A Regional-Scale Method of Forecasting Debris Flow Events Based on Water-Soil Coupling Mechanism   总被引：1，自引：0，他引：1  

ZHANG Shao-jie  WEI Fang-qiang  LIU Dun-long  YANG Hong-juan  JIANG Yu-hong 《山地科学学报》2014,(6):1531-1542

A debris flow forecast model based on a water-soil coupling mechanism that takes the debrisflow watershed as a basic forecast unit was established here for the prediction of disasters at the watershed scale.This was achieved through advances in our understanding of the formation mechanism of debris flow.To expand the applicable spatial scale of this forecasting model,a method of identifying potential debris flow watersheds was used to locate areas vulnerable to debris flow within a forecast region.Using these watersheds as forecasting units and a prediction method based on the water-soil coupling mechanism,a new forecasting method of debris flow at the regional scale was established.In order to test the prediction ability of this new forecasting method,the Sichuan province,China was selected as a study zone and the large-scale debris flow disasters attributable to heavy rainfall in this region on July 9,2013 were taken as the study case.According to debris flow disaster data on July 9,2013 which were provided by the geo-environmental monitoring station of Sichuan province,there were 252 watersheds in which debris flow events actually occurred.The current model predicted that 265 watersheds were likely to experience a debris flow event.Among these,43 towns including 204 debrisflow watersheds were successfully forecasted and 24 towns including 48 watersheds failed.The false prediction rate and failure prediction rate of thisforecast model were 23% and 19%,respectively.The results show that this method is more accurate and more applicable than traditional methods.  相似文献   

基于数值模拟的暴雨泥石流暴发频率计算模型     

黄勋  唐川  周伟 《工程地质学报》2014,22(6):1271-1278

在缺失可靠降雨数据的地区,为解决泥石流暴发频率这一现实问题,从泥石流形成机理出发,由泥石流堆积特征反演形成条件,构建了基于数值模拟的泥石流暴发频率计算模型。该模型利用泥石流固体物质量估算模型和流域洪水流量推算模型,确定固体物质量、洪水流量、泥沙体积浓度后,通过FLO-2D流体模型计算得到与实际情况最符合的模拟情景,即可反推出已发泥石流事件的暴发频率。并以7 4石棉县马颈子沟和熊家沟泥石流为例,计算出两处泥石流的暴发频率皆为100年一遇,案例研究表明,该模型具备定量确定泥石流暴发频率的能力,对于泥石流预警预报和防灾减灾具有较强的理论和实践意义。  相似文献   

A tunnel section through a prograding Namurian (Arnsbergian,E2a) delta,in the western Bowland fells,north Lancashire     

Eric W. Johnson 《Geological Journal》1981,16(2):93-110

The Wyresdale Tunnel was driven through Roeburndale Grit Group sediments in the western Bowland Fells. An Arnsbergian age for the strata is confirmed in a palynological study. The tunnel provided a section through a prograding delta front sequence, and proved the Roeburndale Grit Group to be much thicker than previously recorded. Syndepositional instability within the deltaic sediments is illustrated by slumps and debris slides. A comparison is made with modern deltas. It is suggested that the regional variation in sediment thickness is tectonically controlled.  相似文献   

Contrasting sediment gravity flow processes in the late Llandovery,Rhuddnant Grits turbidite system,Welsh Basin     

Chris J. Clayton 《Geological Journal》1994,29(2):167-181

The Rhuddnant Grits turbidite system was deposited within an elongate, fault-bounded trough in the late Llandovery (Telychian) Welsh Basin. Two groups of sandstones are identified within the system: high-matrix sandstones and laminated sandstones. The high-matrix sandstones are medium to very thick bedded, fine to very coarse-grained muddy sandstones. The high-matrix sandstone beds are almost entirely structureless and have several features indicative of deposition from high density turbidity currents, probably undergoing late stage debris flow behaviour (e.g. grain size discontinuities, inverse grading, floating clasts). The laminated sandstones are thin to very thin bedded, fine-grained and have a distinctive mud/silt lamination. Tractional structures and convolution are common in these beds. They were probably deposited by slow moving, dilute turbidity currents. Dissimilar palaeocurrent vectors and estimates of flow properties from the two types of sandstone support the contrasting nature of the depositing flows. A coarsening and thickening upwards trend is identified in the laminated sandstones of the Rhuddnant Grits Formation. This trend is not reflected in the high-matrix sandstone beds. Although the high-matrix sandstones appear in packets or groups within the laminated sandstone background, they were otherwise deposited in an entirely random manner throughout the exposed system. This may suggest that the two types of sandstone are the result of different triggering mechanisms at source, or of contrasting flow properties developed early in the flow histories.  相似文献   

Multi-hazard susceptibility mapping based on Convolutional Neural Networks     

《地学前缘(英文版)》2022,13(5):101425

Multi-hazard susceptibility prediction is an important component of disasters risk management plan. An effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their interactions. However, with the rapid development of artificial intelligence technology, multi-hazard susceptibility prediction techniques based on machine learning has encountered a huge bottleneck. In order to effectively solve this problem, this study proposes a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks (CNN). First, we use historical flash flood, debris flow and landslide locations based on Google Earth images, extensive field surveys, topography, hydrology, and environmental data sets to train and validate the proposed CNN method. Next, the proposed CNN method is assessed in comparison to conventional logistic regression and k-nearest neighbor methods using several objective criteria, i.e., coefficient of determination, overall accuracy, mean absolute error and the root mean square error. Experimental results show that the CNN method outperforms the conventional machine learning algorithms in predicting probability of flash floods, debris flows and landslides. Finally, the susceptibility maps of the three hazards based on CNN are combined to create a multi-hazard susceptibility map. It can be observed from the map that 62.43% of the study area are prone to hazards, while 37.57% of the study area are harmless. In hazard-prone areas, 16.14%, 4.94% and 30.66% of the study area are susceptible to flash floods, debris flows and landslides, respectively. In terms of concurrent hazards, 0.28%, 7.11% and 3.13% of the study area are susceptible to the joint occurrence of flash floods and debris flow, debris flow and landslides, and flash floods and landslides, respectively, whereas, 0.18% of the study area is subject to all the three hazards. The results of this study can benefit engineers, disaster managers and local government officials involved in sustainable land management and disaster risk mitigation.  相似文献