3DCM的几何与纹理数据一体化管理方法研究

建设三维城市模型(3DCM)首先需要建立场景所需的海量地形地物空间数据库,从而有效组织三维实体数据来满足大范围高精度场景实时绘制的要求.该文提出一种以三维空间实体为单位的基于关系数据库(RDBMS)的3DCM的几何与纹理数据一体化管理方法.采用Direct3D 9.O三维开发平台、C#编程语言实现了3DCM空间数据库模型管理系统.实验证明:该系统在效率、安全、网络多用户访问方面都优于传统基于文件的管理模式,满足了大范围3DCM海量模型数据管理与应用需求.     

考虑水文变异的黄河干流河道内生态需水研究

气候变化及人类活动导致水文变异,变异前后样本总体分布显著不同,即改变了当地生态系统的水文状况,打破生态平衡。本文使用滑动秩和检验(Mann-Whitney U检验) 分析水文变异,并对水文变异成因做了系统的分析。在此基础上,对变异前各月平均流量序列用线性矩法推求GEV分布参数,求出概率密度最大流量,并将其视为相应月河道内生态流量。本文用该法计算黄河干流7 站各月河道内生态流量,即得河道内生态需水情况。分析表明,考虑水文变异的河道内生态需水计算方法是可行的;水文变异后,黄河流域干流各水文站满足生态需水的频率大大降低,汛期降低幅度比非汛期大;黄河生态系统水环境恶化的主要原因是人类活动。     

水环境承载力理论研究与展望

水环境承载力作为衡量水环境与社会经济协调发展程度的研究刚刚起步,目前尚未形成比较完善的理论体系。该文在总结现有研究成果的基础上,从理论上明确了水环境承载力的概念、本质、特征、研究内容及意义。基于力学的基本理论,建立了水环境承载力的表达式,进而提出纳污弹性力的概念,对进一步研究水环境与可持续发展的相关关系具有实际意义。     

元谋干热河谷坡耕地土壤侵蚀造成的土地退化

在元谋干热河谷土壤侵蚀特征分析的基础上，对坡耕地土壤侵蚀造成的土地退化进行了模拟研究。结果表明，土壤侵蚀造成表层耕作土壤的物理性能下降、养分流失和水分入渗能力降低。表层耕作土壤的容重比下层土壤低12．7％，总孔隙度高10．9％，有机质高37．3％，120min累计入渗总量是下层土壤的1．6-2．2倍。模拟土壤侵蚀与土地生产力关系的小区试验结果显示，坡耕地每流失1cm表土，土地生产力水平平均下降4．54％。     

湖南省城市化与经济发展关系的计量分析

运用现代计量经济学的计量分析方法对湖南省城市化与经济发展的相互关系与相互作用进行了探讨。结果表明,城市化与经济发展二者之间存在协整关系即长期均衡关系,但短期失衡,其波动有近35％得到调整;经济发展对城市化的冲击强烈,其解释水平高达到82％;城市化对经济发展冲击微弱,其解释水平仅达到5．4％;经济发展来自自身的冲击较大,而城市化来自本身冲击较小,但有增强趋势。经济发展与城市化二者之间的这种关系作用应引起关注。     

南昌地区建设用地空间扩展的广义转移概率模型建设与应用研究

对南昌地区城市发育约束因素的分析的基础上,基于非城市像元所处的城市化梯度、距离最近建成区斑块的距离、最近建成区斑块的规模、边缘像元的邻域水平等4个城市景观格局因子和道路及地形等两个社会经济和自然影响因子,构建了广义转移概率模型,并开展了相关的动态模拟研究。表明,与传统模拟方法相比,该模型具有比较理想的精度水平,模拟结果能够很好地反映南昌地区今后城市建设用地发展趋势,提出的模型手段改进设计获得了令人满意的效果,是对现行城市景观动态模拟研究工作的一个重要的方法论补充和完善。     

鄱阳湖流域径流模型

流域径流是鄱阳湖主要来水,建立鄱阳湖流域径流模型对揭示湖泊水量平衡及其受流域自然和人类活动的影响具有重要意义.针对鄱阳湖-流域系统的特点:流域面积大(16.22×104km2)、多条入湖河流、湖滨区坡面入湖径流等,研究了相应的模拟方法,建立了考虑流域土壤属性和土地利用空间变化的鄱阳湖流域分布式径流模型.采用6个水文站1991-2001年的实测河道径流对模型进行了率定和验证.结果显示,模型整体模拟精度较高.其中,赣江、信江和饶河均取得了较好的模拟结果,月效率系数为0.82-0.95;抚河和修水模拟精度略低,为0.65-0.78.模型揭示了研究时段内年平均入湖径流总量为1623×108m3,其中,赣江最多,占47%,其次为信江和抚河,分别占13%和12%,湖滨区坡面入湖径流约占4%,其余24%来自饶河、修水以及其它入湖支流.模型将用于评估流域下垫面或气候变化引起的入湖水量变化,为湖泊水量平衡计算提供依据.     

季节内印度洋-西太平洋对流涛动对次季节-季节尺度大气可预报性的影响

利用非线性局部Lyapunov指数和条件非线性局部Lyapunov指数定量估计了季节内印度洋-西太平洋对流涛动（IPCO）和实时多变量Madden-Julian指数（RMM指数）可预报期限,量化了季节内IPCO对S2S尺度大气可预报性的贡献,深入研究了季节内IPCO演变下S2S尺度可预报期限空间分布的变化规律。结果表明：（1）与RMM指数相比,季节内IPCO指数可预报性更强,可预报期限达到31天左右,比RMM指数高出2周以上;（2）印度洋-西太平洋区域S2S尺度大气可预报性最强,可预报期限达到30天以上,其中季节内IPCO是该地区的主要可预报性来源之一,其贡献达到6天,占总可预报期限的25%以上;（3）随着季节内IPCO的演变,印度洋-西太平洋地区S2S尺度大气可预报性有空间结构变化,表现为可预报期限异常的传播和振荡。S2S尺度大气可预报期限正负异常沿季节内IPCO传播路径,一支以赤道中西印度洋为起点北传至印度半岛,一支向东传播,经过海洋性大陆到赤道西太平洋后向北传播,到达日本南部。同时,可预报性异常的传播在在东印度洋和西太平洋表现出反向变化的特征,形成东西两极振荡,当季节内IPCO向正位相发展时,东印度洋具有更强的可预报性,西太平洋具有更弱的可预报性,反之亦然。季节内IPCO的发展（衰退）可使东印度洋（西太平洋）S2S尺度大气可预报性更强,表明模式预报技巧对此具有更大的提升空间。     

Vertical structures of PM10 and PM 2.5 and their dynamical character in low atmosphere in Beijing urban areas

The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower.