Evaluating mine plans under uncertainty: Can the real options make a difference?

Over the last few years, many studies have presented the real options valuation (ROV) as a promising technique of valuing natural resource investments under conditions of uncertainty. Apart from the common conclusion that the ROV is better than the conventional net present value (NPV) method in integrating the value of management flexibility and proper handling of cash flows risk, there is a lack of procedures for testing the usefulness and advantages of the ROV over the static NPV method in practice. Arguably, it is not yet clear whether the ROV can deal with the complexity of mining projects and whether it can really be applied to make decisions that improve project value.     

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.     

Risk-based evaluation of wastewater treatment projects: A case study in Niasar city,Iran

For sustainable wastewater management, it is essential to consider social, environmental, geological and technical features as well as economic feature in the decision-making process. A limitation of many of the earlier works on wastewater management is that they take into account only financial criteria to make a decision for a given problem. Moreover, the decision-makers’ (DMs) attitude to risk, or optimism degree, when faced with uncertainty is not considered. In this paper, we study the application of risk-based multi-attribute decision-making (RB-MADM) methods to achieve sustainable wastewater management. Consideration of uncertainty, value tradeoffs, and different risk attitudes of decision makers are the important features of the developed methodology. A case study on the Iranian city of Niasar is presented to illustrate how this methodology can be applied to select the most preferred alternative for wastewater management among a set of options. The most preferred option is selected with respect to nine attributes under different optimism/pessimism degrees, using six different MADM methods. The results show that the ranking of options is sensitive to the optimism degree of the DMs. The proposed approach may help policy makers to achieve sustainable wastewater management.     

IFRP: a hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty

In this study, an interval-parameter fuzzy-robust programming (IFRP) model is developed and applied to the planning of solid waste management systems under uncertainty. As an extension of the existing fuzzy-robust programming and interval-parameter linear programming methods, the IFRP can explicitly address system uncertainties with complex presentations. Parameters in the IFRP model can be represented as interval numbers and/or fuzzy membership functions, such that the uncertainties can be directly communicated into the optimization process and resulting solution. Furthermore, highly uncertain information for the lower and upper bounds of interval parameters that exist due to the complexity of the real world can be effectively handled through introducing the concept of fuzzy boundary interval. Consequently, robustness of the optimization process and solution can be enhanced. Results of the case study indicate that useful solutions for planning municipal solid waste management practices can be generated. They reflect a compromise between optimality and stability of the study system. Willingness to pay higher costs will guarantee the system stability; however, a desire to reduce the costs will run the risk of potential instability of the system. The results also suggest that the proposed hybrid methodology is applicable to practical problems that are associated with highly complex and uncertain information.     

Evaluating a small deposit next to an economically viable gold mine in West Africa from the points of view of the mining company,the government and the local community

This paper addresses the question of evaluating how much the different stakeholders stand to gain from a mining project. By carefully analysing the breakdown of the cash-flows generated, we were able to estimate the amounts received by the local community and by the national community (outside the mining area), the taxes and royalties received by the government and the profits made by the mining company. A real options framework was used to take account of the inherent uncertainty on the commodity price and the reserves, and the operating flexibility (that is, the possibility for the company to stop mining if the commodity price drops and/or the reserves prove to be lower than that had been envisaged). A synthetic case-study of a gold mine in West Africa was used to illustrate how this procedure could be applied in practice. By using the real option framework we were able to envisage scenarios for developing an extension to a deposit as a function of future values of the commodity price. The procedure proposed should provide governments and NGOs with more objective data for making policy decisions.     

Valuing uncertain asset cash flows when there are no options: A real options approach

The real option valuation method is often presented as an alternative to the traditional discounted cash flow (DCF) approach because it is able to quantify the additional asset value arising from flexible asset management. However, these two valuation methods differ on a more fundamental level: their approach to determining the effects of cash flow uncertainty on asset value. Real option valuation adjusts for risk within the cash flow components while the DCF method discounts for risk at the aggregate net cash flow. This seemingly small difference allows the real option method to differentiate assets according to their unique risk characteristics, while the conventional DCF approach cannot.This paper presents an overview of the real options and conventional DCF frameworks for valuing uncertain cash flows. To emphasize the approaches' different treatment of risk we assume an absence of managerial flexibility. Using simple algebra, this paper demonstrates that the traditional DCF method fails to adequately discount net cash flow risk, no matter what discount rate is used. Finally, in a stylized mining example we show that DCF rules would lead a developer to forego $24.5 million in value creation, at a profitability index of 1.49, by making a poor investment decision.     

Upscaling of Environmental Information: Support of Land-Use Management Decisions by Spatio-Temporal Regionalization Approaches

This article presents several case studies in southwest Germany, which aimed to support land use management decisions by a process-oriented statistical upscaling of point-related environmental monitoring data to the landscape scale. When techniques of data subsetting were used in a sensible way and corresponding to the appropriate scale for the evaluation envisaged, multiple linear regression offered a data mining technique which was able to spatially predict relatively complex environmental patterns with parsimonious, interpretable and accurate models, whereby different evaluation scales were best represented by different DTM resolutions. Scenario models based upon the regression formulas were a valuable tool for visualizing management options and evaluating management impacts (tree species selection) on soil functions (carbon storage), which qualifies the presented methodology as a useful aid in decision making. Such upscaling techniques may be used for forecasting long-term effects of ecosystem management, but they provided no information on temporal dynamics. Therefore, time trends of point information on soil solution data were scaled by linking them to soil chemical data which was available in higher spatial resolution, using both statistical and process-oriented methods.     

MULTICRITERIA PROGRAMMING OF WATER SUPPLY SYSTEMS FOR RURAL AREAS1

ABSTRACT: The aim of this paper is to present a multicriteria methodology for decision aid at the stage of programming a water supply system (WSS) for a rural area. The programming stage is an intermediate one between planning and designing water supply facilities, and can be decomposed into two problems: (a) setting up a priority order of water users, taking into account socio-economic criteria; and (b) choosing the best technical variant of the WSS. Among the criteria considered for the latter problem, there is a criterion of distance between the socio-economic priorities of users and the precedence orders of users according to the technical programming, which plays a coordinating role between problems (a) and (b). All steps of the presented methodology are illustrated by a real case study.     

Strategic Environmental Assessment of Greenhouse Gas Mitigation Options in the Canadian Agricultural Sector

This article presents a methodological framework for strategic environmental assessment (SEA) application. The overall objective is to demonstrate SEA as a systematic and structured policy, plan, and program (PPP) decision support tool. In order to accomplish this objective, a stakeholder-based SEA application to greenhouse gas (GHG) mitigation policy options in Canadian agriculture is presented. Using a mail-out impact assessment exercise, agricultural producers and nonproducers from across the Canadian prairie region were asked to evaluate five competing GHG mitigation options against 13 valued environmental components (VECs). Data were analyzed using multi-criteria and exploratory analytical techniques. The results suggest considerable variation in perceived impacts and GHG mitigation policy preferences, suggesting that a blanket policy approach to GHG mitigation will create gainers and losers based on soil type and associate cropping and on-farm management practices. It is possible to identify a series of regional greenhouse gas mitigation programs that are robust, socially meaningful, and operationally relevant to both agricultural producers and policy decision makers. The assessment demonstrates the ability of SEA to address, in an operational sense, environmental problems that are characterized by conflicting interests and competing objectives and alternatives. A structured and systematic SEA methodology provides the necessary decision support framework for the consideration of impacts, and allows for PPPs to be assessed based on a much broader set of properties, objectives, criteria, and constraints whereas maintaining rigor and accountability in the assessment process.     

Mining and social development: Refocusing community investment using multi-criteria decision analysis

This paper addresses the question: How can mining companies assess social investment projects so that projects create value for the company and communities in which they operate? Mining companies are still wrestling with the limits of their responsibility in relation to social development even though they accept the business case for community investment at a general level. Fully aware of the practical hazards involved in taking an active role in facilitating local development, companies increasingly avoid methods that are overly paternalistic or assume the functions of the national or local governments. Gaining senior management's commitment to long-term social projects, which are characterised by uncertainty and complexity, is made easier if projects are shown to benefit the site's strategic goals. Case study research on large global mining companies, including interviews with social investment decision makers, has assisted in developing a Social Investment Decision Analysis Tool (SIDAT), a decision model for evaluating social projects. Multi-criteria decision analysis techniques integrating business planning processes with social impact assessment have proved useful in assisting mining companies think beyond seeking reputational benefits, to how they can meet their business goals and contribute to sustainable development.     

Land Resources Allocation Strategies in an Urban Area Involving Uncertainty: A Case Study of Suzhou,in the Yangtze River Delta of China

A large number of mathematical models have been developed to support land resource allocation decisions and land management needs; however, few of them can address various uncertainties that exist in relation to many factors presented in such decisions (e.g., land resource availabilities, land demands, land-use patterns, and social demands, as well as ecological requirements). In this study, a multi-objective interval-stochastic land resource allocation model (MOISLAM) was developed for tackling uncertainty that presents as discrete intervals and/or probability distributions. The developed model improves upon the existing multi-objective programming and inexact optimization approaches. The MOISLAM not only considers economic factors, but also involves food security and eco-environmental constraints; it can, therefore, effectively reflect various interrelations among different aspects in a land resource management system. Moreover, the model can also help examine the reliability of satisfying (or the risk of violating) system constraints under uncertainty. In this study, the MOISLAM was applied to a real case of long-term urban land resource allocation planning in Suzhou, in the Yangtze River Delta of China. Interval solutions associated with different risk levels of constraint violation were obtained. The results are considered useful for generating a range of decision alternatives under various system conditions, and thus helping decision makers to identify a desirable land resource allocation strategy under uncertainty.     

An inexact optimization approach for river water-quality management

A previously developed fuzzy waste load allocation model (FWLAM) for a river system is extended to address uncertainty involved in fixing the membership functions for the fuzzy goals of the pollution control agency (PCA) and the dischargers using the concept of grey systems. The model provides flexibility for the PCA and the dischargers to specify their goals independently, as the parameters for membership functions are considered as interval grey numbers instead of deterministic real numbers. An inexact or a grey fuzzy optimization model is developed in a multiobjective framework, to maximize the width of the interval valued fractional removal levels for providing latitude in decision-making and to minimize the width of the goal fulfillment level for reducing the system uncertainty. The concept of an acceptability index for order relation between two partially or fully overlapping intervals is used to get a deterministic equivalent of the grey fuzzy optimization model developed. The improvement of the optimal solutions over a previously developed grey fuzzy waste load allocation model (GFWLAM) is shown through an application to a hypothetical river system. The fuzzy multiobjective optimization and fuzzy goal programming techniques are used to solve the deterministic equivalent of the GFWLAM.     

A dual-interval fixed-mix stochastic programming method for water resources management under uncertainty

In this study, a dual-interval fixed-mix stochastic programming (DFSP) method is developed for planning water resources management systems under uncertainty. DFSP incorporates interval-parameter programming (IPP) and fuzzy vertex analysis (FVA) within a fixed-mix stochastic programming (FSP) framework to address uncertain parameters described as probability distributions and dual intervals. It can also be used for analyzing various policy scenarios that are associated with different levels of economic consequences since penalties are exercised with recourse actions against any infeasibility. A real case for water resources management planning of Zhangweinan River Basin in China is then conducted for demonstrating the applicability of the developed DFSP method. Solutions in association with α-cut levels are generated by solving a set of deterministic submodels, which are useful for generating a range of decision alternatives under compound uncertainties. The results can help to identify desired water-allocation schemes for local sustainable development that the prerequisite water demand can be guaranteed when the available water resource is scarce.     

Multi-Criteria Decision Analysis of Treated Wastewater Use for Agriculture in Water Deficit Regions1

Al-Juaidi, Ahmed E., Jagath J. Kaluarachchi, and Ungtae Kim, 2010. Multi-Criteria Decision Analysis of Treated Wastewater Use for Agriculture in Water Deficit Regions. Journal of the American Water Resources Association (JAWRA) 46(2):395-411. DOI: 10.1111/j.1752-1688.2009.00409.x Abstract: Coastal regions such as the Gaza Strip of Palestine with limited freshwater supply suffer significantly due to the rapid depletion of water levels, seawater intrusion, and increased water demands. In such regions, use of treated wastewater (TWW) is a viable option if public health issues are addressed. The goal of this paper is to address the use of TWW in agriculture while considering net benefit, economic efficiency of water use (EEWU), environmental goals, and public health risks. The proposed methodology considers public health risk assessment and multi-criteria decision analysis to assess the beneficial use of TWW in agriculture. The methodology was demonstrated for the Gaza Strip. The health risk assessment suggests that increasing the elapsed time between irrigation and consumption and switching from surface to sprinkler and drip irrigation are practical measures to reduce public health risks. The optimization and decision analyses show that proper allocation of freshwater and TWW and distribution of land area by crop type can significantly increase the net benefit and EEWU. In most cases, net benefit increased by 44%, groundwater use reduced 29% while increasing the EEWU by threefold compared with the existing conditions. The multi-criteria decision analysis with weighted goal programming can develop flexible management options that considers a given decision-maker preference. When groundwater abstraction for agriculture reduced from 57 to 36 Mm³ as per decision analysis, the corresponding area below mean sea level decreased by 58% indicating significant aquifer recovery.     

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.     

ANALYSIS OF A KARSTIC AQUIFER MANAGEMENT PROBLEM BY FUZZY COMPOSITE PROGRAMMING1

ABSTRACT: A multiple objective framework for water resources problems possessing uncertain or imprecise elements is provided using distance-based concepts, fuzzy set theory, and fuzzy arithmetic. The case of regional management of a karstic aquifer in Hungary in which six conflicting objectives and six alternatives have been identified illustrates the methodology The objectives are classified into three groups of two objectives each, namely: (1) environmental (aesthetics, thermal springs temperature), (2) economic (mining, tourism), and (3) water quality (nitrates, phosphates). Both environmental objectives are formulated under fuzziness, and all objectives are scaled using the extension principle. Fuzzy compromise programming (FCP-I) is then applied; here, all six objectives are entered in a single l_p norm measuring the distance between each alternative and an ideal point. Next, fuzzy composite programming (FCP-II) is developed; here, a trade off is first made within each group of objectives, and then an upper level trade-off takes place between the three groups. The fuzzy numbers describing each alternative as a result from applying these techniques are ranked to yield an ordering of the alternatives. The results of applying FCP.I, FCP-II, and two different ordering techniques are compared. The FCP-II technique appears to provide a relatively simple approach at hierarchical or multilevel multiple objective decision-making, where uncertainty is described by fuzziness. (KEY TERMS: compromise programming; fuzzy arithmetic; fuzzy sets; hierarchical criteria; karstic aquifer; l_p, norms; mining; multiple objectives; thermal springs.)     

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.     

Assessing development options in mining communities using stated preference techniques

In this paper, two key insights are generated about community development options using stated preference techniques. Surveys were conducted to identify how residents of a mining town in central Queensland, Australia, viewed options for the development of their township. First, residents were asked in a Choice Modelling experiment how worthwhile it would be to achieve some more attractive development options if it came at a cost to them. Second, residents were asked in a Choice Behaviour experiment how the different development options might influence their decision to stay or shift from the town in the future. The same development options were used in both experiments to facilitate comparisons between the two assessment forms.     

Mineral reserves under price uncertainty

National reporting organizations and regulatory bodies for the minerals and mining sector are requiring publicly reported Ore-Reserve estimates to take account of uncertainties. Whilst methodologies that account for physical uncertainty appear relatively well developed, methodologies which can take account of economic uncertainty appear much less so. To counter this shortfall, we present an efficient and general methodology which can quantify the effect of price uncertainty within reserve estimates, providing both the expected reserve size and the associated distribution (box whisker plot). This statistical information can be used by interested parties to understand precisely where the reserve risks lie, which we highlight in a worked example.