Predictive GIS-Based Model of Rockfall Activity in Mountain Cliffs

Rockfall susceptibility has been analysed in mountain cliffs of the Cantabrian Range, North Spain. The main aim of this analysis has been to build a predictive model of rockfall activity from a low number of environmental and geological variables. The rockfall activity has been quantified in a GIS. The cartographic information used shows the spatial distribution of all the recent talus screes as well as their associated source areas in the rock-slopes. The area relation At/Ar (recent talus scree polygon/source basins) in the rock slopes has been used as the rockfall activity indicator. This relation has been validated in 50 pilot rock-slopes and compared with the relation number of recent rock fragments/source basin, obtained from field work. The environmental factors causing rockfall depend on the rock slope situation, and these are: altitude and sun radiation on the rock cliff. The geological factors considered are: lithology, relative position of the main discontinuities with respect to the topographic surface and two morphologic parameters: the roughness and slope gradient. A logistic regression analysis has been applied to a population of 442 limestone and quartzite rock cliffs. The dependent variable is the rockfall activity indicator, which allows the definition of two classes of rock cliff units: low and high activity. The independent variables are altitude, sun radiation (equinox radiation, summer solstice radiation, winter solstice radiation), slope roughness, slope gradient,anisotropy and lithology. Results suggest that it is possible tobuild a valid cartographic predictive model for rockfall activity in mountain rock cliffs from a limited number of easily obtainable variables. The method is especially applicable in massive rock slopes or in regions with uniform rock mass characteristics.     

Can flat-ramp-flat fault geometry be inferred from fold shape?: A comparison of kinematic and mechanical folds

The inference of fault geometry from suprajacent fold shape relies on consistent and verified forward models of fault-cored folds, e.g. suites of models with differing fault boundary conditions demonstrate the range of possible folding. Results of kinematic (fault-parallel flow) and mechanical (boundary element method) models are compared to ascertain differences in the way the two methods simulate flexure associated with slip along flat-ramp-flat geometry. These differences are assessed by systematically altering fault parameters in each model and observing subsequent changes in the suprajacent fold shapes. Differences between the kinematic and mechanical fault-fold relationships highlight the differences between the methods. Additionally, a laboratory fold is simulated to determine which method might best predict fault parameters from fold shape. Although kinematic folds do not fully capture the three-dimensional nature of geologic folds, mechanical models have non-unique fold-fault relationships. Predicting fault geometry from fold shape is best accomplished by a combination of the two methods.     

Theory and Method of Mineral Resource Prediction Based on Synthetic Information

Metallogenic prognosis of synthetic information uses the geological body and the miaeral resource body as a statistical unit to interpret synthetically the information of geology, geophysics, geo-chemistry and remote sensing from the evolution of geology and puts all the information into one entire system by drawing up digitalized interpretation maps of the synthetic information. On such basis, differ-ent grades and types of mineral resource prospecting models and predictive models of synthetic informa-tion can be established. Hence, a new integrated prediction system will be formed of metallogenic prog-nosis (qualitative prediction), mineral resources statistic prediction (determining targets) and mlaeral resources prediction (determining resources amount).     

Application of Weights of Evidence to Mineral Potential Mapping of Yujiacun Ore Field in Northwest Yunnan Province, China

The multivariate information conprehensive processing technique is especially important at present to the digital mineral prospecting. However, the GIS-based weights of evidence have provided us with powerful tool for the quantitative assessment of mineral resource potential. In this paper, the mineralization model is established, based on the achievements made by previous researchers, to mend such deficiencies ad few references on ore fields in Yujiacun, Yunnan Province and the shortage of quantitative prediction and assessment of mineral resources. In addition, the weights of evidence are used to make a systematic quantitative prediction and assessment of mineral resources there, so that 2 mineral prospecting target areas of grade Ⅰ and 8 mineral prospecting target areas of grade Ⅱ are delineated, providing the further mineral resource exploration with the basis for the selection of mineral deposits.     

中尺度自忆模式在强降水预报中的应用

根据大气自忆性原理提出的回溯时间积分格式应用于中尺度格点模式MM5,构建了中尺度自忆模式SMM5并做了短期强降水预报的实验.结果表明,SMM5模式与MM5模式相比,由于使用了多个时刻的场资料,预报精度有了明显的提高, SMM5预报的最大雨区的中心位置与降水量也比MM5更接近实际观测场.     

天气学和天气预报的研究进展

全面回顾了75年来中国科学院大气物理研究所科研人员在气团、锋面、梅雨、寒潮、阻高、副高、暴雨、高低空急流、亚澳季风区内涡旋和对流等现象的天气学研究进展及其在不同时期所取得的研究成果,总结了在短中期天气预报及短期气候预测领域在模式发展和改进以及在数值模拟等方面所取得的成就和进展.同时指出模式发展和预测在中国数值天气预报及短期气候预测方面所做出的贡献.     

ENSO动力学与预测

发生在热带太平洋地区的ENSO现象是海气相互作用的集中表现,是年际气候变化中的最强信号.由于它的发生会在全球许多地区引起严重的气候异常,极大地影响着这些地区的工农业生产和人民生活,因此,对ENSO的机理及其预测的研究一直是大气海洋界的一个热点研究课题.中国科学院大气物理研究所在ENSO的机理及其预测等方面进行了大量的研究,取得了许多研究成果.作者将对中国科学院大气物理研究所在这方面的一些研究成果进行回顾和介绍.     

热带气旋路径预报的MCE客观综合决策方法研究

采用MCE(Multi-Criteria Evaluation)方法，在台风路径客观综合预报方法研究与业务实验中，根据多家预报的主要结果进行综合评估分析，提出最佳客观综合预报结果以供决策者及预报员参照。取得初步结果：(1)对9711号台风进行了MCE客观综合决策方法的预报试验。结果表明，对于9711号台风生命史中几个关键点的预报，即登陆预报、台风转向北上预报及出海转向预报等以及全程预报，MCE方法取得较佳预报结果。(2)在综合平台上对近10年的疑难路径台风和2000年全年台风进行了MCE方法试验及多种预报结论的对比分析研究。MCE方法预报误差检验结果较好。(3)所提出的模拟预报员预报思维的联想智能模拟方法，以及可操作综合预警平台，为台风路径预报，包括分析、学习、回忆、对比、推理、联想直到形成综合预报结论提供了一个十分有用的工具。(4)讨论的自反馈函数对形成和推演多规则评估决策有一定的实用性。     

北极涛动对东亚夏季降水的预测意义

分析了春季北极涛动(AO)指数的变化对梅雨—Changma——Baiu带夏季降水年际变化的影响。对观测的东亚10个站的降水长序列资料(1899—1999年)，进行滤波处理，保留10年以下的年际时间尺度的变化，再进行相关分析。结果表明，近百年的5月北极涛动指数与10站夏季平均降水相关最高达—0．45，超过99％信度水平。当北极涛动偏强一个标准差时，整个长江中下游地区到日本南部一带，降水减少平均约8％左右。降水的这种变化与对流层东亚急流的变化密切相关：春季北极涛动强时，随后夏季急流位置通常偏北，雨带位置也北移，从而造成梅雨—Changma——Baiu带降水减少，反之亦然。较强的AO异常对降水的影响更明显，而较弱的AO与降水异常的对应关系并不显著。这对东亚夏季年际降水异常具有一定的预测意义。     

BP神经网络模型在重庆伏旱预测中的应用研究

采用气象要素定义伏旱指数，利用小波分析等方法分析重庆地区伏旱变化特征，最后采用BP神经网络模型对伏旱进行预测试验，结果表明，重庆伏旱变化具有明显的阶段性特征，而基于BP神经网络模型的伏旱预测模型预测效果良好，可以应用于实际预测。