ESTIMATING TMDL BACKGROUND SUSPENDED SEDIMENT LOADING TO GREAT LAKES TRIBUTARIES FROM EXISTING DATA1

ABSTRACT: The total maximum daily load (TMDL) for suspended sediment is the maximum quantity of suspended sediment that can enter a waterway without affecting the beneficial uses of the waterway. It is calculated as the sum of permissible allotments of point sources of suspended sediment, permissible allotments of nonpoint sources of suspended sediment, background (natural) loading of suspended sediment, and a margin of safety. The goal of this project was to develop methods for estimating background levels of sediment loads in tributaries of the Great Lakes. Such quantification is key to determining permissible TMDL in waters that do not meet water quality standards under the Clean Water Act of 1972. Suspended sediment loading for 46 rivers was estimated from data collected at U.S. Geological Survey (USGS) gages. Land use and physiographic attributes were estimated for these gaged basins with a geographic information system (GIS). Basin attributes and sediment yield data are the basis for examining two approaches to estimating background suspended sediment loads. One method, based upon envelope curves of sediment yield and drainage area, will be shown to have considerable merit. A second method, based upon correlation of sediment yield to various basin attributes such as drainage area and land use, will be shown to be fraught with difficulties.     

GROUPWISE MODELING STUDY OF BACTERIALLY IMPAIRED WATERSHEDS IN TEXAS: CLUSTERING ANALYSIS1

ABSTRACT: Under the Clean Water Act (CWA) program, the Texas Commission on Environmental Quality (TCEQ) listed 110 stream segments in the year 2000 with pathogenic bacteria impairment. A study was conducted to evaluate the probable sources of pollution and characterize the watersheds associated with these impaired water bodies. The primary aim of the study was to group the water bodies into clusters having similar watershed characteristics and to examine the possibility of studying them as a group by choosing models for total maximum daily load (TMDL) development based on their characteristics. This approach will help to identify possible sources and determine appropriate models and hence reduce the number of required TMDL studies. This in turn will help in reducing the effort required to restore the health of the impaired water bodies in Texas. The main characteristics considered for the classification of water bodies were land use distribution within the watershed, density of stream network, average distance of land of a particular use to the closest stream, household population, density of on‐site sewage facilities (OSSFs), bacterial loading from different types of farm animals and wildlife, and average climatic conditions. The climatic data and observed instream fecal coliform bacteria concentrations were analyzed to evaluate seasonal variability of instream water quality. The grouping of water bodies was carried out using the multivariate statistical techniques of factor analysis/principal component analysis, cluster analysis, and discriminant analysis. The multivariate statistical analysis resulted in six clusters of water bodies. The main factors that differentiated the clusters were found to be bacterial contribution from farm animals and wildlife, density of OSSFs, density of households connected to public sewers, and land use distribution.     

Optimal control of lake pH for mercury bioaccumulation control

Mercury is recognized internationally as an important pollutant since mercury and its compounds are persistent, bioaccumulative and toxic, and pose human and ecosystem risks. A critical aspect of mercury cycling is its bioaccumulation, mainly as methylmercury, along the aquatic food web resulting in high risk of human exposure through contaminated fish consumption. Since lake acidity (pH) and mercury methylation are correlated, control of lake pH through lake liming is a possible option to mitigate mercury bioaccumulation. This work proposes to use optimal control theory to derive time-dependent lake liming strategies for a tighter control of lake pH. Since the behavior of the freshwater ecosystems such as lakes is often associated with considerable uncertainties, a robust and realistic analysis should incorporate such uncertainties. This work models the time-dependent uncertain variations in the basic lake pH value and derives the liming profiles in the presence of such seasonal pH fluctuations. Established techniques from real options theory are employed for modeling the uncertainty as a stochastic process, and stochastic optimal control is used for deriving liming profiles. The approach is critically evaluated through applications to various case study lakes. Considering the substantial costs associated with liming operations, the work formulates a multi-objective problem highlighting the tradeoff between accurate pH control and liming cost. The results of the control problem solution are also compared with heuristics based liming. The results, while highlighting the success of using time-dependent liming, put forth certain interesting aspects that might be helpful to a decision maker. The analysis is expected to make liming operation more reliable, thereby presenting one more tool to manage the harmful effects of mercury pollution.     

Confidence intervals for the mean of the delta-lognormal distribution

Data that are skewed and contain a relatively high proportion of zeros can often be modelled using a delta-lognormal distribution. We consider three methods of calculating a 95% confidence interval for the mean of this distribution, and use simulation to compare the methods, across a range of realistic scenarios. The best method, in terms of coverage, is that based on the profile-likelihood. This gives error rates that are within 1% (lower limit) or 3% (upper limit) of the nominal level, unless the sample size is small and the level of skewness is moderate to high. Our results will also apply to the delta-lognormal linear model, when we wish to calculate a confidence interval for the expected value of the response variable, given the value of one or more explanatory variables. We illustrate the three methods using data on red cod densities, taken from a fisheries trawl survey in New Zealand.

基于多源数据的PM2.5浓度时空分布预测与制图

随着我国经济、工业化、城市化进程迅速发展,PM_(2.5)污染在中国已经成为一个极端的环境和社会问题,并引起广泛关注.采用新技术估算的地表PM_(2.5)质量浓度,收集并处理了遥感反演的气溶胶光学厚度(AOD),气象数据,其他地理数据和污染物排放数据,采用贝叶斯最大熵(BME)结合地理加权回归(GWR)来分析2015年冬季的PM_(2.5)暴露在我国东部大范围区域的时空变异特征.结果表明,BME模型的十折交叉验证结果的决定系数R~2为0.92,均方根误差(RMSE)为8.32μg·m~(-3),平均拟合误差(MPE)为-0.042μg·m~(-3),平均绝对拟合误差(MAE)为4.60μg·m~(-3),与地理加权回归模型的结果相比(R~2=0.71,RMSE=15.68μg·m~(-3),MPE=-0.095μg·m~(-3),MAE=11.14μg·m~(-3)),BME的预测结果有极大的提高.空间上,PM_(2.5)高浓度地区主要集中在华北、长江三角洲、四川盆地,低浓度地区主要集中在中国的最南部如珠江三角洲和云南的西南部;时间上,不同月份的研究区域PM_(2.5)空间分布所有差别,2015年的12月、2016年1月PM_(2.5)污染最为严重,2015年的11月,2016年的2月污染相对较低.     

基于Bayes的导弹加速贮存试验参数估计

目的研究导弹加速贮存寿命试验中的参数估计问题。方法拟在小子样的情况下,设计一系列反复连续的导弹加速贮存仿真试验,将前一试验的结果作为之后试验的先验分布,基于Bayes方法建立导弹加速贮存寿命模型,给出贮存寿命参数估计算法,探讨导弹贮存可靠性评估方法。结果算例给出贮存寿命参数的极大似然估计,利用RBA方法对参数估计值进行降偏修正,得出参数的修正似然估计值,给出导弹贮存可靠度。给出的参数估计在均方误差意义下结果较优。结论序列试验Bayes算法易行、精度高,可有效对导弹贮存可靠性进行评估。     

基于Seam型裂纹的复合型裂纹起裂角预测的有限元法

目的对处于多轴应力状态下的复合型裂纹起裂角进行预测。方法考虑材料的弹性性能,利用商业有限元软件ABAQUS中的Seam裂纹模拟穿透型裂纹损伤,建立双轴载荷作用下中心带孔边裂纹板的三维有限元模型,通过位移外推法得到裂纹尖端的应力强度因子(Stress Intensity Factor,SIF),并利用求得的SIF基于最大周向应力断裂准则预测孔边裂纹的起裂角。结果通过与相关文献结果进行对比,发现通过该有限元方法计算得到的应力强度因子与文献结果的最大误差在2%以内,预测的裂纹起裂角与文献结果的最大误差在3%以内。结论该有限元方法计算的裂纹起裂角与文献结果一致,因此文中求解复合型裂纹起裂角所使用的有限元方法是可靠有效的。     

重特大事故的离散幂律分布——以煤矿事故为例

研究近年来我国每起煤矿重大和特别重大事故死亡人数统计数据,建立其概率分布模型。基于极大似然法和柯尔莫哥洛夫一斯米尔诺夫检验方法（K-S方法）估计我国煤矿重大和特别重大事故离散幂律分布的参数,并采用MonteCarlo方法随机生成大量的检验样本,对其进行K-S方法拟合优度检验。结果表明在统计学意义上我国煤矿重大和特别重大事故死亡人数比高斯分布的值大得多,服从标度指数为2．72的离散幂律分布。     

水平管道内铝粉爆炸特性的试验研究

为研究铝粉在密闭空间内爆炸特性,降低其爆炸造成的损害,利用自行设计的水平管道式可燃气体-粉尘爆炸装置,在室温下对粒度为6～8μm,9～12μm,15～17μm的铝粉在100～800 g/m3浓度范围内的爆炸特性进行试验研究。结果表明:铝粉在浓度为600 g/m3时,最大爆炸压力和最大压力上升速率最大,爆炸时间最小;铝粉浓度较低时,由于氧气充足,随着铝粉浓度增大,最大爆炸压力和最大压力上升速率增大,爆炸时间减小;当铝粉浓度超过600 g/m3,受到氧气浓度限制,最大爆炸压力和最大压力上升速率随浓度增大而减小,爆炸时间增大;相同浓度的铝粉,粒度越小,最大爆炸压力和最大压力上升速率越大,爆炸时间越小。粒度越小的铝粉,爆炸的可能性和危险性越大。     

基于回归分析的隧道爆破振动传播规律研究

为控制隧道爆破振动效应产生的危害,采用回归分析法对爆破振动的传播规律进行研究。首先采用一元线性回归与二元线性回归对爆破振动实测数据进行分析,确定不同影响因素下萨氏公式的相关参数,进而研究隧道爆破振动的传播规律,然后计算不同爆心距对应的爆破最大段药量,最后通过爆破振速峰值分析来判断隧道爆破的安全程度。研究结果表明,该隧道爆破振动危害在控制范围之内,不会对地表建筑物造成影响。