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.     

Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model1

Moore, R.D. (Dan), J.W. Trubilowicz, and J.M. Buttle, 2011. Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model. Journal of the American Water Resources Association (JAWRA) 48(1): 32‐42. DOI: 10.1111/j.1752‐1688.2011.00595.x Abstract: Prediction of streamflow in ungauged basins is a global challenge, but is particularly an issue in physiographically complex regions like British Columbia (BC), Canada. The objective of this study was to assess the accuracy of a simple water balance model that can be run using existing spatial datasets. The model was developed by modifying an existing monthly water balance model to account for interception loss from forest canopy, glacier melt, and evaporation from lakes. The model was run using monthly climate normals from the ClimateBC application, which have a horizontal resolution of 400 m. Each ClimateBC grid cell was classified as forest, open land, glacier or water surface based on provincial scale digital maps of biogeoclimatic zones, glaciers, and water. The output was monthly mean runoff from each grid cell. These values were integrated within the catchment boundaries for streams gauged by the Water Survey of Canada. Annual runoff was predicted with modest accuracy: after updating the predicted runoff by interpolating errors from neighboring gauged streams, the mean absolute error was 25.4% of the gauged value, and 52% of the streams had errors less than 20%. However, the model appears to be quite robust in distinguishing between pluvial, hybrid, and melt‐dominated hydroclimatic regimes, and therefore has promise as a tool for catchment classification.     

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.     

便携式气相色谱质谱测定水中挥发性有机物再现性和准确度研究

建立了便携式顶空-气相色谱-质谱（HS-GC-MS）测定水中挥发性有机物的方法。以水中苯系物、卤代烃和氯代苯等VOCs为研究对象，在同一实验室内，使用3台便携式HS-GC-MS模拟现场应急监测环境开展检测活动，研究测定结果的再现性和准确度。实验结果表明，检测结果的相对标准偏差为0.7%~13%；绝大多数目标化合物测定结果的回收率为80%~120%。综合来看，方法的精密度和准确度基本满意，能够满足应急监测工作的需要。     

事故状态下污染物排放对水环境影响的预测研究

对辽河油田欢喜岭采油厂在事故状态下污染物排放对大凌河水域环境的影响进行预测研究。计算了洪水淹没、油罐冒顶泄漏、油井井喷泄漏、联合站泄漏、管道泄漏、暴雨径流带走落地油等16种情景下对该河流水质的影响情况,并建立数学模型,进行情景模拟。研究结果表明,事故状态下对大凌河水质影响的次序由大到小依次为:洪水淹没、油罐冒顶泄漏、油井井喷泄漏、联合站泄漏、管道泄漏、暴雨径流。     

河北省火电企业吨煤烟气排放量测定及污染动态预测

火电企业大气污染动态预测是大气污染控制的基础。采用现场实测法,对河北省36家火电企业101台机组锅炉进行现场监测,经统计分析给出不同装机容量吨煤烟气排放量,并与其他方法进行了比较,发现实测结果更为合理。在此基础上,建立吨煤SO₂、NO_x,烟尘排放量和烟气浓度的关系,为火电企业大气污染动态预测提供新的公式,对定量测定火电企业污染物排放提供参考。     

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。     

竹林关大柴沟大型泥石流的形成机理与发展趋势

通过对陕西省丹凤县竹林关镇大柴沟泥石流进行现场勘查分析,总结了泥石流的孕灾背景,揭示了泥石流的典型特征和基本物理力学参数,在此基础上,分别从泥石流的物质来源、形成环境、诱发条件等三大条件分析了泥石流的形成机理,归纳了大柴沟泥石流具有典型的滑坡激发性、周期暴发性、强烈致灾性等特点,对泥石流的危险性进行了现状分析和预测评价。结果表明:软硬相间的岩层和强烈的构造运动是造成岩体变形破碎的主要原因,为泥石流提供了丰富的物源,垂直高差较大、沟道狭窄为泥石流提供了良好的孕灾环境,百年一遇的暴雨是大柴沟泥石流形成的诱发条件,同时受暴雨影响,沟内产生多处浅表层滑坡堵塞沟道,为泥石流聚集了能量,以至形成规模更大、破坏性更强的泥石流。研究过程采用了实测计算与经验公式估算相结合的多种方法进行对比研究,也充分验证了经验公式的适用性。     

一种基于预测法的电磁兼容设计方法

文章以数模混合电路设计实践为基础,介绍了一种基于预测法的电磁兼容设计方法。先以电磁兼容测试理论为基础介绍数模混合电路设计中的电磁兼容方法,在以此方法建立电磁兼容设计模型,并通数模混合电路实践来检验和改进设计模型。     

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.