Violation analysis for solid waste management systems: an interval fuzzy programming approach

This paper introduces a violation analysis approach for the planning of regional solid waste management systems under uncertainty, based on an interval-parameter fuzzy integer programming (IPFIP) model. In this approach, several given levels of tolerable violation for system constraints are permitted. This is realized through a relaxation of the critical constraints using violation variables, such that the model's decision space can be expanded. Thus, solutions from the violation analysis will not necessarily satisfy all of the model's original constraints. Application of the developed methodology to the planning of a waste management system indicates that reasonable solutions can be generated through this approach. Considerable information regarding decisions of facility expansion and waste flow allocation within the waste management system were generated. The modeling results help to generate a number of decision alternatives under various system conditions, allowing for more in-depth analyses of tradeoffs between environmental and economic objectives as well as those between system optimality and reliability.     

A data mining approach to simulating farmers' crop choices for integrated water resources management

Water and land resources in Thailand are increasingly under pressure from development. In particular, there are many resource conflicts associated with agricultural production in northern Thailand. Communities in these areas are significantly constrained in the land and water management decisions they are able to make. This paper describes the application of a data mining approach to describing and simulating farmers' decision rules in a catchment in northern Thailand. This approach is being applied to simulate social, economic and biophysical constraints on farmers' decisions in these areas as part of an integrated water management model.     

ICCLP: An Inexact Chance-Constrained Linear Programming Model for Land-Use Management of Lake Areas in Urban Fringes

Lake areas in urban fringes are under increasing urbanization pressure. Consequently, the conflict between rapid urban development and the maintenance of water bodies in such areas urgently needs to be addressed. An inexact chance-constrained linear programming (ICCLP) model for optimal land-use management of lake areas in urban fringes was developed. The ICCLP model was based on land-use suitability assessment and land evaluation. The maximum net economic benefit (NEB) was selected as the objective of land-use allocation. The total environmental capacity (TEC) of water systems and the public financial investment (PFI) at different probability levels were considered key constraints. Other constraints included in the model were land-use suitability, governmental requirements on the ratios of various land-use types, and technical constraints. A case study implementing the system was performed for the lake area of Hanyang at the urban fringe of Wuhan, central China, based on our previous study on land-use suitability assessment. The Hanyang lake area is under significant urbanization pressure. A 15-year optimal model for land-use allocation is proposed during 2006 to 2020 to better protect the water system and to gain the maximum benefits of development. Sixteen constraints were set for the optimal model. The model results indicated that NEB was between $1.48 × 10⁹ and $8.76 × 10⁹ or between $3.98 × 10⁹ and $16.7 × 10⁹, depending on the different urban-expansion patterns and land demands. The changes in total developed area and the land-use structure were analyzed under different probabilities (q _i ) of TEC. Changes in q _i resulted in different urban expansion patterns and demands on land, which were the direct result of the constraints imposed by TEC and PFI. The ICCLP model might help local authorities better understand and address complex land-use systems and develop optimal land-use management strategies that better balance urban expansion and grassland conservation.     

Adaptive management in the U.S. National Wildlife Refuge System: science-management partnerships for conservation delivery

Adaptive management is an approach to recurrent decision making in which uncertainty about the decision is reduced over time through comparison of outcomes predicted by competing models against observed values of those outcomes. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service is a large land management program charged with making natural resource management decisions, which often are made under considerable uncertainty, severe operational constraints, and conditions that limit ability to precisely carry out actions as intended. The NWRS presents outstanding opportunities for the application of adaptive management, but also difficult challenges. We describe two cooperative programs between the Fish and Wildlife Service and the U.S. Geological Survey to implement adaptive management at scales ranging from small, single refuge applications to large, multi-refuge, multi-region projects. Our experience to date suggests three important attributes common to successful implementation: a vigorous multi-partner collaboration, practical and informative decision framework components, and a sustained commitment to the process. Administrators in both agencies should consider these attributes when developing programs to promote the use and acceptance of adaptive management in the NWRS.     

Risk Management of Sediment Stress: A Framework for Sediment Risk Management Research

Research related to the ecological risk management of sediment stress in watersheds is placed under a common conceptual framework in order to help promote the timely advance of decision support methods for aquatic resource managers and watershed-level planning. The proposed risk management research program relies heavily on model development and verification, and should be applied under an adaptive management approach. The framework is centered on using best management practices (BMPs), including eco-restoration. It is designed to encourage the development of numerical representations of the performance of these management options, the integration of this information into sediment transport simulation models that account for uncertainty in both input and output, and would use strategic environmental monitoring to guide sediment-related risk management decisions for mixed land use watersheds. The goal of this project was to provide a sound scientific framework based on recent state of the practice in sediment-related risk assessment and management for research and regulatory activities. As a result, shortcomings in the extant data and measurement and modeling tools were identified that can help determine future research direction. The compilation of information is beneficial to the coordination of related work being conducted within and across entities responsible for managing watershed-scale risks to aquatic ecosystems.     

A multi-objective optimisation approach to water management

The management of river basins is complex especially when decisions about environmental flows are considered in addition to those concerning urban and agricultural water demand. The solution to these complex decision problems requires the use of mathematical techniques that are formulated to take into account conflicting objectives. Many optimization models exist for water management systems but there is a knowledge gap in linking bio-economic objectives with the optimum use of all water resources under conflicting demands. The efficient operation and management of a network of nodes comprising storages, canals, river reaches and irrigation districts under environmental flow constraints is challenging. Minimization of risks associated with agricultural production requires accounting for uncertainty involved with climate, environmental policy and markets. Markets and economic criteria determine what crops farmers would like to grow with subsequent effect on water resources and the environment. Due to conflicts between multiple goal requirements and the competing water demands of different sectors, a multi-criteria decision-making (MCDM) framework was developed to analyze production targets under physical, biological, economic and environmental constraints. This approach is described by analyzing the conflicts that may arise between profitability, variable costs of production and pumping of groundwater for a hypothetical irrigation area.     

Using system dynamics to model water-reallocation

Improving the efficiency of water allocation has long been recognised as a key problem for the water resources management decision-makers. However, assessing the efficacy of management decision is difficult due to the complexity and interconnectivity of water resource systems. For this reason, it is vital that robust modelling approaches are employed to deal with the feedback loops inherent in the water resource systems. Whilst many studies have applied modelling to various aspects of water resource management, little attention has been given to innovations in modelling approaches to deal with the modelling challenges associated with improving decision-making. The aim of this study is to apply a System Dynamics modelling approach to improve the efficiency of water allocation incorporating a myriad of irrigation system constraints. The system dynamic approach allows the different system components to be organised as a collection of discrete objects that incorporate data, structure and function to generate complex system behaviour. Through the application of a system dynamic approach, a robust model (named the Economical Reallocating Water Model (ERWM)) was developed which was used to examine the options of re-allocating water resources that minimize the water cost all over an irrigated agricultural area. The EWRM incorporated a wide range of complexities likely to be encountered in water resource management: surface and ground water sources, water trading between sources, system constraint such as maximum ground water pumping, rates, maximum possible trading volumes and differential water resource prices. Two hypothetical systems have been presented here as an example. The results show that the System Dynamics approach has a significant advantages in estimating and assessing the outcomes of alternative water management strategies through time and space.     

Optimal Land Use Management for Soil Erosion Control by Using an Interval-Parameter Fuzzy Two-Stage Stochastic Programming Approach

Soil erosion is one of the most serious environmental and public health problems, and such land degradation can be effectively mitigated through performing land use transitions across a watershed. Optimal land use management can thus provide a way to reduce soil erosion while achieving the maximum net benefit. However, optimized land use allocation schemes are not always successful since uncertainties pertaining to soil erosion control are not well presented. This study applied an interval-parameter fuzzy two-stage stochastic programming approach to generate optimal land use planning strategies for soil erosion control based on an inexact optimization framework, in which various uncertainties were reflected. The modeling approach can incorporate predefined soil erosion control policies, and address inherent system uncertainties expressed as discrete intervals, fuzzy sets, and probability distributions. The developed model was demonstrated through a case study in the Xiangxi River watershed, China’s Three Gorges Reservoir region. Land use transformations were employed as decision variables, and based on these, the land use change dynamics were yielded for a 15-year planning horizon. Finally, the maximum net economic benefit with an interval value of [1.197, 6.311] × 10⁹ $ was obtained as well as corresponding land use allocations in the three planning periods. Also, the resulting soil erosion amount was found to be decreased and controlled at a tolerable level over the watershed. Thus, results confirm that the developed model is a useful tool for implementing land use management as not only does it allow local decision makers to optimize land use allocation, but can also help to answer how to accomplish land use changes.     

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).     

ASSESSING ENVIRONMENTAL EFFECTS OF SEVERE SUSTAINED DROUGHT1

ABSTRACT: Evaluation criteria for reservoir and stream resources were developed to provide decision makers with feedback on environmental consequences of water allocation decisions under conditions of severe sustained drought within the Colorado River Basin by using the AZCOL gaming simulation model. Seven categories of flow dependent resources were identified which highlight resource states associated with reservoirs or river reaches within the AZCOL model. AZCOL directly simulates impact of water management decisions on five resource categories: threatened, endangered or sensitive fish; native nonlisted fish; wetland and riparian elements; national or state wildlife refuges; and hatcheries or other flow dependent facilities. Two additional categories - cold and warm water sport fish - are not modeled explicitly but are incorporated in the evaluation of monetary benefits from recreation on Colorado River waters. Each resource category was characterized at each time step in the simulation according to one of four environmental states: stable, threatened, endangered, or extirpated. Changes in resource states were modeled by time and flow-dependent decision criteria tied to either reservoir level or stream flows within the AZCOL model structure. Gaming results using the AZCOL model indicate environmental impacts would be substantial and that water allocation decisions directly impacted environmental resource states.     

Inexact multistage stochastic integer programming for water resources management under uncertainty

In this study, an inexact multistage stochastic integer programming (IMSIP) method is developed for water resources management under uncertainty. This method incorporates techniques of inexact optimization and multistage stochastic programming within an integer programming framework. It can deal with uncertainties expressed as both probabilities and discrete intervals, and reflect the dynamics in terms of decisions for water allocation through transactions at discrete points of a complete scenario set over a multistage context. Moreover, the IMSIP can facilitate analyses of the multiple policy scenarios that are associated with economic penalties when the promised targets are violated as well as the economies-of-scale in the costs for surplus water diversion. A case study is provided for demonstrating the applicability of the developed methodology. The results indicate that reasonable solutions have been generated for both binary and continuous variables. For all scenarios under consideration, corrective actions can be undertaken dynamically under various pre-regulated policies and can thus help minimize the penalties and costs. The IMSIP can help water resources managers to identify desired system designs against water shortage and for flood control with maximized economic benefit and minimized system-failure risk.     

A stochastic fuzzy chance-constrained programming model for energy–environment system planning and management in the City of Beijing

A stochastic and fuzzy chance-constrained programming (SFCCP) model was developed in this study for supporting energy–environment management in the city of Beijing, China. SFCCP was capable of tackling the variables in constraints as fuzzy random variables, which were integration of randomness and vagueness. SFCCP was applied to an energy–environment management system in the city of Beijing. The study results indicated that SFCCP was useful in helping decision makers gain in-depth insights into proposed management system and establish environment-friendly energy allocation alternatives. The application of SFCCP is expected to provide a good demonstration to energy–environment management problems under complex uncertainties.     

Resolution of an uncertain closed-loop logistics model: An application to fuzzy linear programs with risk analysis

With the urgency of global warming, green supply chain management, logistics in particular, has drawn the attention of researchers. Although there are closed-loop green logistics models in the literature, most of them do not consider the uncertain environment in general terms. In this study, a generalized model is proposed where the uncertainty is expressed by fuzzy numbers. An interval programming model is proposed by the defined means and mean square imprecision index obtained from the integrated information of all the level cuts of fuzzy numbers. The resolution for interval programming is based on the decision maker (DM)’s preference. The resulting solution provides useful information on the expected solutions under a confidence level containing a degree of risk. The results suggest that the more optimistic the DM is, the better is the resulting solution. However, a higher risk of violation of the resource constraints is also present. By defining this probable risk, a solution procedure was developed with numerical illustrations. This provides a DM trade-off mechanism between logistic cost and the risk.     

The effect of recycling price uncertainty on municipal waste management choices

This paper analyzes the effect of price uncertainty and irreversible investment on the decision of municipalities to switch from landfill waste disposal to recycling by developing a model to predict recycling adoption behavior and applying it to empirical data. It is shown that uncertainty regarding the price of recycled materials may induce a risk neutral municipality to prefer landfill disposal, even when recycling is less expensive. A model is developed to describe the switching process and estimate its parameters using empirical data from 79 municipalities in Israel. The model is then used to predict municipalities' recycling adoption decisions under various assumptions regarding price uncertainty. The results support the hypothesis that price uncertainty is a major obstacle for recycling. Finally, several options for price stabilization are sketched and it is argued that these policies may be effective in establishing viable recycling markets.     

PLANNING METHODOLOGY FOR ANALYSIS AND MANAGEMENT ON LAKE EUTROPHICATION1

ABSTRACT: The effects of changing nutrient inputs through land use management, waste water treatment, or effluent diversion are not clear, and managers are discovering that decisions which were effective in reversing eutrophication for one lake are often unsuccessful when applied to another. Simple empirical relationships are often used to predict the impact of management decisions. Errors in estimation could result in either substantial costs for overdesign or failure to meet desired eutrophication levels. This paper presents and illustrates a methodology to evaluate the impact of land use and water resource management decisions on lake eutrophication. The problems of worth of additional information, and uncertainty of estimates were handled within a cost-effectiveness framework. The probability of exceeding a critical level of eutrophication was considered as a measure of effectiveness. The cost criterion is the expected value of opportunity costs, costs of analysis and costs of additional information. Uncertainty analysis techniques were used to estimate the effectiveness of various management alternatives. Bayesian methods can be utilized to determine the worth of additional information. The methodology was applied to Beseck Lake, Connecticut, and the cost and effectiveness measures estimated for a number of land management alternatives. Worth of additional information was not determined in this initial effort in uncertainty analysis for lake eutrophication management.     

Licensing resource tracts : A comparison of auction and discretionary systems

This paper uses simulations of a model of a company's decision about the maximum bid value and the optimal investment programme for a resource tract to compare the auction and discretionary systems of licence allocation. The modle includes uncertainty about the size of resource stock and the selling price of extracted resource, as well as risk aversion on the part of the company. It is concluded that an auction system provides the government both with better information about a company's perception of the value of a resource tract and with the potential for considerably higher revenue from its licensing.     

ECOSYSTEM MODELING OF A FORESTED RIVER BASIN1

ABSTRACT: A present concern in decision making processes for forest land use is the environmental effects of land use activities on water, air, and the land itself. Criteria for evaluating the magnitude and detriment of environmental impacts are not definite since it is often difficult to isolate a particular activity as the cause of a particular impact. Instead, interactions between various forest practices must be considered along with their integrated impacts. In order to provide an effective decision tool, the College of Forest Resources, University of Washington, is modeling the forest ecosystem of the Snohomish River Basin located in the Cascade Mountains of western Washington. The project consists of a general system model comprised of subsystem models dealing with product conversion processes, forest production processes, recreation supply processes, wildlife and fisheries supply processes, and the interactions of these processes with water and the atmosphere. The system model is interfaced with a computerized multiple player management game which enables land managers, manufacturing managers, and regulation agency personnel to make management decisions and respond to indications of lack of environmental control. Responses of the hydrologic system to various management decisions are simulated by the water subsystem model. The responses being considered include surface flow quantity and water quality. The model emphasizes the monitoring of non-point as well as point source impacts rather than predicting short-term hydrographs. The significance of impacts vary with land use patterns and the goals of the game player. Therefore, the model has flexible resolution and is able to predict hydrologic conditions for both large and small scale. The water subsystem model responds to management decisions by interpreting the effects of management options selected by game players for 40-acre cells within the Basin. The model then determines which streams are immediately affected, defines the watersheds contributing to these streams, and extracts from a resource data bank the information needed to define model parameters. Using these parameters and precipitation inputs, mean flow discharge on a montly and annual basis is calculated for the impactcd sub watersheds as well as 21 major watersheds of the Basin. Water quality responses predicted for these watersheds include suspended sediment concentration, temperature increases due to stream exposure, dissolved oxygen concentrations, the effects of fertilization on nitrogen content, biocide and herbicide effects, and residues from product conversion processes.     

Inexact fuzzy-stochastic mixed integer programming approach for long-term planning of waste management–––Part B: Case study

In this study, a solid waste decision-support system was developed for the long-term planning of waste management in the City of Regina, Canada. Interactions among various system components, objectives, and constraints will be analyzed. Issues concerning planning for cost-effective diversion and prolongation of the landfill will be addressed. Decisions of system-capacity expansion and waste allocation within a multi-facility, multi-option, and multi-period context will be obtained. The obtained results would provide useful information and decision-support for the City's solid waste management and planning. In the application, four scenarios are considered. Through the above scenario analyses under different waste-management policies, useful decision support for the City's solid waste managers and decision makers was generated. Analyses for the effects of varied policies (for allowable waste flows to different facilities) under 35 and 50% diversion goals were also undertaken. Tradeoffs among system cost and constraint-violation risk were analyzed.Generally, a policy with lower allowable waste-flow levels corresponded to a lower system cost under advantageous conditions but, at the same time, a higher penalty when such allowances were violated. A policy with higher allowable flow levels corresponded to a higher cost under disadvantageous conditions. The modeling results were useful for (i) scheduling adequate time and capacity for long-term planning of the facility development and/or expansion in the city's waste management system, (ii) adjusting of the existing waste flow allocation patterns to satisfy the city's diversion goal, and (iii) generating of desired policies for managing the city's waste generation, collection and disposal.     

Managing United States Public Lands in Response to Climate Change: A View From the Ground Up

Federal land managers are faced with the task of balancing multiple uses and goals when making decisions about land use and the activities that occur on public lands. Though climate change is now well recognized by federal agencies and their local land and resource managers, it is not yet clear how issues related to climate change will be incorporated into on-the-ground decision making within the framework of multiple use objectives. We conducted a case study of a federal land management agency field office, the San Juan Public Lands Center in Durango, CO, U.S.A., to understand from their perspective how decisions are currently made, and how climate change and carbon management are being factored into decision making. We evaluated three major management sectors in which climate change or carbon management may intersect other use goals: forests, biofuels, and grazing. While land managers are aware of climate change and eager to understand more about how it might affect land resources, the incorporation of climate change considerations into everyday decision making is currently quite limited. Climate change is therefore on the radar screen, but remains a lower priority than other issues. To assist the office in making decisions that are based on sound scientific information, further research is needed into how management activities influence carbon storage and resilience of the landscape under climate change.     

Sustainable Water Resources Management in a Conflict Resolution Framework1

Abstract: A decision support system for sustainable water resources management in a water conflict resolution framework is developed to identify and evaluate a range of acceptable alternatives for the Geum River Basin in Korea and to facilitate strategies that will result in sustainable water resource management. Working with stakeholders in a “shared vision modeling” framework, sustainable management strategies are created to illustrate system tradeoffs as well as long‐term system planning. A multi‐criterion decision‐making (MCDM) approach using subjective scales is utilized to evaluate the complex water resource allocation and management tradeoffs between stakeholders and system objectives. The procedures used in this study include the development of a “shared vision model,” a simulated decision‐making support system (as a tool for sustainable water management strategies associated with water conflicts, management options, and planning criteria), and the application of MCDM techniques for evaluating alternatives provided by the model. The research results demonstrate the utility of the sustainable water resource management model in aid of MCDM techniques in facilitating flexibility during initial stages of alternative identification and evaluation in a basin suffering from severe water conflicts.