基于沟床宽度与颗粒粒径的泥石流精细化预报模型

泥石流形成区沟床宽度和颗粒粒径对沟床起动型泥石流的发生影响很大,在强烈地震影响区内显得尤为突出,但目前的泥石流预报中还没考虑到这两个因素,无法准确预测强震区泥石流的发生.在泥石流10 min和1 h精细化预报模型基础上,通过现场调查群发泥石流事件,结合汶川地震强烈影响区泥石流的演化特点,引入了泥石流形成区沟道宽度和颗粒粒径的影响,建立了改进的精细化泥石流10 min和1 h预报模型,并在贵州望谟打易和四川德昌群发泥石流、汶川地震强烈影响区的文家沟多次泥石流事件中获得了很好的验证结果,得出泥石流形成区的颗粒粒径代表泥石流的地质因子,泥石流形成区沟床宽度代表泥石流的地形因子之一,这2个因子在泥石流发生中的作用都非常重要;改进的精细化10 min和1 h预报模型以及临界值,可以用于强烈地震区和一般的泥石流预报.      

沟床起动型泥石流预报研究

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。     

甘肃省白龙江流域降雨型潜在泥石流危险性预报模型

【研究目的】泥石流灾害是白龙江流域分布广泛并常引起群死群伤的重大地质灾害,准确评价泥石流活动规模及其危险度,是泥石流危险性预警预报的前提,合理构建危险性预报模型是泥石流防灾减灾的关键。【研究方法】本文以研究区历史泥石流案例和对应降雨资料为基础数据,采用统计分析方法,通过分析形成泥石流关键地质环境条件及其相互关系,构建了白龙江流域潜在泥石流危险度定量评价模型,提出了两类泥石流危险级别临界判别模式。【研究结果】结果表明：（1）以泥石流活动规模、沟床平均比降、流域切割密度、不稳定沟床比例为判断因子的泥石流危险度动态定量计算模型,能快速准确预测未来不同工程情景和降雨频率工况下泥石流危险度;（2）影响降雨型泥石流发生的地形条件由流域面积、10°~40°斜坡坡度面积比、沟床平均纵比降等组成,降雨条件主要由泥石流爆发前的24 h累积降雨量、触发泥石流1 h降雨量或10 min降雨量等组成;（3）依据30条典型泥石流沟危险度计算结果,获得泥石流危险性临界判别值,提出了降雨型潜在泥石流危险性1 h预报模型（Ⅰ类）和10 min预报模型（Ⅱ类）,其中Ⅰ类模型高危险度以上泥石流预测精度大于87.5%,Ⅱ类模型中等危险度以上泥石流预测精度大于80%,而两类预报模型验证准确率为83.3%。【结论】研究成果为泥石流精准预警预报提供了技术支撑,对建立中小尺度泥石流实时化预警系统具有一定参考意义。创新点：通过确定与泥石流相对应关键地质环境因子,构建了泥石流危险度动态定量评价模型,依据泥石流危险性1 h和10 min临界判别模式可准确实现潜在泥石流预警预报。     

基于数值模拟的群发性泥石流危险性评价

岷县是甘肃南部泥石流频发地区。岷县泥石流多分布于洮河干支流两岸,为群发性泥石流。为了研究群发性泥石流的运动及堆积特征,选取了甘肃岷县麻路河流域为研究区域,以流域内2012年“5·10”暴发泥石流造成重大损失的6条泥石流沟作为整体研究对象,并考虑主河对泥石流堆积物的冲刷携带,运用FLO-2D模拟降雨前主河流动情况及不同降雨频率条件下主河及泥石流的流动情况。根据野外调查结果对比2%降雨频率条件下泥石流模拟结果,验证模型的可靠性。基于模拟结果用ArcGIS进行危险性评价,识别流域内高危险泥石流沟并划定高危险居民区,统计受冲击范围,为泥石流防治和预警工作提供科学依据。     

汶川震区龙门山镇高架子沟“8·18”泥石流灾害机理与特征

2012年8月18日四川省彭州市龙门山镇地区遭受50年一遇的暴雨,引发大规模群发性泥石流灾害,其中以高架子沟最为突出,导致银厂沟内居民生活和交通严重受损。本文据现场调查和航空影像解译,分析高架子沟流域、物源特征的基础上讨论该次泥石流的演化过程、启动方式及灾害机理。结果表明：高架子沟在震前是一条非泥石流沟,震后流域内物源丰富,泥石流形成及演化过程为：地震-滑坡、崩塌-降雨-泥石流,其成灾启动过程包括启动阶段、加速阶段、下切拉槽阶段、堆积四个阶段,启动模式为沟床启动型。该泥石流形成过程中,＂消防水管效应＂使沟道水流快速集中,并强烈冲刷沟床中的松散堆积体,导致沟床固体物质移动形成大规模的泥石流灾害。     

汶川震区文家沟泥石流治理工程效果分析

汶川地震使文家沟内产生大型滑坡并解体成碎屑流堆积在沟道内,成为一条高频泥石流沟,在后期降雨作用下发生了多次泥石流灾害。根据文家沟泥石流的特点,采取了"水沙分离、固护拦停、监测维护"的治理措施进行综合治理,使泥石流起动方式由碎屑堆积体冲刷侵蚀转变为支沟沟床起动。治理后文家沟4个雨季内共发生了3次泥石流,治理工程有效减小了泥石流的规模和危害,但引水截流的实施也伴随了上游清淤等长期性的问题,需进一步重视。通过获得的降雨参数建立了文家沟泥石流临界雨量阈值模型,实施治理工程后泥石流临界雨量有明显提高,并逐年缓慢增长。     

安宁河流域典型沟谷泥石流危险性评价

冕宁县安宁河流域为地质灾害密集分布区,安宁河断裂穿越于此,构造复杂,冷渍沟在上游左岸发育。在强降雨条件下,该沟就会暴发泥石流,堵塞安宁河流域和掩埋杀叶马村房屋和道路。冷渍沟泥石流具有流域面积小,主沟长度短,沟床纵比降大等特征,为了研究安宁河流域内泥石流的危险性,以冷渍沟为例,分析不同降雨周期下的泥石流暴发强度,模拟泥石流的运动过程并进行危险性评价。模拟的最大流速、最大堆积深度和降雨强度三者结合建立冷渍沟泥石流危险性评价模型。研究结果表明,冷渍沟泥石流危险范围内高危险区域占27%,主要集中在松散固体物质较多的沟道,中危险性区域和低危险区域各占56%和17%,该结论为危险范围内的居民和重点设施的风险管控提供参考。     

基于灰色关联法的地震灾区泥石流危险性评价以北川县泥石流为例

汶川地震后,地震灾区泥石流具有暴发临界雨量小,规模大,危险性高的特点。在考虑降雨和地震作用下,采用灰色关联法分析北川县72条泥石流沟的泥石流规模、流域面积、主沟长度、流域相对高差、流域切割密度、不稳定沟床比、年均降雨量和地震烈度8个影响因子的权重,在此基础上建立震区泥石流危险性评价模型并进一步对其进行危险性评价。结果表明:影响因子中,年均降雨量和地震烈度所占权重最大; 运用本文模型得到的评价结果与刘希林模型基本一致,但危险度值相对提高,其中有7条泥石流沟危险度提高一个等级。     

地形因素对白龙江流域甘肃段泥石流灾害的影响及权重分析

白龙江流域甘肃段是我国四大泥石流灾害多发地区之一,其中地形条件是形成泥石流的关键因素。文章在实地调查研究区内发育的1 008条泥石流沟的基础上,通过统计分析沟床比降、沟坡坡度、流域面积和相对高差4个主要地形因素数据与泥石流灾害的类型及易发程度的关系,研究其对泥石流灾害形成的影响。通过熵权法计算4个因素的权重,由权重大小排序分析了它们对泥石流灾害形成的贡献程度。结果表明:在200‰~400‰区间内的沟床比降、坡度大于30°的沟坡、相对高差大于300 m的山体、小于10 km2的流域面积对泥石流的形成和运动最为有利;对泥石流灾害形成贡献程度最大的为沟床比降,其次为相对高差和流域面积,最小的为沟坡坡度。该研究结果对此区域内泥石流灾害的监测预警及防治有一定指导意义。     

人工降雨条件下冲沟型泥石流起动试验研究

下垫面以位于贡嘎山东坡的熊家沟为模型,开展了不同降雨强度条件下冲沟型泥石流起动的模拟试验,初步研究了冲沟型泥石流的形成机理和演化特征.试验研究表明:(1)在强降雨条件下,水体入渗速度、不同深度土体含水量变化与降雨强度呈反比例关系,降雨强度越大,越不利于水体入渗,而有利于坡面汇流、冲沟径流和下切侵蚀; (2)在强降雨和径流条件下,土体破坏方式、破坏程度以及泥石流形成机理表现出差异性.相对较小雨强降雨条件下,土体破坏方式以滑坡为主,泥石流形成模式表现为滑坡液化与转化起动,雨强较大降雨条件下,土体破坏方式以侵蚀垮塌为主,泥石流形成模式为洪流席卷垮塌体和沟床揭底; (3)起动试验中泥石流阵性特征明显.在强降雨条件下,雨强与泥石流的规模、黏度之间没有正相关性,雨强越大,泥石流黏度越小,试验中多出现的是高含砂洪流,而相对较小雨强作用下由土体液化转化形成的泥石流黏度较大.试验现象和结果与熊家沟泥石流起动、发生过程具有较高的一致性.     

A formation model for debris flows in the Chenyulan River Watershed, Taiwan

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.     

Research on prediction of debris flows triggered in channels

The accurate prediction of debris flows occurrence that will allow the reduction or prevention of economic losses and human casualties is presently the most difficult aspect of debris flows studies but also the aspect that receives most attention. Most prediction methods are based on rainfall as the basic parameter, with the moment of occurrence as only result, and without a prediction of debris flow travel time and size. This paper takes Jiangjia Gully in Dongchuan of Yunnan Province as an example, and considers, on the basis of the fulfillment of the essential condition: the abundant availability of loose materials, the conditions for the formation of debris flows. Based on the mechanism of the initiation of debris flows in channels and the volume of rainfall in the basin, this paper also gives a systematic analysis on the travel time and size of the debris flow and suggests that the hydrological condition for forming debris flow is the unit discharge of the flood ≥0.35 m³/s.m. It uses the 10-min rainfall intensity to calculate both the run-off of the rainfall and the unit discharge caused by the run-off, thus predicting the occurrence of debris flows. The velocity and the travel time of a debris flow can also be determined using the unit discharge of the run-off. The total volume of debris flows can be calculated using the 10-min intensity of rainfall and the total volume of the run-off, together with the volume concentration of the sediment in a debris flow.     

水力类泥石流起动机理与预报研究进展与方向

水力类泥石流是泥石流的一大类型,一旦暴发可造成巨大的人员伤亡和财产损失,因而其起动机理和预报是泥石流学科的前沿课题。尽管国内外研究在该领域取得了显著进展,但是由于该类泥石流起动机理的复杂性,已有的预报模型和其实用性仍然有相当的差距。概述了水力类泥石流起动与预报的国内外研究进展,提出未来该研究方向的主要研究内容。未来研究内容应该包括从环境地质学、地貌学和水文学角度认识水力类泥石流的起动成因和过程及相应的临界条件;研究以水文学为主线的水力类泥石流的起动机理和模型,并提出水力类泥石流的起动水文参数临界条件;建立以临界流量法和分布式水文模型为理论依据的水力类泥石流的预报途径和方法。该研究对加强水力类泥石流起动机理及预测预报的创新性研究和促进学科发展具有重要的科学价值和实践意义。     

Rainfall-triggering response patterns of post-seismic debris flows in the Wenchuan earthquake area

Several giant debris flows occurred in southwestern China after the Wenchuan earthquake, causing serious casualties and economic losses. Debris flows were frequently triggered after the earthquake. A relatively accurate prediction of these post-seismic debris flows can help to reduce the consequent damages. Existing debris flow prediction is almost based on the study of the relationship between post-earthquake debris flows and rainfall. The relationship between the occurrence of post-seismic debris flows and characteristic rainfall patterns was studied in this paper. Fourteen rainfall events related to debris flows that occurred in four watersheds in the Wenchuan earthquake area were collected. By analyzing the rainfall data, characteristics of rainfall events that triggered debris flows after the earthquake were obtained. Both the critical maximum rainfall intensity and average rainfall intensity increased with the time. To describe the critical conditions for debris flow initiation, intensity–duration curves were constructed, which shows how the threshold for triggering debris flows increased each year. The time that the critical rainfall intensities of debris flow occurrences return to the value prior to the earthquake could not be estimated due to the absent rainfall data before the earthquake. Rainfall-triggering response patterns could be distinguished for rainfall-induced debris flows. The critical rainfall patterns related to debris flows could be divided on the basis of antecedent rainfall duration and intensity into three categories: (1) a rapid triggering response pattern, (2) an intermediate triggering response pattern, and (3) a slow triggering response pattern. The triggering response patterns are closely related to the initiation mechanisms of post-earthquake debris flows. The main difference in initiation mechanisms and difference in triggering patterns by rainfall is regulated by the infiltration process and determined by a number of parameters, such as hydro-mechanical soil characteristics, the thickness of the soil, and the slope gradient. In case of a rapid triggering response rainfall pattern, the hydraulic conductivity and initial moisture content are the main impact factors. Runoff erosion and rapid loading of solid material is the dominant process. In case of a rainfall pattern with a slow triggering response, the thickness and strength of the soil, high hydraulic conductivity, and rainfall intensity are the impact factors. Probably slope failure is the most dominant process initiating debris flows. In case of an intermediate triggering response pattern, both debris flow initiation mechanisms (runoff erosion and slope failure) can play a role.     

暴雨型泥石流预警模型初步研究

2010年8月13日四川都江堰市龙池地区暴发了特大规模的群发性暴雨型泥石流过程,给龙池地区的震后恢复重建带来了巨大的灾难,因此,研究该区泥石流发生机理和预警十分必要。本文在总结前人关于泥石流暴发与降雨条件研究成果基础上,发现泥石流物源含水量及地表径流流深等是导致流域内松散物源启动的主要原因。根据其前期降雨量和有效降雨强度等特征,建立了泥石流流域物源土体颗粒个别启动、局部启动和大量启动的判别式,建立了适合该区域暴雨泥石流预警模型,将可能诱发泥石流暴发的不同降雨条件划分为蓝、黄和红色3个危险等级,为该区泥石流监测预警提供了科学依据。     

A prediction model for debris flows triggered by a runoff-induced mechanism

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.     

泥石流平均流速预测模型及敏感因子研究

为了探求泥石流平均流速敏感因子及影响因素耦合关系,本文采用BP神经网络和支持向量机模型对蒋家沟泥石流数据进行预测,对两种泥石流平均流速预测模型的学习与泛化能力进行比较,并对平均流速各影响因素的敏感程度进行分析,建立了泥石流平均流速敏感因子预测模型。结果表明:支持向量机的泛化能力优于BP网络,更适合样本数量较少的泥石流动态预测。沟道比降和不稳定层厚度是泥石流平均流速的主要影响因子,各因子之间存在复杂的耦合关系。基于不稳定层厚度和泥面比降的泥石流平均流速预测模型精度较高,能够定量描述泥石流动态与影响因子间的响应关系。研究成果可为泥石流防治提供依据。     

中国泥石流起动物理模拟试验研究进展

为进一步提高泥石流起动物理模拟试验的科学性,完善试验体系,采用资料收集与分析方法,总结了近年来中国泥石流起动物理模拟试验开展的现状,从水流冲刷与泥石流起动试验以及人工降雨与泥石流起动试验两个方面论述了中国泥石流起动试验取得的主要进展和理论成果。在国内外泥石流起动物理模拟试验对照基础上,提出中国泥石流起动物理模拟试验研究的建议:提高水流浓度、降雨雨型与土体特征的相似率;加强降雨或水流作用下土体物理力学特征变化与泥石流起动响应研究;推动降雨与汇流共同作用下泥石流起动综合性物理模拟试验的开展。