Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Evaluating the impact of uncertainty and variability on the value chain optimization of a forest biomass power plant using Monte Carlo Simulation

Mathematical programming models have been used to optimize the design and management of forest bioenergy supply chains. A deterministic mathematical model is beneficial for making optimum decisions; however, its applicability to real-world problems may be limited because it does not capture all the complexities, including uncertainties in the parameters, in the supply chain. In this paper, a combination of Monte Carlo Simulation and optimization model is used to evaluate the impact of uncertainty in biomass quality, availability and cost, and electricity prices on the supply chain of a forest biomass power plant. The optimization model is a deterministic mixed integer non-linear model with monthly time steps over a 1-year planning horizon. Variability in biomass quality, i.e. moisture content (MC) and higher heating value (HHV), based on the historical data of a real case study is studied in detail and fitted probability distributions are used in the model, while for electricity prices different scenarios are considered. The results show that the impact of variability in the MC on profit is higher than that of uncertainty in HHV. It is observed that the annual profit ranges between $13.3 million and $17.9 million in the presence of all possible uncertainties while its average is $15.5 million. Uncertainty in biomass availability and cost and electricity price results in the risks of having annual profit of less than $14 million and low monthly storage levels.     

Proximity economics and environment: assessment and prospects

The use of the theoretical tools provided by proximity economics to address environmental questions, and the emergence of analyses revitalising the role of the spatial dimension in environmental problems, date from the late 1990s. This paper first aims to provide a review of the research conducted in this field and second to suggest some future research directions concerning the respective roles of geographical proximity and organised proximity in the production and management of environmental problems. First, it deals with the topic of ‘geographical proximity and land-use conflicts’, a topic that is currently the most researched in this field. This is followed by a discussion of the role of organised proximity in the regulation of environmental problems. The paper then explores the relation between the uncertainty associated with environmental issues and relations of organised proximity. Next it outlines a few possible research directions, focusing more particularly on the roles of geographical proximity as a mode of regulation of environmental problems, and on the possible role of organised proximity in their production. The concluding section draws an overview of the departures and extensions that have resulted from taking into account environmental issues in the paradigm of proximity economics.     

Costs and benefits of improving wild salmon passage in a regulated river

This paper presents a cost-benefit analysis (CBA) of a trade-off between salmon and hydropower production in the Ume/Vindel River, northern Sweden. A distinctive element of this analysis is that estimated changes in resource conditions are based on detailed river-specific data. A salmon population model was used to develop the scenario and a novel willingness to pay (WTP) question, which caters for uncertainty in a different manner, provided an interval estimate. Non-use values are the major contributors to the benefit (96–517 millions of Swedish kronor (MSEK)) of increasing the stock of wild salmon. Sensitivity analysis suggests that the opportunity costs in terms of lost electricity are typically higher than the estimated benefits.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

以人为本 开创高校工会工作新局面

认真落实科学发展观,以科学发展观统领工会工作,必须体现在党对工会工作的要求上,体现在准确全面履行好工会的职责上,从而充分发挥工会在支持改革开放、促进经济发展、推动社会进步中的积极作用。     

基于科学发展观的安全哲学思考

从科学发展观的理论视角出发,论述安全发展观的哲学内涵:辩证统一的安全利益关系,工人、企业责任人和安全监督人员等不同安全主体应树立正确的安全利益观;统筹安全社会技术系统,统筹不同安全行业,统筹人员、机械设备、环境和管理等安全要素;安全发展观的贯彻落实依靠安全可持续;建议树立全面、协调、可持续的安全发展观。采用系统思考方法构建安全系统动力学模型,在人员、机械设备、环境、管理4个变量因子的影响下,安全系统安全度水平下降,造成安全系统从可持续安全状态进入临界可持续安全状态,最终跃迁到不可持续状态,导致伤亡事故发生,并结合安全木桶安全要素讨论仿真结果。     

中小企业的安全投入行为研究

在分析安全事故的"外部性"和"不确定性"特征的基础上,探讨安全事故的特征对企业安全投入行为的影响。我国中小企业安全投入不足的原因甚多:员工生命价值低估导致人员伤亡赔偿偏低、我国劳动力供大于求的现状、中小企业安全投资决策缺乏科学性等。我国劳动力市场供大于求的状况短期内无法改变,只能通过强化政府的激励和监管作用,促进中小企业建立科学的安全投资决策支持系统,以提高中小企业安全投入水平。     

一种湿度计的校准方法——测量不确定度分析校准法

本文提出了校准湿度计的一种新方法一测量不确定度分析校准法,以利用5121湿度发生器校准可输出（0-5）V的湿度传感器的基本误差为例,介绍了其校准方法确定了该方法校准湿度计的置信度和准确葭：     

An approach to optimise nutrient management in environmental sanitation systems despite limited data

The material flow analysis method can be used to assess the impact of environmental sanitation systems on resource consumption and environmental pollution. However, given the limited access to reliable data, application of this data-intensive method in developing countries may be difficult. This paper presents an approach allowing to develop material flow models despite limited data availability. Application of an iterative procedure is of key importance: model parameter values should first be assessed on the basis of a literature review and by eliciting expert judgement. If model outputs are not plausible, sensitive input parameters should be reassessed more accurately. Moreover, model parameters can be expressed as probability distributions and variable uncertainty estimated by using Monte Carlo simulation. The impact of environmental sanitation systems on the phosphorus load discharged into surface water in Hanoi, Vietnam, is simulated by applying the proposed approach.