北京山区柯太沟泥石流

北京山区为泥石流多发区 ,共有泥石流沟 50 0多条 ,其中不乏河谷型泥石流。为了对北京山区河谷型泥石流进行深入研究和合理防治 ,选择一条无论地质历史时期还是近代 ,泥石流活动都十分活跃的柯太沟作为研究对象 ,以期通过对该沟泥石流的危害、形成条件和发展趋势的研究 ,提高对北京山区河谷型泥石流的认识和了解 ,从而提出更为合理的减灾对策和防治措施。     

评《北京山区泥石流》

对《北京山区泥石流》一书作了简要、客观的介绍,认为该书出版不仅为北京山区泥石流防治提供了科学依据,而且为从事泥石流研究与防治的相关科研技术人员提供了一本系统全面的参考书,同时也是一本理论与实际相结合的具有较高的理论水平和实际运用价值的泥石流及其防治论著。     

青藏高原东缘和邻区晚新生代泥石流活动规律及其成因

本文根据大量野外考察资料和室内测年数据 ,通过对晚新生代以来不同时段泥石流沉积物的分布特征研究 ,总结了青藏高原东部及华北地区第四纪泥石流活动的规律。认为晚新生代大规模的泥石流活动始于晚第三纪 ,晚上新世～早更新世泥石流活动主要中心集中在青藏高原东部边缘地区 ;中更新世是泥石流活动最活跃的时段 ;晚更新世位于大陆内部的秦岭北坡及陇南山地泥石流活动减弱 ,华北北京山区及太行山东麓泥石流活动加强。第四纪泥石流活动的规律性变化与青藏高原的阶段性隆起及亚洲季风的建立有关     

北京山区番字牌西沟泥石流减灾规划探讨

番字牌西沟为北京山区具代表性的一条泥石流沟，1989年和1991年两次暴发泥石流，致死3人，造成严重灾害。泥石流具有容重大（2.0t/m^3），搬运固体物质粒径粗，固体物质以沟床堆积物补给为主，平均约10年一次中小规模、50年一次大规模活动周期等特征，针对泥石流特征，制定出三套减灾工程规划方案，并进行方案优化探讨，提出优化方案供减灾使用。     

基于宽度学习模型的泥石流灾害预报

在泥石流灾害预报模型研究中,科学确定泥石流灾害影响因子及保证模型较高的预报准确率和快速的训练速度是关键问题,也是泥石流灾害预报预警和防灾减灾的重要基础。本研究针对目前泥石流预报模型输入数据维度较大和训练时间较长的问题,采用快速多个主成分并行提取算法(Fast multiple principle components extraction algorithm,FMPCE),选取出6个泥石流灾害影响因子,包括降雨量、山坡坡度、沟床比降、相对高差、土壤含水率和孔隙水压力。基于宽度学习(Broad learning,BL)算法,以泥石流影响因子为输入,泥石流发生概率为输出,构建了泥石流预报模型,并用矩阵随机近似奇异值分解(矩阵随机近似SVD)对模型进行了优化,将优化后宽度学习模型的预报结果与梯度下降法优化的BP神经网络预报模型(GD-BP)、基于支持向量机的预报模型(SVM)、宽度学习预报模型(BL)的结果进行对比,同时,通过输入数据集的扩展,从训练时间上对不同模型进行比较。结果表明,优化宽度学习泥石流灾害预报模型的预报准确率为93.52%,较GD-BP模型、SVM模型和BL模型的预报准确率分别高出1.60%、1.15%和0.03%;优化宽度学习泥石流灾害预报模型的训练时间为0.9039s,较GD-BP模型、SVM模型和BL模型的训练时间分别节省了25.3867 s、17.2620 s和0.8974 s。本研究说明宽度学习算法可以用于对泥石流灾害的发生概率进行预报,同时也可为泥石流预报的实际应用提供新的思路。     

不同损失条件下的泥石流预报模型

泥石流预报是泥石流减灾的重要手段之一，然而泥石流形成的复杂性使泥石流预报准确度低，误报和漏报率较高。泥石流误报和漏报都会造成损失，但二者造成的损失有很大的差别。为了减少泥石流误报或漏报造成的损失，应当考虑两种错报造成损失的不同。根据使总平均损失达到最小的原则，建立了不同损失条件下的泥石流预报模型，并将该模型应用到云南东川蒋家沟。     

四川境内成昆铁路泥石流数据库应用系统

四川境内成昆铁路泥石流数据库应用系统包括泥石流信息管理系统和泥石流预测预报系统。前者是将四川境内成昆铁路367条泥石流沟的41种信息,用汉字dBASE Ⅲ建立的信息管理系统,实现了信息的自动编辑、检索、统计和报表打印;后者根据泥石流预测预报模型,用泥石流信息管理系统中存储的数据和有关信息,在CCDOS 4.0的支持下,再输入有关泥石流的动态信息,在微型计算机上作出泥石流的预测预报,这一系统是用Turbo PROLOG语言完成的。     

北京大烂碴沟泥石流堆积扇的特征及其演变过程

北京山区由于山坡陡峻、构造发育、岩体破碎,加上气候条件,泥石流灾害的发生较为频繁.密云县是北京山区泥石流高发区,冯家峪镇则是密云县泥石流发生最多的区域.密云县冯家峪镇西白莲峪历史上发生多次泥石流,其流域自然地理条件复杂、泥石流堆积形态多样,大烂碴沟泥石流堆积扇具有一定的代表性.研究泥石流堆积特征及其演变过程,以期丰富北京山区泥石流基础资料,同时对完善泥石流灾害防治的危险区区划有所裨益.在收集当地泥石流发生历史资料的基础上,详细的调查了西白莲峪大烂碴沟的自然地理状况和泥石流堆积物的特点.大烂碴沟上游沟谷剖面呈"V"形,切割明显,地形坡度一般在32.以上,而下游沟谷剖面呈"U"形.从泥石流形成的年代和冲刷痕迹推测,"U"形沟谷为泥石流冲刷形成.整个流域成扇形,泥石流形成区面积为0.58 km2,流通区面积为0.09 km2.大烂碴沟流通区沟道极短,这样,形成区汇集洪水到达流通区后,严重冲刷沟谷坡脚,破坏基岩的稳定性,造成两岸岩石滑坡、崩塌和沟床岩石的整体性搬运,从而形成泥石流.流域出口处有泥石流扇形堆积体,砾石含量较多.采用野外调查和室内实验结合的方法对大烂碴沟泥石流的堆积物特点进行研究,具体如下:(1)地貌特征:采用野外量测与填图的方法,主要调查堆积扇的部位及其地形、沟道比降与宽度,堆积物外部形态等.(2)结构组成:主要有颗粒级配、岩性组成、砾石排列与分选性、堆积物的结构与构造特征,以及粒态、擦痕、砾石包裹情况,大漂砾粒径、堆积位置与排列等颗粒特征.砾石的调查通过在沟道内随机选取一定数量的砾石进行abc长度和倾向调查.以上参数通过现场观测、测量取得.选定泥石流堆积区典型部位Ⅰ和Ⅲ,通过挖圆形探坑,取出全部颗粒.将颗粒直径大于10 mm的大颗粒筛出,称重,将剩余颗粒1 kg左右带回实验室分析.粒度分析的主要方法为:平均粒径比中值能更正确地反映碎屑颗粒的集中趋势,按福克和沃德的平均粒径的表达式Mx:φ16 φ50 φ80/3判别碎屑颗粒的集中趋势;采用由福克和沃德提出的标准偏差σ=φ84-φ16/4 φ95-φ5/6.6判别颗粒大小的均匀程度;采用福,克和沃德的偏度公式:SK1=φ16 φ84 2φ50/2(φ84-φ16) φ5 φ95-2φ50/2(φ95-φ5)判别粒度分布的不对称程度;峰度是用来衡量粒度频率曲线尖锐程度的,也就是度量粒皮分布的中部与两尾端的展形之比,采用福克和沃德提'出的峰度公式KG=φ95-φ5 φ80/2.44(φ75-φ25)判别.在查阅历史资料和堆积物调查的基础上,本文对大烂碴沟泥石流堆积扇的发育和演变过程进行了分析.研究结果表明,该区泥石流堆积扇的形成受到初次水石流和二次粘性泥石流两种泥石流形成过程的影响,水石流形成堆积扇主体,粘性泥石流则起到显著改变堆积扇形态特征的作用.大烂碴沟泥石流堆积扇的演变过程和特征明显受到大烂碴主沟和西白莲峪主沟水流的影响.从外部特征来看,堆积扇可以分为Ⅰ,Ⅱ,Ⅲ和Ⅳ四个区,其中Ⅰ,Ⅱ,Ⅲ区表现为二次泥石流堆积特征,Ⅳ区表现为初次泥石流堆积特征.两次泥石流形成过程中固体物质的运动方式、搬运距离和侵蚀强度不同,其堆积扇在不同分区的沙砾粒径、排列方向和圆度也反映出两次泥石流的形成特征.该研究结果对今后进一步探讨北京山区泥石流形成机理和运动过程以及为北京山区泥石流防治制定有效措施提供了科学依据.     

北京山区产业结构特征及其优化开发模式

分析了北京山区的战略地位和职能，划分出了山区经济发展的五个阶段，进而分析了山区产业结构的基本特征，并提出了北京山区优化开发的模式。     

北京山区沟域经济发展的空间组织模式

沟域经济是山区发展的新模式,基本涵盖了沟域发展的各个层面,是独具山区发展特色的经济地理形态.以沟域为载体的山区要素布局的空间耦合关系是山区发展的新命题,理论与现实意义重大.结合多年的山区发展研究,在初步探讨了沟域经济的内涵和空间组织过程的基础上,分析了北京山区沟域经济发展的现状,并对北京沟域经济发展的空间布局特征指向及其影响进行了研究,最后建立了沟域经济空间组织的合理模式框架.研究认为,沟域经济对北京山区新时期的发展转型作用重大,首先它不以行政区域界限为边界,基本串联了山区的大部分村庄,并与主要交通线走向重合,因此至少能在山区产业结构调整、城乡统筹发展等方面会对山区发展产生积极影响.其次,通过分析认为目前北京山区沟域经济发展正处于第二次集中型空间组织阶段,资源节约、环境友好、产业优化是这一阶段的特点,因此北京沟域经济的发展一定程度上有助于协调好山区生态保护与经济发展的关系,促进山区的综合开发.北京山区沟域经济发展模式的成功实践一方面支持了北京山区功能转型的战略决策,另一方面也为其他山区发展提供了借鉴和指导意义.     

良好植被区泥石流防治初探

通过对近年来发生在良好植被区的几次重大泥石流、滑坡灾害的考察,发现植被在泥石流、滑坡形成中的作用有待于进一步认识。通过分析,当中小强度降雨激发下,植被能够削减泥石流、滑坡灾害的规模,甚至抑制泥石流、滑坡灾害的发生;当降雨超过一定阀值后,在水作用下,植被不但不能削减灾害规模,反而增大灾害的规模。在这类地区,简单地使用一般的防治措施,已经不能满足防灾、减灾的需要,客观要求针对这些地区泥石流灾害的形成原因、危害特征,研究防治对策。经初步研究提出3点防治措施:1)加强泥石流滑坡灾害的预测预报工作;2)在重点区域设置自动雨量记录报警装置;3)特别针对漂木拦挡,采取新型结构减轻泥石流的危害。     

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.     

泥石流预报中前期有效降水量的确定

前期有效降水量是泥石流预报的重要参数之一,对不同类型泥石流的形成有不同的影响形式,对土力类泥石流的形成主要是影响泥石流形成区土体的土壤含水量.在每次前期降水增加的土壤含水量和其有效降水量遵循相同衰减规律,以及每次前期降水的有效降水量和其增加的土壤含水量衰减过程都是相互独立的假设条件下,通过分析土壤含水量随时间的变化关系,可以得到前期有效降水量与前期降水量随时间的变化关系,从而可以确定前期有效降水量.通过对云南蒋家沟降水和土壤含水量的实际观测,对这个关系进行了分析研究,并利用最小二乘法得出了前期有效降水量的计算公式.     

雅砻江二滩水电站库区泥石流

雅砻江二滩水电站库区泥石流十分活跃，在库区内，沟谷型泥石流沟１００条．库首左岸的金龙沟，多次暴发过泥石流，用金龙沟泥石流活动特征与短历时雨强的资料，经计算分析后，得到了库区泥石流活动规律、流域环境条件与雨强之间的关系式，并给出了金龙沟暴发泥石流的降水指数３６００，有助于泥右流预报．     

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.     

Empirical models to predict the volumes of debris flows generated by recently burned basins in the western U.S.

Recently burned basins frequently produce debris flows in response to moderate-to-severe rainfall. Post-fire hazard assessments of debris flows are most useful when they predict the volume of material that may flow out of a burned basin. This study develops a set of empirically-based models that predict potential volumes of wildfire-related debris flows in different regions and geologic settings.The models were developed using data from 53 recently burned basins in Colorado, Utah and California. The volumes of debris flows in these basins were determined by either measuring the volume of material eroded from the channels, or by estimating the amount of material removed from debris retention basins. For each basin, independent variables thought to affect the volume of the debris flow were determined. These variables include measures of basin morphology, basin areas burned at different severities, soil material properties, rock type, and rainfall amounts and intensities for storms triggering debris flows. Using these data, multiple regression analyses were used to create separate predictive models for volumes of debris flows generated by burned basins in six separate regions or settings, including the western U.S., southern California, the Rocky Mountain region, and basins underlain by sedimentary, metamorphic and granitic rocks.An evaluation of these models indicated that the best model (the Western U.S. model) explains 83% of the variability in the volumes of the debris flows, and includes variables that describe the basin area with slopes greater than or equal to 30%, the basin area burned at moderate and high severity, and total storm rainfall. This model was independently validated by comparing volumes of debris flows reported in the literature, to volumes estimated using the model. Eighty-seven percent of the reported volumes were within two residual standard errors of the volumes predicted using the model. This model is an improvement over previous models in that it includes a measure of burn severity and an estimate of modeling errors. The application of this model, in conjunction with models for the probability of debris flows, will enable more complete and rapid assessments of debris flow hazards following wildfire.     

Origin of the valley networks on Mars: a hydrological perspective

The geomorphology of the martian valley networks is examined from a hydrological perspective for the compatibility with an origin by rainfall, globally higher heat flow, and localized hydrothermal systems. Comparison of morphology and spatial distribution of valleys on geologic surfaces with terrestrial fluvial valleys suggests that most martian valleys are probably not indicative of a rainfall origin, nor are they indicative of formation by an early global uniformly higher heat flow. In general, valleys are not uniformly distributed within geologic surface materials as are terrestrial fluvial valleys. Valleys tend to form either as isolated systems or in clusters on a geologic surface unit leaving large expanses of the unit virtually untouched by erosion. With the exception of fluvial valleys on some volcanoes, most martian valleys exhibit a sapping morphology and do not appear to have formed along with those that exhibit runoff morphology. In contrast, terrestrial sapping valleys form from and along with runoff valleys. The isolated or clustered distribution of valleys suggests localized water sources were important in drainage development. Persistent groundwater outflow driven by localized, but vigorous hydrothermal circulation associated with magmatism, volcanism, impacts, or tectonism is, however, consistent with valley morphology and distribution. Snowfall from sublimating ice-covered lakes or seas may have provided an atmospheric source of water for the formation of some valleys in regions where the surface is easily eroded and where localized geothermal/hydrothermal activity is sufficient to melt accumulated snowpacks.     

中国山地灾害研究进展与未来应关注的科学问题

本文首先简要回顾了山地灾害研究与防治方面的新进展：认识了山地灾害的空间分布规律,建立了山洪、泥石流、滑坡危险性评价方法;发展了滑坡稳定性分析的原理和计算方法,建立了泥石流流体应力本构关系、泥石流流速流量和冲击力计算公式、粘性泥石流起动模型,提出了山洪和泥石流规模放大效应;基于降雨和地面成灾环境要素耦合分析,发展了山地灾害气象预报方法;基于对灾害物理特性的认识,研发了一系列灾害监测预警仪器、数字流域平台与智能手机网络相结合的山洪预警系统;发展了灾害治理工程技术,形成了适合欠发达地区特点的灾害治理技术体系。在此基础上,分析了在灾害形成、运动、预测预报、防治技术和风险管理等方面还需要进一步深化研究的问题,提出山地灾害学科今后面临的任务。最后,针对国家减灾需求和学科发展目标,提出灾害对生态的响应机制、气候变化对山地灾害的影响与巨灾预测、水—土耦合的细观结构力学、灾害风险的理论与方法、基于灾害形成理论的机理预报模式、灾害防治技术规程的健全等未来应该关注的科学技术问题。     

气候变化影响下藏东南帕隆藏布流域高山区泥石流的地貌效应

高海拔或高纬度山区（尤其高山冰川及冻土急剧消退区）常孕育适宜泥石流发育的地形和物源条件。气候变化（如升温、强降雨事件增多等）影响下,高山区潜在孕灾环境更易于成灾,泥石流成为主要的灾害类型和物质输移方式,也是高山区地貌变化的重要驱动力。由于野外监测困难,数据资料匮乏,鲜有针对高山区泥石流过程地貌效应的分析报道。以中国藏东南高山区泥石流多发的帕隆藏布流域为研究区,以古乡沟、天摩沟和扎木弄沟为典型小流域,结合遥感影像、DEM数据、无人机航拍、高精度RTK测量和野外踏勘调查,分析泥石流沟道地貌发育特征（冲淤变化、平面摆动）及其对主河河流地貌的影响,并探讨大规模泥石流事件影响下河谷地貌的长期演变趋势。高山区泥石流过程强烈塑造沟道自身地貌,上游物源区深切展宽和溯源蚀退,沟口堆积扇冲淤变化受控于泥石流事件规模和水流强度。泥石流过程显著影响主河道河流地貌,造成主河道横向冲淤和摆动,并影响堰塞体上游河段平面形态发育。长时间尺度上,河谷地貌在平面上发育形成宽窄相间的藕节状而在纵剖面上形成台阶状形态。