三峡库区水土流失特点及其环境危害防治措施探讨

水土流失是三峡库区主要环境问题之一,也是库区产生大量泥沙的根本因素,更是造成库区人民生活贫困的根源。本文就三峡库区水土流失的特点及其环境危害作了分析,提出了相应的防治措施,为水土流失防治工程提供科学依据。     

SELECTING TREND TESTS FOR WATER QUALITY SERIES WITH SERIAL CORRELATION AND MISSING VALUES1

ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily.     

湖北省2008年初低温雨雪冰冻过程气候特征分析

2008年初，湖北省出现了严重的低温雨雪冰冻灾害，直接经济损失高达110亿元以上，有必要对灾害期间的气候特征进行系统、科学的分析和总结。对湖北省76个气象站2008年1月12日～2月3日气温、降水（雪）、日照以及低温持续日数等要素进行时空间差异分析及历史与同期比较，并选取10个代表站历史上所有低温雨雪天气过程，对其过程持续低温日数、最长连续雨雪日数、过程极端低温进行比较分析。结果表明：（1）此次过程的平均气温异常偏低，该省大部为-1～-2℃，比常年同期偏低4～6℃，为各站历史同期最低，其中主要是最高气温异常偏低所致，但极端低温并不低；（2）降雪过程频繁，雨雪量异常偏多；（3）低温冰冻持续时间长，该省大部在16～22 d，位于历史第一；（4）日照异常偏少。持续而稳定的大气环流异常形势是湖北省大范围低温雨雪天气的直接原因。     

Dynamics of growth and seed production in the Siberian stone pine: The level and pattern of variation in characters

A statistical analysis of interannual variation in a set of vegetative and generative characters over 13 years has been performed to characterize the growth and seed production dynamics of the Siberian stone pine (Pinus sibirica Du Tour) in the southeast of the forest zone in western Siberia. The results have shown that the range of fluctuations in most of vegetative characters is ordinary and their distribution is close to normal. The range of fluctuations in many generative characters is enormous (from 0 to +∞), and the distribution of their values is usually skewed, with low values being recorded several times more frequently than high values. Most variable are the proportion of abortive cones and other characters that are determined mainly in the spring of the pollination year. These characters account for a very high level of variation in the total seed production.     

Coincidence and Upgrade： A Typical Case Study of Rural Ecotourism Development

At present, internal rural tourism is at the stage of upgrading and renewing, and ecotourism has been considered to be the main direction. This paper discussed the concepts and criteria of rural tourism and ecotourism, analyzed a typical case of Nongke Village of Chengdu City-being considered to be the first rural tourism site in China, went deep into the problems of the contents and criteria of the development of rural ecotourism, and tried to probe into the principles of the development of rural ecotourism both theoretically and practically so as to understand the rules of the development of rural ecotourism .     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

长江三峡柑桔的冻害和热害（二）

本文从柑桔冻害和热害的危害因子和指标等级划分的研究和选取入手,着重探讨了长江三峡地区(湖北境内)两害显著的时空变化特征、差异与关联性及对柑桔生产的影响;揭示了80年代以来冬暖春热的重大气候变化是使两害向“两极分化”的根本原因;讨论了三峡水利工程对两害时空格局的可能调整及减灾原理;最后提出了可能的对策。     

ARSENIC CONSUMPTION AND HEALTH RISK PERCEPTIONS IN A RURAL WESTERN U.S. AREA1

ABSTRACT: Churchill County, Nevada, has approximately 23,000 residents, among whom an estimated 13,500 relied on private wells for water supply in 2002. This study examined exposure to arsenic in water supplies among residents with private domestic wells and factors related to householder choice to consume tap water. It compared opinions and concerns about water quality with consumption habits and observed concentrations from tap water samples. The results from 351 households indicated that a majority (75 percent) of respondents consumed tap water and that a minority (38 percent) applied treatment. Approximately 66 percent of those who consumed tap water were exposed to concentrations of arsenic that exceeded 10 ppb. Water consumption was related to application of treatment. Among 98 respondents who were not at all concerned about the health effects of aqueous arsenic, 59 (60 percent) reported consuming tap water with concentrations of arsenic exceeding 10 ppb. Conversely, among 86 respondents who were highly concerned about arsenic, 33 (37 percent) consumed tap water with concentrations of arsenic exceeding 10 ppb. Results from a national sampling effort showed that 620 of 5,304 private wells sampled (11.7 percent) had arsenic concentrations above 10 ppb. The paradox of awareness of arsenic in water supplies coupled with consumption of aqueous arsenic in concentrations greater than 10 ppb may be common in other parts of the nation. Enhanced educational efforts, especially related to tap water sampling and explanations of efficacy of available treatment, may be useful means of reducing exposure through private water supplies.     

岷江上游崩塌滑坡分布规律研究

岷江为长江—级支流，上游长３３０ｋｍ，自１９８６年以来，发生崩塌滑坡２００余处，体积约２．１亿ｍ￣３。作者研究了岷江上游崩塌滑坡的分布规律。采用统计指标法，将岷江上游分为三种不同的崩塌滑坡分布密度区：①ＵＸＳ．高密度区；②ＭＸＳ，中密度区；③ＬＸＳ＿３低密度区。