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1.
Debris flow susceptibility mapping(DFSM) has been reported in many studies, however, the irrational use of the same conditioning factor system for DFSM in regional-scale has not been thoroughly resolved. In this paper, a region-partitioning method that is based on the topographic characteristics of watershed units was developed with the objective of establishing multiple conditioning factor systems for regional-scale DFSM. First, watershed units were selected as the mapping units and created throughout the entire research area. Four topographical factors, namely, elevation, slope, aspect and relative height difference, were selected as the basis for clustering watershed units. The k-means clustering analysis was used to cluster the watershed units according to their topographic characteristics to partition the study area into several parts. Then, the information gain ratio method was used to filter out superfluous factors to establish conditioning factor systems in each region for the subsequent debris flow susceptibility modeling. Last, a debris flow susceptibility map of the whole study area was acquired by merging the maps from all parts. DFSM of Yongji County in Jilin Province, China was selected as a case study, and the analytical hierarchy process method was used to conduct a comparative analysis to evaluate the performance of the region-partitioning method. The area under curve(AUC) values showed that the partitioning of the study area into two parts improved the prediction rate from 0.812 to 0.916. The results demonstrate that the region-partitioning method on the basis of topographic characteristics of watershed units can realize more reasonable regional-scale DFSM. Hence, the developed region-partitioning method can be used as a guide for regional-scale DFSM to mitigate the imminent debris flow risk.  相似文献   

2.
In the meizoseismal areas hit by the China Wenchuan earthquake on May 12, 2008, the disasterprone environment has changed dramatically, making the susceptibility assessment of debris flow more complex and uncertain. After the earthquake, debris flow hazards occurred frequently and effective susceptibility assessment of debris flow has become extremely important. Shenxi gully in Du Jiangyan city, located in the meizoseismal areas, was selected as the study area. Based on the research of disaster-prone environment and the main factors controlling debris flow, the susceptibility zonations of debris flow were mapped using factor weight method（FW）, certainty coefficient method（CF） and geomorphic information entropy method（GI）. Through comparative analysis, the study showed that these three methods underestimated susceptible degree of debris flow when used in the meizoseismal areas of Wenchuan earthquake. In order to solve this problem, this paper developed a modified certainty coefficient method（M-CF） to reflect the impact of rich loose materials on the susceptible degree of debris flow. In the modified method, the distribution and area of loose materials were obtained by field investigations and postearthquake remote sensing image, and four data sets, namely, lithology, elevation, slop and aspect, wereused to calculate the CF values. The result of M-CF method is in agreement with field investigations and the accuracy of the method is satisfied. The method has a wide application to the susceptibility assessment of debris flow in the earthquake stricken areas.  相似文献   

3.
The Longchi area with the city of Dujiangyan, in the Sichuan province of China, is composed of Permian stone and diorites and Triassic sandstones and mudstones intercalated with slates. An abundance of loose co-seismic materials were present on the slopes after the May 12, 2008 Wenchuan earthquake, which in later years served as source material for rainfall-induced debris flows or shallow landslides. A total of 48 debris flows, all triggered by heavy rainfall on 13th August 20l0, are described in this paper. Field investigation, supported by remote sensing image interpretation, was conducted to interpret the co-seismic landslides in the debris flow gullies. Specific characteristics of the study area such as slope, aspect, elevation, channel gradient, lithology, and gully density were selected for the evaluation of debris flow susceptibility. A score was given to all the debris flow gullies based on the probability of debris flow occurrence for the selected factors. In order to get the contribution of the different factors, principal component analyses were applied. A comprehensive score was obtained for the 48 debris flow gullies which enabled us to make a susceptibility map for debris flows with three classes. Twenty-two gullies have a high susceptibility, twenty gullies show a moderate susceptibility and six gullies have a low susceptibility for debris flows.  相似文献   

4.
lINTRODUCTIONDebrisflowisoneofthesixprimarynaturalhaz-ards,whichinfluencesthedevelopmentofnationalso-cietyandeconomyinChina.Itsseverityissecondarytoflood,draught,earthquake,typhoon,butstrongerthanbiologicalhazards.Morethan3ooOodebrisflowcreeksarescatteredihthewholemountainousarea,andes-PeciallyconcentratedinsouthwestofChina.DebrisFlowInformationSystem(DFIS)operatedbytheInsti-tuteofMountainHazardsandEnvironmentoftheChi-neseAcademyofScienceshasalreadyestablishedadatabaseandcataloguec…  相似文献   

5.
Debris flow fan affects the river profile and landscape evolution.The propagation of multiple debris flows along a river can cause inundation and breaching risk,which can be exemplified by the Min River after the Wenchuan earthquake,Sichuan province,China.In this work,large flume tests were conducted to examine the interactions between debris flows and water current with the fan geometry,momentum,runout distance,deposited width,the relative water level upstream and dominated stress.The results reveal that stony flow commonly travels at a high speed and forms a long rectangle shape fan,while the muddy flow generally travels at a low speed and forms a fan-shaped depositional area.The stony flow can block a river even when the momentum is close to the water current;the muddy flow can block a river when the momentum is lower than that of water current.In case of complete river damming,the relative water level upstream indicates that the inundation risk from the muddy flow damming river would be higher than the inundation risk of stony flow.The diversion ratio of muddy flow decreases as damming ratio.Comparison of dimensionless numbers reveals that stony flow is dominated by grain collision stress combined with turbulent mixing stress,while the muddy flow is dominated by viscous shear stress over friction stress.The fan geometry,damming ratio,diversion ratio,and the dominated stress all together indicate that stony flow strongly interacts with water current while the muddy flow does not.The results can be helpful for understanding the physical interactions between water current and various debris flows,and debris flow dynamics at the channel confluence area.  相似文献   

6.
Critical rainfall assessment is a very important tool for hazard management of torrents and debris flows in mountainous areas. The Wenchuan Earthquake 2008 caused huge casualties and property damages in the earthquake-stricken area, which also generated large quantities of loose solid materials and increased occurrence probabilities of debris flows. There is an urgent need to quantify the critical rainfall distribution in the area so that better hazard management could be planned and if real time rainfall forecast is available, torrent and debris flow early-warning could be issued in advance. This study is based on 49-year observations （1954-2003） of up to 678 torrent and debris flow events. Detailed contour maps of 1 hour and 24 hour critical rainfalls have been generated （Due to the data limitation, there was insufficient 10 minute critical rainfall to make its contour map）. Generally, the contour maps from 1 hour and 24 hours have similar patterns. Three zones with low, medium and high critical rainfalls have been identified. The characteristics of the critical rainfall zones are linked with the local vegetation cover and land forms. Further studies and observations are needed to validate the finding and improve the contour maps.  相似文献   

7.
基于信息量模型和数据标准化的滑坡易发性评价   总被引：1，自引：0，他引：1  
本文以北川曲山-擂鼓片区为研究区,将坡度、坡向、高程、地层、距断层的距离、距水系的距离和距道路的距离作为该区域滑坡易发性评价因子。采用信息量模型计算了各项评价因子的信息量值,并运用4种标准化模型对信息量值进行标准化处理。各评价因子的权重由层次分析法（AHP）确定。在GIS中将权重值和各评价因子的标准化信息量值,进行叠加计算得到区域滑坡总信息量值,并基于自然断点法对其进行重分类,将研究区划分为极高易发区、高易发区、中易发区、低易发区和极低易发区5级易发区。将基于4种标准化模型和信息量模型得到的滑坡易发性评价结果进行了对比分析,结果表明：基于最值标准化信息量模型的滑坡易发性评价结果的ROC曲线下面积AUC值为0.807,高于其余模型的AUC值,说明最值标准化信息量模型的滑坡易发性评价效果最好。极高易发区面积占研究区面积的20.03%,离断层和水系较近,主要分布地层为寒武系、志留系和三迭系。研究结果可为区内滑坡风险评价和灾害防治提供参考。  相似文献   

8.
Landslide susceptibility maps(LSMs) play a vital role in assisting land use planning and risk mitigation. This study aims to optimize causative factors using logistic regression(LR) and an artificial neural network(ANN) to produce a LSM. The LSM is produced with 11 causative factors and then optimized using forward-stepwise LR(FSLR), ANN, and their combination(FSLR-ANN) until eight causative factors were found for each method. The ANN method produced superior validation results compared with LR. The ROC values for the training data set ranges between 0.8 and 0.9. On the other hand, validation with the percentage of landslide fall into LSM class high and very high, ANN method was higher(92.59%) than LR(82.12%). FSLR-ANN with nine causative factors gave the best validation results with respect to area under curve(AUC) values, and validation with the percentage of landslide fall into LSM class high and very high. In conclusion, ANN was found to be better than LR when producing LSMs. The best Optimization was combination of FSLR-ANN with nine causative factors and AUC success rate 0.847, predictive rate 0.844 and validation with landslide fall into high and very high class with 91.30%. It is an encouraging preliminary model towards a systematic introduction of FSLR-ANN model for optimization causative factors in landslide susceptibility assessment in the mountainous area of Ujung Loe Watershed.  相似文献   

9.
The data on the hillslope and channelized debris flows in the Shitou area of central Taiwan occurred during Typhoons Toraji and Nali in 2001 were applied in this paper. The geomorphic parameters, including the flow length, gully gradient, drainage area and form factor of the debris flows were determined by spatial analysis using a Geographic Information System （GIS） based on the data derived from field investigation, aerial photographs, and topographical maps. According to such determined geomorphic parameters, the threshold conditions and empirical equations, such as the relationship between the gully gradient and drainage area and that between gully length and drainage area and topographic parameter, are presented and used to distinguish the geomorphic characteristics between the channelized and hillslope debris flows.  相似文献   

10.
A probabilistic view of debris flow   总被引：1，自引：1，他引：0  
  相似文献   

11.
In August 2009,Typhoon Morakot brought a large amount of rainfall with both high intensity and long duration to a vast area of Taiwan.Unfortunately,this resulted in a catastrophic landslide in Hsiaolin Village,Taiwan.Meanwhile,large amounts of landslides were formed in the Jiaopu Stream watershed near the southeast part of the Hsiaolin Village.The Hsiaolin Village access road（Provincial Highway No.21 and Bridge No.8） was completely destroyed by the landslide and consequent debris flow.The major scope of this study is to apply a debris flow model to simulate the disaster caused by the debris flow that occurred in the Jiaopu Stream during Typhoon Morakot.According to the interviews with local residents,this study applied the destruction time of Bridge No.8 and Chen＇s house to verify the numerical debris flow model.By the spatial rainfall distributions information,the numerical simulations of the debris flow are conducted in two stages.In the first stage（before the landslide-dam failure）,the elevation of the debris flow and the corresponding potential damages toward residential properties were investigated.In the second stage（after the landslidedam failure）,comparisons of simulation results between the longitudinal and cross profiles of the Jiaopu Stream were performed using topographic maps and satellite imagery.In summary,applications of the adopted numerical debris flow model have shown positive impact on supporting better understanding of the occurrence and movement of debris flow processes.  相似文献   

12.
Slope debris flows in the Wenchuan Earthquake area   总被引：1，自引：0，他引：1  
Avalanches and landslides, induced by the Wenchuan Earthquake on May 12, 2008, resulted in a lot of disaggregated, solid material on slopes that could be readily mobilized as source material for debris flows. Rainstorms triggered numerous slope debris flows with great damage to highways and rivers over the subsequent two years. Slope debris flows (as opposed to channelized debris flows) are defined as phenomena in which high-concentration mixtures of debris and water flow down slopes for short distances to highways and river banks. Based on field investigations and measurements of 19 slope debris flows, their main characteristics and potential mitigation strategies were studied. High rainfall intensity is the main triggering factor. Critical rainfall intensities for simultaneous occurrence of single, several and numerous slope debris flow events were 20 mm/day, 30mm/day, and 90 mm/day, respectively. Field investigations also revealed that slope debris flows consist of high concentrations of cobbles, boulders and gravel. They are two-phase debris flows. The liquid phase plays the role of lubrication instead of transporting medium. Solid particles collide with each other and consume a lot of energy. The velocities of slope debris flows are very low, and their transport distances are only several tens of meters. Slope debris flows may be controlled by construction of drainage systems and by reforestation.  相似文献   

13.
不同机器学习预测滑坡易发性的建模过程及其不确定性有所差异, 另外如何有效识别滑坡易发性的主控因子意义重大。针对上述问题, 以支持向量机(support vector machine, 简称SVM)和随机森林(random forest, 简称RF)为例探讨了基于机器学习的滑坡易发性预测及其不确定性, 创新地提出了"权重均值法"来综合计算出更准确的滑坡主控因子。首先获取陕西省延长县滑坡编录和10类基础环境因子, 将因子频率比值作为SVM和RF的输入变量; 再将滑坡与随机选择的非滑坡样本划分为训练集和测试集, 用训练好的机器学习预测出滑坡易发性并制图; 最后用受试者工作曲线、均值和标准差等来评估建模不确定性, 并计算滑坡主控因子。结果表明: ①机器学习能有效预测出区域滑坡易发性, RF预测的滑坡易发性精度高于SVM, 而其不确定性低于SVM, 但两者的易发性分布规律整体相似; ②权重均值法计算出延长县滑坡主控因子依次是坡度、高程和岩性。实例分析和文献综述显示RF模型相较于其他机器学习模型属于可靠性较高的易发性模型。   相似文献   

14.
In the Wenchuan Earthquake area,many co-seismic landslides formed blocking-dams in debris flow channels. This blocking and bursting of landslide dams amplifies the debris flow scale and results in severe catastrophes. The catastrophic debris flow that occurred in Qipan gully(Wenchuan,Southwest China) on July 11,2013 was caused by intense rainfall and upstream cascading bursting of landslide dams. To gain an understanding of the processes of dam bursting and subsequent debris flow scale amplification effect,we attempted to estimate the bursting debris flow peak discharges along the main gully and analyzed the scale amplification process. The results showed that the antecedent and triggering rainfalls for 11 July debris flow event were 88.0 mm and 21.6 mm,respectively. The event highlights the fact that lower rainfall intensity can trigger debris flows after the earthquake. Calculations of the debris flow peak discharge showed that the peak discharges after the dams-bursting were 1.17–1.69 times greater than the upstream peak discharge. The peak discharge at the gully outlet reached 2553 m~3/s which was amplified by 4.76 times in comparison with the initial peak discharge in the upstream. To mitigate debris flow disasters,a new drainage channel with a trapezoidal V-shaped cross section was proposed. The characteristic lengths(h1 and h2) under optimal hydraulic conditions were calculated as 4.50 m and 0.90 m,respectively.  相似文献   

15.
In order to evaluate the danger of debris flow properly, eight factors were selected as the risk assessment indexes of the debris flow, namely the vertical slope, valley relative difference, hillside slope, area of basin, loose solid material reserves, the path length of sediment supply probability, silting and scouring derricking and vegetation coverage. The improved Analytic Hierarchy Process (AHP) method was used to obtain the weights of the factors; and the efficacy coefficient method was adopted to evaluate the risks of six typical debris flow gullies. According to the research, the improved AHP method not only avoids the subjectivity in the individual factor valuation by comparing two factors of each layer, but also makes the subsequent consistency check unnecessary.  相似文献   

16.
Large spoil tips from reconstruction works as a result of the Wenchuan Earthquake in China are new debris flow hazards to the human society. However, there is a lack of detailed comparative study on debris flow initiation in different spoil materials. This paper describes a series of tests and analyses on debris flow characteristics (initiation, scale and mechanism) at six sites with limestone and sandstone materials near the Dujiangyan area. Research shows the limestone spoil contains debris flow prone clay content with high concentration of montmorillonite (highly expandable). In addition, limestone spoil is of such a low permeability that water mainly concentrates in the upper surface layer. Those factors make it easy for the increase of pore water pressure, decline of internal friction and conhesion force, leading to the occurence of large debris flows. In contrast, the sandstone spoil is less problematic and causes no major debris flow threats. Based on our research on the mechanism, the“stereometric drainage”method is sucessfully applied to control limestone spoil debris flows.  相似文献   

17.
The upper Yangtze River region is one of the most frequent debris flow areas in China. The study area contains a cascade of six large hydropower stations located along the river with total capacity of more than 70 million kilowatts. The purpose of the study was to determine potential and dynamic differences in debris flow susceptibility and intensity with regard to seasonal monsoon events. We analyzed this region’s debris flow history by examining the effective peak acceleration of antecedent earthquakes, the impacts of antecedent droughts, the combined effects of earthquakes and droughts, with regard to topography, precipitation, and loose solid material conditions. Based on these factors, we developed a debris flow susceptibility map. Results indicate that the entire debris flow susceptibility area is 167,500 km2, of which 26,800 km2 falls within the high susceptibility area, with 60,900 km2 in medium and 79,800 km2 are in low susceptibility areas. Three of the six large hydropower stations are located within the areas with high risk of debris flows. The synthetic zonation map of debris flow susceptibility for the study area corresponds with both the investigation data and actual distribution of debris flows. The results of debris flow susceptibility provide base-line data for mitigating, assessing, controlling and monitoring of debris flows hazards.  相似文献   

18.
《山地科学学报》2020,17(8):1860-1873
At present,most researches on the critical rainfall threshold of debris flow initiation use a linear model obtained through regression.With relatively weak fault tolerance,this method not only ignores nonlinear effects but also is susceptible to singular noise samples,which makes it difficult to characterize the true quantization relationship of the rainfall threshold.Besides,the early warning threshold determined by statistical parameters is susceptible to negative samples(samples where no debris flow has occurred),which leads to uncertainty in the reliability of the early warning results by the regression curve.To overcome the above limitations,this study develops a data-driven multiobjective evolutionary optimization method that combines an artificial neural network(ANN) and a multiobjective evolutionary optimization implemented by particle swarm optimization(PSO).Firstly,the Pareto optimality method is used to represent the nonlinear and conflicting critical thresholds for the rainfall intensity I and the rainfall duration D.An ANN is used to construct a dual-target(dual-task) predictive surrogate model,and then a PSO-based multiobjective evolutionary optimization algorithm is applied to train the ANN and stochastically search the trained ANN for obtaining the Pareto front of the I-D surrogate prediction model,which is intended to overcome the limitations of the existing linear regression-based threshold methods.Finally,a double early warning curve model that can effectively control the false alarm rate and negative alarm rate of hazard warnings are proposed based on the decision space and target space maps.This study provides theoretical guidance for the early warning and forecasting of debris flows and has strong applicability.  相似文献   

19.
Accurate prediction on geological hazards can prevent disaster events in advance and greatly reduce property losses and life casualties.Glacial debris flows are the most serious hazards in southeastern Tibet in China due to their complexity in formation mechanism and the difficulty in prediction.Data collected from 102 glacier debris flow events from 31 gullies since 1970 and regional meteorological data from 1970 to 2019 in ParlungZangbo River Basin in southeastern Tibet were used for Artificial Neural Network(ANN)-based prediction of glacial debris flows.The formation mechanism of glacial debris flows in the ParlungZangbo Basin was systematically analyzed,and the calculations involving the meteorological data and disaster events were conducted by using the statistical methods and two layers fully connected neural networks.The occurrence probabilities and scales of glacial debris flows(small,medium,and large)were predicted,and promising results have been achieved.Through the proposed model calculations,a prediction accuracy of 78.33%was achieved for the scale of glacial debris flows in the study area.The prediction accuracy for both large-and medium-scale debris flows are higher than that for small-scale debris flows.The debris flow scale and the probability of occurrence increase with increasing rainfall and temperature.In addition,the K-fold cross-validation method was used to verify the reliability of the model.The average accuracy of the model calculated under this method is about 93.3%,which validates the proposed model.Practices have proved that the combination of ANN and disaster events can provide sound prediction on geological hazards under complex conditions.  相似文献   

20.
四川省小流域泥石流危险性评价   总被引：1，自引：0，他引：1  
泥石流危险性评价是泥石流防灾减灾的重要内容。本文以四川省为研究区,以DEM为数据源,通过提取水流方向,计算汇流累积量,实现四川省小流域划分。基于收集的已查明泥石流流域资料,分析了泥石流孕灾环境与成灾特点,选择流域高差、流域面积为指标,建立基于能量条件的潜势泥石流流域判识模型,对划分的小流域进行判识,识别出7798个小流域具备泥石流发生所需能量条件,面积为31.1×104 km2,占四川省总面积的64.18 %。进而建立了泥石流危险性评价指标体系和可拓物元模型,开展了小流域泥石流危险性评价,划分了危险度等级,得到中度、高度、极高危险区的小流域个数分别为1946、1725和1002个,面积分别为9.1×104、7.7×104和3.4×104 km2,中度以上危险区面积共20.2×104 km2,占四川省总面积的41.67%。最后对评价结果可靠性和各等级泥石流危险区在各地市级行政区、各大流域的分布进行了分析。其结果对促进泥石流判识与危险性评价理论,区域泥石流防灾减灾与山区可持续发展等具有重要的理论和现实意义。  相似文献   

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