贡嘎山东坡亚高山不同林地土壤水分特性与生态环境效应

森林土壤水分特性，包括水分的渗透与蒸发、保持与贮存等对森林生态环境都有重要意义。本文研究了长江上游贡嘎山亚高山不同森林类型土壤的水分特征及其生态环境作用，结果表明：成熟林、过熟林土壤在储水、渗透、容水、蒸发和持水特性等多数方面利于保持和改善生态环境，次生或林分单一森林类型次之，林木皆伐后最差。研究区以成熟林和过熟林为主，生态环境保护较好。尽管该区与长江上游其它地区一样同具自然地理条件差、生态环境脆弱的特征，但由于该区森林植被和环境得到了有效保护，土壤水分特性好，促进了森林生态系统的良性循环，生态环境问题得到进一步改善。     

一种台风海面非对称风场的构造方法

针对台风数值预报中由于采用对称模型而导致预报误差的现实，通过引入非对称分布的台风最大风速、最大风速半径等因子，在得到台风报告中7级风和10级风的半径的基础上，利用最佳权系数方案来得到非对称的台风外围风速分布因子，从而对Chan and Williams 1987年提出的切向风廓线方案进行改造，进而得到了台风海面非对称风场的计算式。检验表明，该方法能够描述台风海面风场的非对称分布，具有较好的应用前景。     

A CLOUD-RESOLVING MODELING STUDY OF SURFACE RAINFALL PROCESSES ASSOCIATED WITH LANDFALLING TYPHOON KAEMI(2006)

The detailed surface rainfall processes associated with landfalling typhoon Kaemi(2006) are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 days with imposed large-scale vertical velocity, zonal wind, horizontal temperature and vapor advection from National Center for Environmental Prediction (NCEP) / Global Data Assimilation System (GDAS) data. The simulation data are validated with observations in terms of surface rain rate. The Root-Mean-Squared (RMS) difference in surface rain rate between the simulation and the gauge observations is 0.660 mm h^-1, which is smaller than the standard deviations of both the simulated rain rate (0.753 mm h^-1) and the observed rain rate (0.833 mm h^-1). The simulation data are then used to study the physical causes associated with the detailed surface rainfall processes during the landfall. The results show that time averaged and model domain-mean P_s mainly comes from large-scale convergence (Q_WVF) and local vapor loss (positive Q_WVT). Large underestimation (about 15%) of P_s will occur if Q_WVT and Q_CM (cloud source/sink) are not considered as contributors to P_s. Q_WVF accounts for the variation of P_s during most of the integration time, while it is not always a contributor to P_s. Sometimes surface rainfall could occur when divergence is dominant with local vapor loss to be a contributor to P_s. Surface rainfall is a result of multi-timescale interactions. Q_WVE possesses the longest time scale and the lowest frequency of variation with time and may exert impact on P_s in longer time scales. Q_WVF possesses the second longest time scale and lowest frequency and can explain most of the variation of P_s. Q_WVT and Q_CM possess shorter time scales and higher frequencies, which can explain more detailed variations in P_s. Partitioning analysis shows that stratiform rainfall is dominant from the morning of 26 July till the late night of 27 July. After that, convective rainfall dominates till about 1000 LST 28 July. Before 28 July, the variations of in rainfall-free regions contribute less to that of the domain-mean Q_WVT while after that they contribute much, which is consistent to the corresponding variations in their fractional coverage. The variations of Q_WVF in rainfall regions are the main contributors to that of the domain-mean Q_WVF, then the main contributors to the surface rain rate before the afternoon of 28 July.     

黄土高原半干旱区非均一下垫面粗糙度分析

利用2007年4月17日-2008年4月16日兰州大学半干旱气候与环境观测站边界层气象塔的风速、 风向、 温度、 气压、 湿度等观测资料, 采用经典的廓线法和风速、 风向标准差法, 分别计算了中性大气层结下观测站下垫面粗糙度长度, 并得到了具有黄土高原地理特征的地表粗糙度及其时空变化特征。计算结果表明, 季节变化对粗糙度的影响幅度可达0.159 m, 空间非均一性对粗糙度的影响幅度可达0.155 m。测站附近粗糙度春季为0.017 m, 夏季为0.062 m, 秋季为0.065 m, 冬季为0.018 m。测站西北方向上游粗糙度春季为0.17 m, 夏季为0.22 m, 秋季为0.34 m, 冬季为0.05 m。测站东南方向上游粗糙度春季为0.11 m, 夏季为0.17 m, 秋季为0.19 m, 冬季为0.05 m。该站下垫面粗糙度计算宜选用风速为6±1.5 m·s-1, 风向变化30°范围内的数据。     

不规则网土壤测量在水系沉积物异常查证中的应用

在大兴安岭森林沼泽景观区,植被茂盛、土壤表层腐殖质发育,且通视条件差,运用传统的规则网土壤测量方法进行1/5万水系沉积物异常查证,工作周期长、劳动强度大;采用不规则网土壤测量方法进行异常查证,取得了快速评价异常、追踪异常源,缩短找矿周期的效果。     

Spatial variability of soil nutrients in Punta Fort William,Greenwich Island,maritime Antarctic

This study aims to report baseline soil nutrients, specifically the organic carbon, nitrogen and phosphorus profile, in soil samples collected from Puntta Fort William on Greenwich Island in maritime Antarctic. Samples were collected along two transect lines during the early summer of 2008. Ward＇s method of hierarchical agglomerative clustering was employed to group the sampling points based on their physico-chemical properties. In this context, the soil samples can be grouped into three major clus- ters： （1） Samples with intensive biological activities, （2） samples from the area recently exposed by glacial retreat and （3） samples from barren and dried areas. Nutrient contents in Punta Fort William are driven by the intensity of biological activities as well as melt water from the Qnito glacier.     

火山岩与地形联合约束下海岛土壤稀土元素地球化学空间分布异质性——以广西涠洲岛为例

海岛土壤地球化学特征的研究对于认识海岛表生地质环境有重要意义。本研究以我国最大的第四纪火山海岛——涠洲岛为案例,重点研究亚热带海岛环境下火山岩风化土壤的稀土元素（REE）地球化学特征,并探讨影响其空间分布的关键因素。结果表明,涠洲岛土壤REE总量（ΣREE）自然变化范围较大,介于59.07~575.30 mg/kg,平均值为285.53 mg/kg,高于中国大陆土壤背景值（163.86 mg/kg）,指示火山岩风化海岛具有较高的土壤REE丰度。反距离权重插值法（IDW）分析指示,岛内土壤的REE含量高低变化呈现出以带状和斑块状为主体形态的空间分布不均一性,推断其成因与母质岩石类型和地形位置等因素密切相关。3种不同岩性的成土母岩的ΣREE含量变化序列为：玄武岩（236.66 mg/kg）>火山碎屑岩（215.58 mg/kg）>含生物碎屑海滩沉积物（18.99 mg/kg）,对应的土壤ΣREE含量具有类似变化规律,即玄武岩土壤（307.20 mg/kg）>火山碎屑岩土壤（297.46 mg/kg）>含生物碎屑海滩沉积物土壤（89.73 mg/kg）。该证据指示母岩是控制岛内土壤REE含量变化的首位因素,玄武岩整体上易形成具有较高REE丰度的土壤,火山碎屑岩次之,而含生物碎屑海滩沉积物反之。此外,本研究还发现火山碎屑岩单一岩性区内,发育的土壤REE含量也会随地形地貌差异而出现显著变化,其原因是地形地貌制约了土壤矿物和化学风化程度,海蚀丘陵比海积平原更利于海岛土壤中REE次生富集作用的发生。

     

山东省桓台地区土壤F的地球化学特征及其影响因素

为研究土壤氟的地球化学特征及其影响因素,选取山东省桓台地区为研究区,系统采集了70件表层土壤样品,并测试分析了其中F元素、有机碳含量、pH值等共计8项指标。绘制了元素地球化学图,掌握了该区F元素含量的空间分布特征。研究结果表明,表层土壤F含量范围为466.30~793.40 mg/kg,平均F含量为621.31 mg/kg,显著高于山东省背景值和全国背景值,具有潜在环境生态风险。研究区总面积70%的土壤F含量较高,其中F含量过剩的土壤相对集中分布在城镇附近;研究区东南部青银高速附近和北部呈零星分布的土壤中氟为适中及边缘含量水平。土壤中F含量主要受控于土壤pH、有机碳含量和施肥。该研究结果为改善研究区环境质量,防止地方性氟中毒提供了基础数据和科学依据。     

沙地节水渗灌自动控制系统的研制

文章介绍了一种沙地节水渗灌自动控制系统装置,主要叙述了渗灌装置的结构组成与连接方法,以及系统的软、硬件组成与仪器功能指标,整个系统设计简洁,成本低,可靠性好,能自动监测沙地水分上下限和渗坛水位上下限,根据所需信息系统自动向管道供水,大幅度减轻操作人员的劳动强度。采用微机技术有利于农业现代化管理,是我国节水渗灌农业值得推广的自动化控制系统     

Neumann stochastic finite element method for calculating temperature field of frozen soil based on random field theory

To study the effect of uncertain factors on the temperature field of frozen soil, we propose a method to calculate the spatial average variance from just the point variance based on the local average theory of random fields. We model the heat transfer coefficient and specific heat capacity as spatially random fields instead of traditional random variables. An analysis for calculating the random temperature field of seasonal frozen soil is suggested by the Neumann stochastic finite element method, and here we provide the computational formulae of mathematical expectation, variance and variable coefficient. As shown in the calculation flow chart, the stochastic finite element calculation program for solving the random temperature field, as compiled by Matrix Laboratory (MATLAB) software, can directly output the statistical results of the temperature field of frozen soil. An example is presented to demonstrate the random effects from random field parameters, and the feasibility of the proposed approach is proven by comparing these results with the results derived when the random parameters are only modeled as random variables. The results show that the Neumann stochastic finite element method can efficiently solve the problem of random temperature fields of frozen soil based on random field theory, and it can reduce the variability of calculation results when the random parameters are modeled as spatially random fields.