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1.
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   

2.
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   

3.
影响云南省滑坡泥石流活动的几个自然因素   总被引：15，自引：0，他引：15  
根据1989～2002年云南省滑坡、泥石流调查资料，在单因素分析的基础上，确定地形、岩土体类型、降雨、地震、活动断裂、气候带和植被覆盖率共7个因素是云南省影响滑坡泥石流的主要自然因素。通过R-型因子分析、逐步回归分析和灰色关联度分析，得出对滑坡影响程度由大到小的因子排序是：海拔和高差、地形坡度、地震、活动断裂、岩组、降雨量；对泥石流影响程度由大到小的因子排序是：活动断裂、海拔和高差、岩组、降雨量、地震。  相似文献   

4.
汶川震区北川9.24暴雨泥石流特征研究   总被引：32，自引：1，他引：31  
2008年9月24日汶川震区的北川县暴雨导致区域性泥石流发生,这次9.24暴雨泥石流灾害导致了42人死亡,对公路和其他基础设施造成严重损毁。本研究采用地面调查和遥感解译方法分析地震与暴雨共同作用下的泥石流特征,获取的气象数据用于分析泥石流起动的临界雨量条件。本文探讨了研究区泥石流起动和输移过程,并根据野外调查,分析了泥石流形成的降雨、岩石和断层作用,特别是强降雨过程与物源区对泥石流发生的作用。根据应急调查发现北川县境内暴雨诱发的泥石流72处,其分布受岩石类型、发震断层和河流等因素控制。根据对研究区震前和震后泥石流发生的临界雨量和雨强的初步分析,汶川地震后,该区域泥石流起动的前期累积雨量降低了14.8%～22.1%,小时雨强降低25.4 %～31.6%。震区泥石流起动方式主要有二种,一是由于暴雨过程形成的斜坡表层径流导致悬挂于斜坡上的滑坡体表面和前缘松散物质向下输移,进入沟道后转为泥石流过程;二是消防水管效应使沟道水流快速集中,并强烈冲刷沟床中松散固体物质,导致沟床物质起动并形成泥石流过程。调查和分析发现沟内堆积的滑坡坝对泥石流的阻塞明显,溃决后可导致瞬时洪峰流量特别大。研究结果表明了汶川震区已进入一个新的活跃期。因此,应该开展对汶川地震区的泥石流风险评估和监测、早期预警,采取有效的工程措施控制泥石流的发生和危害。  相似文献   

5.
Many debris flows were triggered within and also outside the Dayi area of the Guizhou Province, China, during a rainstorm in 2011. High-intensity short-duration rainfall was the main triggering factor for these gully-type debris flows which are probably triggered by a runoff-induced mechanism. A revised prediction model was introduced for this kind of gully-type debris flows with factors related to topography, geology, and hydrology (rainfall) and applied to the Wangmo River catchment. Regarding the geological factor, the “soft lithology” and “loose sediments” in the channel were added to the list of the average firmness coefficient for the lithology. Also, the chemical weathering was taken into account for the revised geological factor. Concerning the hydrological factor, a coefficient of variation of rainfall was introduced for the normalization of the rainfall factor. The prediction model for debris flows proposed in this paper delivered three classes of the probability of debris flow occurrence. The model was successfully validated in debris flow gullies with the same initiation mechanism in other areas of southwest China. The generic character of the model is explained by the fact that its factors are partly based on the initiation mechanisms and not only on the statistical analyses of a unique variety of local factors. The research provides a new way to predict the occurrence of debris flows initiated by a runoff-induced mechanism.  相似文献   

6.
贵州省望谟县2011年6月6日暴发了特大山洪泥石流,其中暴雨中心所在的打易镇多处暴发泥石流。短历时强降雨激发了沟床起动类型的泥石流。本文通过对贵州望谟河流域群发泥石流的调查,得出该流域的66条沟中,22条沟无沟床起动类型泥石流暴发,25条沟暴发沟床起动类型泥石流,还有19条沟无法确定是否有沟床起动类型泥石流暴发。在前期工作基础上,提出了地质条件和降水条件因子的改进方法;并在前期工作的3大条件（地形条件、地质条件和降水条件）之间的关系基础上,由贵州望谟群发泥石流数据得出改进沟床起动类型泥石流的临界值,提出了泥石流的预报模型。本文模型在我国西南地区的泥石流验证中非常成功,为泥石流的预报提供了一个新方法。预报模型中的地形因子和地质因子还可以判断泥石流流域的暴发频率,为正确地判断泥石流流域的特征打下了基础。预报模型也可以估算泥石流的暴发规模,为定量地预测泥石流危害范围提供了依据。  相似文献   

7.
泥石流危险度的划分是泥石流研究中的重点与难点,泥石流危险度的确定对于泥石流整体特征的把握具有十分重要的作用。采用熵值-理想点法建立了泥石流危险度划分模型,选取流域面积、主沟长度与泥石流沟相对最大高差等10个评价指标。利用现场3条泥石流沟作为工程评价对象,通过熵值法确定各评价指标的权重系数,并采用理想点法进行泥石流危险度的划分研究。根据模型分析结果,泥石流沟2与3属于高危险度(贴近度为0.79与0.83),泥石流沟1属于中危险度(贴近度为0.82)。泥石流危险度与现场情况及已有研究资料基本一致,证明了该法在泥石流危险度划分中的合理性与有效性。  相似文献   

8.
Rapid debris flows, a mixture of unconsolidated sediments and water travelling at speeds > 10 m/s are the most destructive water related mass movements that affect hill and mountain regions. The predisposing factors setting the stage for the event are the availability of materials, type of materials, stream power, slope gradient, aspect and curvature, lithology, land use and land cover, lineament density, and drainage. Rainfall is the most common triggering factor that causes debris flow in the Palar subwatershed and seismicity is not considered as it is a stable continental region and moderate seismic zone. Also, there are no records of major seismic activities in the past. In this study, one of the less explored heuristic methods known as the analytical network process (ANP) is used to map the spatial propensity of debris flow. This method is based on top-down decision model and is a multi-criteria, decision-making tool that translates subjective assessment of relative importance to weights or scores and is implemented in the Palar subwatershed which is part of the Western Ghats in southern India. The results suggest that the factors influencing debris flow susceptibility in this region are the availability of material on the slope, peak flow, gradient of the slope, land use and land cover, and proximity to streams. Among all, peak discharge is identified as the chief factor causing debris flow. The use of micro-scale watersheds demonstrated in this study to develop the susceptibility map can be very effective for local level planning and land management.  相似文献   

9.
The Parlung Zangbo Basin in the southeastern Tibet Plateau is affected by the summer monsoon from the Indian Ocean, which produces large rainfall gradients in the basin. Rainfall data during 2012–2015 from five new meteorological stations are used to analyse the rainfall characteristics. The daily rainfall, rainfall duration, mean rainfall intensity, and peak rainfall intensity are consistent, but sometimes contrasting. For example, these values decrease with increasing altitude, and the gradient is large downstream and small upstream, respectively. Moreover, the rainfall intensity peaks between 01:00 and 06:00 and increases during the afternoon. Based on the analysis of 14 debris flow cases in the basin, differences in the rainfall threshold differ depending on the location as sediment varieties. The sediment in the middle portions of the basin is wet and well structured; thus, long-duration, high-intensity rainfall is required to generate debris flows. Ravels in the upstream area are arid and not well structured, and short-duration rainfall is required to trigger debris flows. Between the above two locations, either long-duration, low-intensity rainfall or short-duration, high-intensity rainfall could provoke debris flows. Clearly, differences in rainfall characteristics and rainfall thresholds that are associated with the location must be considered in debris flow monitoring and warnings.  相似文献   

10.
松散物质是流域侵蚀演化的产物,对于泥石流流域而言,物质供给能力影响着泥石流的易发程度和活动频率。以岷江上游都江堰—汶川部分区域147个泥石流小流域为例,运用面积?高程法和面积?坡度积分对流域地貌演化阶段和侵蚀强度定量划分,并结合地貌演化阶段和侵蚀强度开展泥石流物质供给能力研究。研究结果表明:采用单一的地貌演化阶段或侵蚀强度解释泥石流的易发程度具有一定局限性,泥石流暴发主要集中于壮年期、壮年偏幼年期及侵蚀强度Ⅲ～Ⅴ级;随着物质供给能力的提升,泥石流的暴发率上升,而面积对泥石流的暴发有一定限制作用,初步确定研究区内供给能力处中、强、极强三种水平泥石流流域,其优势发育面积范围分别为:20～35 km2、10～50 km2、10～40 km2;对于物质供给能力水平较高、面积处于优势发育范围内、且长期未有明显泥石流活动迹象的流域,应进一步排查流域松散物质储量和分布特征,确定泥石流活动稳定性,采取合理的防灾减灾措施。  相似文献   

11.
2012年8月18日汶川震区的银厂沟区域暴发群发性泥石流,造成人员伤亡,公路、房屋等基础设施严重受损。这场泥石流灾害发生在汶川地震极震区内,是地震与强降雨共同作用下的结果,因此研究其成灾机制和灾害特征对于进一步认识强震区泥石流活动具有重要意义。本研究采用地面调查和遥感解译方法,分析银厂沟区域泥石流形成条件的变化。研究结果表明强震条件下崩塌、滑坡等产生的松散固体物质,是泥石流活动的物质基础; 沟道受松散岩土体堵塞,有利于泥石流规模放大; 快速激发型的雨量特征为泥石流暴发提供了动力。在此基础上讨论了泥石流起动、运动和堆积过程,总结了泥石流活动特征,发现泥石流沿发震断裂呈带状分布,成因组合上属于降雨控制型,尚处于青年期,且在成灾模式上满足致承耦合效应。  相似文献   

12.
周伟  邓玖林 《水科学进展》2019,30(3):392-400
对台风暴雨泥石流发生的可能性进行定量预测,有助于减少危险区内的人员伤亡、降低经济损失。以台湾地区南投县陈有兰溪流域的47条泥石流沟为研究对象,从泥石流形成所需的地形地貌、物源和降雨条件中,初步选取台风暴雨泥石流发生的影响因子,包括沟床平均坡度、有效流域面积、形状系数、主沟长度、岩性、崩滑比和平均雨强。根据因子重要性排序结果,选择崩滑比和平均雨强作为模型的预测因子,基于Fisher判别法建立了台风暴雨泥石流预测模型。采用随机取样技术,选取70%的数据用于构建模型,剩余30%的数据用于验证模型。以精确度、准确率、漏报率和误报率指标,定量评价模型的预测效果,并确定最优的预测模型。结果表明:基于Fisher判别法构建的台风暴雨泥石流预测模型,综合考虑了泥石流形成所需的物源条件和降雨条件,弥补了降雨阈值模型仅依靠降雨资料分析的不足,预测效果更好。  相似文献   

13.
甘肃陇南武都区泥石流易发性评价   总被引：4，自引：0，他引：4  
文章分析了甘肃陇南市武都区泥石流形成的自然环境背景、发育特征及易发性。通过野外实地考察,查明了泥石流的发育情况,在此基础上,采用模糊物元可拓方法对泥石流的易发性进行了评价。分析表明,研究区的泥石流具有分布密度高、冲沟及坡面泥石流成片发育、北岸泥石流较南岸发育且粘性泥石流所占比例大于南岸的发育特征;选取岩性、沟床比降、山坡坡度、完整系数、发育程度、降水、断层密度7个因子构建泥石流易发性评价指标体系。通过易发性评价,研究区104条泥石流沟中,66条为高易发性,占总数的63.5%;32条为中等易发性,占总数的30.8%;6条为低易发性,占总数的5.7%。  相似文献   

14.
泥石流是我国山区常见的地质灾害,为了定量研究泥石流灾害致灾因子的敏感性并确定各个致灾因子的权重大小,本文通过野外调查、数理统计法和层次分析法对龙溪河流域泥石流灾害的主要致灾因子进行定性规律分析和定量权重计算。结果表明:（1）泥石流灾害的发生与致灾因子的敏感性区间主要定性表现为:流域面积小于1 km2以内、高差在200~400 m范围内、距断层距离为0~2 km、山坡坡度30°~50°、岩性为砂岩、纵比降在400‰~600‰等,其泥石流发生与致灾因子具有相关性,且相关性较好;（2）选取了泥石流灾害致灾因子中的历史因子、地形因子、地质因子和降雨因子等4个一级因子以及流域面积、高程、相对高差、纵坡比、地层岩性等14个二级因子建立层次分析模型和计算判断矩阵,定量计算权重值得出降雨,流域面积,地层岩性,纵比降等四个因子对泥石流发生的敏感性最强。这一结论具有普遍性,可对该区域泥石流的易发性,危险性,风险性评价提供一定的数据参考意义。  相似文献   

15.
In the framework of the landslide susceptibility assessment, the maps produced should include not only the landslide initiation areas, but also those areas potentially affected by the traveling mobilized material. To achieve this purpose, the susceptibility analysis must be separated in two distinct components: (1) The first one, which is also the most discussed in the literature, deals with the susceptibility to failure, and (2) the second component refers to the run-out modeling using the initiation areas as an input. Therefore, in this research we present a debris flow susceptibility assessment in a recently burned area in a mountain zone in central Portugal. The modeling of debris flow initiation areas is performed using two statistical methods: a bivariate (information value) and a multivariate (logistic regression). The independent validation of the results generated areas under the receiver operating characteristic curves between 0.91 and 0.98. The slope angle, plan curvature, soil thickness and lithology proved to be the most relevant predisposing factors for the debris flow initiation in recently burned areas. The run-out is simulated by applying two different methods: the empirical model Flow Path Assessment of Gravitational Hazards at a Regional Scale (Flow-R) and the hydrological algorithm D-infinity downslope influence (DI). The run-out modeling of the 36 initiation areas included in the debris flow inventory delivered a true positive rate of 83.5% for Flow-R and 80.5% for DI, reflecting a good performance of both models. Finally, the susceptibility map for the entire basin including both the initiation and the run-out areas in a scenario of a recent wildfire was produced by combining the four models mentioned above.  相似文献   

16.
In the mountain area of Southwestern China, there are large quantities of runoff-generated debris flows that are threatening the local people and facilities seriously. Gangou is a typical runoff-generated debris flow; its source is old deposit from floods and the debris flows downstream of the channel. On June 30, 2005, Gangou occurred debris flow, the debris flow destroying the road, the communications facilities and the farmland at the gully mouth. Unlike the formation mechanisms of other debris flows, the formation of 2005 debris flow in Gangou has its distinctive characteristics as follows. (1) The supply of the loose sources is intensive and distribute near the mouth of the gully; it is rare to see any debris flow initiate at such a lower location. (2) The debris flow finishes its initiation, flow and deposition around the 700-m-long channel, accompanied with the blocking process in the gully when the debris flow ran out; however, 10 min later, it releases and amplifies the peak flow about three times. (3) The topographic condition of the basin does not contribute much to the formation of the 2005 debris flow; instead, its formation is the result of the co-effort of continuous rainfall and a short-time heavy rainfall. In other words, the previous cumulative precipitation enables the moisture content of the soil on the right bank of the gully to reach saturation; then the soil slides into the channel under the action of the heavy rainfall at a later time. Meanwhile, the heavy rainfall accelerates the formation of gully run-off and initiates the loose mass in the channel from slide, thus forming the debris flow.  相似文献   

17.
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   

18.
The Longxi river basin with the city of Dujiangyan, in the Sichuan province of South West China, belongs to the seismic area of the May 12, 2008 Wenchuan earthquake. Lots of loose co-seismic materials were present on the slopes, which in later years served as source material for rainfall-induced debris flows. A total of 12 debris flows, were triggered by heavy rainfall on August 13, 2010 in the study area. The FLO-2D numerical analysis software was adopted to simulate debris flows intensity, including movement velocities and maximum flow depths. A comparison of the measured fan spreading with the simulation results, the evaluation parameter Ω was used to verify accuracy of simulation, the results show Ω values ranging between 1.37 and 1.65 indicating relative good simulation results. This study also estimated the flood hydrograph for various recurrence intervals (20, 100, and 200 years, respectively) to perform scenario simulations of debris flows, and followed Swiss and Austrian standards to establish a debris flow hazard classification model on the basis of a combination of the debris flow intensity and the recurrence period. This study distinguishes three hazard classes: low, medium, and high. This proposed approach generated a debris flow hazard distribution map that could be used for disaster prevention in the Wenchuan earthquake-stricken area, South West China.  相似文献   

19.
The goals of this work are to show the range of debris-flow volumes and watershed characteristics for several locations, and the differences in flow volumes for events triggered soon after wildfire. A dataset of 929 events was divided into groups based on location and burn status. The three unburned locations show significant differences: debris flows from the Italian Alps are larger and generate more debris per unit basin area or unit channel length than flows in the Western USA or in the Pacific Northwest. However, some of the observed differences may be attributed to the skew of the Italian Alps dataset towards larger events, and the small size and limited range of the Pacific Northwest data. For burned watersheds in the Western U.S. events, there is a clear progression in decreasing volume in debris flows as basins recover from the wildfire: it takes approximately 1 year, or at a few locations, as much as 3 years, for debris production to return to pre-fire rates. The difference is most apparent when the data are normalized for basin area (the area yield, which is 2× larger for burned basins) or for channel length (the length yield, which is 1.6× larger for burned basins). When normalized simultaneously for basin area, channel length, and channel gradient, burned areas produce significantly more debris (2.7–5.4 times as much). Burned areas in the Western USA are more sensitive to wildfire and produce larger debris flows than burned areas in more humid climates such as the Pacific Northwest.  相似文献   

20.
Susceptibility is an important issue in debris flow analysis. In this paper, 26 large-scale debris flow catchments located in the Wudongde Dam site were investigated. Seven major factors, namely, loose material volume per square kilometer, loose material supply length ratio, average gradient of the main channel, average hill slope, drainage density, curvature of the main channel, and poor vegetation area ratio, were selected for debris flow susceptibility analysis. Geographic information system, global positioning system, and remote sensing, collectively known as 3S technologies, were used to determine major factors. Weights of major factors affecting debris flow susceptibility were determined. This paper applied the combination weighting method, which considers both the preference of the engineers for major factors and the objective major factor information by using analytic hierarchy process and entropy method. Combination weights of major factors for the investigated 26 debris flow catchments are 0.20, 0.12, 0.20, 0.10, 0.08, 0.19, and 0.11, respectively. Combination weights follow the order of loose material volume per square kilometer = average gradient of the main channel > curvature of the main channel > loose material supply length ratio > poor vegetation area ratio > average hill slope > drainage density. This paper applied extension theory, which is used to solve incompatibility and contradiction problems, to determine susceptibility. Susceptibility results show that the susceptibility of 4 debris flow catchments are very low, 13 are low, 8 are moderate, and 1 is high. Assessment results exhibit consistency with the activity analysis.  相似文献   

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