Multi-criteria decision-making considering risk and uncertainty in physical asset management

In this work we present a method for risk-informed decision-making in the physical asset management context whereby risk evaluation and cost-benefit analysis are considered in a common framework. The methodology uses quantitative risk measures to prioritize projects based on a combination of risk tolerance criteria, cost-benefit analysis and uncertainty reduction metrics. There is a need in the risk and asset management literature for a unified framework through which quantitative risk can be evaluated against tolerability criteria and trade-off decisions can be made between risk treatment options. The methodology uses quantitative risk measures for loss of life, loss of production and loss of property. A risk matrix is used to classify risk as intolerable, As Low As Reasonably Practicable (ALARP) or broadly tolerable. Risks in the intolerable and ALARP region require risk treatment, and risk treatment options are generated. Risk reduction benefit of the treatment options is quantified, and cost-benefit analysis is performed using discounted cashflow analysis. The Analytic Hierarchy Process is used to derive weights for prioritization criteria based on decision-maker preferences. The weights, along with prioritization criteria for risk reduction, tolerance criteria and project cost, are used to prioritize projects using the Technique for Order Preference by Similarity to Ideal Solution. The usefulness of the methodology for improved decision-making is illustrated using a numerical example.     

Catchment-Wide Wetland Assessment and Prioritization Using the Multi-Criteria Decision-Making Method TOPSIS

It is widely accepted that wetland ecosystems are under threat worldwide. Many communities are now trying to establish wetland rehabilitation programs, but are confounded by a lack of objective information on wetland condition or significance. In this study, a multi-criteria decision-making method, TOPSIS (the Technique for Order Preference by Similarity to Ideal Solution), was adapted to assist in the role of assessing wetland condition and rehabilitation priority in the Clarence River Catchment (New South Wales, Australia). Using 13 GIS data layers that described wetland character, wetland protection, and wetland threats, the wetlands were ranked in terms of condition. Through manipulation of the original model, the wetlands were prioritized for rehabilitation. The method offered a screening tool for the managers in choosing potential candidate wetlands for rehabilitation in a region.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

An Objective Multiattribute Analysis Approach for Allocation of Scarce Irrigation Water Resources1

Zardari, Noor ul Hassan, Ian Cordery, and Ashish Sharma, 2010. An Objective Multiattribute Analysis Approach for Allocation of Scarce Irrigation Water Resources. Journal of the American Water Resources Association (JAWRA) 46(2):412-428. DOI: 10.1111/j.1752-1688.2009.00410.x Abstract: In this study, end user (farmer) and decision maker (water allocator) opinions were surveyed and a conjoint analysis (CA) based method was applied to the quantitative and qualitative data to assess the utility associated with each attribute that plays a role in forming the final thinking of the water users. The application of CA for estimating the utility for each attribute level is a novel approach, which helps provide a formal, objective basis for assigning relative scales for each attribute interval within a multiattribute decision-making model. The utilities (part-worths) obtained from the CA have a cardinal scale and were found to be comparable within and across the attributes. A farmers’ survey on five water allocation attributes was completed from 62 farmers and their opinions on the relative importance of attributes were elicited for a subarea of the Indus River Basin. The CA method was then applied to the survey data and the utilities for each attribute level were determined. This allowed, for instance, decisions to be made, which take account of the perceived value of the water and of the availability of local labor to work on the farm. Finally, these interval scales were used within the specification of the ELECTRE multiattribute decision-making method to provide a complete and objective ranking of nine irrigation districts so that the best decisions on water allocation could be made.     

Setting the most robust effluent level under severe uncertainty: Application of information-gap decision theory to chemical management

Decisions in ecological risk management for chemical substances must be made based on incomplete information due to uncertainties. To protect the ecosystems from the adverse effect of chemicals, a precautionary approach is often taken. The precautionary approach, which is based on conservative assumptions about the risks of chemical substances, can be applied selecting management models and data. This approach can lead to an adequate margin of safety for ecosystems by reducing exposure to harmful substances, either by reducing the use of target chemicals or putting in place strict water quality criteria. However, the reduction of chemical use or effluent concentrations typically entails a financial burden. The cost effectiveness of the precautionary approach may be small. Hence, we need to develop a formulaic methodology in chemical risk management that can sufficiently protect ecosystems in a cost-effective way, even when we do not have sufficient information for chemical management. Information-gap decision theory can provide the formulaic methodology. Information-gap decision theory determines which action is the most robust to uncertainty by guaranteeing an acceptable outcome under the largest degree of uncertainty without requiring information about the extent of parameter uncertainty at the outset. In this paper, we illustrate the application of information-gap decision theory to derive a framework for setting effluent limits of pollutants for point sources under uncertainty. Our application incorporates a cost for reduction in pollutant emission and a cost to wildlife species affected by the pollutant. Our framework enables us to settle upon actions to deal with severe uncertainty in ecological risk management of chemicals.     

水污染突发事件：演化模型与应急管理

概述了突发事件演化研究的现状,总结了现阶段中国水污染突发事件的典型案例,研究了事件的演化过程,提出把社会因素和全过程干预作为水污染突发事件演化动因的一个重要方面,并在此基础上分析了水污染突发事件演化的主要动力因素,运用灾害学、应急管理、环境科学等相关理论构建了事件演化的动力因素体系,最后从系统分析的角度构建了水污染突发事件演化模型。研究表明：社会因素和应急干预对水污染突发事件的演化具有推动作用;事件演化具有阶段性,不同阶段的动力因素存在差异;水污染突发事件应急管理具有多目标性,单一目标应急管理不能有效控制水污染突发事件演化。研究水污染突发事件演化机理可为政府有效地预警与事件初期的应急决策提供重要的理论依据。     

A spatially explicit backcasting approach for sustainable land-use planning

General backcasting as a decision support and planning method starts from desired future states and simulates developments backwards until reaching the present state. Development pathways that reveal steps to be taken to reach a certain future state, and milestones that serve as interim goals, are created during the process. Backcasting has hitherto only been applied in workshops or as a theoretical framework and no spatially explicit backcasting model has previously been established. This paper presents the development of a spatially explicit backcasting model. The proposed model first creates a future scenario utilizing an agent-based model and then simulates backwards. It is implemented using the programming language Python. The model has been applied to a case study for sustainable land-use planning in Salzburg, Austria. The results of the model run show a successful backcasting of land-use classes from a future state back to the present, in 10 year time steps.     

Getting caught up in the game: managing non-formal dynamics in the remediation of contaminated sediments in Oslo harbor

This study aims at describing, analyzing and evaluating the relation between management styles and process dynamics of a complex planning process confronted with unexpected dynamics. The development of an aquatic disposal site for dredged contaminated sediments in Oslo was managed by a project management style focused on timely and cost-effective implementation. Coupling the remediation project with another infrastructural project and the actual construction of the site led to unexpected dynamics in terms of resistance and controversy. Project management had difficulties in adjusting its style accordingly, resulting in even more delay and resistance. Managing complex planning projects requires a style suitable to the characteristics of the project and the capability of adjusting it to changing circumstances. The paper concludes with some explanations why it is difficult to change management styles in complex planning and implementation processes and complexity-embracing approaches to deal with this.     

Ecosystem services assessments in local municipal decision making in South Africa: justification for the use of a business-based approach

The ecosystem services (ES) concept is being increasingly incorporated into environmental policy formulation and management approaches. The Corporate Ecosystem Services Review (ESR) is a framework used to assess the dependence and impact that a business has on ES. The success of the corporate experience of ES assessment provides an opportunity for adaption for local authority decision making. In this paper, the ESR tool was adapted to the South African setting at a local government level, and tested at two sites in the Msunduzi Municipality, KwaZulu-Natal. In testing the tool and gathering feedback from key stakeholders, it was found that there are both opportunities and challenges to this approach. Overall, however, it provides an opportunity for the systematic inclusion of ES assessment into existing regulatory frameworks for land-use planning and Integrated Environmental Management, whether in a strategic application, at a broader spatial (municipal) scale or in a specific locale within the municipality.     

多源信息融合技术在内陆湖库水华预警中的研究进展与展望

面对水体富营养化愈来愈严重,水华爆发越来越频繁的严峻形式;为减少水华发生频率及由此造成的损失,开展水华预警已成当务之急。水华爆发是水体中营养盐的累积、气候条件与水力条件等众多因素非线性共同作用的产物;为此,有必要在众多水华影响因素的动态监测信息的融合基础上,寻求水华爆发与这些影响因素间的影射关系,这就需要信息融合技术。通过归纳总结多源信息融合技术在内陆湖库水华预警中应用的研究进展,结合目前我国水华预警的具体需求,提出建立基于多源信息融合技术的水华预警决策支持系统的研究前景与初步设想。信息融合技术为水华预警提供了一个良好的平台,它将与水华相关的不同信息源（水文、气象、水环境质量与环境遥感）所提供的局部不完整的观测信息加以集成与互补,消除多源信息之间存在的冗余和矛盾,形成对水华爆发环境相对完整的感知与描述;从而提高水华预警与应急响应决策的效率,提高预警信息的时间与空间分辨率,扩展信息的时空监测范围。