青海地区钻孔应变干扰及异常分析

简要叙述了青海地区6个钻孔应变台站的观测概况,通过分析,认为主要存在观测技术系统和观测环境变化这两类干扰。在排除各类干扰后,发现只有乐都台和湟源台在汶川地震前出现了前兆异常。     

DEM流径算法的相似性分析

流径算法是分布式水文模型、土壤侵蚀模拟等研究中的关键技术环节,决定着汇水面积、地形指数等许多重要的地形、水文参数的计算。本文以黄土高原两个典型样区的不同分辨率DEM为研究对象,对常用的五种流径算法(D8、Rho8、Dinf、MFD和DEMON)通过相对差系数、累积频率图、XY散点分布图等进行了定量的对比分析。结果表明:算法的差异主要集中在坡面区域,汇流区域各类算法的差别较小;算法差异在不同DEM尺度下都有所体现,但高分辨率下的差异会更明显;在地形复杂区域,多流向算法要优于单流向算法。研究也进一步指出汇水面积、地形指数等水文参数对流径算法具有强烈的依赖性。     

汶川8.0级地震前后表层水温的异常变化研究

对汶川8.0级地震震中周围800km范围内73个井孔的表层水温资料进行了分析。根据设定的异常与不确定性异常判定依据,发现有9个井孔出现了前兆异常;有5个井孔的异常不能确定是否为前兆异常;有3个井孔出现了典型非前兆异常变化;其余未出现任何异常变化。分析认为异常存在早期、中期和晚期三个阶段,表现为缓变、突变和向下的阶梯状变化。对9个异常井孔的同井水位、气氡等其它流体测项以及同台或邻近台站形变仪器(钻孔应变、钻孔倾斜、洞体应变等)在表层水温异常变化时段内的动态变化特征进行了对比,发现地壳形变与表层水温在异常的晚期阶段具有一定的相关关系;而同井水位与表层水温异常的关系不大。     

2008年8月30日和静M_S5.6地震序列及震前部分测震学异常分析

简要介绍了2008年8月30日新疆和静MS5.6地震的基本参数、震源机制解、地震序列特征和局部构造应力场等,分析了地震前震源区周围及相关构造区域出现的中、短期地震活动异常特征。结果显示,该序列为主-余型,余震活动呈间歇式,衰减迅速,震源断错性质为走滑型。震前震源区东侧存在长时间4级地震平静、3级地震围空及多台地震波振幅比的异常等现象,同时在地震发生前1~3个月出现了短期异常,表现为振幅比异常的回返、空区瓦解和地震窗的异常。依据多种异常变化,在震前对该地震做出了三要素准确的短期预报。     

高邮-宝应4.9级地震地磁谐波振幅比异常特征初步分析

针对高邮-宝应4.9级地震发生前后附近地区未发生其它中等以上地震、地震事件孤立及周边地磁台站分布较密有利于研究地震地磁异常时空特征的特点,较为系统地分析总结了该地震发生前后地磁谐波振幅比的变化特征,研究结果进一步验证了目前对地磁谐波振幅比异常特征的认识,即地磁谐波振幅比异常特征表现出与地电阻率类似的下降-转折-恢复上升的异常变化过程,地震一般发生在异常转折或恢复上升过程中,距震中较近的台站会出现不同步现象——南北向与东西向的不同步以及长短周期的不同步。     

SANDRA法对北京小时强降水扰动环流场的分型研究

利用cost733class软件中的SANDRA(Simulated ANnealing and Diversified RAndomization)客观分型方法对北京地区2007～2014年暖季5～9月的小时强降水日的500 hPa扰动位势高度场进行分型研究。结果显示,所划分的4类环流形势分别在蒙古、东北—华北地区、河套地区和俄罗斯远东地区存在扰动低压区。根据4类环流形势的质心,将2007～2014年暖季所有日划归4类,计算每类小时强降水日占各自类型总天数的百分比得出蒙古扰动低压类的小时强降水日出现概率最大。统计小时强降水日的探空廓线得出,925 hPa和850 hPa的比湿中位数分别为13.01 g kg~(-1)和10.64 g kg~(-1),这2个层级上最常出现的风向是180°～225°。     

Aster多光谱遥感异常提取在新疆天湖铁矿中的应用

ASTER遥感数据因波段范围宽、波段多,在蚀变异常提取与矿产勘探中有较好的应用前景.据金属矿床常见蚀变矿物光谱特征与ASTER数据波段设置特点,提出硅酸盐铁、Fe~(2+)、白云石等提取的光谱指数.在此基础上研究该数据大气校正、干扰剔除等数据处理技术方法,提出了异常提取技术流程与步骤,在新疆东天山天湖铁矿区进行了试验研究,将矿物提取结果与地质图对比分析,表明提取结果与数据处理技术流程较可靠.     

STRATIFIED MARINE LAKES OF PALAU (WESTERN CAROLINE ISLANDS)

The physical geography of the limestone islands of Palau permits permanent water-column stratification in 13 tropical sea-level marine lakes, each with unique water-column physics, chemistry, and biology. Embayments and lagoons amid the coral became isolated as marine lakes after Miocene uplifting. Surface mixing of lake water by wind is reduced by jungle-covered karst ridges. Surface tidal exchange through fissures in fenestrated karst is slow while midwater exchange through submarine tunnels is fast, but both produce damped, delayed tides with modest seawater exchange from the barrier-reef lagoon. Topographic protection from wind, heavy regular rain throughout the year, with precipitation exceeding evaporation, and modest tidal exchange produce stratified water columns with brackish waters above permanently anoxic saline hypolimnia. Permanent lake stratification is documented for 18 years; sediment cores (by others) show stratification for >100 years, and recent constant sea level implies ecosystem stability for thousands of years. Therefore, the marine lakes in Palau are small, closed, simple ecosystems that do not change over time–steady-state chemostats permitting replicate field measurements of biological and physical attributes from day to day, month to month, or decade to decade. [Key words: Palau, meromictic, marine lake, karst, lake stratification, tides, model ecosystem.]     

空间U统计量法在遥感蚀变信息提取中的应用研究

鉴于传统蚀变异常信息提取方法的局限性,试图在二维光谱特征空间(即散点图)中研究遥感蚀变信息的提取方法.在二维散点图中,两个波段灰度值的联合分布体现了各向异性的特点,聚类常呈类似椭圆形分布.对散点图中点的频数使用空间U统计量法逐个获得地物聚类的椭圆参数,将每个椭圆内的点映射到遥感图像上,经过目视解译,最终获得蚀变异常信息...     

Improving the assessment of ICESat water altimetry accuracy accounting for autocorrelation

Given that water resources are scarce and are strained by competing demands, it has become crucial to develop and improve techniques to observe the temporal and spatial variations in the inland water volume. Due to the lack of data and the heterogeneity of water level stations, remote sensing, and especially altimetry from space, appear as complementary techniques for water level monitoring. In addition to spatial resolution and sampling rates in space or time, one of the most relevant criteria for satellite altimetry on inland water is the accuracy of the elevation data. Here, the accuracy of ICESat LIDAR altimetry product is assessed over the Great Lakes in North America. The accuracy assessment method used in this paper emphasizes on autocorrelation in high temporal frequency ICESat measurements. It also considers uncertainties resulting from both in situ lake level reference data. A probabilistic upscaling process was developed. This process is based on several successive ICESat shots averaged in a spatial transect accounting for autocorrelation between successive shots. The method also applies pre-processing of the ICESat data with saturation correction of ICESat waveforms, spatial filtering to avoid measurement disturbance from the land–water transition effects on waveform saturation and data selection to avoid trends in water elevations across space. Initially this paper analyzes 237 collected ICESat transects, consistent with the available hydrometric ground stations for four of the Great Lakes. By adapting a geostatistical framework, a high frequency autocorrelation between successive shot elevation values was observed and then modeled for 45% of the 237 transects. The modeled autocorrelation was therefore used to estimate water elevations at the transect scale and the resulting uncertainty for the 117 transects without trend. This uncertainty was 8 times greater than the usual computed uncertainty, when no temporal correlation is taken into account. This temporal correlation, corresponding to approximately 11 consecutive ICESat shots, could be linked to low transmitted ICESat GLAS energy and to poor weather conditions. Assuming Gaussian uncertainties for both reference data and ICESat data upscaled at the transect scale, we derived GLAS deviations statistics by averaging the results at station and lake scales. An overall bias of −4.6 cm (underestimation) and an overall standard deviation of 11.6 cm were computed for all lakes. Results demonstrated the relevance of taking autocorrelation into account in satellite data uncertainty assesment.