Comparison of Stream Invertebrate Response Models for Bioassessment Metrics1

Waite, Ian R., Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, and James L. Orlando, 2012. Comparison of Stream Invertebrate Response Models for Bioassessment Metrics. Journal of the American Water Resources Association (JAWRA) 48(3): 570-583. DOI: 10.1111/j.1752-1688.2011.00632.x Abstract: We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R² from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R² values than RICHTOL for the two regions tested. Modeled O/E R² values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.     

Application of Rosgen’s BANCS Model for NE Kansas and the Development of Predictive Streambank Erosion Curves1

Sass, Christopher K. and Tim D. Keane, 2012. Application of Rosgen’s BANCS Model for NE Kansas and the Development of Predictive Streambank Erosion Curves. Journal of the American Water Resources Association (JAWRA) 48(4): 774‐787. DOI: 10.1111/j.1752‐1688.2012.00644.x Abstract: Sedimentation of waterways and reservoirs directly related to streambank erosion threatens freshwater supply. This study sought to provide a tool that accurately predicts annual streambank erosion rates in NE Kansas. Rosgen (2001, 2006) methods were employed and 18 study banks were measured and monitored from 2007 through 2010 (May‐June). Bank profiles were overlaid to calculate toe pin area change due to erosional processes. Streambanks experienced varied erosion rates from similar Bank Erosion Hazard Index (BEHI)‐Near Bank Stress (NBS) combinations producing R² values of 0.77 High‐Very High BEHI rating and 0.75 Moderate BEHI rating regarding predictive erosion curves for NE Kansas. Moderate ratings demonstrated higher erosion rates than High‐Very High ratings and BEHI trend lines intersected at lower NBS ratings, suggesting a discrepancy in the fit of the model to conditions in the NE Kansas region. BEHI model factors were evaluated and assessed for additional influences exerted in the region. Woody vegetation adjacent to the stream seemed to provide the most variation in erosion rates. This study’s findings allowed us to calibrate and modify the existing BEHI model according to woody vegetation occurrence levels along streambanks with high clay content. Modifications regarding vegetation occurrence of the BEHI model was completed and the results of these modifications generated new curves resulting in R² values of 0.84 High‐Very High BEHI and 0.88 Moderate BEHI ratings.     

一种移动通信基站发射天线非轴向功率密度预测模式

以移动通信基站轴向功率密度计算公式为基础,根据非轴向方向上实际监测点位和轴向方向的相对位置,对轴向功率密度计算公式参数进行系列修正,从而建立一种简单适用的移动通信基站非轴向方向上功率密度预测模式.     

基于LS-SVR、BP-ANN和MLR模型的PM10浓度预测

利用宁东能源化工基地PM10和气象监测数据,分别采用LS-SVR、BP-ANN和传统MLR模型预测PM10浓度变化。结果表明,较BP-ANN模型、MLR模型,LS-SVR模型能更好地刻画PM10浓度与各气象因素间的非线性相依关系,更准确地预测PM10浓度。     

Analysis of uncertainty consideration in environmental assessment: an empirical study of Canadian EA practice

Identifying and communicating uncertainty is core to effective environmental assessment (EA). This study evaluates the extent to which uncertainties are considered and addressed in Canadian EA practice. We reviewed the environmental protection plans, follow-up programs, and panel reports (where applicable) of 12 EAs between 1995 and 2012. The types of uncertainties and levels of disclosure varied greatly. When uncertainties were acknowledged, practitioners adopted five different approaches to address them. However, uncertainties were never discussed or addressed in depth. We found a lack of suitable terminology and consistency in how uncertainties are disclosed, reflecting the need for explicit guidance, and we present recommendations for improvement. Canadian Environmental Impact Statements are not as transparent with respect to uncertainties as they should be, and uncertainties in EA need to be better considered and communicated.     

压力传感器位移分析及疲劳寿命预测

完成了依据有限元疲劳分析为基础的传感器寿命预测研究工作。阐述压力传感器工作原理,定义影响系统寿命的参数组,既包含力学环境参数,亦包括材料属性、几何形式等结构参数。针对不同参数属性,依据疲劳强度计算需求,构建有限元数值计算模型;根据影响传感器寿命的传感单元单晶硅S-N(应力-循环)分布,完成变载荷输入条件下模型疲劳分析,依据数值计算结果完成该压力传感器寿命预测工作。结果表明:压力传感器使用寿命在7.068E8次数以上。本课题研究提出的新方法,摆脱了传统依靠试验完成多种材料组成结构体的疲劳分析及寿命预测窘境,具有通用性。     

工业园区氯碱项目环境风险预测评价——以新疆某城市工业园区氯碱项目为例

对工业园区引入的化工项目进行环境风险评价,是园区规划的重点工作之一。对氯碱生产项目潜在的环境风险环节进行识别和风险类型的确定,对发生泄漏性事故进行环境风险评价,预测了事故发生对环境的影响程度及范围。对事故发生后的风险提出防范和应急减缓措施,并对项目提出规划建议。     

Terrestrial exposure of oilfield flowline additives diminish soil structural stability and remediative microbial function

Onshore oil production pipelines are major installations in the petroleum industry, stretching many thousands of kilometres worldwide which also contain flowline additives. The current study focuses on the effect of the flowline additives on soil physico-chemical and biological properties and quantified the impact using resilience and resistance indices. Our findings are the first to highlight deleterious effect of flowline additives by altering some fundamental soil properties, including a complete loss of structural integrity of the impacted soil and a reduced capacity to degrade hydrocarbons mainly due to: (i) phosphonate salts (in scale inhibitor) prevented accumulation of scale in pipelines but also disrupted soil physical structure; (ii) glutaraldehyde (in biocides) which repressed microbial activity in the pipeline and reduced hydrocarbon degradation in soil upon environmental exposure; (iii) the combinatory effects of these two chemicals synergistically caused severe soil structural collapse and disruption of microbial degradation of petroleum hydrocarbons.     

基于SVM的矿井通风阻力系数影响因素分析与预测

矿井通风阻力系数是通风安全最重要的基础参数之一,为了实现矿井通风阻力系数简单准确地预测,提出了利用支持向量机（SVM）来预测矿井通风阻力系数的方法。通过分析影响因子与矿井通风阻力系数的相关性关系,并利用MATLAB逐步建立单影响因素与矿井通风阻力系数、多影响因素与矿井通风阻力系数之间的SVM预测模型,对比分析各预测模型的相对误差,确定最佳矿井通风阻力系数预测模型,即当输入模型影响因素为巷道断面积、周长和支护方式时,预测相对误差小于10%的样本数占测试样本的76%,相对误差小于20%的样本数占测试样本的90%。结果表明:该预测方法在矿井通风阻力系数预测中是可行的,并具较高的准确性。     

不同自燃倾向性煤的指标气体产生规律实验研究

为研究不同自燃倾向性煤的自燃指标气体变化规律,提高对煤早期自燃预测预报的准确度,采用程序升温实验系统,得到内蒙古褐煤、神东长焰煤、河南气煤及枣庄焦煤4种不同变质程度煤的氧化时间随温度的变化关系,以及指标气体浓度在煤氧化过程中的变化规律。结果表明:自燃倾向性最高的褐煤应以CO和乙烯作为煤自燃早期预报的首选指标气体;易自燃的长焰煤应采用乙烯和烯烷比为主、以CO为辅的煤自燃判定指标;自燃倾向性较低的气煤应以乙烯和烯烷比作为煤自燃预报指标;CO是自燃倾向性最低的焦煤的最佳自燃预报指标气体。