流域地理景观的GIS数据三维可视化

应用以"GIS"为核心的空间信息技术,是开展"数字流域"工程建设自然和最佳的选择。结合"清江流域水文水情与洪水演进仿真系统"的具体研制,分析流域地理数据特点及传统GIS在"数字流域"建设中的优缺点,在应用传统GIS二维方式展示形式管理和预处理先期各类基础流域地理空间数据及其相应属性数据的基础上,为满足仿真系统系列三维可视化要求,建立面向流域空间实体对象的数据模型,定义流域地理空间对象数据结构,将流域地理常规的GIS数据以三维形式展示,在实际的系统开发过程中,取得较好的三维可视化效果,并可满足"数字清江"建设各阶段综合处理、分析、评价、决策以及可视化等方面的需求。     

La prévision du climat : de l'échelle saisonnière à l'échelle décennale

The atmosphere and the ocean are subject to many dynamical instabilities, which limit the time during which their behaviour can be deterministically forecasted. At longer timescales, the atmosphere can be predicted at best using statistical methods, as a response to external forcing linked to sea- and land-surface anomalies. Climate being defined as the mean of atmospheric states, it appears that it can be predicted up to a few months in advance, which is the characteristic time of the so-called slow components of the climate system. Forecasting can sometimes be extended to longer time ranges, especially when the coupled ocean–atmosphere system exhibits internal variability modes, with characteristic times of a few years. Seasonal climate forecasting is most often based upon Monte-Carlo simulations, where the various realisations correspond to slightly different initial conditions. The present sate-of-the-art in Europe (ECMWF) and/or in the USA (IRI) allows to forecast such major phenomena, as El Niño, up to six months in advance. Finally, some parameters may exhibit predictability at still longer time-ranges (inter-annual to decadal), but only for certain regions. The example of electricity production is used to underline the potentially large economical benefit of seasonal climate forecasting. To cite this article: J.-C. André et al., C. R. Geoscience 334 (2002) 1115–1127.

Résumé

L'atmosphère et l'océan sont le siège d'instabilités dynamiques, qui limitent la durée pendant laquelle il est possible d'en prévoir l'évolution de façon déterministe. Au-delà, l'atmosphère n'est plus prévisible, au mieux, que de façon statistique, en fonction du forçage externe qu'exerce(nt) sur elle l'océan et/ou la surface des continents. Le climat (au sens d'une moyenne des états atmosphériques) se révèle ainsi prévisible jusqu'à des échéances temporelles de quelques mois, échelle de temps caractéristique des composantes dites « lentes » du système climatique. La prévision peut s'étendre à des échéances parfois plus longues, dans le cas où le système couplé océan–atmosphère posséderait des modes de variabilité temporelle de périodes caractéristiques de quelques années. La prévision climatique saisonnière est très souvent construite à partir de simulations de type Monte-Carlo, avec des ensembles de réalisations utilisant des conditions initiales légèrement différentes. Dans l'état actuel de ces prévisions, qu'elles soient réalisées en Europe (CEPMMT) ou aux États-Unis (IRI), il est possible de prévoir environ six mois à l'avance un certain nombre de phénomènes climatiques, en particulier ceux liés aux épisodes dits « El Niño », pour lesquels l'amplitude des variations est suffisamment importante. Il existe, par ailleurs, une prévisibilité à encore plus longue échéance (inter-annuelle à décennale), mais seulement pour certains paramètres et certaines régions. L'exemple de la production d'électricité montre l'importance économique potentielle très grande de la prévision climatique saisonnière. Pour citer cet article : J.-C. André et al., C. R. Geoscience 334 (2002) 1115–1127.     

地质灾害的非线性数据处理与建模技术

本文简略地介绍了几种地质灾害数据处理与建模的非线性方法,主要包括GMDH自组织建模技术、神经网络方法。GMDH是一种高阶非线性回归建模方法,它是以简单的二元二次回归方程为基础,通过"代复一代"的"生产"过程,客观、自动地求得实际资料的非线性模型。而神经网络则是用工程技术手段模拟生物神经网络的结构特征和功能特征的一类人工系统。与常规统计方法相比,神经网络最突出的优点为它是通过对网络的学习和训练,来掌握变量之间的非线性关系。因此,其处理复杂问题的能力更强大。实例检验效果表明,这些非线性数据处理与建模技术考虑了地质灾害问题的非线性特性,其比基于常规统计理论的数据处理方法的精度要高得多。     

A modified ISBA surface scheme for modeling the hydrology of Athabasca River Basin with GCM-scale data

A soil–vegetation–atmosphere transfer model (SVAT), interactions between the soil–biosphere–atmosphere (ISBA) of Météo France, is modified and applied to the Athabasca River Basin (ARB) to model its water and energy fluxes. Two meteorological datasets are used: the archived forecasts from the Meteorological Survey of Canada’s Global Environmental Multiscale Model (GEM) and the European Centre for Mid-range Weather Forecasts global re-analysis (ERA-40), representing spatial scales typical of a weather forecasting model and a global circulation model (GCM), respectively. The original treatment of soil moisture and rainfall in ISBA (OISBA) is modified to statistically account for sub-grid heterogeneity of soil moisture and rainfall to produce new, highly non-linear formulations for surface and sub-surface runoff (MISBA). These new formulations can be readily applied to most existing SVATs. Stand alone mode simulations using the GEM data demonstrate that MISBA significantly improves streamflow predictions despite requiring two fewer parameters than OISBA. Simulations using the ERA-40 data show that it is possible to reproduce the annual variation in monthly, mean annual, and annual minimum flows at GCM scales without using downscaling techniques. Finally, simulations using a simple downscaling scheme show that the better performance of higher resolution datasets can be primarily attributed to improved representation of local variation of land cover, topography, and climate.     

Efficient seismic response data storage and transmission using ARX model‐based sensor data compression algorithm

This paper presents a linear predictor (LP)‐based lossless sensor data compression algorithm for efficient transmission, storage and retrieval of seismic data. Auto‐Regressive with eXogenous input (ARX) model is selected as the model structure of LP. Since earthquake ground motion is typically measured at the base of monitored structures, the ARX model parameters are calculated in a system identification framework using sensor network data and measured input signals. In this way, sensor data compression takes advantage of structural system information to maximize the sensor data compression performance. Numerical simulation results show that several factors including LP order, measurement noise, input and limited sensor number affect the performance of the proposed lossless sensor data compression algorithm concerned. Generally, the lossless data compression algorithm is capable of reducing the size of raw sensor data while causing no information loss in the sensor data. Copyright © 2005 John Wiley & Sons, Ltd.     

Influence of long‐period filter cut‐off on elastic spectral displacements

The effect of the long‐period filter cut‐off, T_c, on elastic spectral displacements is investigated using a strong ground‐motion database from Europe and the Middle East. The relation between the filter and oscillator responses is considered to observe the influence of T_c for both analogue and digital records, and the variations with site classification, magnitude, filter order and viscous damping. Robust statistics are derived using the re‐processed European data to generalize the effects of the long‐period filter cut‐off on maximum oscillator deformation demands as a function of these seismological and structural features. Statistics with a 95% confidence interval are derived to suggest usable period ranges for spectral displacement computations as a function of T_c. The results indicate that the maximum period at which spectral displacements can be confidently calculated depend strongly on the site class, magnitude and filter order. The period range where reliable long‐period information can be extracted from digital accelerograms is twice that of analogue records. Copyright © 2006 John Wiley & Sons, Ltd.     

Study on the processing method of nighttime CO_2 eddy covariance flux data in ChinaFLUX

At present, using Eddy Covariance (EC) method to estimate the "true value" of carbon sequestration in terrestrial ecosystem arrests more attention. However, one issue is how to solve the uncertainty of observations (especially the nighttime CO2 flux data) appearing in post-processing CO2 flux data. The ratio of effective and reliable nighttime EC CO2 flux data to all nighttime data is relatively low (commonly, less than 50%) for all the long-term and continuous observation stations in the world. Thus, the processing method of nighttime CO2 flux data and its effect analysis on estimating CO2 flux annual sums are very important. In this paper, the authors analyze and discuss the reasons for underestimating nighttime CO2 flux using EC method, and introduce the general theory and method for processing nighttime CO2 flux data. By analyzing the relationship between nighttime CO2 flux and air fraction velocity u., we present an alternate method, Average Values Test (AVT), to determine the thresholds of fraction velocity (u.c) for screening the effective nighttime CO2 flux data. Meanwhile, taking the data observed in Yucheng and Changbai Mountains stations for an example, we analyze and discuss the effects of different methods or parameters on nighttime CO2 flux estimations. Finally, based on the data of part ChinaFLUX stations and related literatures, empirical models of nighttime respiration at different sites in ChinaFLUX are summarized.     

云南兰坪—思茅盆地中轴构造带的特征及其研究意义

笔者利用云南西部已有的DSS地震测深、石油反射地震资料的再解释,并通过地球物理、地球化学以及矿产等资料的综合分析,对滇西兰坪—思茅盆地内的中轴构造带的构造特征进行了深入分析。研究结果表明兰坪—思茅盆地内的中轴构造带是一条近南北走向的集断裂带、伸展构造、深部隆起为一身的大型构造带。地震测深的速度结构及反射地震剖面表明,中轴构造带在思茅盆地南部存在有深部地幔的上隆现象,该构造带内的断裂系统倾向在盆地南北有差异。研究发现该构造带与矿床、侵入碱性岩体及区域地化异常分布有密切的关系。结合地质构造分析研究,表明该构造带是一多期活动的重要构造带,具有伸展走滑的性质;中轴构造带在形成、演化过程中被近东西向的多条直线型断裂所错断,从构造形态上看与大洋中脊有相似的展布特征。该构造带对盆地的构造演化以及矿产形成具有重要控制作用。     

共反射面叠加在实际地震资料处理中的应用

共反射面叠加方法运用3个地震波场参数来描述地下反射面元时距关系,不对地下反射界面形状做任何假设,并且是一种不依赖于宏观速度模型的反射波成像方法。共反射面叠加利用了邻近多个共反射点道集的相似性,提高了资料的覆盖次数,从而压制了随机噪声,增强反射波同相轴的连续性,大幅提高了地震资料的信噪比。通过在实际地震资料处理中的应用,证明了该方法的这些特性。     

水文资料在水土保持中的应用研究

本文简要分析了我国水文资料的基本特点及其在水土保持中的应用情况,并结合水文资料在水土保持中的研究实例,探讨了加强水文资料在水土保持中应用范围与价值,在新一轮的站网调整建设中应与水土保持监测站网建设结合起来,避免重复建设,加强水文站网功能,发挥现有水文站网作用。