基于GIS的淄博市地质灾害预警预报系统建设

淄博市地质灾害预警预报系统基于MapGIS K9平台进行二次开发,以数据库和地理底图为基础,集成数据、图像于一体搭建起一个高度信息化、专业化、智能化的地质灾害预警预报及管理平台。此系统的建设能够显著提高淄博市地质灾害气象预警预报的精细化水平,熟练掌握和运用该系统是进行预警分析、提前预报和及时防范地质灾害发生的有效手段。     

黄河上游洪灾及流域面雨量预报

通过统计分析黄河上游流域特征、洪灾特征和强降水特征及成因等 ,首先建立了强降水预报智能模型。并在此预报结论的基础上 ,利用三角形面积计算法和流域分区原理在MICAPS系统上进行二次开发 ,完成了黄河上游流域及各区段面雨量预报业务系统的建立 ,使用效果良好。     

湖北武汉典型地区岩溶发育特征分析

本文在分析以往地质资料和完成的武汉市1∶5万岩溶塌陷调查成果的基础上,从武汉市岩溶发育的形态及规模、不同岩溶条带、不同构造条件、不同地层、不同埋深和不同地貌七个方面,分别系统总结了武汉市典型地区岩溶发育的特征。区内岩溶总体中等发育,岩溶形态主要为溶隙、溶孔以及小规模溶洞;在水平方向上存在5个走向NWW—SEE、各自相对独立的碳酸盐岩条带,其中白沙洲条带岩溶最为发育,在垂直方向上浅层溶蚀发育;各地层的岩溶发育强度依次为P2q>T1d>C2h+d>T1-2j;在褶皱核部或转折端、断层带附近、长江一级阶地、山前补给局部地区等地下水交替循环强烈地带和可溶岩与非可溶岩接触带,岩溶发育相对强烈。结论可为武汉市岩溶塌陷地质灾害防治提供地质基础支撑。     

Geochemical modeling,fate distribution,and risk exposure of potentially toxic metals in the surface sediment of the Shyok suture zone,northern Pakistan

The objective of the current study was to assess the contamination of potentially toxic metals (PTMs) in weathered surface sediment, along stream tributaries, and surrounding area of the river Chitral, Shyok suture zone district Chitral, Pakistan. To understand the geochemical features of 113 sediment, samples were collected from the Mirkhani and Drosh area. Then, different statistical tools including the geo-accumulation index (Igeo), cluster analysis (CA), principal component analysis (PCA), and ecological risk assessment (ERA) were used to unravel the origin, intensity, and exposure level of PTMs to control risk and restore the ecosystem within the study area. The results for the PTMs namely nickle (Ni), chromium (Cr), copper (Cu), cadmium (Cd), lead (Pb), zinc (Zn), and cobalt (Co) in Mirkhani and Drosh were in the following ranges: 10–150, 15–210, 15–250, 0.08–1.00, 10–70, 76–240 and 14–51; and 13–240, 17–210, 15–150, 0.08–0.60, 7–140, 47–150 and 13–36 mg/kg, respectively. In consequence, the potential ecological risk caused by Pb, Ni, Cu, Co, Cr, and Zn is reflected by the percentages of samples with an ecological risk index (ERI) greater than one which were 100%, 91%, 100%, 100%, 92%, and 100%, respectively. However, the overall mean decreasing order of ecological risk of PTMs in the district Chitral was Pb > Ni > Cu > Co > Cr > Zn > Cd. Moreover, the PCA yielded 78% variability which indicated that mineral prospects play an important role in the contamination of sediment. Furthermore, the mineral phases of Pb and Zn suggested supersaturation, while that for Cd revealed unsaturation. The results of Igeo, ERI, and CA indicated contamination of PTMs in the study area. The ERI value of Pb, Ni, Cu, Co, Cr, and Zn was higher than 1 suggesting an ecological risk in the study area. Moreover, the current study showed the dominance of geogenic contamination with major contributions from ultramafic rock and known mineral prospects. Therefore, contaminated sediment of the Shyok suture zone is extremely detrimental to the aquatic ecosystem of the study area.     

龙门山断裂带南段应力状态与强震危险性研究

龙门山断裂带可分为南段、中段和北段,2008年汶川M8.0级地震发生在该断裂带中-北段. 龙门山断裂带南段是否存在发生强震的危险性倍受关注. 利用1977—2012年四川区域地震台网资料,获得了龙门山断裂带南段的地震活动性参数b值图像以及汶川地震前、后b值的差值Δb图像. 同时,根据宽频带数字地震波形资料,计算了2007年以来南段及附近区域ML≥3.8级地震的视应力. 结果表明,2008年汶川地震后,龙门山断裂带南段天全—芦山、泸定和宝兴北部等区域应力增强,而靠近汶川余震区南端的大邑地区应力水平降低. 天全至宝兴段应力水平相对较高,具有发生中-强地震的条件. 鲜水河断裂带康定以南段应力水平低,短期内发生强震的可能性较小.     

地震重灾区诱发次生地质灾害风险评价研究

为了揭示地震重灾区与次生地质灾害的关联性,以某地震灾区为例,在分析次生地质灾害类型与危害的基础上,通过计算一次泥石流总量及流量确定其危险度,并引入易损性指数,确定各评价单元次生山地灾害的易损性大小,设置评价指标;结合研究区实际,采用层次分析法构建次生地质灾害风险评价模型,对地震重灾区诱发次生地质灾害风险进行评价。实验以次生地质灾害中的泥石流产生的灾害风险为例进行研究,结果表明,采用本文研究方法可在有效确定地震重灾区诱发次生地质灾害的位置方面具有一定优势,但在纵向地震造成次生地质灾害风险评价方面需进一步进行研究。     

天文光干涉与综合孔径技术的发展

本文简单介绍了光干涉与综合孔径技术发展的历史、国际上用于天文观测的一些著名光干涉仪的技术特点和进展、以及近年来我国开展的与光干涉 ,综合孔径技术有关的工作 ,最后简要介绍了在光学综合孔径技术领域所发展的光纤与集成光学等新技术     

我国地震海浪初步分析

总结了我国地震海浪的25次记录,在做初步分析后认为我国的地震海浪多由近海海洋地震引起,其多发地区为渤海沿岸与东南沿海一带.随着对沿海地区开发的深入,这类记载逐渐增多,受灾程度加大.另外分析了在社会历史变迁中,国家对海洋的开发政策、沿海开发下城市近海地理位置、沿海港口及海洋贸易的规模与地震海浪受灾程度之间的关系.     

A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.