite index of the attributes rather than each attribute. Bayes theorem is used to evaluate uncertainty about whether the state of a landscape is sustainable.     

Analyzing the factors affecting environmental risks of projects using a hybrid approach of DEMATEL‐ANP,artificial neural network: A case study

The increasing growth of the economy in each country necessitates a great amount of investment in infrastructure. The belief that projects involve various uncertainties, such as technical skills, management quality, and the like, indicates that most projects fail to achieve their aims, interests, costs, as well as their timeframes and space requirements. As the environment can pose significant uncertainty to any project, environmental risks should be deeply studied by project management departments. This study intends to analyze as a case the environmental risk management system within a consulting firm. From this analysis, each aspect of a project's environmental risk management is ranked using a fuzzy analytical network process (ANP), a neural network algorithm, and a decision‐making trial and evaluation laboratory (DEMATEL) methodology. From the organizational aspect, budget risk is the most significant. From the technical aspect, the risk of regulations is the most important one. Finally, the risk of project failure from poor communication is another identified main risk in this research. By studying high‐ranking items in this hierarchy, it can be understood that these criteria exist in different aspects; therefore, all aspects of the risk should be taken into account to cover and assess risk. A neural network algorithm for validating and reassessment of ranking is employed. Results of this application showed that, based on Spearman's rank correlation method, two different approaches resulted in similar rankings. Finally, some practical implications for responding to the most highly ranked risks are proposed.     

Integrated resource assessment and sustainable land use

Decision makers and planners in resource sectors recognize, at least in theory, the multiple uses of land, reflecting possible choices and options for society, and the need to evaluate the economic, social, and environmental implications of these choices. As such, the need for integrated resource management is now widely accepted in resource planning. This article contributes to the understanding of sustainable resource development through a specific case study. An integrated analytical system is developed and applied to the Peace River Region, British Columbia, Canada, to examine the impacts of a wide range of land-use options and policies upon the achievement of multiple resource use goals. The results indicate that an integrated approach in land resource analysis is not only possible but a necessary step in the move to develop procedures for assisting public decision makers in integrating the diverse functions of the land resource base and to revise demands or develop alternative strategies in order to move society closer to sustainable outcomes.     

Electricity price and Southern California’s water supply options

This paper evaluates the impact of fluctuating electricity prices on the cost of five options to increase the water supply to urban areas in Southern California—new surface storage, water purchases, desalination, wastewater recycling, and conservation.We show that the price of electricity required to produce and transport water influences the cost of water supply options and may alter the decision makers economic ranking of these options. When electricity prices are low, water purchase is the cost effective option. When prices exceed US$ 86/MWh, conservation of electricity and water through installation of high efficiency clothes washers is the most effective option.     

Uncertainty and risk in wildland fire management: a review

Wildland fire management is subject to manifold sources of uncertainty. Beyond the unpredictability of wildfire behavior, uncertainty stems from inaccurate/missing data, limited resource value measures to guide prioritization across fires and resources at risk, and an incomplete scientific understanding of ecological response to fire, of fire behavior response to treatments, and of spatiotemporal dynamics involving disturbance regimes and climate change. This work attempts to systematically align sources of uncertainty with the most appropriate decision support methodologies, in order to facilitate cost-effective, risk-based wildfire planning efforts. We review the state of wildfire risk assessment and management, with a specific focus on uncertainties challenging implementation of integrated risk assessments that consider a suite of human and ecological values. Recent advances in wildfire simulation and geospatial mapping of highly valued resources have enabled robust risk-based analyses to inform planning across a variety of scales, although improvements are needed in fire behavior and ignition occurrence models. A key remaining challenge is a better characterization of non-market resources at risk, both in terms of their response to fire and how society values those resources. Our findings echo earlier literature identifying wildfire effects analysis and value uncertainty as the primary challenges to integrated wildfire risk assessment and wildfire management. We stress the importance of identifying and characterizing uncertainties in order to better quantify and manage them. Leveraging the most appropriate decision support tools can facilitate wildfire risk assessment and ideally improve decision-making.     

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.     

An Evaluation of Multiple Objective Decision Support Weighting Techniques in Natural Resource Management

Multiple objective decision support (MODS) is a structured framework for evaluating decision alternatives against multiple, and often conflicting, criteria. Its ability to handle complex trade-offs in a variety of quantitative and qualitative units gives it much potential in the field of natural resource management (NRM). A key component of MODS is the process used to obtain information from decision makers on the relative importance of evaluative criteria. Ranking algorithms then use this information to determine the relative value of each decision alternative. This paper explores how practising community based NRM decision makers respond to five generic methods for weighting the criteria. It presents a study in which 55 decision makers throughout five regions in Queensland, Australia, applied MODS to evaluate environmental projects seeking funding under the Australian Natural Heritage Trust. Weighting methods applied include fixed point scoring, rating, ordinal ranking, a graphical method and paired comparisons. Decision makers evaluated each weighting method in terms of ease of use and of how much it helped clarify the decision problem. Results show that decision makers felt uncomfortable applying fixed point scoring and generally preferred to express their preferences through ordinal ranking. This has implications for the types of ranking algorithms that can be applied to evaluate the decision alternatives.     

A practical real option methodology for the evaluation of farm-in/out joint venture agreements in mineral exploration

Although the “real option valuation” (ROV) methodology offers extremely valuable insights in optimising investment decisions in the face of uncertainty, its practical acceptance in the mining industry has until recently been slow because of its perceived computational complexity. Recent conceptual advances in the use of binomial lattices and software developments in the areas of decision trees and dynamic programming, have significantly simplified ROV analysis and made it of practical application in day-to-day financial evaluations and decisions involving uncertainty. This paper provides general background on the ROV methodology and an example of how a typical farm-in/out agreement, as a preliminary to the establishment of a joint venture (JV), can be valued as a series of sequential and compound real options. For illustrative and quality assurance purposes, a simple farm-in/out agreement is valued from the point of view of the party acquiring equity in the project (the farm-inee) using two distinct methods, i.e. (a) a binomial lattice and (b) a decision tree in combination with binomial stochastic processes, in both cases neutralising risk using the user-friendly “risk-neutral probability”. The fact that exactly the same ROV is obtained by both methods provides confidence in the modified decision tree approach, which opens up the capacity to value the more complex sequential/compound real options inherent in real-life farm-in/out agreements. The model is then modified to incorporate a number of realistic contractual conditions often encountered in typical exploration and mining farm-in/out deals. The paper demonstrates how the increased complexity of the model can be relatively easily addressed using a decision tree with dynamic programming capability.     

Local Institutional Development and Organizational Change for Advancing Sustainable Urban Water Futures

This paper presents the local institutional and organizational development insights from a five-year ongoing interdisciplinary research project focused on advancing the implementation of sustainable urban water management. While it is broadly acknowledged that the inertia associated with administrative systems is possibly the most significant obstacle to advancing sustainable urban water management, contemporary research still largely prioritizes investigations at the technological level. This research is explicitly concerned with critically informing the design of methodologies for mobilizing and overcoming the administrative inertia of traditional urban water management practice. The results of fourteen in-depth case studies of local government organizations across Metropolitan Sydney primarily reveal that (i) the political institutionalization of environmental concern and (ii) the commitment to local leadership and organizational learning are key corporate attributes for enabling sustainable management. A typology of five organizational development phases has been proposed as both a heuristic and capacity benchmarking tool for urban water strategists, policy makers, and decision makers that are focused on improving the level of local implementation of sustainable urban water management activity. While this investigation has focused on local government, these findings do provide guideposts for assessing the development needs of future capacity building programs across a range of different institutional contexts.     

Water Management Decision Making in the Face of Multiple Forms of Uncertainty and Risk

In the Wasatch Range Metropolitan Area of Northern Utah, water management decision makers confront multiple forms of uncertainty and risk. Adapting to these uncertainties and risks is critical for maintaining the long‐term sustainability of the region's water supply. This study draws on interview data to assess the major challenges climatic and social changes pose to Utah's water future, as well as potential solutions. The study identifies the water management adaptation decision‐making space shaped by the interacting institutional, social, economic, political, and biophysical processes that enable and constrain sustainable water management. The study finds water managers and other water actors see challenges related to reallocating water, including equitable water transfers and stakeholder cooperation, addressing population growth, and locating additional water supplies, as more problematic than the challenges posed by climate change. Furthermore, there is significant disagreement between water actors over how to best adapt to both climatic and social changes. This study concludes with a discussion of the path dependencies that present challenges to adaptive water management decision making, as well as opportunities for the pursuit of a new water management paradigm based on soft‐path solutions. Such knowledge is useful for understanding the institutional and social adaptations needed for water management to successfully address future uncertainties and risks.