四川省小流域泥石流危险性评价

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。     

InSAR在云南德钦县一中河泥石流物源汇集及失稳模式中的探究

针对传统方法难以定量描述大尺度泥石流形成机理的问题,提出一种联合SAR卫星影像相位信息和后向散射信息全面识别泥石流发育机制的方法,并使用该方法探究云南省德钦县一中河泥石流物源汇集及失稳模式.通过后向散射系数反演研究区土壤含水量的时空变化趋势,利用升降轨Sentinel-1 A数据获取坡表二维形变.结果表明,研究区土壤含...     

Prediction of debris-flow danger area by combining hydrological and inundation simulation methods

Debris flows have caused serious human casualties and economic losses in the regions strongly affected by the Ms8.0 Wenchuan earthquake of 2008. Debris flow mitigation and risk assessment is a key issue for reconstruction.The existing methods of inundation simulation are based on historical disasters and have no power of prediction.The rain-flood method can not yield detailed flow hydrograph and does not meet the need of inundation simulation. In this paper,the process of water flow was studied by using the Arc-SCS model combined with hydraulic method,and then the debris flow runoff process was calculated using the empirical formula combining the result from Arc-SCS.The peak discharge and runoff duration served as input of inundation simulation. Then,the dangerous area is predicted using kinematic wave method and Manning equation.Taking the debris flow in Huashiban gully in Beichuan County,Sichuan Province,China on 24 Sep.2008 as example,the peak discharge of water flow and debris flow were calculated as 35.52 m3·s-1 and 215.66 m3·s-,with error of 4.15%compared to the measured values.The simulated area of debris-flow deposition was 161,500 m2,vs.the measured area of 144,097 m2,in error of 81.75%.The simulated maximum depth was 12.3 m,consistent with the real maximum depth between 10 and 15 m according to the field survey.The minor error is mainly due to the flow impact on buildings and variations in cross-section configuration.The present methodology can be applied to predict debris flow magnitude and evaluate its risk in other watersheds inthe earthquake area.     

Effectiveness analysis of the prediction of regional debris flow susceptibility in post-earthquake and drought site

Debris-flow disasters occurred frequently after the Mw 8.0 Wenchuan earthquake on 12 May 2008 in Sichuan Province, China. Based on historical accounts of debris-flow disaster events, it found that debris flow occurrence is closely related to the impact of earthquakes and droughts, because earthquakedrought activities can increase the loose solid materials, which can transform into debris flows under the effect of rainstorms. Based on the analysis of historical earthquake activity(frequency, magnitude and location), drought indexes and the trend of climate change(amount of rainfall), a prediction method was established, and the regional debris flow susceptibility was predicted. Furthermore, in a debris flow-susceptible site, effective warning and monitoring are essential not only from an economicpoint of view but are also considered as a frontline approach to alleviate hazards. The advantages of the prediction and early monitoring include(1) the acquired results being sent to the central government for policy making;(2) lives and property in mountainous areas can be protected, such as the 570 residents in the Aizi valley, who evacuated successfully before debris flows in 2012;(3) guiding the government to identify the areas of disasters and the preparation for disaster prevention and mitigation, such as predicting disasters in high-risk areas in the period 2012-2017, helping the government to recognize the development trend of disasters;(4) the quantitative prediction of regional debris-flow susceptibility, such as after the Wenchuan earthquake, can promote scientific and sustainable development and socioeconomic planning in earthquake-struck areas.     

基于DEM的福建省小流域划分研究

以1∶10万的数字线划图为工作底图,在ARC/INFO软件环境下,采用空间内插法生成福建省的DEM。其在ARC/INFO软件的水文模块环境下,经过数据预处理、流向分析、汇流分析和流域识别等过程,最终自动提取1435个小流域。研究结果表明:在山区,流域界线基本与分水岭吻合,但在平坦地区由于等高线稀疏,加上福建海岸线非常曲折,海湾支离破碎,流域提取的结果不尽人意,流域界线需要人工进一步修正。基于DEM的流域的快速提取,大大节省了的人力、物力,从提取的效率和精度来看都是切实可行的。随着DEM的精度将不断提高,这种方法将为在全省范围内实现流域各自然要素空间组合特征的快速分析与站点观测数据的综合管理,以及流域信息的空间可视化浏览、查询、统计和流域水文模型的应用分析奠定了坚实的基础,从而推动了生态环境保护、生态环境建设等生态环境管理工作的实施。     

Artificial Neural Network-based prediction of glacial debris flows in the ParlungZangbo Basin,southeastern Tibetan Plateau,China

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.     

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.     

A catastrophic debris flow in the Wenchuan Earthquake area,July 2013: characteristics,formation, and risk reduction

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.     

广西荔浦石灰岩矿山地质环境保护与恢复治理

目前,矿山地质灾害主要表现在崩塌、滑坡、岩溶地面塌陷、泥石流等方面,对矿区进行地质灾害的预测并根据情况提出相应防治措施,能有效避免和减轻地质灾害造成的损失;同时也维护了矿区的正常作业和人民生命和财产安全。根据广西荔浦石灰岩矿山的地质环境条件,结合矿山地质环境问题的实地调查,在综合分析的基础上进行影响评估,并有针对性地提出了恢复治理措施。     

基于栅格最大值法的县域综合地质灾害建模

四川省地形高低悬殊, 岩性构造发育, 各类地质灾害频发, 开展地质灾害易发性评价具有重要意义。崩塌、泥石流属于广义上的滑坡, 以四川省丹巴县为例, 从考虑不同滑坡类别的区域性地质灾害易发性出发综合考虑崩塌、滑坡、泥石流的空间概率分布。基于ArcGIS通过高精度数字高程模型共选取高程、坡度等10个地质灾害关键控制因素, 采用信息量模型对综合地质灾害进行了易发性评价。最终通过ArcGIS的单元统计(Cell Statistics)功能实现多个栅格图层最大值法合成综合易发性, 进一步利用受试者工作特征曲线(ROC)验证单种滑坡类别易发性模型的精度。按照自然断点法将研究区划分为极低、低、中、高、极高易发区, 高易发区和极高易发区主要集中分布在章谷镇、太平桥乡以及甲居镇等地。研究结果证明信息量模型能对单类地质灾害进行评价, 栅格最大值法是获取综合易发性的一种有效评价方法。      

Analysis of runoff in ungauged mountain watersheds in Sichuan, China using kinematic-wave-based GIUH model

Floods are one of the most common natural hazards occurring all around the world. However, the knowledge of the origins of a food and its possible magnitude in a given region remains unclear yet. This lack of understanding is particularly acute in mountainous regions with large degrees in Sichuan Province, China, where runoff is seldom measured. The nature of streamflow in a region is related to the time and spatial distribution of rainfall quantity and watershed geomorphology. The geomorphologic characteristics are the channel network and surrounding landscape which transform the rainfall input into an output hydrograph at the outlet of the watershed. With the given geomorphologic properties of the watershed, theoretically the hydrological response function can be determined hydraulically without using any recorded data of past rainfall or runoff events. In this study, a kinematic-wave-based geomorphologic instantaneous unit hydrograph (KW-GIUH) model was adopted and verified to estimate runoff in ungauged areas. Two mountain watersheds, the Yingjing River watershed and Tianquan River watershed in Sichuan were selected as study sites. The geomorphologic factors of the two watersheds were obtained by using a digital elevation model (DEM) based on the topographic database obtained from the Shuttle Radar Topography Mission of US’s NASA. The tests of the model on the two watersheds were performed both at gauged and ungauged sites. Comparison between the simulated and observed hydrographs for a number of rainstorms at the gauged sites indicated the potential of the KW-GIUH model as a useful tool for runoff analysis in these regions. Moreover, to simulate possible concentrated rainstorms that could result in serious flooding in these areas, synthetic rainfall hyetographs were adopted as input to the KW-GIUH model to obtain the flow hydrographs at two ungauged sites for different return period conditions. Hydroeconomic analysis can be performed in the future to select the optimum design return period for determining the flood control work.     

降雨模式对震后泥石流起动模式影响的试验研究: 以九寨天堂沟为例

降雨过程中降雨强度的变化会影响土体渗透率及饱和过程, 从而改变土体的力学性质, 影响泥石流起动模式及破坏规模。为探究不同降雨模式对震后泥石流起动机制的影响, 自制了小比例模型槽, 结合可控雨型的降雨模拟系统, 进行了人工降雨诱发泥石流的室内模型试验; 基于不同降雨模式下泥石流的起动过程分析, 对坡体内部含水率和孔隙水压力的变化规律进行了研究。研究结果表明: 递增型降雨模式下泥石流发生突然, 呈整体滑坡转化为泥石流起动模式, 坡体破坏规模最大; 递减型降雨模式下表现为后退式溃散失稳起动模式; 均匀型降雨模式下则表现为溯源侵蚀起动模式; 中峰型降雨模式下以局部滑坡转化为泥石流起动模式; Ⅴ型降雨模式下则由坡面侵蚀加剧转化为泥石流启动模式, 破坏规模最小。研究结果可以为九寨沟地区泥石流的预报预警提供参考。      

基于地理信息系统的雷电业务系统

介绍了地理信息系统（GIS）在四川省雷电业务系统构建中的应用方法。四川省防雷中心在雷电监测新技术和新手段的基础上,将GIS技术与雷电潜势预报和短临预警技术有效的结合起来,构建了雷电业务应用系统。并通过对此系统在2008年“9．23”四川雷电天气过程中的应用分析,说明此系统可以准确地对未来12小时的雷电过程进行预报和未来1小时的雷电过程进行预警。     

基于地理信息系统的雷电业务系统

介绍了地理信息系统（GIG）在四川省雷电业务系统构建中的应用方法。四川省防雷中心在雷电监测新技术和新手段的基础上,将GIS技术与雷电潜势预报和短临预警技术有效的结合起来,构建了雷电业务应用系统。并通过对此系统在2,008年“9．23”四川雷电天气过程中的应用分析,说明此系统可以准确地对未来12小时的雷电过程进行预报和未来1小时的雷电过程进行预警。     

Annual precipitation gray forecast in disaster year of Chedaren debris flow

The Chedaren ravine belongs to high-prone areas of debris flow in Jilin Province,which threaten the local people's life and security seriously. The authors used the residual correction theory to amend the GM (1, 1) model and forecast annual precipitation in disaster year of the Chedaren ravine; it provides scientific foundation for early warning of debris flow disaster in the rainy season based on weather forecast. The prediction results show that annual precipitation is 724.7 mm in 2009; the region will probably occur large-scale debris flow during the rainy season.     

Comparison of different sampling strategies for debris flow susceptibility mapping: A case study using the centroids of the scarp area,flowing area and accumulation area of debris flow watersheds

The quality of debris flow susceptibility mapping varies with sampling strategies. This paper aims at comparing three sampling strategies and determining the optimal one to sample the debris flow watersheds. The three sampling strategies studied were the centroid of the scarp area(COSA), the centroid of the flowing area(COFA), and the centroid of the accumulation area(COAA) of debris flow watersheds. An inventory consisting of 150 debris flow watersheds and 12 conditioning factors were prepared for research. Firstly, the information gain ratio(IGR) method was used to analyze the predictive ability of the conditioning factors. Subsequently, 12 conditioning factors were involved in the modeling of artificial neural network(ANN), random forest(RF) and support vector machine(SVM). Then, the receiver operating characteristic curves(ROC) and the area under curves(AUC) were used to evaluate the model performance. Finally, a scoring system was used to score the quality of the debris flow susceptibility maps. Samples obtained from the accumulation area have the strongest predictive ability and can make the models achieve the best performance. The AUC values corresponding to the best model performance on the validation dataset were 0.861, 0.804 and 0.856 for SVM, ANN and RF respectively. The sampling strategy of the centroid of the scarp area is optimal with the highest quality of debris flow susceptibility maps having scores of 373470, 393241 and 362485 for SVM, ANN and RF respectively.     

小流域山洪灾害危险性分析之降雨指标选取的初步研究

降雨是诱发山洪灾害的直接动力和激发条件,是山洪灾害危险性分析中不可或缺的重要指标。对于不同的研究区,不同频次和历时的降雨对山洪灾害的影响不同,危险性分析所选取的降雨指标也可能不同。本文基于1:5万小流域数据、历史山洪灾害空间分布数据和暴雨图集资料,以江西省婺源县小流域为例,采用相关分析法对初步选取的24个降雨指标进行相关性分析,筛选出相关性不强的降雨指标;利用GIS技术和基于局部Getis-Ord Gi*算法的优化热点分析工具对历史山洪灾害点进行空间聚类分析,获得研究区每个小流域山洪灾害危险度的估值,该值能够较好地反映小流域山洪灾害危险性的空间分布;通过地理探测器模型中的因子探测器和交互探测器对已筛选出的降雨指标和小流域山洪灾害危险度进行综合探测分析,从而获取对该研究区小流域山洪灾害危险性影响较大的降雨指标,即100年一遇最大6 h降雨和100年一遇最大24 h降雨。本文研究对小流域山洪灾害危险性分析降雨指标的定量选取具有参考和指导意义。     

Development of a region-partitioning method for debris flow susceptibility mapping

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.     

Debris flow hazard assessment using set pair analysis models: Take Beichuan county as an example

Assessment of debris flow hazards is important for developing measures to mitigate the loss of life and property and to minimize environmental damage. Two modified uncertainty models, Set Pair Analysis （SPA） and modified Set Pair Analysis （mSPA）, were suggested to assess the regional debris flow hazard. A ease study was conducted in seven towns of the Beichuan county, Sichuan Province, China, to test and compare the application of these two models in debris flow hazard assessment. The results showed that mSPA only can fit for value-variables, but not for non value-variable assessment indexes, Furthermore, as for a given assessment index xi, mSPA only considers two cases, namely, when grade value increases with xi and when grade value decreases with xi. Thus, mSPA can not be used for debris flow hazard assessment but SPA is credible for the assessment because there are no limitations when using SPA model to assess the debris flow hazard. Therefore, in this study SPA is proposed for assessing debris flow hazard.     

山东省典型地区地质灾害野外科学观测效果初探

重点选取山东省具有代表性的典型地质灾害易发区：济南市历城区阁老滑坡、青岛崂山区青山滑坡以及临沂市城区岩溶塌陷易发区,进行地质灾害野外科学观测和预警预报研究,并提出下一步研究方向,以期提高山东省预警预报的可信度和准确度,并将其作为地质灾害自动化观测的试验点和示范点在全省推广应用。