Coupling hydrologic and economic modeling for wetland management multi-optimization in Tram Chim National Park,Vietnam

We developed a comprehensive coupling framework with a multi-objective optimization that bridges a water balance model (WBM) and a wetland service model (WSM) to supporting wetland management. The framework was tested for management in Tram Chim National Park (with four wetland zones) where hydro-economic optimization was needed. The framework used (1) a model coupling process bridging WBM and WSM to create a modular hydro-economic model (MHEM), (2) a multi-objective optimization, and (3) an anneal scheduling for scenario optimization. The framework demonstrated its competency in identifying cause–effect/interaction flows (bridges) between WBM and WSM to design MHEM to simulate optimized scenarios; for the case study, the multi-objective optimization was met for all wetland zones. Results suggested a flexible consideration of management scales for optimization, i.e. hydrologic optimization at a zone level and net benefit optimization at a Park level. Our framework is applicable to supporting complex wetland decisions considering multiple objectives.     

Jordan’s climate change governance framework: from silos to an intersectoral approach

Jordan is not immune from climate change impacts. The complex characteristics (cross-boundary, multi-level, multi-sector, multi-agency settings, long-term challenges, and uncertainty) and long-term impacts of climate change confront Jordan’s decision-makers with a pressing question: Is the current governance framework adequate to respond coherently to the climate change impact, or is a new framework needed for future preparedness? To address this question, four qualitative research methods were applied to collect data reflecting diverse views about issues and in different contexts. Data were examined from different perspectives to aid in validating the conclusions. Results show that there are limitations in the current climate change governance framework. Better understanding of the intersectoral approach is necessary to develop appropriate adaptation and mitigation strategies that recognize the full extent of climate change vulnerability, rather than viewing single sectors in isolation. Accordingly, an intersectoral coordination roadmap was proposed to support the implementation of Jordan’s climate change policy (2013–2020).     

基于Kriging模型的载人航天某装置结构优化设计研究

对于处在振动环境中的载人航天某装置复杂结构,设计过程中存在最小化质量、同时最大化一阶整体振动频率的多目标优化问题,可以利用多目标遗传算法(NSGA-II)求解得到Pareto最优解集,但利用NSGA-II进行求解计算量大,对于复杂结构更甚。为了节省计算时间,提出基于Kriging代理模型的复杂结构多目标优化设计方法,首先通过拉丁超立方采样获得样本点,然后通过样本点创建Kriging模型,最后利用多目标遗传算法求解代理模型得到Pareto最优解集,方便设计师从中选择最优解,优化结果表明本文所述方法合理有效。     

Fusing strategic risk and futures methods to inform long-term strategic planning: case of water utilities

Risks and futures methods have complementary strengths as tools for managing strategic decisions under uncertainty. When combined, these tools increase organisational competency to evaluate and manage long-term risks, improving the flexibility and agility of the organisation to deal with gross uncertainties. Here, we set out a framework to guide the assessment of strategic risks for long-term business planning, based on its application at Portugal’s largest water utility, Empresa Portuguesa das Águas Livres. Our approach extends strategic risk assessment by incorporating scenario planning—a futures approach used to help the utility move beyond single point forecast of risks to focus on critical dimensions of uncertainty that are fundamental to the resilience of corporate objectives and their vulnerability to external pressures. We demonstrate how we combine two complementary approaches—risk and futures—and use them to assess (i) how a set of baseline strategic risks for a water utility evolves under alternative futures, (ii) the aggregate corporate-level risk exposure, and (iii) the process and responses needed to manage multiple, interdependent strategic risks. The framework offers a corporate approach to evolving strategic risks and improves a utility’s (i) knowledge of uncertainties, (ii) ability to assess the impacts of external developments over long time horizons and the consequences of actions and (iii) degree of flexibility to adapt to possible future challenges. The framework supports risk managers in their long-term strategic planning, through the appraisal and management of multiple, interdependent long-term strategic risks and can be replicated in other organisational contexts to bridge operational and corporate perspectives of enterprise risk.

     

INTEGRATED MODELING FOR WATERSHED MANAGEMENT: MULTIPLE OBJECTIVES AND SPATIAL EFFECTS1

ABSTRACT: This paper presents an optimization framework for prioritizing sites for wetlands restoration on a watershed or landscape scale. The framework is designed for analyzing the potential environmental impacts of alternative management strategies while accounting for economic constraints, thereby aiding decision makers in explicitly considering multiple management objectives. The modeling strategy consists of two phases. First, relationships between the configuration of land use types in a watershed and valued ecosystem services are specified mathematically. Second, those functions are incorporated into a spatial optimization model that allows comparisons of the expected environmental impacts and economic costs of management strategies that change the configuration of land use in the watershed. By way of a stylized example, this paper develops the general structure of the framework, presents simulation results based on two production functions for ecosystem services, and discusses the potential utility of the methodology for watershed management.     

Multi-objective optimization of waste and resource management in industrial networks – Part II: Model application to the treatment of sewage sludge

In the present article, the thermal treatment of digested sewage sludge generated in the Swiss region of Zürich is modeled and optimized from an environmental perspective. The optimization problem is solved using a multi-objective mixed-integer linear program that combines material flow analysis, process models, life cycle assessment (LCA), and mathematical optimization techniques. The treatment options include co-incineration in municipal solid waste incineration, co-processing in cement production, and mono-incineration with the prospect of phosphorus recovery. The model is optimized according to six environmental objectives. Five of the six single-objective optimal solutions involve splits over the treatment options. The results reflect the available treatment capacities and other constraints, aspects rarely considered in conventional LCA studies. Co-processing in cement production is used to the maximum extent possible when minimizing impacts on climate change, human toxicity, fossil resource depletion, and fully aggregated impacts (ReCiPe H/A), whereas mono-incineration with phosphorus recovery receives the bulk of the sludge when optimizing for ecotoxicity and mineral resource depletion. Four of the single-objective optimal solutions (minimization of fossil energy resource depletion and contribution to climate change, human toxicity, and fully aggregated impacts) outperform the reference case over the six impact categories considered, showing that the current situation can be improved in some environmental categories without compromising others. The results of the sensitivity analysis indicate that assumptions regarding the product systems displaced by recovered by-products are critical for the outcome of the optimization. Our approach identifies in all of the cases solutions in which significant environmental improvements can be attained.     

A Conceptual Approach for a Quantitative Economic Analysis of Farmers’ Decision-Making Regarding Animal Welfare

Decisions related to animal welfare (AW) standards depend on farmer’s multiple goals and values and are constrained by a wide range of external and internal forces. The aim of this paper is twofold, i.e., (1) to develop a theoretical framework for farmers’ AW decisions that incorporates farmers’ goals, use and non-use values and (2) to present an approach to empirically implement the theoretical framework. The farmer as a head of the farm household makes choices regarding production to maximize the utility of the household. The overall utility of the farmer is determined by his multiple objectives. For the analysis of multi-objective problems, the multiple criteria decision-making paradigm provides an appropriate theoretical framework. However, theories from the field of social-psychology are needed to facilitate the identification of all relevant aspects in the decision making (i.e., factors that explain behavior). The practical use of the conceptual framework is demonstrated using a simple numerical application of a multi-objective programming model. Two workshops were devoted to examining the scientific consistency and the practical usefulness of the approach. Implementing this approach will increase knowledge of the main factors and barriers that determine farmers’ decisions with regard to AW standards. This knowledge is relevant during the development of new AW concepts that aims to supply products that comply with above-legal AW standards for middle-market segments.     

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.     

System Dynamics to Sustainable Water Resources Management in the Eastern Snake Plain Aquifer Under Water Supply Uncertainty1

Abstract: Water supply uncertainty continues to threaten the reliability of regional water resources in the western United States. Climate variability and water dispute potentials induce water managers to develop proactive adaptive management strategies to mitigate future hydroclimate impacts. The Eastern Snake Plain Aquifer in the state of Idaho is also facing these challenges in the sense that population growth and economic development strongly depend on reliable water resources from underground storage. Drought and subsequent water conflict often drive scientific research and political agendas because water resources availability and aquifer management for a sustainable rural economy are of great interest. In this study, a system dynamics approach is applied to address dynamically complex problems with management of the aquifer and associated surface‐water and groundwater interactions. Recharge and discharge dynamics within the aquifer system are coded in an environmental modeling framework to identify long‐term behavior of aquifer responses to uncertain future hydrological variability. The research shows that the system dynamics approach is a promising modeling tool to develop sustainable water resources planning and management in a collaborative decision‐making framework and also to provide useful insights and alternative opportunities for operational management, policy support, and participatory strategic planning to mitigate future hydroclimate impacts in human dimensions.     

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.     

ENVIRONMENTAL AUDITING: A Synoptic Approach for Assessing Cumulative Impacts to Wetlands

/ The US Environmental Protection Agency's Wetlands ResearchProgram has developed the synoptic approach as a proposed method forassessing cumulative impacts to wetlands by providing both a general and acomprehensive view of the environment. It can also be applied more broadly toregional prioritization of environmental issues. The synoptic approach is aframework for making comparisons between landscape subunits, such aswatersheds, ecoregions, or counties, thereby allowing cumulative impacts tobe considered in management decisions. Because there is a lack of tools thatcan be used to address cumulative impacts within regulatory constraints, thesynoptic approach was designed as a method that could make use of availableinformation and best professional judgement. Thus, the approach is acompromise between the need for rigorous results and the need for timelyinformation. It is appropriate for decision making when quantitative,accurate information is not available; the cost of improving existinginformation or obtaining better information is high; the cost of a wronganswer is low; there is a high demand for the information; and the situationcalls for setting priorities between multiple decisions versus optimizing fora single decision. The synoptic approach should be useful for resourcemanagers because an assessment is timely; it can be completed within one totwo years at relatively low cost, tested, and improved over time. Anassessment can also be customized to specific needs, and the results arepresented in mapped format. However, the utility of a synoptic assessmentdepends on how well knowledge of the environment is incorporated into theassessment, relevant to particular management questions.KEY WORDS: Cumulative impact assessment; Landscape ecology; Regionalprioritization     

On process optimization considering LCA methodology

The goal of this work is to research the state-of-the-art in process optimization techniques and tools based on LCA, focused in the process engineering field. A collection of methods, approaches, applications, specific software packages, and insights regarding experiences and progress made in applying the LCA methodology coupled to optimization frameworks is provided, and general trends are identified. The "cradle-to-gate" concept to define the system boundaries is the most used approach in practice, instead of the "cradle-to-grave" approach. Normally, the relationship between inventory data and impact category indicators is linearly expressed by the characterization factors; then, synergic effects of the contaminants are neglected. Among the LCIA methods, the eco-indicator 99, which is based on the endpoint category and the panel method, is the most used in practice. A single environmental impact function, resulting from the aggregation of environmental impacts, is formulated as the environmental objective in most analyzed cases. SimaPro is the most used software for LCA applications in literature analyzed. The multi-objective optimization is the most used approach for dealing with this kind of problems, where the ε-constraint method for generating the Pareto set is the most applied technique. However, a renewed interest in formulating a single economic objective function in optimization frameworks can be observed, favored by the development of life cycle cost software and progress made in assessing costs of environmental externalities. Finally, a trend to deal with multi-period scenarios into integrated LCA-optimization frameworks can be distinguished providing more accurate results upon data availability.     

An integrated impact assessment and weighting methodology: evaluation of the environmental consequences of computer display technology substitution

Computer display technology is currently in a state of transition, as the traditional technology of cathode ray tubes is being replaced by liquid crystal display flat-panel technology. Technology substitution and process innovation require the evaluation of the trade-offs among environmental impact, cost, and engineering performance attributes. General impact assessment methodologies, decision analysis and management tools, and optimization methods commonly used in engineering cannot efficiently address the issues needed for such evaluation. The conventional Life Cycle Assessment (LCA) process often generates results that can be subject to multiple interpretations, although the advantages of the LCA concept and framework obtain wide recognition. In the present work, the LCA concept is integrated with Quality Function Deployment (QFD), a popular industrial quality management tool, which is used as the framework for the development of our integrated model. The problem of weighting is addressed by using pairwise comparison of stakeholder preferences. Thus, this paper presents a new integrated analytical approach, Integrated Industrial Ecology Function Deployment (I2-EFD), to assess the environmental behavior of alternative technologies in correlation with their performance and economic characteristics. Computer display technology is used as the case study to further develop our methodology through the modification and integration of various quality management tools (e.g., process mapping, prioritization matrix) and statistical methods (e.g., multi-attribute analysis, cluster analysis). Life cycle thinking provides the foundation for our methodology, as we utilize a published LCA report, which stopped at the characterization step, as our starting point. Further, we evaluate the validity and feasibility of our methodology by considering uncertainty and conducting sensitivity analysis.     

Incorporating Complex Adaptive Systems Theory into Strategic Planning: The Sierra Nevada Conservancy

Conservation organizations rely increasingly on integrated planning approaches that explicitly address social and economic goals while pursuing ecological conservation. Moreover, the spatial and temporal scale at which these organizations operate is growing. The Sierra Nevada Conservancy, established as a new state agency by California legislation in 2004 to pursue social, economic and ecological sustainability across a 25 million acre region, exemplifies this large-scale, integrated approach. Therefore, the new agency faces a complex set of policy objectives that must be pursued across a widely varying geography of social, economic and ecological conditions. Using the Conservancy's fire management program area as an example, the paper illustrates how application of an analytic framework from complex adaptive systems theory can guide the Conservancy to deploy its resources more effectively than broader-scale application of a single, agency-wide strategy relying on a more static model. Therefore, the complex adaptive systems framework offers promise in strategic planning. The paper illustrates how the model's four-stage cycle can be applied at the sub-regional and programmatic level to identify opportunities for agency intervention that address varying local conditions. This approach is likely to increase the effectiveness of programs for agencies facing similar complexities and challenges.     

Multi-objective optimization of a novel crude lipase-catalyzed fatty acid methyl ester (FAME) production using low-order polynomial and Kriging models

In this paper, conventional response surface methodology (RSM) based on low-order polynomials and an alternative Kriging-based method are used for the model-based single and multi-objective optimization of fatty-acid methyl ester (FAME) production catalyzed by a novel crude lipase from the yeast Cryptococcus diffluens (D44). The coefficient of determination for the two modeling approaches was calculated as 0.97 for the Kriging method, and 0.86 for RSM; showing a more reliable representation of experimental data by Kriging. Both models were used to perform single (maximizing FAME titer and temporal productivity separately) and multi-objective (maximizing FAME titer and temporal productivity simultaneously) optimizations of four important operating conditions (reaction time and temperature; amount of crude enzyme; and volume of methanol used). In all cases, the highest temperature considered (60°C) gave the best results. A reduction of reaction time in half was seen to be necessary to achieve optimum productivity compared to titer, when the two objectives were considered separately. The observed trade-off between the two objectives was quantified via multi-objective optimization using Pareto-front analysis.     

Design for environment: A new framework for strategic decisions

For most of its history of environmental protection, U.S. policy has concentrated on a pollution control strategy based on single medium emissions: air, water, or land. Efforts to mitigate environmental impacts to one medium often resulted in greater impacts to others. While much environmental improvement has occurred via this system over the last quarter-century, it is generally recognized that alternative strategies which address environmental impacts across all media in an integrated manner will be necessary for continued improvement. Increasingly, regulatory strategies that result in only passive compliance will be insufficient to meet these demands. This article demonstrates why new strategies which encourage proactive behavior are necessary. A new framework for making strategic decisions—design for environment—concerning the relation between our actions and environment is necessary to ensure a sustainable future.     

Measuring Positive,Negative, and Null Impacts of Forest Disturbances: A Case Study Using Dwarf Mistletoe on Douglas Fir

Not all disease activity causes an impact. Not all impacts are negative. The aim of this study was to examine a method that could conceptually specify when impacts occur and that could quantify both negative and positive disease impacts. For this study, dwarf mistletoe (Arceuthobium douglasi) of Douglas fir (Pseudotsuga menziesii) in southwestern Oregon was used as a case study. The method uses six variables for forest growth, mortality, and stand structure, and six categorical disease severity scores. The impact model displays stands as points in multidimensional scaling space, where relative position is determined by values of the six stand variables. Positions in this two-dimensional space change when stand characteristics change. Differences associated with disease severity could be traced as trajectories, and impact was quantified using the length and direction of these trajectories. This multivariate impact assessment method was contrasted to impact assessments based on single variables. Methods based on multiple variables offer a useful way of characterizing impact on multiple objectives. The model indicates that dwarf mistletoe has positive, negative, and neutral impacts and that these could be illustrated and quantified using this method.     

Nonparametric Monte Carlo Simulation for Flood Frequency Curve Derivation: An Application to a Korean Watershed1

Abstract: A mix of causative mechanisms may be responsible for flood at a site. Floods may be caused because of extreme rainfall or rain on other rainfall events. The statistical attributes of these events differ according to the watershed characteristics and the causes. Traditional methods of flood frequency analysis are only adequate for specific situations. Also, to address the uncertainty of flood frequency estimates for hydraulic structures, a series of probabilistic analyses of rainfall‐runoff and flow routing models, and their associated inputs, are used. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated to evaluate the probability of floods. Therefore, the objectives of this study were to develop a flood frequency curve derivation method driven by multiple random variables and to develop a tool that can consider the uncertainties of design floods. This study focuses on developing a flood frequency curve based on nonparametric statistical methods for the estimation of probabilities of rare floods that are more appropriate in Korea. To derive the frequency curve, rainfall generation using the nonparametric kernel density estimation approach is proposed. Many flood events are simulated by nonparametric Monte Carlo simulations coupled with the center Latin hypercube sampling method to estimate the associated uncertainty. This study applies the methods described to a Korean watershed. The results provide higher physical appropriateness and reasonable estimates of design flood.     

Sustainable construction--the role of environmental assessment tools

Construction has been accused of causing environmental problems ranging from excessive consumption of global resources both in terms of construction and building operation to the pollution of the surrounding environment, and research on green building design and using building materials to minimise environmental impact is already underway. However, relying on the design of a project to achieve the goal of sustainable development, or to minimise impacts through appropriate management on site, is not sufficient to handle the current problem. The aim for sustainability assessment goes even further than at the design stage of a project to consider its importance at an early stage, before any detailed design or even before a commitment is made to go ahead with a development. However, little or no concern has been given to the importance of selecting more environmentally friendly designs during the project appraisal stage; the stage when environmental matters are best incorporated. The main objectives of this paper are to examine the development, role and limitations of current environmental building assessment methods in ascertaining building sustainability used in different countries which leads to discuss the concept of developing a. sustainability model for project appraisal based on a multi-dimensional approach, that will allow alternatives to be ranked is discussed in detail in the paper.