近40a来海南岛南岸的相对海平面变化

根据海南岛榆林验潮站１９５４～１９９２年连续３９ａ潮位观测资料，经过统一基准面校正后，运用多种统计分析方法研究，得出近４０ａ来海南岛南岸的相对海平面变化呈上升趋势，相应的平均上升速率为０．６４ｍｍ／ａ，这一数值较近百年来１～２ｍｍ／ａ的全球海平面上升速率明显偏小，反映出同期海南岛南岸的地面是微弱抬升的。     

Microcoleus autumnalis and filamentous algae-dominated mats and chlorophyll-a increase with agricultural land use but respond differently to associated nutrient and sediment enrichment

ABSTRACT

This study investigated the impact of pastoral land use and nutrient and fine sediment inputs on Microcoleus autumnalis and filamentous algae-dominated mats, and benthic chlorophyll-a in streams (lower North Island, New Zealand). Surveying and sampling was undertaken monthly at 61 sites spanning a wide gradient in catchment cover and environmental conditions. Two boosted regression tree models were built. The first models included pastoral land cover and five environmental variables as predictors. In the second model pastoral land cover was replaced by nutrient/sediment data. The abundance of the two mat types and chlorophyll-a increased when pastoral land cover was between 20% and 70% (model 1). Replacement of pastoral land cover by nutrient/sediment data (model 2) slightly improved the model fit for all three periphyton variables. Microcoleus autumnalis-dominant mats increased with dissolved inorganic nitrogen concentrations up to ca. 0.6?mg?L^?1, and in streams with more frequent flushes. In contrast, filamentous algal-dominated mats increased with turbidity, and in streams with less frequent flushes. Chlorophyll-a generally followed the response of the dominant periphyton type. Increased knowledge on responses of specific periphyton types, rather than total biomass, to environmental variables is essential to guide effective management strategies.     

山东省大中型水库水化学性状研究──几种主要水化因子的变化及其在评价水库鱼产力中的作用

本文通过对山东省３８座代表性大、中型水库总氮（ＴＮ）、总磷（ＴＰ）、化学耗氧量、硬度及电导率（λ）五种主要水化因子连续两年（１９８９～１９９０）的调查与研究，探讨了水化因子与水库鱼产力的关系。用反映鲢、鳙生长状况的综合生长指数（ＧＩ）作为水库鱼产力的指标。它与水化因子相关分析表明，总磷是山东省３８座水库鱼产力的主要影响因子。提出ＧＩ与总磷、总氮及电导率等水化因子的逐步回归方程关系非常显著。证明利用水化因子作为水库鱼产力的评价指标是可行的。并指出：同一水库的相同水化因子存在年间差异，其主要原因在于降雨量和水库进水量的不同，鉴于此．同一水库鱼产力也存在年间差异。     

成都地区大气平均温度建模及其在GPS/PWV计算中的应用研究

地基GPS气象学的关键技术是在于通过垂直方向上GPS信号的湿分量延迟值来确定大气可降水量-PWV,而这两个物理量间进行转换时需要用到一个关键性的参数——大气加权平均温度。本文首先讨论了估算加权平均温度的几种方法,然后利用成都地区2005年全年的大气探空数据,采用回归分析方法,建立了适合成都地区的大气加权平均温度模型,精度为±2.21K。最后将该公式应用到成都地区PWV的计算中,得到了非常理想的效果。     

Monotone Regression and Correction for Order Relation Deviations in Indicator Kriging

The indicator kriging (IK) is one of the most efficient nonparametric methods in geo-statistics. The order relation problem in the conditional cumulative distribution values obtained by IK is the most severe drawback of it. The correction of order relation deviations is an essential and important part of IK approach. A monotone regression was proposed as a new correction method which could minimize the deviation from original quintiles value, although, ensuring all order relations.     

基于高光谱Hyperion数据的线性光谱混合模型与神经网络模型的比较

混合像元问题是定量遥感中的热点问题之一,为了改进从遥感数据中提取定量信息,人们建立了各种混合光谱分解技术,其中线性光谱混合模型和神经网络模型就是两种比较成熟的方法。以陕西省横山地区的高光谱Hyperion数据为研究基础,通过最小噪声变换(MNF)、像元纯度指数(PPI)转换和RMS误差分析的迭代方法相结合提取影像中的纯净像元作为终端端元。分别运用神经网络模型和线性光谱混合模型对影像进行光谱分解,得到各个组分的分解图像。以标准植被指数(NDVI)影像为衡量标准,选取训练样本点,分别对两种模型进行回归分析,结果显示NDVI影像与线性光谱混合模型植被分解图像的判定系数(R2=0.91)要大于其与神经网络模型的判定系数(R2=0.81)。进一步分析表明在一般情况下,线性光谱混合模型具有比神经网络模型略高的分离精度,但是神经网络模型对细部信息的提取的效果要好于线性光谱混合模型,最后提出了端元均方根误差(EAR)指数,一种新的混合像元分解的思路。     

天津市地下水开采对地面沉降影响的多元回归分析

地下水的过量开采是天津市引起地面沉降的主要原因。因此天津市提出了“压缩地下水开采量”、“地下水人工回灌”、“调整地下水开采层次”等控制地面沉降的3大技术措施。经过多年的努力,控制地面沉降效果明显。如何解决地下水开发与控制地面沉降的关系,更好的贯彻这3大技术措施,是该文编写的初衷。即在开采同样地下水量的情况下,如何使地面沉降量最小;或在地面沉降量容许的情况下,如何开采最大量的地下水。压缩地下水开采量是治理地面沉降的根本措施,亦即如何压缩采水量或调整开采层次会达到最好效果。论文对天津市某区各个地下水开采层的多年累计开采量、累计沉降量进行数据统计分析,建立了该地区累计沉降量及各个地下水开采层的多元相关方程。在此基础上,分析了各个地下水开采层对地面沉降影响的相关程度。以此为该区控制地面沉降的提供依据。     

鲁北平原区井灌回归系数分析

利用井灌回归系数计算回归补给水量,是地下水资源评价计算井灌回归水量的基本方法。井灌回归系数确定的合理与否,直接影响到地下水资源评价成果的合理性。以试验站的观测资料为基础,结合引水灌溉调查成果,对影响井灌回归系数大小的因素和区域分布规律进行了系统分析,依地下水埋深和灌溉方式划分引黄灌区、井河结合灌区、井灌区三种类型,分析确定鲁北平原区适用的井灌回归系数。     

新疆天山公路沿线地质灾害危险性评价

新疆天山公路（国道217线）是连接南、北疆的一条重要交通干线。通过调查研究沿线的地质条件,采用多元线性回归分析方法,选取地层岩性、地面坡度、相对高差、构造密度、多年平均降雨量、冻融作用、地震强度、植被覆盖率、开挖深度、灾害的分布密度和规模大小等11个评价因子,建立了地质灾害危险性级别的评价模型,得出了公路沿线的危险性级别图。     

Change of Support for Estimating Local Block Grade Distributions

An important aspect in mineral resource evaluation is the reduction of variance when post-processing the grade distributions defined on the support (volume) of the available data into distributions defined on the support of the proposed selective mining units. Although the volume-variance relationship is well understood for the estimation of global grade distributions, it is still an unsolved issue for local estimation studies based on non-parametric geostatistical methods, such as indicator kriging, for which the support correction is not inherent to the method. To clarify this relationship, the local change of support problem is examined in the scope of two parametric models (multi-Gaussian and discrete Gaussian models). It is shown that the variance reduction factor between point and block-support local distributions depends on the block being considered and is less than the global variance reduction factor. As a consequence, post-processing the local point-support grade distributions on the basis of the latter systematically understates the importance of the change of support at the local scale and makes selective mining appear more economically attractive than it really is. In the light of these results, a methodology is proposed to post-process the local point-support distributions obtained via non-parametric (indicator) methods into block-support distributions. An application to simulated data indicates that this methodology provides an accurate estimation at the block support when dealing with diffusion-type random fields.