BAYESIAN MODELS OF FORECASTED TIME SERIES1

Bayesian Processor of Forecasts (BPF) combines a prior distribution, which describes the natural uncertainty about the realization of a hydrologic process, with a likelihood function, which describes the uncertainty in categorical forecasts of that process, and outputs a posterior distribution of the process, conditional upon the forecasts. The posterior distribution provides a means of incorporating uncertain forecasts into optimal decision models. We present fundamentals of building BPF for time series. They include a general formulation, stochastic independence assumptions and their interpretation, computationally tractable models for forecasts of an independent process and a first-order Markov process, and parametric representations for normal-linear processes. An example is shown of an application to the annual time series of seasonal snowmelt runoff volume forecasts.     

EFFECTS OF RATE STRUCTURE KNOWLEDGE ON HOUSEHOLD WATER USE1

ABSTRACT: Socioeconomic determinants of individual household water use were estimated using regressions of these characteristics with actual household water use for winter and summer. Results were disaggregated between those consumers who were aware of an increasing block rate price structure and those who were not. Most of the informed group members believed that this price structure did result in significant reductions in water use. Nevertheless, overall water use was greater for the informed group. The determinants of water use were found to differ between informed and uninformed users as well as between winter and summer. The uninformed users were influenced by a larger set of variables in each season than the informed group. In winter, the informed group members with swimming pools and/or arid landscaping used less water than their uninformed counterparts. Summer water use increased with length of tenancy in home for the uninformed group but not for informed, while increasing with ownership for informed consumers.     

COST REDUCTIONS DUE TO SEASONAL VARIATION IN MUNICIPAL WASTE WATER TREATMENT LEVELS1

ABSTRACT: Varying treatment levels to meet seasonal variation in assimilative capacity of streams can reduce total costs of treatment. A mathematical model of a Pennsylvania stream based on a theoretically sound approximation of the physical relationships underlying the distribution of DO in a river system was used to determine discharge constraints for an economic optimization model which produced estimates of sewage treatment cost savings. Increasing the number of flow periods during the year enhances cost reducing opportunities even when land application processes are considered. Also, the least cost treatment process for year around operation may not be the least costly under multiple flow period management.     

Investigation of seat belt use among the drivers of different education levels

Seat belt use habit has been investigated according to the education level of drivers. Copies of a questionnaire were distributed to 1000 participants of four different education levels. Factors such as seat belt usage habit, restricting factors and crash data have been investigated. Data have been analyzed with SPSS 15.0 software. Increased level of education leads to increased seat belt usage, lower numbers of crashes and crash severities. The factors restricting seat belt use are lack of habit, discomfort and short distance driving. The use of precaution signal and increases in comfort can increase seat belt usage. The primary and high school education on traffic safety and seat belt usage has been serving the purpose.     

Water quality assessment of Almatti Reservoir of Bijapur (Karnataka State, India) with special reference to zooplankton

The present investigation deals with the limnobiotic status of Almatti reservoir from February, 2003 to January, 2005. The study revealed that, the distribution and population density of zooplankton species depend upon the physico-chemical factors of the environment. Statistical analysis showed that there exists a significant relation between the biological and non-biological factors. The benthic fauna constituting the food of fish can be utilized for extensive culture operation so that the nutrients in the reservoir are not only properly cycled but also serve as a check on further eutrophication.     

寒区典型湿地浮游植物功能群季节变化及其与环境因子关系

安邦河湿地是一个典型的寒区湿地,本文运用功能群的方法对其浮游植物季节变化进行研究,并运用多元分析方法分析其与环境因子的关系.安邦河湿地共有浮游植物种8门104种,划分为14个功能群,分别是C、D、E、F、H1、J、Lo、M、MP、N、P、SN、X1和Y.其中重要功能群是C、D、E、J、Lo、N、P和Y.浮游植物的功能群组成季节变化明显,春季以功能群E和Lo生物量所占比例最大,分别为27.45%和20.49%;夏季以功能群D、J、P占优,为28.59%、18.53%和19.47%;秋季以功能群J、P为主,占39.65%和13.34%.可见,安邦河湿地浮游植物功能群的季节变化呈现为E+Lo→D+J+P→J+P的特点,反映了水环境特征:春季低水温低营养盐、夏季高水温高营养盐且水体混浊、秋季水温和营养盐均较高.运用冗余分析(RDA)分析浮游植物功能群与环境因子之间的关系,结果显示水温(WT)、无机氮(DIN)和溶解性磷酸盐(SRP)是安邦河湿地浮游植物功能群季节变化的主要环境因子.     

紫色土丘陵坡地土壤微生物群落的季节变化

采用稀释平板法和Biolog-ECO微平板技术,以剌槐（Robinia pseudoacacia）天然次生林为研究对象,研究湖南省衡阳市紫色土丘陵坡地表层（0~10 cm）土壤微生物群落的季节变化特征。结果表明：1）夏季,土壤微生物总数,细菌数量、真菌数量和放线菌数量最高,分别为16.34×106、16.09×106、10.43×104和14.64×104 cfu·g-1干土,春季次之：11.61×106、11.45×106、5.00×104和10.65×104 cfu·g-1干土,秋季最低：5.87×106、5.78×106、4.67×104和4.08×104 cfu·g-1干土,春、夏和秋3季的差异达显著水平（P<0.05）;2）在培养168 h时,土壤微生物C源平均颜色变化率（Average well color development, AWCD）以夏季最高（1.20）,春季次之（0.88）,秋季最低（0.83）;3）土壤微生物功能多样性表现为夏季明显高于春、秋2季（P<0.05）,夏季的Patrick丰富度指数（R）（28）、Shannon-Wiener指数（H）（3.22）、Simpson指数（D）（0.96）和McIntosh指数（U）（8.20）显著高于春、秋2季（P<0.05）,而春、秋2季的R（23,24）、H（3.06,3.08）、D（0.95,0.95）和U（5.90,5.91）无显著差异（P>0.05）;4）氨基酸类、聚合物类和羧酸C源类是衡阳紫色土丘陵坡地土壤微生物偏好且利用率较高的C源类型;5）主成分分析表明,土壤微生物群落的C源利用可分为2类,一类在夏季,另一类在春、秋2季,其得分系数的分布范围分别为（2.59~6.00,2.43~5.09）和（-7.65~-1.90,-6.38~-3.43）。研究结果为科学评价湖南省衡阳市紫色土丘陵坡地土壤生境质量退化和恢复过程中微生物特征的变化提供了本底值参考。     

皖南地区铜陵市大气颗粒物污染特征及潜在源研究

利用2018年3月—2021年2月环境和气象数据对皖南地区铜陵市大气颗粒物的污染特征和潜在贡献源进行了系统性研究.铜陵市大气颗粒物污染具有明显的季节变化特征,冬季污染物浓度最高,PM_2.5和PM₁₀平均为（60.3±31.0）μg·m^-3和（89.2±42.2）μg·m^-3.计算发现PM_2.5/PM₁₀超过0.5,铜陵市的大气颗粒物污染问题与细颗粒物关系密切.后向轨迹聚类分析表明铜陵市大气颗粒物的输送路径具有季节性差异.春季以西北、东北和西南方向气流为主,占比83.73%;夏季以东南和南部方向气流为主,占比82.90%;秋季以东北气流为主,占比51.00%;冬季则是以北方和西北气流为主,占比69.81%.其中,冬季气流轨迹所对应的PM_2.5和PM₁₀的浓度最高,平均为59.7和92.0μg·m^-3;夏季最低,平均为23.8和43.8μg·m^-3.潜在源贡献因子（WPSC...     

甘肃南部典型城镇PM2.5浓度及水溶性离子特征分析

为研究甘肃南部城镇PM_2.5及水溶性离子（WSIIs）浓度水平,于2019年4月—2020年2月在甘肃成县按季度进行PM_2.5样品采集,分析了其变化特征,并运用相关和主成分分析法进行来源解析.结果表明：采样期间甘肃成县PM_2.5年平均质量浓度为（57.2±26.9） μg·m^-3,表现为冬季>春季>秋季>夏季的季节变化特征,冬季质量浓度约为夏季的1.9倍,全年空气质量优良率为81%,其中夏季达100%.WSIIs质量浓度呈现SO₄^2->NO₃^->Na⁺>NH₄⁺>Ca²⁺> K⁺>Cl^->Mg²⁺的特征.SNA是浓度水平最高的3种水溶性离子,占8种主要水溶性离子浓度的70.1%.ρ（NO₃^-）/ρ（SO₄^2-）平均值为0.6,表明工农业生产及化石燃料燃烧排放等固定源是颗粒物污染的主要来源.新型冠状病毒疫情期间人员管控对PM_2.5和水溶性离子中SNA质量浓度影响显著,PM_2.5平均质量浓度降幅达44.2%.源解析表明,PM_2.5中WSIIs主要来自化石燃料燃烧、生物质燃烧及二次源和道路建筑扬尘等.     

深圳市不同区域大气CO2变化特征与来源分析

于2020年12月1日~2021年12月1日分别在深圳市大学城和路边站两点位对大气CO₂和CO浓度进行了为期1a的观测.本次观测期间内两点位大气CO₂平均浓度分别为432×10^-6和439×10^-6,均呈现了“秋冬季高、春夏季低”的季节变化特征与“昼低夜高”日变化特征,且日变化特征在早晚高峰期受到交通源排放的显著影响.此外,通过引入CO₂和CO的净变化值得到大学城和路边站两点位的ΔCO₂/ΔCO值分别为136.8~184.8、59.0~119.3,结果表明机动车排放对深圳市大气CO₂贡献突出.