与T63数值预报产品相结合的江苏西南大风的预报方法

国家气象中心发送的T63数值预告产品在本台于95年6月份投入业务运行,为尽好、尽快地最大限度地将T63数值产品投入业务使用,以发挥其作用,从而具体体现T63的价值所在、在这方面,我们作了一些探讨与尝试。我们把《江苏大面积西南大风预报工具》与T63数值预告产品进行结合与释用,取得了良好的效果。     

T639数据格式及其读取方法

本文对2008年12月19日-21日朔州市强寒潮天气过程的高、低空环流形势、单站气象要素变化进行了分析,结果表明：500 hPa横槽转竖、中西伯利亚地面冷高压维持加强后南压爆发、850 hPa冷平流是产生强降温的主要原因.     

拱坝系统三维非线性地震波动分析

本文将显式有限元结合外推人工边界的方法发展应用于三维非线性近场波动问题的研究。首次提出了拱坝－库水－地基系统三维非线性地震反应波动分析方法，并与传统的无质量地基分析方法进行了比较。     

灰色预测模型GM(1.1)在水文预测中的应用——以玛纳斯河为例

由于灰色预测模型理论较时间序列预测具有很大的优势,所以在许多领域得到广泛的应用.为将该方法应用于水文与水资源预测,本文以玛纳斯河流量预测为例,应用GM(1.1)灰色预测模型对水文水资源要素进行预测,并分析该预测模型在水文水资源中的应用.经分析认为,GM(1.1)灰色预测模型对水文水资源要素预测具有重要的意义.     

海岸沙席形态及近表层沉积物粒度对台风的响应

依据2014年第10号强台风“麦德姆”登陆前后福建平潭岛典型海岸沙席的形态观测与近表层沉积物粒度数据,综合分析了海岸沙席对台风的响应特征。结果表明：① 海岸沙席形态对“麦德姆”的响应明显,主要表现为沙席前缘高程降低（最大侵蚀深度为0.40 m）,中部变化较小（-0.06~0.09 m）,后缘明显升高（最大堆积厚度为1.62 m）,沙席体积增大2.02%。② 海岸沙席近表层沉积物粒度受“麦德姆”影响较小,其粒度参数在台风前后并无质的等级性变化。③ 海岸沙席的台风响应特征主要因台风过程中大风的非选择性侵蚀和搬运及海岸沙席与海滩沙粒度的相近性所造成的,同时也受到周边地势及植被等的影响。     

基于GP RMax的隧道衬砌检测数值模拟及应用

利用基于时间域有限差分法( FDTD)的GPRMax,针对常用的400、900、1500 MHz三种不同中心频率的天线,数值模拟了隧道衬砌不同钢筋网密度、不同钢筋直径及其下方的钢拱架、空气界面等目标体的探地雷达反射及干扰信号图像特征;在混凝土试件上开展实验研究,并运用克希霍夫积分偏移处理了数值模拟和实验数据,压制了钢筋的绕射波和多次波,提高了钢筋网下方弱反射信号的成像效果;通过对比分析数值模拟、实验测量和工程实测结果,为探地雷达在隧道衬砌检测中取得更好的探测效果提供了借鉴。     

The use of digital technologies for landslide disaster risk research and disaster risk management: progress and prospects

Landslide is a serious natural disaster next only to earthquake and flood, which will cause a great threat to people’s lives and property safety. The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective , difficult to quantify, and no pertinence. As a new research method for landslide susceptibility assessment, machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models. Taking Western Henan for example, the study selected 16 landslide influencing factors such as topography, geological environment, hydrological conditions, and human activities, and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination (RFE) method. Five machine learning methods [Support Vector Machines (SVM), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Linear Discriminant Analysis (LDA)] were used to construct the spatial distribution model of landslide susceptibility. The models were evaluated by the receiver operating characteristic curve and statistical index. After analysis and comparison, the XGBoost model (AUC 0.8759) performed the best and was suitable for dealing with regression problems. The model had a high adaptability to landslide data. According to the landslide susceptibility map of the five models, the overall distribution can be observed. The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest, the Xiaoshan Mountain range in the west, and the Yellow River Basin in the north. These areas have large terrain fluctuations, complicated geological structural environments and frequent human engineering activities. The extremely high and highly prone areas were 12043.3 km² and 3087.45 km², accounting for 47.61% and 12.20% of the total area of the study area, respectively. Our study reflects the distribution of landslide susceptibility in western Henan Province, which provides a scientific basis for regional disaster warning, prediction, and resource protection. The study has important practical significance for subsequent landslide disaster management.     

西藏狮泉河地区高钾-钾玄质火山岩的岩石学、地球化学及锆石U-Pb年龄

报道的高钾-钾玄质火山岩位于狮泉河镇南东方向约20km处,向东延伸。高钾-钾玄质火山岩SiO2变化于60.35%~68.68%之间,属中酸性岩范畴;具有高的K2O+Na2O含量（8.8%~10.66%）,K2O/Na2O值在1.92~2.49之间,MgO含量较低,介于0.88%~3.47%之间,Al2O3含量为14.02%~14.91%,属于高钾-钾玄质系列。岩石强烈富集大离子亲石元素（LILE）Rb、Ba、Th、U和轻稀土元素（LREE）,高场强元素（HFSE）Nb、Ta、Ti具有明显负异常,Cr、Ni、Co相容元素含量低于或接近地壳的平均含量,结合Th/Yb-Ta/Yb、（Th×100）/Zr-（Nb×100）/Zr判别图及La-La/Yb图解,暗示岩浆源区可能为下地壳。在左左乡南东约2km处和狮泉河水泥厂北东约1km处各采集1个高钾-钾玄质火山岩样品,对其中的锆石进行LA-ICP-MS U-Pb同位素测定,得到的206Pb/238U年龄加权平均值分别为22.04±0.42Ma和22.29±0.31Ma,此年龄被解释为狮泉河一带高钾-钾玄质火山岩的喷发时代,即中新世阿启塔期。由此表明,该火山岩是印度板片向北俯冲时在狮泉河一带俯冲板片断离,岩浆发生部分熔融的产物。     

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