A large-scale obliquely inclined bedding rockslide, activated by a heavy rainstorm, occurred on July 8, 2020, at 7:05 (UTC?+?8) in Shiban Village, Songtao Miao Autonomous County, Guizhou Province, China. The loss of life in this event was greatly reduced owing to the local warning system for rainstorm-induced geohazards. To understand the failure characteristics, triggering factors, the genetic mechanism of the landslide, the geomorphological features, geological characteristics, hydrological conditions, and rainfall characteristics were systematically studied by a synthetic approach including field investigations, satellite imagery, unmanned aerial vehicle (UAV) photography, laboratory tests, and rainfall data statistics. The results indicated that the interface between the soft and hard rock, the well-developed joints, and the free face in front of the slope constituted the boundaries of this landslide. The concave topography at the back and southern edge of the landslide, the bare ground, and the cataclastic structure of the rock mass provided favorable conditions for the collection or infiltration of rainwater. The concentrated rainstorm was the direct trigger for the landslide, which led to a rapid inflow and retention of rainfall in the landslide through favorable landform and geological conditions. The groundwater recharge that cannot be drained in time caused the mechanical deterioration of rock mass and induced a rapid increase in pore water pressure in the landslide. Moreover, the water level of the Ganlong River at the toe of the slope also rose rapidly, and the uplift pressure in front of the slope increased accordingly. Under the combined action of these adverse factors, the overall anti-sliding force of the slope was less than the sliding force, finally resulting in the landslide. Remarkably, the local warning system for rainstorm-induced geohazards successfully forecasted the landslide, but the shortcoming is that the forecast time in advance is short. Nevertheless, the prediction has significantly reduced human casualties and provided valuable experience for the prediction of this type of landslide.
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作为我国地质调查领域最重要的数据源之一,地质调查报告中蕴含着丰富的地学知识及地质体描述等关键信息,准确高质量地抽取地质命名实体为地学知识图谱构建、知识推理及知识演化提供基础。笔者等在阐述地质命名实体识别任务基础上,分析地质实体不仅包含大量专业术语,还存在实体嵌套、大量长实体等领域特性,进一步增加了地质命名实体识别难度。笔者等提出一种基于轻量级预训练模型(ALBERT)—双向长短时记忆网络(BiLSTM)—条件随机场(CRF)模型的地质命名实体识别方法。首先利用ALBERT对输入字符上下文特征进行建模,并采用BiLSTM对其进行进一步上下文特征表征,最后采用CRF实现标注序列预测。实验结果表明,在构建的地质命名实体识别数据集上,相比于主流的命名实体识别模型算法,本文所提出的方法具有更好的抽取性能,提出的命名实体识别模型能为领域实体识别提供借鉴,同时为地学领域实体关系抽取和地学知识图谱构建提供有力方法支撑。 相似文献
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Freshwater mussels are a major component of the zoobenthos and they therefore play an important role in freshwater ecosystems. The community composition and the standing crop of freshwater mussels in Poyang Lake, the largest freshwater lake in China and one of two lakes connected to the Changjiang (Yangtze) River, were investigated from February 2008 to May 2009. Mussels were sampled in hydrologically and geographically distinct sampling areas. A total of 42 species and 13 genera were identified, of which 32 species were endemic to China. Two species, Unio douglasiae and Lamprotula caveata, dominated all sampling areas. The number of genera and species, and the number of species within each genus, differed significantly among sampling areas. Freshwater mussels were very abundant, with an overall density of 0.28 ± 0.22 ind./m2 and biomass of 4.08 ± 3.96 g/m2. Significant variation observed among sampling areas and among genera was probably due to the variety of habitats among the areas sampled and to the adaptability of different freshwater mussels to environments. This study suggests that Poyang Lake and other freshwater lakes in the region are important sites of freshwater mussel biodiversity and conservation. 相似文献
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为满足政府、企业和公众等用户对GIS实时性应用的迫切需求。在分析传统WebGIS采用请求/响应工作模式不足的基础上,利用服务器推送Comet技术,基于Pushlet开源框架和MapGIS IGServer,设计了一种实时WebGIS框架,利用Pushlet订阅/发布机制,实现基于标准的HTTP协议的地理空间信息服务器端实时推送;利用数据库触发器实现更新数据的即时分发;利用富客户端Flex技术进行客户端信息展示。在气象监测预警系统中对该框架的可行性进行验证,为实时WebGIS的开发应用提供新的方法和思路。 相似文献
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Yu Haibing Li Changdong Zhou Jia-Qing Gu Xiaoping Duan Ying Liao Liufeng Chen Wenqiang Zhu Yinbin Long Jingjing 《Landslides》2022,19(5):1119-1130
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选取大气可降水量的地基GPS水汽遥感法,探空反演法以及经验公式计算法,以贵州西部的威宁作为研究个例,对比分析3种方法在乌蒙山区对大气可降水量反演的异同。以探空反演结果作为基准值,得出地基GPS遥感水汽值和经验公式计算值较基准值偏大,3个方法的反演值之间具有很好的相关性,地基GPS遥感水汽值与探空反演值之间的相关性最好,平均绝对误差值最小,为3.5 mm,均方根误差为4.14 mm。在乌蒙山区,对流层加权平均温度(Tm)的本地经验公式与探空计算值之间的平均误差为1.1 K,本地Tm公式对大气可降水量反演的结果影响较小。有降水事件发生及昆明准静止锋常驻的11月至次年4月,GPS水汽反演精度较高,平均绝对误差仅为1 mm。5—10月,经验计算方法的计算精度较高,平均绝对误差为0.74 mm。 相似文献
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