复杂河流系统水污染的计算机图形模拟

讨论在河流系统水污染规划中应用交互式计算机图形技术。通过对复杂河流系统水污染的图形模拟,提出建立图模型的一般理论和方法,并就浑太流域河流水污染案例给出实际模拟结果。     

Decision making with option pricing and dynamic programming: development and application

In this study, an option pricing model and a dynamic programming model are developed. These models contribute to the improvement of the decision making process in two respects. First, these models allow for the own growth rate of mining costs to be incorporated into the analysis. Second, these models are developed to estimate the satisfactory gross revenue for investing, so that these models are helpful in analyzing multi-metal mines.The two models are applied to estimate the satisfactory revenue for investing in the Carlin east gold mine, Nevada, USA. The satisfactory revenue estimated by the option pricing model is found to be $42.2M, while that estimated by the dynamic programming model is found to be $44.4M. Since the revenue calculated on the basis of the current conditions is $36M, then the decision by option pricing and dynamic programming is to wait and not to invest now. Despite the difference between the two models in estimating and applying the discount rate, the two models generate the same decision.     

Major accident management in the process industry: An expert tool called CESMA for intelligent allocation of prevention investments

A tool (called CESMA) was developed to carry out cost–benefit analyses and cost-effectiveness analyses of prevention investments for avoiding major accidents. A wide variety of parameters necessary to calculate both the costs of the considered preventive measures and the benefits related with the avoidance of accidents were identified in the research. The benefits are determined by estimating the difference in (hypothetical) major accident costs without and with the implementation of a preventive measure. As many relevant costs and benefits as possible were included into the tool, based on literature and expert opinion, in order to be able to deliver an all-embracing cost–benefit analysis and cost-effectiveness analysis to assist in the investment decision process. Because major accidents are related to extremely low frequencies, the tool takes the uncertainty of the unwanted occurrence of a major accident into account through the usage of a so-called ‘disproportion factor’. Compared with existing software, the CESMA tool is innovative by striving for an as-accurate-as-possible picture of costs and benefits of major accident prevention, and taking the uncertainties accompanying disastrous events into consideration. Furthermore, an illustrative example of CESMA is presented in the paper.     

Approaches to developing risk management objectives: an analysis of international strategies

Risk assessment/management frameworks employed around the world to guide environmental decision-making were analyzed for their approaches to developing risk management objectives and the decision criteria necessary for environmental policy implementation. Frameworks from the Netherlands, the UK, Sweden, Australia/New Zealand, Canada, and the USA were considered. Progress in refining the scientific basis for risk assessment/management has been made, but there has been little parallel development in defining the mechanisms by which available scientific information may be used to define risk management goals or identify and select between management options using a priori decision criteria. The lack of detailed guidance on the setting and achievement of risk management goals that appropriately balance technical information and public input remains an important challenge to the use and practice of all risk assessment/management frameworks.     

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.     

Passive and active adaptive management: approaches and an example

Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. Yet there remains considerable confusion about what adaptive management entails, and how to actually make resource decisions adaptively. A key but somewhat ambiguous distinction in adaptive management is between active and passive forms of adaptive decision making. The objective of this paper is to illustrate some approaches to active and passive adaptive management with a simple example involving the drawdown of water impoundments on a wildlife refuge. The approaches are illustrated for the drawdown example, and contrasted in terms of objectives, costs, and potential learning rates. Some key challenges to the actual practice of AM are discussed, and tradeoffs between implementation costs and long-term benefits are highlighted.     

Adaptive management of natural resources--framework and issues

Adaptive management, an approach for simultaneously managing and learning about natural resources, has been around for several decades. Interest in adaptive decision making has grown steadily over that time, and by now many in natural resources conservation claim that adaptive management is the approach they use in meeting their resource management responsibilities. Yet there remains considerable ambiguity about what adaptive management actually is, and how it is to be implemented by practitioners. The objective of this paper is to present a framework and conditions for adaptive decision making, and discuss some important challenges in its application. Adaptive management is described as a two-phase process of deliberative and iterative phases, which are implemented sequentially over the timeframe of an application. Key elements, processes, and issues in adaptive decision making are highlighted in terms of this framework. Special emphasis is given to the question of geographic scale, the difficulties presented by non-stationarity, and organizational challenges in implementing adaptive management.     

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.     

Use of decision analysis interviews to support the sustainable use of the forests in Finnish Upper Lapland

Controversy between alternative uses of forests in Finnish Upper Lapland has been going on for decades, and in recent years it has been escalated to a serious conflict. The core of the conflict is the adverse impacts of forestry on old forests which are important grazing areas for reindeer and which are regarded as intact nature and wilderness areas. This paper describes the experiences of applying multi-criteria decision analysis interview approach on this conflict. The approach provides tools for structuring the problem and preferences of the stakeholders as well as for analyzing the effects of different alternatives in a common framework. We focus on the practical experiences gained from the application of this approach in this context. Multi-criteria decision analysis was found to be a useful approach to evaluate the economic, ecological and cultural aspects of this intense conflict. The obtained experiences also support the view that the approach works best when tightly integrated into the planning process.