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201.
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. 相似文献
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W. Andrew Marcus Carl J. Legleiter Richard J. Aspinall Joseph W. Boardman Robert L. Crabtree 《Geomorphology》2003,55(1-4):363
This article evaluates the potential of 1-m resolution, 128-band hyperspectral imagery for mapping in-stream habitats, depths, and woody debris in third- to fifth-order streams in the northern Yellowstone region. Maximum likelihood supervised classification using principal component images provided overall classification accuracies for in-stream habitats (glides, riffles, pools, and eddy drop zones) ranging from 69% for third-order streams to 86% for fifth-order streams. This scale dependency of classification accuracy was probably driven by the greater proportion of transitional boundary areas in the smaller streams. Multiple regressions of measured depths (y) versus principal component scores (x1, x2,…, xn) generated R2 values ranging from 67% for high-gradient riffles to 99% for glides in a fifth-order reach. R2 values were lower in third-order reaches, ranging from 28% for runs and glides to 94% for pools. The less accurate depth estimates obtained for smaller streams probably resulted from the relative increase in the number of mixed pixels, where a wide range of depths and surface turbulence occurred within a single pixel. Matched filter (MF) mapping of woody debris generated overall accuracies of 83% in the fifth-order Lamar River. Accuracy figures for the in-stream habitat and wood mapping may have been misleadingly low because the fine-resolution imagery captured fine-scale variations not mapped by field teams, which in turn generated false “misclassifications” when the image and field maps were compared.The use of high spatial resolution hyperspectral (HSRH) imagery for stream mapping is limited by the need for clear water to measure depth, by any tree cover obscuring the stream, and by the limited availability of airborne hyperspectral sensors. Nonetheless, the high accuracies achieved in northern Yellowstone streams indicate that HSRH imagery can be a powerful tool for watershed-wide mapping, monitoring, and modeling of streams. 相似文献
206.
滇西兰坪盆地北部发育了一类受逆冲推覆构造控制的浅成热液Cu—Ag—Pb-Zn矿化,形成了白秧坪、富隆厂、吴底厂、麻栗坪及金满、科登涧等大-中型矿床和矿点,并存在矿化分带。文章利用这些矿化脉体的流体包裹体和热液方解石的碳氧同位素组成资料,研究成矿流体与矿化分带的关系。结果表明,成矿流体主要属于NaCl-H2O成分体系,盐度ω(NaCleq)为2%~11%,形成温度为170~300℃,形成于1.8~3.8km深度内,这些相似性说明这类矿化的发生具有相似的流体性质和沉淀机制。热液方解石在δ^13C-δ^18O图解中呈近水平线展布的型式,指示流体源自地壳浅部的地下水系统,与海相灰岩等围岩作用形成了溶解碳以[HCO3^]-为主的成矿流体,流体与岩石的相互作用可能是成矿流体沉淀的主要机理。从西到东,流体包裹体的盐度-温度由高到低变化与矿化分带和逆冲推覆构造的根带→中带→锋带相配套,显示重力驱动流动可能是主要的流体流动机制。成矿流体在不同构造部位流动的通畅及流体.岩石系统的封闭-开放程度等流体流动性质与矿化发生的强度和规模有关,兰坪北部逆冲推覆构造中带的流体通畅地流动及沉淀时处于相对开放状态,有利于该区形成较大规模的浅成热液多金属矿化。 相似文献
207.
金沙江某水电站库区泥石流地质灾害研究 总被引:1,自引:0,他引:1
李进元 《中国地质灾害与防治学报》2003,14(3):44-49
金沙江是我国水能资源最为丰富的江河之一,但在金沙江上修建水库,泥石流是经常遇到的地质灾害问题。文章在详细调查了库区地层岩性、构造、滑坡的前提下,结合金沙江某水库区泥石流发育与降雨、地层岩性、构造、滑坡及地形地貌的关系深入探讨了库区泥石流的类型、规模、特征及发育阶段。研究表明:(1)本库区泥石流活动历史久远,泥石流地质灾害活跃,在部分泥石流地质灾害衰退的同时,更多的泥石流沟在逐步形成:(2)水库蓄水,减小了泥石流沟的比降,会在一定程度上降低泥石流的活动性及破坏能力;(3)泥石流对水库的影响主要为输送泥沙,造成水库淤积。 相似文献
208.
冯俊录 《中国地质灾害与防治学报》2003,14(3):136-137,141
北碚醪糟坪泥石流防治工程,在施工中使用了多工艺方法,泥石流前缘采用桩、粱、锚支挡工程,相互连接及帷幕灌浆,改变土质性能,加强稳定性,泥石流中段大胆采用碎石毛石重力坝,阻拦上部泥石流,加上盲沟连接碎石桩和重力坎,排泄地下水、地表水。为了防止泥石流上段北岸继续造成滑塌,在北岸进行护坡桩保护。后缘是根据彻底根治原则,用人工挖孔抗滑桩,桩上端与横粱相连,粱与锚桩连接,切断了泥石流物质来源。该泥石流是地表水和地下水不畅通而引起的,在泥石流中下部修建了盲沟网格,明渠修建在下部外围稳定的土体上,水渠沟沟相通,最后集中排泄到明渠中流走。该泥石流采用综合整治方法,大胆使用碎石桩毛石重力坎,这一工艺获得了理想效果。 相似文献
209.
晋祠泉断流与地下水资源保护关系 总被引:4,自引:0,他引:4
通过对晋祠泉域岩溶地下水水文地质条件的分析,阐述了晋泉形成机理和断流原因,认为晋泉断流是多种因素的综合效应。说明地下水资源保护是一项系统工程,应采取统一的、科学的、多层次的全面管理,才能有效地保护有限的地下水资源,唤醒人们在进行经济建设的同时,要注意保护我们赖以生存的地球环境。 相似文献
210.