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.     

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.     

An Adaptive‐Management Framework for Optimal Control of Hiking Near Golden Eagle Nests in Denali National Park

Abstract: Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive‐management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles.     

基于ISO14067的长江上游某水电项目碳足迹分析

以长江上游某大型水电站为案例,根据国际标准化组织碳足迹量化标准(ISO14067)评价流程,对该水电站全生命周期(建设阶段,运行维护阶段,退役阶段)碳足迹进行估算,并着重考虑了蓄水前后水库温室气体通量差异。研究以碳足迹系数和能源回收率作为指标进行评价,结果表明生命周期碳足迹为5 417.0万t CO_(2eq),碳足迹系数为7.0~13.1 g CO_(2eq)/kW·h,中位值为9.4 g CO_(2eq)/kW·h,该水电站项目能源回收率达236.4。与各种能源电站以及国内外同类型水电站相比较,该水电站碳足迹明显较低,且能源回收率显著较高,说明以该水电站为代表的我国西南水电具有显著的优质性,大力开发水电能有效节能减排,明确了生命周期评价方法对于水电站碳足迹评估的适用性。     

气候试验箱内部条件不确定度计算(下)

提供了对温度和湿度气候试验箱内部环境条件进行不确定度分析的方法。首先介绍了测量的不确定度概念,然后讨论容差的意义。考虑到湿度和温度测量是采用确定和合成不确定度。结合校准空载试验箱和有负载试验箱的条件测量的案例。最后,逐条整理成为范本用于分析结果以给出规范的不确定度评估依据。     

Assessing and testing prediction uncertainty for single tree-based models: A case study applied to northern hardwood stands in southern Québec, Canada

Estimating prediction uncertainty for a single tree-based model is hindered by the complex structure of these models. In this paper, we addressed this issue with a case study applied to northern hardwood stands in Québec, Canada. SaMARE is a stochastic single tree-based model that was designed for these types of stands. Using a Monte Carlo approach, the model can provide a mean predicted value and its confidence limits for some plot-level attributes.The mean predicted values were compared to observed values in terms of bias and accuracy. In addition to these common statistics, we compared nominal coverage of Monte Carlo-simulated confidence intervals with real (observed) coverage to verify the adequacy of the simulated uncertainty. A comparison was made using several plot-level attributes, which exhibited an increasing discriminative complexity. This complexity ranges from coarse attributes, such as all-species basal area, up to more complex ones, such as basal area for stems of a particular species and with sawlog potential.The results showed that in terms of absolute value, biases were small, but could be relatively high with respect to the average observed value when the discriminative complexity of the attribute increased. The comparison between nominal and real coverage of confidence intervals gave satisfactory results for all-species plot-level attributes. However, for some species-specific attributes, the Monte Carlo-simulated confidence intervals overestimated the real coverage.     

兰-白城市群主要大气污染物网格化排放清单及来源贡献

甘肃兰-白城市群为我国西北地区重要的重工业基地,大气污染物排放总量较大.研究高空间分辨率的污染物排放清单对于区域空气质量预报预警、减排方案模拟研究及大气污染防治等具有重要的科学意义.本文以兰州和白银为主要研究区域,基于研究区域污染源排放及统计年鉴等数据资料,建立了兰（2015年）-白（2016年）城市群7种（类）主要大气污染物网格化排放清单,并对其空间排放特征以及排放源贡献进行了详尽地讨论分析.结果表明,兰-白城市群7种主要污染物年排放量分别为：NO_x 2.22×10⁵ t、NH₃ 4.53×10⁴ t、VOCs 7.74×10⁴ t、CO 5.62×10⁵ t、PM₁₀ 4.95×10⁵ t、PM_2.5 1.91×10⁵ t和SO₂ 1.37×10⁵ t.其中CO的排放量最大,NH₃的排放量最小.本清单与北大和清华MEIC清单对比结果表明,交通源排放3个清单一致性较高,CO排放总量和其工业源排放与北大和清华MEIC清单排放源相差30%~40%,推测原因主要为清单计算过程中排放因子、分辨率和数据年份的差异.本清单网格化空间分布显示除NH₃外的其他6种（类）污染物,排放主要集中在市区,排放源中工业非燃烧过程源均为最大贡献占比,NH₃的主要贡献源是氮肥的施用及禽畜排放,其污染分布受耕地分布等因素影响较大.因此,减少工业非燃烧过程源、整合优质高效电力供应、使用清洁能源、严格控制工地扬尘、工业粉尘和做好城区绿化等,能有效地降低兰-白城市群NO_x、VOCs、CO、PM₁₀、PM_2.5和SO₂这6种（类）主要污染物的排放.NH₃的减排则主要可从控制氮肥的使用及减少禽畜排放两方面考虑.本研究还利用蒙特卡洛法分析了排放清单的不确定性,NH₃的不确定性最大为-31%~30%,CO的不确定性最小为-18%~16%,清单整体可信度较高.     

可控震源振动器系统不确定性分析

为了解决可控震源施工过程中振动器系统的安全性问题,采用故障树法建立仿真 模型。通过失效分析得出各故障单元的失效模式及单元间分布规律,计算出振动器系统 的可靠度。开展对该系统敏感性的不确定性分析,得出影响振动器系统可靠性的关键因 素为重锤上部密封失效。采用有限元法对其应力场进行模拟仿真。结果表明:随着工作 频率的升高,O形圈应力波动越大,密封越容易失效。Von Mises应力随压缩率的增大先 减小后增大,随槽口半径的增大而增大;接触应力在一定范围内随压缩率及槽口半径的 增大而增大。为振动器的结构优化与可靠性设计提供理论依据,并为油气资源勘探开发 的安全作业提供工程应用指导。     

产品碳足迹评价中不确定度与敏感度相结合的数据质量分析

产品碳足迹评价中,数据种类、来源、获取途径和量化方法的选择不同将直接影响到评价结果的可靠与否.本文建立了结合敏感度和DQI-Monte Carlo不确定度分析的产品碳足迹评价数据质量分析模型.首先通过敏感度分析识别出产品碳足迹评价中的主要数据,再采用DQI-Monte Carlo不确定度分析方法对主要数据进行数据质量判定,甄选出影响评价结果可靠性的关键数据,并由此有针对性地提出数据质量改进意见,从而有效地优化数据收集方案,减少碳足迹评价结果的不确定度.建立的方法应用于我国某塑料软包装印刷企业的印刷前阶段碳足迹评价中.