Debris Fan Produced by Failure of Canyon-Blocking Pyroclastic Flows

Ash-rich pyroclastic flows from the cataclysmic eruption of Mount Mazama (~7700 yr. B. P.), Cascade volcanic arc, Oregon, entered and blocked the narrow, bedrock-lined canyon of the Williamson River approximately 35 to 44 km from the source volcano. The blockage impounded a body of water which then released producing four stratigraphic units in the downstream debris fan. The four stratigraphic units are a boulder core comprised of locally sourced bedrock boulders and three sand-rich units including a fine-grained sand unit, a sandy pumice gravel (±basalt/hydrovolcanic tuff) unit, and a pumice pebble-bearing, crystal-rich sand unit. Hand-drilled auger holes up to ~1.6 m deep were used to obtain samples of the sand-rich units. Units were delimited using surface and down-hole observations, composition and texture, estimated density, statistical parameters of grain size, and vertical and lateral distribution of properties. Overtopping followed by rapid incision into the ash-rich pyroclastic flows progressively cleared the canyon, but a bedrock knickpoint near the head of the canyon limited the volume of debris available for transport to about 0.04 km3 to 0.08 km3. Co-deposition of bedrock boulders and lithic-rich sand was followed by rapid deposition with minimal reworking of remobilized pyroclastics. Continued draining of the impounded lake sent hyperconcentrated flows onto the debris fan depositing pumice-rich gravels that graded upward to crystal-rich sands.

Modeling Experiment of Break of Debris-Flow Dam

Glaciers are extensively developed in the southwest of Tibet and the moraines are widely distributed with large depth. Large-scale debris flows are often reported which blocked rivers and formed dams. In this paper, seven large debris flows in four valleys are discussed, among which five dams developed. 13 sets of experiments have been conducted in laboratory to simulate the formation and failure of the dam. Finally, a model of dam failure is proposed and a formula is established to calculate the flood discharge： Q=kbnnk/TB^-/LG^0.1,where bk is the outlet width of the dam at the original water level, hk the erosive depth, T the time from overflow to final state of failure, the average width of lake; L the length of the lake, and G the total potential energy of the water in the lake.

Numerical Analysis of Emergency River Restoration Scheme for Qingping Mega Debris Flow

The mega debris flow occurred on August 13 th 2010 in Qingping town,China(hereafter called '8.13' Debris Flow) have done great damage to the local habitants as well as to the re-construction projects in the quake-hit areas,and the channel-fill deposit problem caused by the debris flow was the most destructive.Moreover,it is of high possibility that an even severe deposit problem would reappear and result in worse consequences.In order to maximize risk reduction of this problem,relevant departments of the government established a series of emergency river restoration schemes,for which the numerical analysis is an important procedure to evaluate and determine the optimized one.This study presents a numerical analysis by applying a twodimensional debris flow model combined with a relevant water-sediment model to simulate the deposit during the progress of the debris flow,and to calculate and analyze the river flow field under both the present condition and different restoration conditions.The results show that the debris flow model,which takes the confluence of the Wenjia Gully to the main river into account,could simulate the deposit process quite well.In the reproduced debris flow from the simulation of the '8.13' Debris Flow,the original river flow path has switched to a relatively lower place just along the right bank with a high speed of near 7m.s-1 after being blocked by the deposit,which is highly hazardous.To prevent this hazard,a recommended scheme is derived through inter-comparison of different restoration conditions.It shows that the recommended scheme is able to reduce the water level and as well to regulate the flow path.Based on the given conditions of the mainstream and the tributary confluence for the simulated '8.13' Debris Flow,when encountering a debris flow with deposit volume less than 0.5 million m3,the river channel can endure a 20-year return flood;however,when the deposit volume increases to 2 million m3,the flood capacity of the river will be greatly impacted and the scheme becomes invalid.The recommended scheme supported by the present study has been applied to the emergency river restoration after this mega-debris flow.

Characteristics, Impacts and Risks of Dammed Lakes Induced by Debris Flows at the Wenchuan Earthquake Areas

After the Wenchuan Earthquake, many large-scale debris flows blocked rivers, generated dammed lakes, and produced outburst flood at the seriously hit areas. This paper mainly discussed the formation, outburst, impacts and risks of debris flow dammed lakes. The field investigation showed that the dammed lakes were created by debris flows from gullies and hill-slopes as well as the combination of debris flow and landslides, and also distributed along rivers step-by-step. The height of dams and the length of dammed lakes along river channel varied from 4 m to 18 m and from 400 m to 5000 m, respectively, and the reservoir capacity of dammed lakes were from 1.5 × 105 m3 to 3 × 106 m3. Due to geomorphological impact, dammed lakes commonly partially outburst along their front of debris flow deposition dams (1/4 - /3 outburst) or the suture between debris flow and landslide, and hardly completely outburst. Moreover, the subsequent debris flows continuously increased the magnitude and height of dams, not only increasing the stability of a single dam, but also improving the risks of outburst flood induced by intensive rainstorm. Dammed lakes produced steep rage in the sites of dams with the 4% - 9% of slope and rapidly raised river channel in the upstream due to a mass of alluvial sediment. As a result, the landscapes of step-dams and step-lakes dominate driver channels, significantly increasing the hazards of floods. Then the hazards, impacts and risk of debris flow dammed lakes along Min River from Dujiangyan to Wenchuan were analyzed. In order to mitigate dammed lakes induced by debris flows, the identification model of debris flow blocking rivers, the process of the formation, outburst and evolvement of dammed lakes, and the model of risk assessment for step-dammed lakes were strongly suggested to explore, and be used at the rivers of Min, Yuzi, Caopo, Longxi, Mianyuan, Jian, Shiting, Baishui and Jushui.

Comparison of Debris Flow Modeling Results with Empirical Formulas Applied to Russian Mountains Areas

Construction of debris flow protection structures is impossible without studying the processes first. Therefore, the purpose of this research was to calculate the magnitude of debris flows in three study areas. Initial information was provided by JSC Sevkavgiprovodkhoz and the Research Center “Geodinamika”. The first object of this research was the river Ardon and its tributary the Buddon, because of disastrous consequences for Mizur village of passed debris flows and floods. Modeling of unsteady water movement was carried out for estimation of potential flooding. During modeling, 5 cases of flash floods and debris flows of various probabilities from 0.5% to 1% percent were considered. Therefore, maximum floods for the cross-sections above and in the Mizur village itself were obtained. The second study area was the Chat-Bash stream, which is also situated in the north of Caucasus mountains. For this stream, the maximum discharge that could impact the mining complex at Tyrnyauz was determined. The third study area was the Krasnoselskaia river due to frequent floods in Yuzhno-Sakhalinsk. Applying three cases of various probabilities from 10% to 0.1%, the model determined maximum discharge and water level for the last cross-section above confluence into the Susuya river. Numerical experiments for all study areas with different roughness values were conducted to identify optimal ones. Comparing the model results for all study areas with empirical formulas (Golubcov V.V., Herheulidze I.I., Kkhann, Sribnyj and ASFS of EMERCOM of Russia) revealed that formulas contain only average depth slope angle and empirical coefficients and do not allow estimating flood areas and maximum characteristics of the event with a certain degree of accuracy.

Process-driven susceptibility assessment of glacial lake outburst debris flow in the Himalayas under climate change

Global warming is causing glaciers to retreat and glacial lakes to expand in the Himalayas,which amplifies the risk of glacial lake outburst debris flows(GLODFs)and poses a significant threat to downstream lives and infrastructures.However,the complex interplay between GLODF occurrences and associated indicators,coupled with the lack of a comprehensive susceptibility indicator system that considers the entire GLODF process,presents a substantial challenge in assessing GLODF susceptibility in the Himalayas.This study proposes a process-driven GLODF susceptibility assessment indicator system responding to climate change that considers the complete process of GLODF formation,incorporating relevant parameters about upstream,themselves,and downstream of glacial lakes.Furthermore,to mitigate subjective factors associated with traditional evaluation methods,we developed three novel hybrid machine-learning models by integrating classic machine-learning algorithms with the whale optimization algorithm(WOA)to delineate the distribution of GLODF susceptibility in the Himalayas.All the hybrid models effectively predicted the GLODFs occurrence,with the WOA-SVC model demonstrating the highest prediction accuracy.Approximately 34%of the catchments exhibit high and very high susceptibility levels,primarily concentrated along the north and south sides of the Himalayan ridge,particularly in the eastern and central Himalayas.Indicators capturing the physical formation process of hazards,such as topographic potential(highest relative importance value of 40%),can precisely identify GLODF.A total of 128 catchments pose potential transboundary threats,with 24 classified as having a very high susceptibility level and 25 as having a high susceptibility level.Notably,the border region between China and Nepal is a prominent hotspot for transboundary threats of GLODF.These findings can provide valuable clues for disaster prevention,mitigation,and cross-border coordination in the Himalayas.

Flood susceptibility modelling using advanced ensemble machine learning models

Floods are one of nature's most destructive disasters because of the immense damage to land,buildings,and human fatalities.It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods.Therefore,earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters.In this study,we applied and assessed two new hybrid ensemble models,namely Dagging and Random Subspace(RS)coupled with Artificial Neural Network(ANN),Random Forest(RF),and Support Vector Machine(SVM)which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin,the northern region of Bangladesh.The application of these models includes twelve flood influencing factors with 413 current and former flooding points,which were transferred in a GIS environment.The information gain ratio,the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors.For the validation and the comparison of these models,for the ability to predict the statistical appraisal measures such as Freidman,Wilcoxon signed-rank,and t-paired tests and Receiver Operating Characteristic Curve(ROC)were employed.The value of the Area Under the Curve(AUC)of ROC was above 0.80 for all models.For flood susceptibility modelling,the Dagging model performs superior,followed by RF,the ANN,the SVM,and the RS,then the several benchmark models.The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.

四川金阳县2023年“8·21”山洪泥石流灾害成因分析

2023年8月21日凌晨,四川金阳县芦稿林河流域受短时强降雨影响暴发山洪,位于下游的沿江高速JN1(金宁一)标段项目部钢筋加工场民工驻地板房被冲毁,造成52人死亡失联。灾害发生后,四川省委、省政府高度重视,派出专家对灾害过程进行调查评估。结合现场调查情况,通过水文气象分析计算、河道行洪能力计算等,分析了灾害形成过程及致灾原因,可供类似项目山洪灾害防御工作参考。

崩塌滑坡-堰塞湖-溃决洪水-泥石流灾害链演化特征分析及防治对策研究

某沟谷两岸坡面陡峻,沟谷狭窄,纵坡降较大,在地震、降雨等不利因素影响下,其左岸堆积体上方的崩滑堵沟隐患点可能出现失稳,并发展为崩塌滑坡-堰塞湖-溃决洪水-泥石流灾害链。针对此灾害链不同阶段的演化特征,采用相应的数值模拟模型和数值计算方法进行模拟分析和计算,评价其对沟口桥梁工程的影响,并采取相应的防治对策。经分析计算,崩塌滑坡隐患点距沟底高程落差约1 km,岩体体积约8×10^(6)m^(3),平均厚度约26 m,崩塌滑坡堵河可形成最大水深为14.4 m、面积约为7.19×10^(4)m^(2)、方量约为2.74×10^(5)m^(3)的堰塞湖;堰塞湖溃决形成洪水过程中,桥梁处最大水深为4.43 m(不含原始水位),最大流速为7.54 m/s,峰值流量为807 m^(3)/s;在溃决洪水强烈揭底冲刷和侵蚀的条件下,溃决洪水引发的泥石流在桥梁处的最大水深为7.1 m、最大流速为8 m/s、峰值流量为1685.5 m^(3)/s、最大冲刷深度为16.58 m。为减少该灾害链对桥梁工程的影响,采取河道疏通、岸坡防护和监测预警等防治措施。

降雨型山洪泥石流灾害成因及实证分析

为了更加有效地预防、应对和减少降雨引发山洪泥石流灾害造成的群死群伤事件,基于实证案例开展了山洪泥石流灾害成因分析。通过描述山洪、泥石流和山洪泥石流灾害基本特征与危害特点,分析了强降雨、流域地形、运动路径环境效应和承灾体等成灾要素。为了细化灾害成因性质认定,把山洪分为悬移质山洪和推移质山洪、山洪泥石流分为山洪泥石流和山洪水石流、泥石流分为泥流和泥石流,结合典型案例阐述了不同亚类山洪泥石流灾害的含义。

Numerical simulation of deposit in confluence zone of debris flow and mainstream

Abundant solid materials were formed as a result of landslide and collapse due to Wenchuan earthquake.The solid source around mountains would form a debris flow when appropriate rain condition occurs.Such a debris flow is structurally very large and strong,and the river flow can hardly wash away the deposit when the debris flow enters into the mainstream.As a result,the deposit on the river bed due to debris flow will cause a series of hazards.Based on the previous researches and relevant data,this paper simplified the interaction between debris flow and current of the main river,and adopted the finite element characteristic-based-split algorithm which is favorable to the stabilization of dealing with the convection.Finally,the numerical model of the confluence of debris flow deposit and main river was developed,and the deposit progress of the mega-debris flow from Wenjiagou in Mianyuan river was reproduced.Furthermore,the influence of the deposit on the flow route of the main river,and distribution of velocity and water depth were analyzed.The results showed that the simulation deposit terrain qualitatively agreed with the field data through comparison,including the deposit area and depth distribution.Furthermore,the improvement of the model in future was discussed.

崩塌滑坡泥石流灾害链分类研究

为了科学预防应对跨越时空的灾害链锁效应,提高多灾种灾害链风险综合防御的科学性、针对性和效能性,作者基于自己多年研究体会和国内外研究案例,开展了崩塌滑坡泥石流灾害链分类研究。崩塌滑坡泥石流灾害链是指自然因素或人类活动更多的是两者迭加作用引发的冰雪岩土崩塌滑坡或泥石流灾害作为首环而接续产生的一系列灾害链式反应,后续环节表现为碎屑流、涌浪、洪流倾泻、堰塞湖淹没、溃决洪水冲击等不同组合,具有空间关联、时间接续、动力转换、灾情放大的基本特点。根据作者经验和国内外诸多典型案例的分析综合,作者提出了崩塌滑坡泥石流为首环的灾害链的基本认识、分类依据和包括5类21种的分类体系。第1类是自然崩塌滑坡接续灾害链,包括崩塌滑坡间歇级联、周期接续、多级顺直俯冲和多级折转冲击等4种灾害链。第2类是自然崩塌滑坡泥石流及其转化灾害链,包括崩塌滑坡导致激流倾泻、涌浪传播、涌浪-堰塞-淹没-溃决、转化为泥石流、沟道堵溃-泥石流淤堵河道、泥石流-淤堵-洪水和土体液化-泥土流灾害链等7种灾害链。第3类是工程土体滑坡泥石流及其转化灾害链,包括滑坡-滑坡、泥石流-堵河洪水、滑坡-泥石流和尾矿坝溃决-泥石流等4种灾害链。第4类是雪崩冰崩滑坡泥石流及其转化灾害链,包括雪崩-埋压-堵塞-洪水泥石流、冰崩岩崩-滑坡-涌浪-堰塞-溃决和冰崩滑坡-冰湖溃决-洪水泥石流等3种灾害链。第5类是火山或海域崩塌滑坡泥石流灾害链,包括火山滑坡-泥石流-堰塞、海岸崩塌滑坡-海啸和海底滑坡-泥石流等3种灾害链。本项研究试图为研究每一种类崩塌滑坡泥石流灾害链的静力学、动力学和运动学指明方向,为建立整体论与分割论相结合的地质灾害链预防应对工程技术体系和决策支持平台奠定理论基础。

基于logistics回归模型的山洪泥石流风险评估

山洪泥石流作为一种常见的自然灾害,其突发性和破坏性给人类社会的生产生活带来了巨大的威胁。在全球气候变暖的背景下,山洪泥石流的发生频率和破坏力呈现增加趋势。通过采用有序logistics回归模型,对四川省北川羌族自治县地区山洪泥石流危险性进行了定量化评估,选取流域切割密度、流域相对高差、主沟长度、50年一遇泥石流规模等多个关键因素,构建了logistics回归模型进行危险性评估。根据模型结果发现,主沟长度和50年一遇规模的影响最为显著。本文不仅对山洪泥石流风险进行了较为精确的定量化评估,同时也为防治措施的制定提供了科学依据。

川西特大暴雨后公路山洪泥石流灾损分析

为分析山洪泥石流对公路的灾损特征,基于2019年8月雅安特大暴雨后国道351调查,结合区域工程地质条件,针对63处公路损毁段,从泥石流堆积物、支挡结构损毁、路基损毁和总损失4个方面研究灾损特征,并提出应急措施。结果表明:泥石流堆积物超2×10^(4)m^(3)的工点占81.28%,堆积多呈扇形,且泥石流冲出物粒径差异较大,其成分因物源形成而存在差异;支挡结构损毁超1500 m3的工点占56.82%,损毁主要为河道侧蚀、块石撞击等导致;路基损毁超300 m的工点占26.67%,主要为河流冲刷侧蚀掏空路基、靠山侧崩塌、滑坡掩埋路基等导致;总损失超700万元的工点占26.55%。山区公路勘察设计应充分评估公路沿线易损区段和承灾脆弱区段,分阶段实施不同粒径填料搭建临时保通道路。

北京市昌平区韩台村“23·7”暴雨山洪泥石流灾害特征分析

【目的】近年来,受极端降雨事件影响,北京西部和北部山区山洪泥石流灾害频发,给当地造成巨大的生命财产损失。针对北京市昌平区韩台村“23·7”暴雨山洪泥石流灾害事件开展灾害过程和特征研究,为小流域灾害防治及提升灾害应对能力供基础支撑和参考依据。【方法】以昌平区高崖口沟韩台村支沟为研究区,采用“区域灾情调查-重灾区现场调研-室内评估分析”相结合的方式,查明研究区的雨水情特征及灾情特征。基于堆积物沉积结构、实物破坏形式和流体的内在特性,分析了韩台村支沟内山洪泥石流的灾害过程和基本特征,初步探讨了此次灾害的成因,并提出灾害防范对策建议。【结果】结果表明:(1)韩台村上游沟道集雨面积约0.1 km^(2),根据王家园水库自动站2023年8月31日12时至13时降雨数据,估算的韩台村上游沟道内1小时洪水总量约6870 m^(3),其破坏力非常大。(2)韩台村支沟自沟顶至韩台村西部村南口,具有典型的泥石流特征。村南口进村120 m范围内有泥石流堆积物,覆盖于山洪沉积物之上,属于典型的泥石流堆积前缘特征。由此至韩台村北口(韩台村支沟沟口),具有明显的山洪灾害特征,平均洪水深度超过5 m,淹没面积约33940 m^(2)。(3)2305号台风“杜苏芮”外围残余环流北上引发的极端强降雨是此次灾害的直接致灾因子,同时,受区域地形地貌、山洪泥石流作用及居民对所处地质环境的认知程度等因素的影响。【结论】此次昌平区高崖口沟韩台村支沟特大暴雨洪涝灾害是一次极端暴雨引发的山洪泥石流复合灾害事件。短时强降雨导致地表径流流量陡增是造成此次灾害的直接原因,初步推测泥石流发生时间晚于山洪,亦或是形成于山洪减弱阶段。自支沟顶至韩台村西部村南口(约1.4 km)为泥石流区域,村南口进村120 m左右为泥石流堆积前缘区域,同时部分区域具有山洪特征,村南口至村北口(支沟口)为山洪受灾区域。

排洪渠工程总体设计及探讨——以张家川胡川片区排洪渠工程为例

近年来,西北地区由于常年的季节性暴雨,使得已建城市、园区内涝现象多发,解决该问题主要在城市、园区建设的前期阶段;在园区排洪系统建设中,不光计算洪水流量,还应计算泥石流流量;不光要求排洪渠布线顺畅,还应遵循园区总体规划,兼顾现有建筑影响;不光计算排洪渠过水断面计算,还应通过排洪渠不淤计算。

乌鲁木齐市无资料地区山洪泥石流临界雨量推求

确定暴雨山洪、泥石流临界雨量对于受影响地区防灾减灾具有十分重要的意义,本文根据暴雨山洪、泥石流的成因,计算乌鲁木齐山洪、泥石流临界雨量。有资料地区通过分析整理雨量资料来确定临界雨量;无资料地区假定灾害与降雨同频率,分析灾害次数,确定灾害发生频率,从而求出临界雨量。乌鲁木齐雨量站较少,无法绘制临界雨量的等值线。根据计算临界雨量值,利用反距离加权距离法进行研究区临界雨量空间插值,从而得出各小流域的临界雨量值。

2013年西藏嘉黎县“7.5”冰湖溃决洪水成因及潜在危害

冰湖溃决洪水(泥石流)是西藏自治区主要自然灾害之一.2013年7月5日,西藏自治区嘉黎县忠玉乡发生"7.5"冰湖溃决洪水灾害事件,导致人员失踪,房屋被毁,桥梁、道路等基础设施遭到严重破坏,直接经济损失高达2.7亿元.基于不同时间段地形图和遥感影像资料,利用地理信息技术,发现导致"7.5"洪灾的溃决冰湖为然则日阿错.该冰湖溃决的直接诱因可能是雪崩和冰崩的共同作用,溃决前的强降水过程及气温的快速上升是其间接原因,而冰湖长期稳定的扩张导致水量聚集是其溃决并造成巨大灾害的基础.然则日阿错溃决后形成2个冰湖,面积分别为0.25 km2和0.01 km2,再次发生溃决的概率极小.这次溃决洪水和泥石流灾害事件阻塞了尼都藏布的罗琼沟及衣布沟,并形成2处面积分别为0.33 km2和0.13 km2堰塞湖,且存在溃决风险,在今后一段时间内应加强监测工作与排险工程实施.

冰湖溃决泥石流的形成、演化与减灾对策

本文分析了主要由冰滑坡和冰崩入湖导致的冰湖溃决的机理和条件。进而 ,从气候条件、水文条件、终碛堤、冰湖规模、冰滑坡、沟床特征和固体物质补给等方面分析了冰湖溃决泥石流的形成条件和特点 ,归纳出冰湖溃决泥石流沿程演化的 6种模式 :溃决洪水 -稀性泥石流、溃决洪水 -黏性泥石流、溃决洪水 -稀性泥石流 -黏性泥石流、溃决洪水 -黏性泥石流 -稀性泥石流、溃决洪水 -稀性泥石流 -黏性泥石流 -稀性泥石流和溃决洪水 -黏性泥石流 -稀性泥石流 -洪水。针对冰湖溃决泥石流突发性强、频度低、洪峰高、流量大、流量过程暴涨暴落、破坏力强和灾害波及范围广等特点 ,提出了 7点减灾对策。

冰川终碛湖溃决泥石流流量计算

冰川终碛湖溃决泥石流是青藏高原常见的泥石流灾害类型之一,也是青藏高原地区泥石流防治的重点之一.在溃决洪水研究的基础上,结合泥石流本身的特征,针对瞬间部分溃决的情况,推导了冰川终碛湖溃决泥石流流量的计算方法.具体包括冰川终碛湖溃决口泥石流洪峰流量Qdmax=kQmax和距离溃决口一定距离的河道某处泥石流洪峰的最大高度Hd\%max=kHHmax.由于计算方法中涉及泥石流的特征参数,依据泥石流的特征,定义了特征参数的含义,并给出了计算方法k=1+(γd-γw)/(γ\%s-γd),kH=k·kG,kG是与沟道形态有关的参数.为了检验推导计算方法的合理性和精度,选定西藏米堆沟冰川终碛湖溃决泥石流作为实例,进行了验证.结果表明,推导计算方法的物理概念清晰,计算结果与实际调查数据在趋势上吻合.