Modelling the effects of ‘coastal’ acidification on copper speciation

We present here a copper speciation model that accounts for the long-term (‘coastal-acidification’) and short-term (daily and seasonal variation) variability in water pH and water temperature. The developed model is applied to a sub-tropical estuary (Moreton Bay, Australia) at a one hundred year time scale so that outputs are consistent with climate change projections. The model predicts that the mean cupric ion concentration (Cu²⁺) in the estuary will increase by 115% over the next 100 years as a result of the projected decrease in pH and increase in water temperature. Through calibration, the estimated concentration of copper-complexing dissolved organic matter (DOM) in the estuary is found to be 22.5 nM. An increase in the concentration of Cu²⁺, which is the most toxic and bioavailable form of copper, has implications for ecosystem health and may have a negative effect on the detoxifying capacity of DOM. Models that provide a framework for coupling biological, chemical and physical processes are important for providing a holistic perspective of coastal systems, especially for better understanding a system within the context of climatic and non-climatic drivers.     

Dependability assessment of network-based safety-related system

Advances in electronic integration and radio communication have led to the emergence of a new kind of safety systems, i.e. Wireless Sensor Network (WSN). This network-based safety-related system is becoming more and more present in the domain of safety due to its easy deployment. It does not need a wire infrastructure and its range of applications is wide. Usually, such a system is composed of various nodes (sensors) collaborating to monitor a targeted phenomenon. In most cases, nodes are battery powered and this is the weakness of the system makes it necessary to design an energy saving policy. The present paper gives a dependability viewpoint of such a system. A modeling framework is suggested integrating the interdependency of the components. Stochastic Petri nets are used to implement this model and two heuristics to schedule component activity. The first is based on the proposed importance measures, the second on a multi-objective genetic algorithm. The aim is to conserve energy and so to extend WSN dependability.     

Info-Gap Decision Theory for Assessing the Management of Catchments for Timber Production and Urban Water Supply

While previous studies have examined how forest management is influenced by the risk of fire, they rely on probabilistic estimates of the occurrence and impacts of fire. However, nonprobabilistic approaches are required for assessing the importance of fire risk when data are poor but risks are appreciable. We explore impacts of fire risk on forest management using as a case study a water catchment in the Australian Capital Territory (ACT) (southeastern Australia). In this forested area, urban water supply and timber yields from exotic plantations are potential joint but also competing land uses. Our analyses were stimulated by extensive wildfires in early 2003 that burned much of the existing exotic pine plantation estate in the water catchment and the resulting need to explore the relative economic benefits of revegetating the catchment with exotic plantations or native vegetation. The current mean fire interval in the ACT is approximately 40 years, making the establishment of a pine plantation economically marginal at a 4% discount rate. However, the relative impact on water yield of revegetation with native species and pines is very uncertain, as is the risk of fire under climate change. We use info-gap decision theory to account for these nonprobabilistic sources of uncertainty, demonstrating that the decision that is most robust to uncertainty is highly sensitive to the cost of native revegetation. If costs of native revegetation are sufficiently small, this option is more robust to uncertainty than revegetation with a commercial pine plantation.     

A LINEAR ANALYSIS OF AN URBAN WATER SUPPLY SYSTEM1

The use of linear programming as a planning tool for determining the optimal long-range development of an urban water supply system was explored. A stochastic trace of water demand was synthesized and used as an input to the model. This permitted evaluating the feasibility of imposing demand restrictions as an effective cost reduction mechanism. The City of Lincoln, Nebraska, was used as the urban model. The fundamental problem was to allocate limited water supplies from several sources to an urban load center to minimize costs and comply with system constraints. The study period covered twenty years, and findings indicate the planning direction for stage development during this period. Sensitivity analyses were performed on cost coefficients and demands. Thirteen sources were included in the initial computations. Conclusions were that linear programming and generated demand traces are useful tools for both short- and long-term urban water supply planning. Lowering peak demands results in long-range development of fewer sources of supply and more economic and efficient use of the supplies developed.     

基于不确定性的水资源配置双层模型及其实证研究

针对水资源管理系统的不确定性和复杂性,引入区间参数表达系统中的不确定信息,建立了反映水资源管理者和使用者之间层次关系的区间双层规划模型,并以北京市丰台区水资源管理系统为例进行实证研究.同时,基于交互式算法和模糊满意度算法,用Lingo软件编程求解,确定了丰台区水资源的优化配置方案.规划结果表明:丰台区水资源管理系统的供需水量基本达到平衡,75%的供水量来源于本地地表水和南水北调水源;规划期内的系统经济效益预期达到2.22×10~9~5.16×10~9元,COD排放量将达到1.47×10~4~1.89×10~4t.区间结果提高了优化方案的灵活性,系统满意度体现了上层决策者与下层决策者的交互.其次,通过设计4种COD最大允许排放情景,说明了不同的COD排放约束将对规划结果产生重要影响.最后,通过3种模型的对比分析可以为丰台区水资源配置提供不同发展情景下的优化方案.     

Evaluating the management strategies of a forestland estate--the S-O-S approach

Connecting Multiple Criteria Decision Support (MCDS) methods with SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis yields analytical priorities for the factors included in SWOT analysis and makes them commensurable. In addition, decision alternatives can be evaluated with respect to each SWOT factor. In this way, SWOT analysis provides the basic frame within which to perform analyses of decision situations. MCDS methods, in turn, assist in carrying out SWOT more analytically and in elaborating the results of the analyses so that alternative strategic decisions can be prioritized also with respect to the entire SWOT. The A'WOT analysis is an example of such hybrid methods. It makes combined use of the Analytic Hierarchy Process (AHP) and SWOT. In this study, a hybrid method of the Stochastic Multicriteria Acceptability Analysis with Ordinal criteria (SMAA-O) and SWOT is developed as an elaboration of the basic ideas of A'WOT. The method is called S-O-S (SMAA-O in SWOT). SMAA-O enables the handling of ordinal preference information as well as mixed data consisting of both ordinal and cardinal information. Using SMAA-O is enough to just rank decision elements instead of giving them cardinal preference or priority ratios as required by the most commonly used MCDS methods. Using SMAA-O, in addition to analyzing what the recommended action is under certain priorities of the criteria, enables one to analyze what kind of preferences would support each action. The S-O-S approach is illustrated by a case study, where the shareholders of a forest holding owned by a private partnership prepared the SWOT analysis. Six alternative strategies for the management of their forest holding and of old cottage located on the holding were formed. After S-O-S analyses were carried out, one alternative was found to be the most recommendable. However, different importance orders of the SWOT groups would lead to different recommendations, since three of the six alternatives were efficient according to S-O-S analyses.     

RESERVOIR OPERATION ANI EVALUATION OF DOWNSTREAM FLOW AUGMENTATION1

ABSTRACT: Operation of a storage‐based reservoir modifies the downstream flow usually to a value higher than that of natural flow in dry season. This could be important for irrigation, water supply, or power production as it is like an additional downstream benefit without any additional investment. This study addresses the operation of two proposed reservoirs and the downstream flow augmentation at an irrigation project located at the outlet of the Gandaki River basin in Nepal. The optimal operating policies of the reservoirs were determined using a Stochastic Dynamic Programming (SDP) model considering the maximization of power production. The modified flows downstream of the reservoirs were simulated by a simulation model using the optimal operating policy (for power maximization) and a synthetic long‐term inflow series. Comparing the existing flow (flow in river without reservoir operation) and the modified flow (flow after reservoir operation) at the irrigation project, the additional amount of flow was calculated. The reliability analysis indicated that the supply of irrigation could be increased by 25 to 100 percent of the existing supply over the dry season (January to April) with a reliability of more than 80 percent.     

An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit metal mine

Air Pollution Control model is developed for open-pit metal mines. Model will aid decision makers to select a cost-effective solution. Open-pit metal mines contribute toward air pollution and without effective control techniques manifests the risk of violation of environmental guidelines. This paper establishes a stochastic approach to conceptualize the air pollution control model to attain a sustainable solution. The model is formulated for decision makers to select the least costly treatment method using linear programming with a defined objective function and multi-constraints. Furthermore, an integrated fuzzy based risk assessment approach is applied to examine uncertainties and evaluate an ambient air quality systematically. The applicability of the optimized model is explored through an open-pit metal mine case study, in North America. This method also incorporates the meteorological data as input to accommodate the local conditions. The uncertainties in the inputs, and predicted concentration are accomplished by probabilistic analysis using Monte Carlo simulation method. The output results are obtained to select the cost-effective pollution control technologies for PM_2.5, PM₁₀, NO_x, SO₂ and greenhouse gases. The risk level is divided into three types (loose, medium and strict) using a triangular fuzzy membership approach based on different environmental guidelines. Fuzzy logic is then used to identify environmental risk through stochastic simulated cumulative distribution functions of pollutant concentration. Thus, an integrated modeling approach can be used as a decision tool for decision makers to select the cost-effective technology to control air pollution.     

Emergy-based fuzzy optimization approach for water reuse in an eco-industrial park

The establishment of an eco-industrial park (EIP) provides opportunity for individual plants to cooperate with each other in order to utilize resources efficiently and thus reduce waste. The goal of an EIP is to “close the loop” through recycling and reuse of material and energy streams. Studies show with current freshwater consumption trends there would be water stress aggravated by global warming in the near future. This paper presents a model to design an EIP water reuse network that considers overall system sustainability as measured with emergy, as well as cost saving desired by individual plants. Case studies from literature are then solved to illustrate the advantage of this method in decision making. The illustrative examples show how the model achieves a compromise among the potentially conflicting fuzzy goals of the various EIP stakeholders.     

平原河网地区双向生态补偿机制与核算方法

针对平原河网地区地势平坦、水流流向不定、上下游关系不明确的特点,以太湖流域为例,根据“十二五”期间流域内各区域COD和NH₃-N两种污染物的削减量和削减成本,运用非线性回归获得各区域的污染物削减成本函数.根据污染物削减成本函数,以流域污染物削减总成本最小为规划目标,以区域间污染物转移量不超过30%为约束条件,构建基于单目标非线性规划方程组的流域污染物削减总成本最小化模型,求解模型获得太湖流域各区域间的污染物削减成本优化配额方案,计算行政指令配额方案与成本优化配额方案下各区域污染物削减成本的差额,以此为依据,核算生态补偿金额并确定生态补偿方向.核算结果表明,相比行政指令配额方案,太湖流域的成本优化配额方案能够节省9 897.03×104元的污染物削减总成本,根据成本优化配额方案,江苏省需要向浙江省和上海市提供10 577.86×104元的生态补偿费用,浙江省和上海市可分别获得8 909.12×104和1 668.74×104元的生态补偿费用.这种基于流域污染物削减成本最小化的生态补偿机制,根据污染物削减成本函数核算生态补偿金额并确定补偿方向,由于污染物削减成本函数有一定的变动性,因此,允许两个区域间根据成本变动情况改变补偿方向,是一种双向生态补偿机制.