西藏波密米堆沟泥石流堵河模型试验

通过室内模型试验,对西藏波密米堆沟不同类型、不同规模的泥石流与主河不同频率洪水遭遇情况下,泥石流堵塞主河及溃决可能性,泥石流、洪水的危害模式进行了研究。米堆沟泥石流堵河模型试验结果表明。不同类型、规模泥石流进入主河与不同规模洪水遭遇。在交汇口表现出不同的堵溃特征;频率P=5％,重度12．74kN／H13,试验流量4．50l／S的水石流在主河仅暂时阻水。不会对主河产生堵塞和溃决;频率P：2％。重度14．70kN／m^3,模型流量8．01l／S稀性泥石流会部份阻塞主河道,瞬间完全阻塞及溃决现象不会出现;频率P=1％,重度16．66kN／ml,模型流量10．21l／S泥石流,对主河造成较为严重阻塞,但不会造成瞬间完全堵塞和溃决。     

泥石流输沙及其对山区河道的影响

泥石流能在很短时间内将大量大小混杂的固体物质输入主河,影响主河河床演变,形成灾害。在连续观测资料的基础上,对泥石流输沙的强度、级配和时空分布特征进行了分析。通过实际测量,分析了泥石流在沟道内冲淤特征以及影响泥石流冲淤特征的因素,如泥石流活动规模和局部沟道条件等。通过水槽实验,分析了泥石流与主河交汇的机理,将泥石流入汇主河的模式概括为掺混模式、潜入模式、推进模式和堵河模式,并且从能量角度阐释了汇流区的水沙交汇特征,提出了泥石流堵江的判据。最后,分析了泥石流多发区受泥石流入汇影响,主河河床在平面形态、横断面形态、纵断面形态和河型等方面的变化特征。     

南水北调西线一期工程区泥石流规模预测及其对调水工程的影响

泥石流是南水北调西线一期工程区的主要山地灾害之一,可能对调水工程建设与运行期间的工程安全构成一定的威胁和危害。据调查,工程区分布有一定规模的有现代泥石流活动的沟111条、潜在性泥石流沟58条。主要探讨了泥石流发生规模预测中的清水流量、泥石流峰值流量、一次泥石流流出总量等参数的计算方法,在此基础上引入主、支流量比,分析了泥石流堵河问题及其可能堵河高度与回水长度,为评估泥石流对调水工程的影响提供了科学可行的定量分析方法。     

西藏东南部泥石流堵塞坝的形成机理

西藏东南部山高谷深,冰川发育,冰碛等松散堆积物厚度大,经常发生大型或特大型泥石流堵断主河,形成堵塞坝。针对西藏东南部4条典型泥石流沟所发生的7次大型或特大型泥石流中,有5次形成堵塞坝,来剖析泥石流堵塞坝形成的机理和主要因素,提出由于冰雪崩、冰湖溃决或大规模滑坡活动,所激发的首阵或前几阵大流量、高速度、多巨砾,并与主河正交的粘性泥石流,最容易形成堵塞坝。     

雍家沟泥石流活动特征与堵江

自2008年汶川地震以来,四川省绵竹市清平乡雍家沟已暴发过多场泥石流,造成了严重的堵断公路和堵塞河流事件,其中,2012年“8·18”暴发的泥石流规模最大,造成绵远河全部堵塞.通过分析2010年“8·13”与2012年“8· 18”两场泥石流的降雨过程发现,雍家沟暴发泥石流的前期累积雨量在增加,激发雨强在降低.2008年汶川地震导致雍家沟的主沟和支沟内堆积了大量的松散固体物质.野外调查发现,雍家沟多次暴发泥石流的活动路径并不一致,其中,2012年“8· 18”泥石流主要沿1号支沟活动,沟道的侵蚀宽度随着与主沟沟口距离的增加而变窄,沟道内剩余堆积体厚度随着距离的增加呈现先增后减的规律,且沟道内的物质粒径分布具有随机性.对雍家沟在不同暴雨频率下暴发泥石流可能引起的堵江情况进行了分析,结果表明,在暴雨频率大于20％的情况下暴发泥石流便可造成堵江事件,甚至可将主河全部堵塞.     

一场典型的冰雪雨水泥石流过程

1989年7月26日,贡嘎山东坡南关沟发生了一场典型的冰雪雨水泥石流。它下行30多公里后堵塞大渡河,造成直接经济损失245万元。这场泥石流历时约3小时,持续流动时间2小时。到达大渡河时的流速9.4米/秒,最大流量6768.0立方米/秒,总径流量1716.4万立方米,总输沙量627.0万立方米,残留沉积物总方量310.4万立方米(其中泥石流堵塞大渡河的扇形地方量30.0万立方米),弯道爬高15.5—16.5米。输往堵河扇形地下游方的固体物质方量是扇形地方量的19.9倍,泥石流尾流作用强烈。     

泥石流与环境演变

泥石流具有淤埋、冲毁、冲刷、漫流、磨蚀、直进等特性 .其堵河成湖 ,堵河溃冲 ,淤积成扇 ,垫高河床 ,改造地貌 ,改变生态系统等都是逼使环境在新的起点上进行演变 .泥石流作用过程的巨量输沙、快速沉积和堆积地貌 (多为扇形地 )都是可以利用的     

小江流域泥石流堆积扇形成的制约因素及其特征

在系统分析了各种因素对泥石流堆积扇形成影响的基础上,提出流域腹地中流域面积、沟床比降和堆积区主河河谷宽度及主河能量等因素对泥石流堆积扇发育的影响较大。结合TM卫星影象和1:5万地形图,解译了小江流域内泥石流堆积扇的范围。在此基础上,统计了流域腹地内两大重要条件-流域面积和沟床比降与堆积扇面积之间的关系。在小江流域,堆积扇的面积随流域面积的增加而增加,二者之间是正的指数关系;而堆积扇面积与沟床比降之间可用一个负的指数关系式表达。最后,堆积区特征对小江流域泥石流堆积扇的影响主要是其堆积空间限制了大型堆积扇,比如蒋家沟泥石流堆积扇的发展。     

灰色理论在舟曲南屿沟泥石流灾害危险性评价中的应用研究

为分析不同因素对泥石流灾害危险性的影响程度，基于对舟曲南屿沟泥石流灾害影响因素调查结果总结和分析，利用灰色理论分析了泥石流灾害危险性与影响因素间关联程度，并建立了其预判模型。结果表明：沟岸坡度、沟道堵塞程度及冲淤变幅，沟道平均纵坡降和长度，沟道内植被覆盖率、流域面积及人口密度，松散固体物源量和灾害点密度等因素的影响程度较接近；相同区域内不同沟道泥石流灾害危险性程度受沟岸坡度、沟道堵塞程度、冲淤变幅、沟道平均纵坡降及长度等因素影响显著；基于自然和人为因素建立了泥石流灾害易发程度预估模型，其能够为区域内泥流灾害防治工作部署提供依据。     

1985年四川境内的首场灾害泥石流

1985年4月25日和5月4日,理县城东约2公里杂谷脑河支沟日底寨沟先后发生两次粘性泥石流(容重1.80—2.30吨/立方米),泥石流固体物质方量约3万立方米。 泥石流固体物质冲入杂谷脑河后,河道遭阻塞,回水至打色尔沟沟口,构成一临时水库。库长500多米,平均水深约4米,平均水宽50余米,蓄水11万立方米。库水淹没杂谷脑河左岸的成都—阿坝公路300多米,水深0.7—1.4米,沥青路面经浸泡后,车辆难以通行,日最大堵车量在1000辆以上;理县公路养护段大院和当地公路道班被淹;堵河、溃坝与河床淤高,威胁着阻塞坝下游25米的公路桥,以及杂谷脑河右岸的理县党校、车队和印刷厂等单位的安全,灾情较为严重。     

区域和沟谷相结合的泥石流预报及其应用

在分析泥石流预报现状和泥石流减灾决策对泥石流预报的要求的基础上,提出了建立区域和单沟相结合的泥石流预报的问题。以泥石流发育的基础数据库、降水的动态预报与监测和泥石流预报模型为基础,以GIS技术为工具,建立泥石流预报平台。泥石流预报模型采用基于模糊数学的泥石流预报模型,预报结果应用概率分级进行表述,以适应泥石流预报准确率低的不足,并最大程度地克服了过分依赖临界降水量进行泥石流预报的不足。将该泥石流预报方法应用到北京山区泥石流预报中,建立了北京山区泥石流预报系统。     

坡面泥石流发生的坡度阀值研究

对重庆市北碚区的21个坡面泥石流的实地调查表明,坡度对坡面泥石流发生具有重要的控制性作用。在对坡面泥石流流域大量原始坡度进行统计分析后发现,各坡面泥石流的坡度服从正态分布规律。根据这一分布规律,将本区坡面泥石流发生的坡度阀值确定为三类。文章从定量的角度阐述了坡度阀值与坡面泥石流发生的关系,为生态脆弱区的划分、工程建设、防灾减灾和政府决策提供服务。     

泥石流易损度评价

泥石流易损度是指在一定区域和给定时段内 ,由于泥石流灾害而可能导致的该区域内所存在的一切人、财、物的潜在最大损失。易损度评价因子主要分为财产指标和人口指标两大类。财产指标包括建筑资产、交通设施资产、生命线工程资产、个人财产和土地资源 ;人口指标包括人口年龄、受教育程度、富裕状况、人口自然增长率和人口密度。财产指标和人口指标具有不同的计量单位因而不能直接相加。本文提出的“转换赋值函数”解决了人、财、物统一标度和综合表达的难题 ,使泥石流易损度定量表达为财产指标转换函数赋值与人口指标转换函数赋值之和的二分之一的平方根。易损度取值范围介于 0～ 1或 0 %～ 10 0 %之间     

云南滑坡泥石流灾害的气象成因与监测

根据云南滑坡泥石流灾害资料，分析了其形成环境与分布特征，给出了典型降水滑坡泥石流灾害事件，研究了滑坡泥石流灾害与气象环境的关系。云南滑坡泥石流灾害主要出现在盛夏7～8月，主要影响天气系统有切变线、冷锋、西风槽、西南涡、孟加拉湾风暴、南海西行台风和两高辐合区。诱发滑坡泥石流灾害的前期降水类型有3种，即暴雨型，中～大雨型和连阴雨型。得出了云南滑坡泥石流发生的区域临界雨量指标，提出了滑坡泥石流灾害的气象监测预警方法。     

坡度阀值与坡面泥石流--以重庆市北碚区为例

通过对重庆市北碚区的 2 1个坡面泥石流的实地调查表明 ,坡度对坡面泥石流发生具有重要控制性作用。在对坡面泥石流流域大量原始坡度进行统计分析后发现 ,各坡面泥石流的坡度分布具有明显的正态分布特征 ,且平均坡度分布具有显著的规律。根据这一分布规律 ,将本区坡面泥石流发生的坡度阀值确定为三类 :第一类的坡面泥石流植被覆盖率高 ,远离居民区 ,人类影响活动微弱 ,坡度阀值为 32 4° ;第二类坡面泥石流无一例外均位于林地结合部 ,森林覆盖率很低 ,人类活动影响十分剧烈 ,坡度阀值为 2 7 3° ;第三类的两条坡面泥石流相邻 ,均位于观音峡峡谷地带 ,它们的发生完全受地形条件的控制 ,坡度阀值为 36 8°。本文从定量的角度阐述了坡度阀值与坡面泥石流发生的关系 ,为生态脆弱区的划分、工程建设、防灾减灾和政府决策提供服务     

滑坡转化泥石流起动研究现状

滑坡转化泥石流起动研究是基础前沿性研究，直接关系到泥石流其他方面研究的进展，特别是预测预报。分析了国内外在滑坡转化泥石流起动研究方面的进展，分别从野外观测研究、实验设计和理论分析三个方面进行了阐述。重点介绍了目前国内外在理论上的进展，并进行了初步评价。通过讨论，提出了深入研究的思路与急需解决的问题，为下一步研究提供依据。     

贡嘎山东坡磨西河流域泥石流暴发的临界雨量值初探

在实地调查和前人研究的基础上,查明了贡嘎山东坡磨西河流域内泥石流沟的分布状况、暴发规律及危害特征等;并根据近20年来流域内发生的典型泥石流灾害,分析了泥石流发生前的降雨过程,发现磨西河流域内泥石流发生的当日雨量和前6 d有效雨量之间具有明显的幂函数关系,据此以泥石流发生的当日雨量和前6 d有效雨量为指标,初步探讨了磨西河流域内泥石流暴发的雨量值。     

A study on the early-warning technique concerning debris flow disasters

According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN) real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system's performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type and hazardous zone, the torrent management, the early-warning of disasters and the disaster reduction and prevention.     

A study on the early-warning technique concerning debris flow disasters

According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN)real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system′s performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type and hazardous zone, the torrent management, the early-warning of disasters and the disaster reduction and prevention.     

A study on the early—warning technique concerning debris flow disasters

According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN) real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system’s performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type and hazardous zone, the torrent management, the early-warning of disasters and the disaster reduction and prevention.