遥感技术在地质灾害调查及灾害规律研究中的应用——以辽宁省建昌县为例

地质灾害与地质环境条件、人类工程活动关系密切,严重威胁着人类生命财产安全,制约社会经济的可持续发展。运用遥感技术对辽宁省建昌县进行地质灾害调查,利用ENVI5.3软件对高分二号数据进行预处理,建立遥感解译标志并开展了野外验证,最终解译滑坡、崩塌、泥石流、地面塌陷等地质灾害点75个;同时,利用Arcgis10.4空间分析功能,对遥感解译地质灾害点与地貌、坡度、坡向、构造、水系及人类工程活动等因子进行叠加分析,基本查清了研究区地质灾害规模、空间分布特征和发育规律,为研究总结区域上地质灾规律及有效预防提供了详实可靠的基础资料。     

用T/P测高数据反演海域重力异常

以反解 Stokes公式为数学模型 ,应用由 T/ P测高数据计算的大地水准面高反演了海域平均重力异常 ,并与船测平均重力异常和 OSU91A位模型计算的平均重力异常进行了比对分析 ,得出了一些有益的结论。     

空间直角坐标和大地坐标的转换

目前国内在空间直角坐标和大地坐标转换公式使用问题上 ,还明显缺乏必要的统一性。针对这个问题 ,本文作者在全面分析和比较国内外现有各种转换方法的基础上 ,重点推荐和介绍根据 Bowring研究思路导出的转换公式 ,这组公式既简单又具有很高的计算精度 ,能够满足各个部门的使用要求     

凡口铅锌矿床海底热泉喷溢成矿的地质地球化学特征

凡口铅锌矿是发育于海相碳酸盐岩建造中的海底热泉喷溢沉积矿床。在研究矿床地质特征和地球化学特征的基础上,总结了发育于同沉积断裂两侧的矿体的形态、产状,矿石组构,成矿元素、微量元素、稀土元素的组成与分布,成矿温度和流体的性质,提出了热泉成矿作用与海相碳酸盐沉积作用同时演化的结论。     

凡口铅锌矿床海底热泉喷溢成矿的物理化学环境

凡口铅锌矿是发育于碳酸盐岩建造中的海底喷溢沉积矿床 ,以“一大二富三集中”的特点和典型的地质地球化学特征吸引着中外矿床地质工作者。叠层状矿体发育于同沉积断裂的旁侧 ,矿层与灰岩呈沉积接触关系。矿石具沉积碎屑组构 ,黄铁矿、闪锌矿具外生特征。稀土元素组成和硫同位素组成反映矿床与同生作用有关。铅同位素组成具有壳源和下地壳来源铅的特征。矿区主要矿层经历海底热泉喷溢沉积—成岩的演化     

Synchronous structure control of superlarge ore deposits

The control of synchronous structures on formation of superlarge stratabound ore deposits is immense. Based on studies of ore deposits in South Qiniing, northern Guangdong, Langshan and other areas, three new ideas in comparison with examples of ore control of synchronous structures both in China and abroad are proposed: (i) multiorder ore control of synchronous structures, which means that synchronous structures of different orders display different controls on ore deposits; (ii) synchronous structures in different stages of basin evolution display different controls on basin fluid system and ore-forming system; (iii) synchronous strurture accompanying hydrothermal mineralization as a preexisting weak surface in earth crust often reactivate in later tcctono-thermal event to be a channelway for magma or thermal fluids which superimposed on and reformed preexisting ore beds to form large or superlarge composite ore deposits.     

矩形钢筋混凝土水处理池震害预测方法及抗震对策

提出了矩形钢筋混凝土水处理池的一种震害预测方法,并对海口市米铺水厂中的水处理池进行了计算分析,论述了水处理池的对抗对策。     

对流层高层偏北气流在梅雨暴雨中的作用

文中对江淮梅雨暴雨过程中的高低空流场特征及物理过程进行分析．结果表明：对流层上部青藏高原东侧常有高空偏北大风轴汇入南亚东风急流中．在这支强北风轴北端发现高空辐散和辐散的增长．亦即有利于低层辐合上升的持续、发展和加强;表明了低层西南急流与高空青藏高压东侧的偏北强风轴之间的次级环流圈,有利于梅雨暴雨的持续．     

An assessment of the predictability of the East Asian Subtropical Westerly Jet based on TIGGE data

The predictability of the position, spatial coverage and intensity of the East Asian subtropical westerly jet(EASWJ) in the summers of 2010 to 2012 was examined for ensemble prediction systems(EPSs) from four representative TIGGE centers,including the ECMWF, the NCEP, the CMA, and the JMA. Results showed that each EPS predicted all EASWJ properties well, while the levels of skill of all EPSs declined as the lead time extended. Overall, improvements from the control to the ensemble mean forecasts for predicting the EASWJ were apparent. For the deterministic forecasts of all EPSs, the prediction of the average axis was better than the prediction of the spatial coverage and intensity of the EASWJ. ECMWF performed best, with a lead of approximately 0.5–1 day in predictability over the second-best EPS for all EASWJ properties throughout the forecast range. For probabilistic forecasts, differences in skills among the different EPSs were more evident in the earlier part of the forecast for the EASWJ axis and spatial coverage, while they departed obviously throughout the forecast range for the intensity. ECMWF led JMA by about 0.5–1 day for the EASWJ axis, and by about 1–2 days for the spatial coverage and intensity at almost all lead times. The largest lead of ECMWF over the relatively worse EPSs, such as NCEP and CMA, was approximately 3–4 days for all EASWJ properties. In summary, ECMWF showed the highest level of skill for predicting the EASWJ, followed by JMA.     

低温雨雪过程的粒子群-神经网络预报模型

利用逐日气温和降水量数据、NCEP/NCAR再分析资料以及预报场资料,通过分析提取我国南方区域持续性低温雨雪过程及其预报因子,使用粒子群-神经网络方法建立非线性的统计集合预报模型 (PSONN-EPM),对我国南方区域持续性低温雨雪过程进行预报试验。结果表明:以过程的冷湿程度及影响范围为标准,将低温雨雪过程分为一般过程和严重过程,并建立不同的预报模型效果较好。通过10 d独立样本预报试验看,基于粒子群-神经网络方法建立的集合预报模型比基于逐步回归方法建立的预报模型的预报平均相对误差小,对严重过程预报能力高于对一般过程预报,且这种非线性统计集合建模方法在建模过程中不需要调整神经网络参数,在实际预报业务中值得尝试。