ANALYZING CORRELATIONS BETWEEN STREAM AND WATERSHED ATTRIBUTES1

ABSTRACT: Bivariate correlation analysis has been widely used to explore relationships between stream and watershed attributes that have all been measured on the same set of watersheds or sampling locations. Researchers routinely test H₀: ρ= 0 for each correlation in a large table and then go on to discuss only those that are declared “significant.” Such test results are inaccurate because no allowance is made for multiple testing, and also because the tests are not mutually independent. This paper reviews the Bonferroni approach to controlling the overall error rate in multiple testing and shows how the approach becomes impractical for large correlation tables. The Hotelling/Williams test is introduced for comparing two dependent correlations that share a variable, and numerical constraints for two such correlations are illustrated. References are also given for testing other hypothesized patterns among dependent correlations, and links to dependent correlation software are provided. The methods are illustrated for watershed and stream variables sampled in 23 small agricultural watersheds of the Willamette Valley, Oregon.     

滑坡灾害危险性评价模型比较

通过对庆元地区滑坡灾害的详细研究，比较讨论了单变量评价、决策树评价与逻辑回归法等3种滑坡危险性评价模型在实际应用中的效果。单变量模型最为简单，计算方便，得到的结果也具有较高的准确性，当收集到的滑坡因素越多，对滑坡发育的刻画越精确，则最终评价结果也越可信；决策树算法能迅速从大量样本中归纳出一般规则，并具有较高的精度，但其结果也受到训练样本数量大小和样本维数即参与评价的因素集数量的影响；逻辑回归模型具有计算方法简单、评价结果物理意义明确等突出优点，但需要有大量样本数据的支持才能取得较好的效果。     

森林可燃物参数与林分特征关系

森林地被可燃物是引起森林火灾的重要原因,掌握森林地被可燃物的载量分布,对森林火灾的预防有着十分重要的意义.但森林地被可燃物载量数据的获得是比较困难的,运用Spss11.0 for windows统计软件系统,对兴安落叶松林和杨桦林的林分因子和各类地被可燃物载量进行后向逐步线性回归分析,建立了一套数学模型,取得了较为满意的结果,从而可以通过林分因子推算各类地被可燃物载量.     

AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.     

洪涝灾害评价的威布尔模型

首次将威布尔分布用于淮河流域水灾成灾面积研究,揭示了淮河流域洪涝灾害成灾面积形成的 内在规律,进而利用河南、安徽、江苏和山东4省的各自灾度对淮河流域的灾害风险建立了线性回归模型.实证分析表明,本方法切实可行,特别适用于大样本计算.     

中国水灾社会脆弱性评估方法的改进与应用--以长沙地区为例

中国是洪水灾害发生频繁的国家之一,研究水灾脆弱性对中国的灾害风险管理有重要的意义.但是,合理评估脆弱性尤其是社会脆弱性却面临着极大的挑战.论文对评估社会脆弱性指数的研究现状进行了分析,指出了传统评估方法存在的问题,并尝试改进Hoovering评估模式.选择湘江流域的长沙地区为研究区,应用改进模型对研究区进行了社会脆弱性指数的评估.结果表明,长沙地区社会脆弱性从1980年至2000年基本处于下降趋势,但是在2002年和2003年增长迅速.2003年,长沙5区4县中社会脆弱性指数最大的是开福区,其次是长沙县,而宁乡县的社会脆弱性指数最低.     

地下水水质评价的多元线性回归分析模型研究

运用回归分析理论和方法,建立了一个基于多元线性回归分析法的地下水水质评价模型,并将该模型用于遵义市海龙坝地下水水质评价.结果表明,建立的模型较符合本研究区的实际情况.     

Predictive Model of Avian Electrocution Risk on Overhead Power Lines

Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red‐tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution‐risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high‐risk poles for retrofitting. Modelo Predictivo del Riesgo de Electrocución de Aves en Líneas Eléctricas Elevadas     

基于GM-SVR的小样本条件下化工设备可靠性预测

为了准确预测化工设备可靠性趋势，针对化工设备失效寿命数据为小样本的情形，基于灰色估计法与支持向量回归机在小样本数据处理中的优势，建立了失效寿命时间服从三参数威布尔分布的化工设备可靠性模型；结合GM（1，1）和SVR对模型进行参数估计，在压缩机可靠性分析中进行了实例应用，对比分析了最小二乘法、灰色估计法和GM-SVR的估计效果。研究结果表明:GM-SVR对威布尔分布参数的估计精度明显优于最小二乘法和灰色估计法，可以有效地应用于化工设备失效数据为小样本时的可靠性预测。     

基于移动监测和土地利用回归模型的上海市近地面黑碳浓度空间模拟

黑碳(BC)是大气污染物的重要组成部分,对空气质量与人类生活健康产生重要的影响.本研究采用移动样带手段开展上海市近地面BC浓度监测,分析其基本统计特征和空间分异性.在此基础上,利用土地利用回归模型(LUR),探讨人口密度、经济产值和交通道路网密度等因素对上海市近地面BC浓度空间分异的影响.结果表明上海市近地面BC平均浓度为(9.86±8.68)μg·m~(-3),空间差异明显,郊区[(10.47±2.04)μg·m~(-3)]比市中心地区[(7.93±2.79)μg·m~(-3)]高32.03%(2.54μg·m~(-3)).气象要素(风速和相对湿度)和交通道路变量(路网长度、省道距离、高速距离等)显著影响上海市近地面BC浓度(r为0.5~0.7,P0.01).基于气象和交通道路变量的LUR模型能较好模拟上海近地面BC浓度(调整后R2为0.62~0.75,交叉验证R2为0.54~0.69,RMSE为0.15~0.20μg·m~(-3)),其中100 m和5 km缓冲距离的LUR模型相对较优,在一定程度上表明上海市近地面BC浓度主要受气象要素和交通源的影响.本研究有利于加深对上海市BC浓度空间分布格局及其影响因素的客观认识,可为模拟和预测BC对人类活动和自然环境的响应机制提供科学依据和理论支撑.