共查询到19条相似文献，搜索用时 343 毫秒
1.
泥石流的发生受各种因素共同影响,确定泥石流临界雨量是突发地质灾害预警预报工作的一项重要内容,探索新方法用于泥石流临界雨量计算也是目前突发地质灾害预警预报工作的需求。本文分析了门头沟区泥石流灾害分布特征和影响因素,在前期研究基础上,以灾害频率与降雨频率分析方法计算了不同时间段泥石流临界雨量阈值,结果显示:门头沟区特殊的地质条件构成了泥石流形成的物源与地形基础,降雨是泥石流的激发因素,根据泥石流发生时的历史雨量监测数据,计算得出的临界雨量值均小于历史雨量监测数据。本研究推荐的门头沟区泥石流不同时间段临界雨量阈值可用于北京市泥石流灾害预警预报工作,研究结果可为北京市泥石流灾害预警预报工作提供科技支撑。 相似文献
2.
北京山区泥石流预警阈值初步研究 总被引：1，自引：0，他引：1
泥石流预警阈值,是突发地质灾害防灾减灾的重要参考指标。本文结合北京山区泥石流灾害特点和已有降雨阈值研究成果,一方面在泥石流沟易发性、物源和危害人数进行分级的基础上,提出不同级别沟谷在不同前期降雨条件下,不同发灾概率的激发雨量,极大地方便了中短期预警实际工作;另一方面将泥石流流域降雨量、土壤含水率、次声、泥位4个参数,作为泥石流短临灾害预警关键物理参数,开展了泥石流专业监测设备预警阈值研究。最终,从技术层面上构建不同时间维度的泥石流监测预警阈值体系,为北京山区泥石流监测预警提供技术支持。 相似文献
3.
北京山区泥石流灾害临界雨量研究 总被引：1，自引：0，他引：1
白利平 《地质灾害与环境保护》2006,17(4):101-104
目前北京山区泥石流灾害的临界雨量研究方法主要是基于统计资料的临界雨量阈值判别法,该方法没有包含泥石流形成地区的地质背景条件与形成机理的信息,因此在推广上存在难度。本文从松散物质失稳引发泥石流的机理出发,推导了松散物质失稳时的雨量计算公式,该公式可用于计算不同流域内泥石流沟道的松散物质起动的临界雨量。将该公式与常规的临界雨量阈值判别公式相结合,能够提高北京地区泥石流灾害预报预警的准确度。 相似文献
4.
基于可拓理论的泥石流灾害预警预报系统开发:以北京市为例 总被引：2，自引：0，他引：2
泥石流是北京山区主要的地质灾害,北京市于2003年启动了地质灾害气象预警预报工作,但近几年的预报效果并不理想。为进一步提高泥石流灾害预警预报的准确性,选取地形、地层岩性、地质构造和植被作为基础因子,以北京市地质灾害易发分区为响应因子,以降雨作为诱发因子,根据各因子与泥石流灾害的相关性分析,采用层次分析法(AHP)计算各因子的权重系数,提出了基于可拓理论的泥石流预警预报模型,并通过G IS系统和IDL开发平台实现准确预报。利用20组历史上北京地区发生的泥石流雨量资料对建立的预警预报模型进行验证,结果表明模型预报结果与实际情况基本吻合。研究成果对于提高北京市泥石流灾害预警预报水平,减少人民生命和财产损失具有重要的意义。 相似文献
5.
基于功效系数法的泥石流灾害预警研究 总被引：5，自引：0，他引：5
泥石流灾害破坏力巨大,预测预报泥石流发生的可能性是防灾减灾的重要手段,也是国内外学者研究的热点。基于功效系数法原理,在综合分析泥石流灾害发生的气象、地质环境影响因素的基础上,选取了山坡坡度、相对高差、植被覆盖率、沿沟松散物储量、5 d累计降雨量、最大小时雨强和当日雨量为评价因子,采用改进后的层次分析法计算评价因子的权重系数,建立了泥石流预测预警模型。以岫岩地区泥石流为例对预警模型进行检验,预测结果较好地反映了实际情况。表明基于功效系数法的泥石流预测预警模型具备较高的可靠性和实用性,研究结果为泥石流预测预警提供了一种新的思路和方法。 相似文献
6.
缺资料地区泥石流预警雨量阈值研究 总被引：4，自引：0，他引：4
合理的雨量阈值指标是保障泥石流预警报准确性的关键,对于研究泥石流形成机制、分析预测未来活动特点以及指导防治工程设计等方面均具有重要意义。由于国内山区大多数泥石流沟均无降雨和灾害资料,目前国内外通行的实证法和频率计算法不能满足其泥石流预警报的需要。通过分析泥石流预警区的降雨条件、水文特征及下垫面条件,提出了基于水力类泥石流起动机制来计算泥石流预警雨量阈值的方法。主要根据流域地形及松散固体物质等特征,计算该流域泥石流起动的临界水深,并结合流域产汇流机制、特征降雨量随海拔变化规律、暴雨雨型特征,进而计算该流域泥石流预警雨量阈值。研究成果在四川省凉山州宁南县城后山史家沟流域进行了应用和验证,结果表明该方法具有合理性和可行性。该方法解决了缺资料地区泥石流预警报的难题,为山区泥石流预警报提供了一种新的思路。 相似文献
7.
搜集了汶川震区暴雨泥石流发生的降雨数据,采用詹氏法和修正法两种雨场分割法对其进行处理,研究了降雨参数（降雨强度、累积雨量和降雨历时）与泥石流发生之间的关系,建立了汶川震区暴雨泥石流发生的降雨阈值模型。结果表明:采用詹氏法和修正法这两种雨场分割方法所获得的降雨参数之间存在差异。两者的累积雨量差异不大,但后者的平均雨强要小于前者,其原因在于修正法改善了詹氏法估计降雨时间过短的缺点,延长了降雨历时。通过分析平均雨强~历时、累积雨量~历时、标准化平均雨强~历时和标准化累积雨量~历时之间的关系,采用单线法建立了汶川震区暴雨泥石流发生的降雨阈值。研究成果在四川省绵竹市清平乡的泥石流灾害事件中进行了应用与验证,结果表明该方法具有合理性和可行性。 相似文献
8.
选取湖北省恩施地区1 000 km2区域作为典型研究区, 在全面分析该区域历史滑坡资料的基础上, 根据该区滑坡生成与地层岩性之间的关系, 将研究区地层划分为高、中、低3类易发性岩组.分岩组统计降雨监测数据与历史滑坡信息, 得出有效降雨强度与关键降雨持续时间的散点图, 由此确定不同滑坡发生概率的有效降雨强度阈值, 提出该区的滑坡灾害危险性预警判别模型.基于样本区统计数据建立滑坡预测指标体系, 运用GIS得出研究区域的滑坡空间易发性区划结果, 并根据不同易发岩组-有效降雨强度模型, 叠加滑坡灾害易发性分区结果与降雨危险性预警等级分级结果, 对研究区的滑坡灾害危险性进行了预测预警.结果表明: 不同易发岩组-有效降雨强度模型所得预警结果与实际情况吻合, 预警模型具有考虑全面和预警精度高的特点, 在实际预警中切实可用. 相似文献
9.
滑坡所处不同易发等级的区域,降雨预警阈值差别较大。为提高滑坡降雨预警的针对性和准确率,文章以野外地质调查和滑坡易发条件分析为基础,结合信息量模型和层次分析法开展滑坡易发性评价,再通过滑坡发生概率与前期累计降雨量的相关性分析,分区进行滑坡降雨预警阈值模型研究。结果表明：坡度、高程、距断层距离、工程地质岩组、水系是龙陵县滑坡的主要孕灾地质条件;龙陵县滑坡非易发区面积为14.33 km2,低易发区面积为1 053.87 km2,中易发区面积为1 471.65 km2,高易发区面积为254.73 km2;确定单日和前3日为降雨预警时间,分区分时细化了降雨预警阈值模型;对比降雨预警阈值模型应用于龙陵县滑坡监测预警中的前后,预警信息减少了70条,预警准确率提高了14.4%,并实现了镇安镇户帕村施家寨组滑坡的有效预警。文章为区域滑坡降雨预警阈值确定提供了一种较好的参考方法。 相似文献
10.
针对雨型随机性所导致山洪灾害预警预报空报、漏报率过高问题,为提升山洪灾害预警精度,依据概率分布传递扩散原理,以雨型特征参数为控制条件,提出了基于参数控制的随机雨型生成法,建立了基于随机雨型的山洪灾害临界雨量计算模型及考虑决策者风险偏好的预警模式。以裴河流域为例,对不同雨型集下的临界雨量进行对比分析,并确定研究区6h临界雨量阈值空间。结果表明:雨峰位置、峰值倍比、前期土壤含水量对临界雨量的影响范围分别为32%~34%、33%~34%、15%~22%;雨型较前期影响雨量对临界雨量影响幅度更大;由雨峰位置系数和峰值倍比(r,bmax)双因子雨型集所确定的6h临界雨量阈值空间为98~185mm;考虑决策者不同风险偏好的临界雨量预警模式合理可靠,对更合理地开展山洪灾害预警工作具有指导意义。 相似文献
11.
Qing Wang Yuanyuan Kong Wen Zhang Jianping Chen Peihua Xu Huizhong Li Yiguo Xue Xiaoqing Yuan Jiewei Zhan Yujie Zhu 《Arabian Journal of Geosciences》2016,9(18):718
A method was developed to analyze the susceptibilities of 541 regional basins affected by debris flows at the Wudongde Dam site in southwest China. Determining susceptibility requires information on source material quantity and occurrence frequency. However, the large number of debris flows can hinder the individual field investigation in a each small basin. Factors that may trigger debris flows can be identified using remotely sensed interpretation information. Susceptibility analysis can then be conducted based on these factors. In this study, SPOT5 satellite imagery, digital elevation models (DEM), a lithology distribution map, and rainfall monitoring data were used to identify 12 debris flow trigger factors: basin relief ratio, slope gradient in the initiation zone, drainage density, downslope curvature of the main channel, vegetation coverage, main channel aspect, topographic wetness index, Melton’s ruggedness number, lithology, annual rainfall, form factor, and cross-slope curvature of the transportation zone. Principal component analysis was used to obtain the eight principal components of these factors that contribute to susceptibility results. Then, a self-organizing map method was adopted to analyze the principal components, which resulted in a debris flow susceptibility classification. Field validation of 26 debris flow basins was used to evaluate the errors of the susceptibility classification, as well as assess the causes of such errors. The study found that principle component analysis and self-organizing map methodologies are good predictors of basin susceptibility to debris flows. 相似文献
12.
Debris flows represent dangerous occurrences in many parts of the world. Several disasters are documented due to this type of fast-moving landslides; therefore, natural-hazard assessment of debris flows is crucial for safety of life and property. To this aim, much current work is being directed toward developing geotechnical-hydraulic models for the evaluation of debris flow susceptibility. A common base for such current models is parameterization of background predisposing and triggering factors such as inherent characteristics of geo-materials, topography, landscape and vegetation cover, rainfall regime, human activities, etc. which influence the occurrence of these processes on slopes. The same factors are also taken into account in soil erosion prediction models. Consequently, it seems worth investigating the effectiveness of the soil erosion index as debris flows susceptibility indicator. To this aim, a logistic regression analysis was carried out between the erosion index assessed by means of the Revised Universal Soil Loss Equation (RUSLE) model and the inventory of debris flows that have occurred in an area in Sicily (Southern Italy). Model assumptions were verified and validated by means of a series of statistical tools. Different possible scenarios were also evaluated by considering hypothetical changes in soil erosion rate under different rain erosivity conditions. Notwithstanding the rough approximations in model data collection, the outcomes appear encouraging. 相似文献
13.
An empirical approach for evaluation of the potential of debris flow occurrence in mountainous areas 总被引：3，自引：2，他引：1
Debris flows can occur relatively suddenly and quickly in mountainous areas, resulting in major structural damage and loss of life. The establishment of a model to evaluate the occurrence probability of debris flows in mountainous areas is therefore of great value. The influence factors of debris flows are very complex; they can basically be divided into background factors and triggering factors. Background factors include the mechanical characteristics of geo-materials, topography and landscape, and soil vegetation; and triggering factors include hydrological and rainfall conditions, and human activities. By assessing the dynamic characteristics of debris flows in mountainous areas, some important influence factors are selected here for analysis of their impacts on the occurrence probability of debris flow. A mathematical model for evaluation of the occurrence probability of debris flows is presented and combined with probability analysis. Matlab software is used for the numerical implementation of the forecasting model, and the influences of rainfall, lithology and terrain conditions on the occurrence probability of debris flows are analyzed. Finally, the presented model is applied to forecast the occurrence probability of debris flows in the mountainous area around Qingping Town; the simulation results show that many loose landslide deposits and heavy rainfall are the key factors likely to trigger debris flows in this region. 相似文献
14.
白龙江流域为泥石流等地质灾害密集分布区。2020年8月由于强降雨激发,白龙江流域武都段发生了大规模的群发性泥石流灾害,造成严重损失。文章以白龙江流域甘肃省陇南市武都段（宕昌县两河口乡—武都区桔柑镇）为研究区,通过野外实地考察,选取流域面积、流域形状系数、平均坡度、沟谷密度、物源参照值（HI）、岩性、流域中心距活动断层距离、一小时最大降雨量、植被覆盖度作为泥石流危险性评价因子。基于灾害熵理论,分别以泥石流单沟和小流域单元作为评价单元,利用ArcGIS软件,进行区域泥石流危险性评价。分析结果表明,研究区内泥石流沟大多数都属于中、高危险性。致灾因子中岩性、物源参照值（HI）、距断层距离、植被覆盖度及平均坡度的权重最大,与实际考察结果一致。且以小流域单元作为评价单元的评价结果更符合研究区的泥石流发育情况。 相似文献
15.
分形理论在区域地质灾害预测中的应用 总被引：12，自引：0，他引：12
以青衣江Ⅲ级流域滑坡,泥石流的发育,分布规律为研究对象,引入分形理论,结合映射分析成果,初步提出了滑坡,泥石流评价预测的河谷形态分维模型,为开展区域地质灾害的评价预测提供新的途径和方法。 相似文献
16.
北京市山区泥石流灾害的发育特征及预报方法探讨 总被引：1，自引：0，他引：1
赵忠海 《中国地质灾害与防治学报》2009,20(3):5-10
北京山区泥石流灾害较为发育。泥石流分布地域广泛,但相对集中于部分乡镇、主干断裂构造带附近或几组断裂构造交汇部位、坚硬岩石分布区、末级和二级沟谷以及降雨高值区内,且多发生在7-8月份暴雨季节。受地形地貌、地质条件、降雨分布、土壤类型、气温条件以及植被覆盖程度等影响明显。对于泥石流的预报,目前主要依据的是临界雨量值。本文通过认真研究北京地区泥石流的发育规律,深入分析了泥石流的形成条件和影响因素,并在此基础上对北京地区泥石流预报方法进行了初步探讨。建立了综合考虑地形地貌、地质条件、土壤类型以及降雨情况等因素的判断公式,并就如何开展北京地区泥石流预报工作提出了建议。 相似文献
17.
Many debris flows were triggered in the Chenyulan River Watershed in Taiwan in a rainstorm caused by the Typhoon Toraji. There are 117 gullies with a significant steep topography in the catchment. During this Typhoon, debris flows were initiated in 43 of these gullies, while in 34 gullies, it was not certain whether they have occurred. High-intensity short-duration rainfall was the main triggering factor for these gully type debris flows which are probably entrained by a “fire hose” mechanism. Previous research identified 47 factors related to topography, geology, and hydrology, which may play a role in the formation of gully type debris flows. For a better understanding of the probability of the formation of debris flows, it is proposed to represent the factors related to topography, geology, and hydrology by one single factor. In addition to the existing topographic and geological factor, a normalized critical rainfall factor is suggested with an effective cumulative precipitation and a maximum hourly rainfall intensity. In this paper, a formation model for debris flows is proposed, which combines these topographic, geological, and hydraulic factors. A relationship of these factors with a triggering threshold is proposed. The model produces a good assessment of the probability of occurrence of debris flows in the study area. The model may be used for the prediction of debris flows in other areas because it is mostly based on the initiation mechanisms and not only on the statistical analyses of a unique variety of local factors. The research provides a new and exciting way to study the occurrence of debris flows initiated by a “fire hose” mechanism. 相似文献
18.
北京地区突发性地质灾害危险度评价 总被引：1，自引：0，他引：1
赵忠海 《地质灾害与环境保护》2009,20(3):39-44
北京地区地质构造条件复杂,新构造活动频繁,人为活动剧烈,故地质灾害较为发育。主要的突发性地质灾害有泥石流、采空塌陷、崩塌以及地裂缝等。本文在北京市各区县地质灾害调查与区划工作的基础上,对北京地区的突发性地质灾害的发育情况进行了深入调查和分析。采用袭扰系数法,对突发性地质灾害的易发程度进行了综合评价。采用模糊综合评判模型,对影响地质灾害演变趋势的降雨条件、人类工程活动、地震活动以及区域岩组结构等因素进行了综合评判。并在此基础上．对突发性地质灾害的危险度进行了评价和预测,将北京地区划分出了地质灾害高风险区、地质灾害中风险区及地质灾害低风险区。 相似文献
19.
Chia-Nan Liu Jia-Jyun Dong Yih-Ferng Peng Hsiao-Fung Huang 《Engineering Geology》2009,104(3-4):241-253
Typhoon Herb in 1996 caused widespread debris flows in central Taiwan. The 7.3 Chi-Chi earthquake on September 21, 1999, which also took place in central Taiwan, induced many landslides in the region. These landslides turned into debris flows when Typhoon Toraji struck Taiwan in 2001. This research selects three regions which suffered a ground motion class of 5, 6, and 7 on the Richter scale during the Chi-Chi earthquake as study areas. Air photos from 1997 and 2001 of these regions are used to map the gully-type debris flows that took place after Typhoons Herb and Toraji, respectively. The gullies adjacent to the debris flow, but without a trace of debris flows, are also mapped as the non-debris flow data. The topography, hydrogeology, and rainfall factors – where debris flow occurred and in which there was no occurrence of debris flows in these gullies were retrieved from DTM, geological maps, and iso-countour maps, and of rainfall through GIS processing. These characteristic are introduced into a probabilistic neural network to build a predicting model for the probability of the occurrence of debris flows. Three series of cross analyses are conducted to compare the probability of the occurrence of debris flows of the same dataset predicted by different prediction models. The results reveal that the susceptibility of debris flows was elevated after the Chi-Chi earthquake struck. The upsurge of susceptibility was more obvious for the regions that received a higher class of ground motion. 相似文献