日本俯冲带应力产生与传播的数值模拟

用三维有限元模拟了日本地冲带，分析了板块推力、板块拉力、动态闭锁断层和解耦板间地震对上覆板块内部应力状态的贡献，表明大洋板块推力是海沟。岛弧地区挤压应力的主要来源，这种应力仅有小部分传播到上覆板块内部，软流圈的蠕变能促进这个应力传播过程使岛弧区的应力增大，由密度差异引起的板块拉力产生了分散的挤压应力和拉张应力。断层闭锁导致应力局部集中，板间地震的断层错动只对破裂附近小范围的应力状态产生影响     

Environmental influences on landslide activity: Almora Bypass,Kumaun Lesser Himalaya

Landslides are self-organizing and self-referenced systems. The conditions which lead to their emergence along Himalayan highways are not the same as those which govern their subsequent evolution. Landslides originate at sites which differ from average conditions by having significantly higher, steeper roadcuts, carved into steeper hillsides, with more finely bedded but less steeply dipping rocks, and fewer trees upslope. These variables do not correlate with measures of landslide size. Landslide morphometric variables correlate with other landslide variables and with few external factors. The system exhibits independence (autopoiesis) from its environment. Additionally, landslides dominated by rock-mechanical processes tend to produce lower angle outfalls from higher, north-facing, roadcuts than those dominated by soil-mechanical processes which are associated with greater depths of below-soil regolith. However, the outfall volumes produced by the landslides of different type are similar. These findings are generated from statistical (correlation/T-test/stepwise discriminant) analyses of data produced by a field survey of average environmental conditions, and the morphometry and environmental contexts of 88 landslides, on 7.6 km of the Almora Bypass.     

滑坡灾害预测分区的计算机制图

本文在滑坡灾害预测分区的信息模型基础上,重点讨论了灾害预测的计算机制图化的主要过程:因素的数值化,单元边界的确定和彩色图件的绘制。运用中国地质大学计算机系开发的Mapcad系统,在Mv/10000计算机上较好地处理了不规则图幅边界的自然裁剪,不规则单元的输入,以及彩色图件的绘制等问题。     

Potential nitrate pollution of groundwater in Germany: A supraregional differentiated model

Implemented on behalf of the Federal Ministry for Research and Technology (BMFT), a model is developed to trace the nutrient flow of nitrate in the soil and the groundwater on a supraregional scale. Research work is intended to indicate regionally differentiated hazardous potentials and thereby provide a basis for recommending comprehensive measures to protect groundwater in Germany. The adaption of the model to the hydrogeological and agricultural conditions of other states is possible in principle. This article focuses on the hydrogeological model parts. A high nitrate pollution of groundwater can be expected in all regions with intensive agricultural use of the topsoil. In particular, groundwater in solid rock areas is susceptible to nitrate pollution. There a rapid groundwater turnover and thus a short residence time for the groundwater in the aquifer is typical. Oxidizing aquifer conditions usually prevail in solid rock aquifers, preventing nitrate degradation. In many loose rock areas, in contrast, the groundwater has a low flow velocity and a long residence time in the aquifer. Because of a lack of free oxygen, a complete degradation of nitrate can occur, as long as iron sulfide compounds and/or organic carbon are available in the aquifer. A more detailed presentation of the whole research work is given in Wendland et al. (1993).     

滑坡破坏时间预报新理论探讨

本文概述了当前滑坡破坏时间预报的研究水平和现状。为了完善滑坡预报方法和提高滑坡预报水平,作者从滑坡破坏的基本概念入手,提出了一种滑坡破坏时间预报的新理论,推导和确定了预报标准,比较科学地建立了预报参数,并具体地探讨了各阶段预报的预报策略及其分析处理方法。同时,还展望了滑坡动力反应及其应用研究的广阔前景。     

土质滑坡体破坏的突变模型

本文运用突变理论，分析了土质坡体破坏的两种方式:突变式破坏和渐变式破坏，建立了相应的在突变模型，从理论上解释了高速滑坡与低速滑坡的产生根源。对于受水文条件诱发的滑坡，提出了相应的判别准则。     

Landslide identification using machine learning

Landslide identification is critical for risk assessment and mitigation.This paper proposes a novel machinelearning and deep-learning method to identify natural-terrain landslides using integrated geodatabases.First,landslide-related data are compiled,including topographic data,geological data and rainfall-related data.Then,three integrated geodatabases are established;namely,Recent Landslide Database(Rec LD),Relict Landslide Database(Rel LD)and Joint Landslide Database(JLD).After that,five machine learning and deep learning algorithms,including logistic regression(LR),support vector machine(SVM),random forest(RF),boosting methods and convolutional neural network(CNN),are utilized and evaluated on each database.A case study in Lantau,Hong Kong,is conducted to demonstrate the application of the proposed method.From the results of the case study,CNN achieves an identification accuracy of 92.5%on Rec LD,and outperforms other algorithms due to its strengths in feature extraction and multi dimensional data processing.Boosting methods come second in terms of accuracy,followed by RF,LR and SVM.By using machine learning and deep learning techniques,the proposed landslide identification method shows outstanding robustness and great potential in tackling the landslide identification problem.     

北部湾环流和沉积物输运的数值模拟

研究环流和沉积物输运对北部湾的环境保护和资源开发十分重要。本文使用区域海洋模型（ROMS）,研究了北部湾海域的季节环流、沉积物输运以及长期的地形演变过程。展示了湾内冬季和夏季都存在逆时针环流,冬季的风生环流比夏季强的特征。悬沙浓度较大值主要分布在琼州海峡、海南岛西侧海域,以及越南沿岸、雷州半岛沿岸等近岸地区。沉积物在琼州海峡附近表现为在冬季由东向西输运,夏季则相反;在琼州海峡西口处,沉积物全年以西向输运为主。结果显示,北部湾内沉积物输运主要由潮流引起的再悬浮控制。侵蚀和淤积的分布模式为：（1）湾内大部分区域侵蚀淤积不明显,（2）琼州海峡两侧口门附近淤积比较明显,（3）琼州海峡内深槽侵蚀严重,（4）海南岛西侧海域存在侵蚀和淤积交替发生区域。     

新疆阜康市新世纪煤矿地质灾害危险性预测评估研究

预测评估是指对工程建设场地可能危及工程建设安全,对邻近地区可能引发和加剧工程设施遭受地质灾害的危险性做出评估。依据工程项目类型、规模,预测工程项目在建设过程中和建设后,对地质环境的改变及影响,评价是否会引发或加剧对本工程建设有危害的地质灾害。     

基于小波变换的SA误差建模与预报

运用小波分析方法对GPS单点动态定位误差进行分解,提出了基于小波变换的信号去噪与粗差的定位和剔除方法。将时间序列分析方法用于SA误差建模,提出了基于小波变换的SA误差建模及预报方法,并通过实例验证了方法的正确性