Valuing environmental amenities through inverse optimization: Theory and case study

Amenity values of private forests are implicit but play a critical role in decision and policy making. This study presents an innovative valuation approach integrating techniques of operations research and economic theory of pricing environmental goods. A forest planning problem was inversed through altering its reward function of timber values so that the observed harvesting behavior became optimal. The discrepancy between the original and new rewards uncovered amenities values which were linked to forest attributes via hedonic models. This method was applied to a case study of the U.S. southern pine region. Depending on forest conditions, total economic values of amenities varied from zero to just under one thousand dollar per ha. At a discount rate of 3%, a typically managed forest generated on average $243 ha⁻¹ of amenities values per annum, more than twice of harvested timber values. Structural diversity and density of large pine trees were the key determinants to preserving forests for environmental amenities.     

PRISM vs. CFSR Precipitation Data Effects on Calibration and Validation of SWAT Models

Precipitation is one of the most important drivers in watershed models. Our objective was to compare two sources of interpolated precipitation data in terms of their effect on calibration and validation of two Soil and Water Assessment Tool (SWAT) models. One model was a suburban watershed in metropolitan Atlanta, Georgia. The precipitation sources were Parameter‐elevation Relationships on Independent Slopes Model (PRISM) data on a 4‐km grid and climate forecast system reanalysis (CFSR) data on a 38‐km grid. The PRISM data resulted in a better fit to the calibration data (Nash Sutcliffe efficiency [NSE] = 0.64, Kling‐Gupta efficiency [KGE] = 0.74, p‐factor = 0.84, and r‐factor = 0.43) than the CFSR data (NSE = 0.47, KGE = 0.53, p‐factor = 0.67, and r‐factor = 0.39). Validation results were similar. Sensitive parameters were similar in both the PRISM and CFSR models, but fitted values indicated more rapid groundwater flow to the streams with the PRISM data. The same comparison was made in the Big Creek watershed located approximately 1,000 km away, in central Louisiana. Results were similar with a more responsive groundwater system indicating PRISM data may produce better predictions of streamflow because of a more accurate estimate of rainfall within a watershed or because of a denser grid. Our study implies PRISM is providing a better estimate than CFSR of precipitation within a watershed when rain gauge data are not available, resulting in more accurate simulations of streamflows at the watershed outlet. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Optimization of thermal performance of the parabolic trough solar collector systems based on GA-BP neural network model

The aim of this paper is to optimize the thermal performance (system output energy, thermal efficiency, and heat loss of cavity absorber) of parabolic trough solar collector (PTC) systems in order to improve its thermal performance, based on the genetic algorithm-back propagation (GA-BP) neural network model. There are a number of undefined problems, fuzzy or incomplete information and a complex thermal performance of the PTC systems. Therefore, the thermal performance prediction of the PTC systems based on GA-BP neural network model was developed. Subsequently, the metrics performances have been adopted to comprehensively understand the algorithm and evaluate the prediction accuracy. Results revealed that the GA-BP neural network model can be successfully used to predict the complex nonlinear relationship between the input variables and thermal performance of the PTC systems. The cosine effect has a great influence on the thermal performance; thereby the geometrical structure of the PTC systems was optimized. It was found that the optimized geometrical structure was beneficial to improve the thermal performance of the PTC system. In conclusion, the GA-BP neural network model has higher prediction accuracy than the other algorithm and it can be feasible and reliable.     

Optimization of pretreatment conditions for enhanced sugar release

Present investigation was done to evaluate various algal genera found in water bodies of Varanasi city. The potential of any biomass for biofuels (bioalcohols, biohydrogen, etc.) production depends on the quantity of extractable sugar present in it. Acid (H₂SO₄) and alkali (NaOH) pretreatment were performed, and H₂SO₄ was chosen due to its nearly double yield as compared with alkaline pretreatment. Response surface methodology was utilized for the optimization of operating parameters such as treatment temperature, time, and acid concentration. Sugar yield up to 0.33 g/g of dry biomass was obtained using cyanobacterial biomass of Lyngbya limnetica, at 100°C, 59.19 min, and H₂SO₄ concentration of 1.63 M.     

Starting improvement of micro-wind turbines operating in low wind speed regions

The study deals with the design and optimization of external and internal geometry of micro-wind turbines blades. A specified objective function which consists of the power coefficient and the starting time was defined and the genetic algorithm optimization technique in conjunction with the blade-element momentum theory was adopted to find the geometry of the blades including the distributions of the chord, the twist angle and also the shell thickness. Moreover, the allowable stress of the blades was considered as a constraint to the objective function. Results show that a reasonable compromise is achievable such that the starting time of the blades reduces noticeably in return for a small drop in the power coefficient. The significant improvement of the hollow blades over the solid ones indicates that the power coefficient and the starting performance could be improved through the appropriate distributions of the considered decision variables, i.e. the chord, the twist angle and also the shell thickness.     

Dominance based fuzzy decision support framework for g-resilient (ecosilient) supplier selection: an empirical modelling

A novel decision support framework has been proposed herein to solve supplier selection problems by considering green as well as resiliency criteria, simultaneously. An expert team involving a finite number of Decision-Makers (DMs) is to be employed to obtain degree of importance of each of the evaluation criteria and also to assign an appropriate rating for each supplier alternative with respect to the criteria. Since subjective human judgment often bears some sort of ambiguity as well as vagueness, application of fuzzy set theory can be recommended in this context. The present work represents a dominance based decision support system in the light of fuzzy set theory which is basically a simplified version of TODIM and PROMETHEE. It explores dominance between two alternatives with respect to a particular criterion, based on which a global dominance measure is computed to facilitate ranking order of candidate suppliers. The approach proposed in this research seems straightforward which can exclude complex and tedious computational steps of TODIM as well as PROMETHEE. Application potential of the proposed dominance based fuzzy decision-making approach has been compared to that of Fuzzy-TOPSIS and Fuzzy-VIKOR. Good agreement has been observed. In addition to this, the concept of a unique performance index i.e. ‘g-resilient’ (also called ‘ecosilient’) index has been introduced to help in assessing suppliers’ overall performance extent. The work has also been extended to identify the ill (poor)-performing areas in which suppliers are lagging and seek further improvement towards enhancing g-resilient performance level.     

长江流域的空间结构研究

在认识空间结构内涵与确定研究范围的基础上,运用主成分和聚类分析方法,获得了长江流域的空间分异状况。长江流域空间结构符合核心 边缘结构模式,包括3个一级核心、8个二级核心、两大跨省成长三角、1条主轴、2条辅轴、3条地方轴、1个外围区和1个边缘区。长江流域空间结构的演变,经历了低水平的离散型阶段、极化发展的非均衡阶段、扩散的多核非均衡阶段,未来将向区域一体化的高水平均衡阶段发展。从聚散原理、空间相互作用和国家宏观区域发展战略等3方面,分析了长江流域空间结构的演变机制。长江流域空间结构的优化,要从内部要素与外部力量两方面入手做3件事情。一要加快单个节点的发展和尽快形成核心区域,尤其是上游地区要构建一个以成渝为双核的兼顾南北较大范围的成长多边形;二要加快东西通道的建设和注重主轴与辅轴间的连接通道的构建或完善;三要注重基于市场一体化的区域空间治理体制的创新.     

城市景观生态网络规划的空间模式应用探讨

城市景观生态网络空间模式研究是生态城市和景观规划设计现今研究的重要领域之一,目的在于依据景观生态网络模式的应用建立起生态城市规划建设的基本框架和技术途径。在探讨城市景观生态系统特征和城市景观生态网络结构的基础上,总结景观生态网络空间模式并重点分析了水景树的空间生态模式、森林 道路 住宅复合网络模式、平原城市农田 灌木丛 河流交叉网络模式、岛屿城市的绿地 道路生态网络模式4种城市景观生态网络典型模式的图示特征及其生态意义。依此为理论指导基础,以都江堰为例,在继承都江堰大地景观格局并结合都江堰市灾后重建需求的前提下,研究都江堰市城市景观生态格局和生态过程,探讨在不同尺度和不同维度上运用4种网络图示进行都江堰城市景观生态网络优化调整的空间模式和对策。(1)依据“水景树图式”优化调整纵向维度景观生态格局;(2)依据“森林 道路 住宅”和“农田 灌木丛 河流”网络调整横向维度景观生态格局;(3)依据岛屿城市的“绿地 道路”景观生态网络调整城市组团景观生态格局.     

Legalizing markets and the consequences for poaching of wildlife species: the vicuña as a case study

Vicuña provide an excellent case study for examining the sustainable use of wildlife outside protected areas: the community-based conservation approach. Vicuña populations in the high Andes of Argentina, Bolivia, Chile, Ecuador and Perú fell to a critically low level, but a Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) ban on trade in their fiber has seen numbers recover dramatically, and now live shearing of vicuña for a high-value international market is being promoted as a mechanism to secure both sustainable vicuña populations and local livelihoods. We used a dynamic optimization model to explore the consequences of legalizing markets, including the consequences for poaching which is critical in vicuña dynamics. Using parameters obtained from the literature and expert knowledge, we explored different scenarios for the Argentine region of Cieneguillas. Our results showed that the role of the international market is ambiguous; live shearing for an international market can provide the very best of outcomes for both vicuña and local people, with large herds generating high revenues. But an international market also creates a market for poached vicuña fiber; as a result, vicuña numbers risk once again falling to critically low levels, resulting also in minimal revenues from sale of fiber. The message for the international community is that if community-based conservation is not implemented carefully then its impact can easily be perverse.     

基于GIS的城市火灾信息管理与分析系统

以地理信息系统为基础平台 ,研究了城市火灾信息系统的基本构成与功能 ,着重于系统中的数据分层与组织 ,并探讨了模糊评估法在建筑火灾危险性模型分析中的应用