斜坡失稳时间的协同预测模型

斜坡岩体由小变形到大变形乃至滑坡的发生，实质上是由组成斜坡的各子系统协同作用的结果．将协同学引入斜坡的稳定性预测评价中，并提出了一种新的斜坡失稳时间预测模型──协同预测模型．经实例检验，该模型预测精度较高，可用于滑坡的短期或临滑预报．     

综合气体地球化学测量

本文在综合大量资料的基础上,总结了气体地球化学的发展历史,对有关综合气体测量在发展过程中出现的一些术语,阐述了一点浅见,介绍了综合气体测量的采样方法、理论依据,提出了综合气体测量的发展方向。     

泥炭档案气候变化重建的定量模型

泥炭档案气候变化重建的定量模型＊陶发祥洪业汤（中国科学院地球化学研究所，贵阳５５０００２）李汉鼎冷雪天（东北师范大学地理系，长春１３００２４）关键词泥炭档案纤维素稳定同位素气候变化定量模型用泥炭档案定量重建大气ＣＯ２浓度的研究已取得重要进展［１］，但...     

APPROACH TO KARST SOLUTION PROCESS RESPONSES ON CLIMATE

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Application of discovery process models in estimating petroleum resources at the play level in China

Discovery process modeling has gained wide acceptance in the Chinese exploration community. In recent years, a variety of discovery process models have been applied to the prediction of undiscovered petroleum resources at the play level in sedimentary basins in China. However, challenging problems have been encountered, particularly when one method alone has been applied to small plays in nonmarine sedimentary basins or in plays with an unusual order of discovery wells. This paper presents results gotten by using the lognormal discovery process model of the Geological Survey of Canada and the geoanchored method for three petroleum plays in basins with different geologic settings. Although the predicted shapes of the parentsize distributions which use these two models, were not always similar, the expected values of the total resources and the number of fields (pools) to be discovered are comparable. The combined use of two discovery process models in the same play compensates for the weaknesses in one method compared with the other and vice versa. Thus, more reliable estimates are the result.     

秦岭巴山地区高陵─达县重磁剖面初步解释

高陵－达县剖面位于秦岭中段，斜跨中朝准地台、秦岭褶皱系、扬子准地台三大构造单元。在研究剖面实磁场特征的基础上，综合地质、物性、省内及邻省深部物探资料，建立了剖面地质－地球物理模型，依此对剖面通过地段的地壳结构、断裂带深部特征、三大构造单元的深部格架进行了解释推断。     

隧道开挖模拟计算中的模型识别方法初探

介绍了利用隧道施工的位移量测信息来选择计算模型的原理和方法。应用实例表明，本文所提出的方法有较好的应用前景。     

The identifiability of parameters in a water quality model of the Biebrza River, Poland

The identifiability of model parameters of a steady state water quality model of the Biebrza River and the resulting variation in model results was examined by applying the Monte Carlo method which combines calibration, identifiability analysis, uncertainty analysis, and sensitivity analysis. The water quality model simulates the steady state concentration profiles of chloride, phosphate, ammonium, and nitrate as a function of distance along a river. The water quality model with the best combination of parameter values simulates the observed concentrations very well. However, the range of possible modelled concentrations obtained for other more or less equally eligible combinations of parameter values is rather wide. This range in model outcomes reflects possible errors in the model parameters. Discrepancies between the range in model outcomes and the validation data set are only caused by errors in model structure, or (measurement) errors in boundary conditions or input variables. In this sense the validation procedure is a test of model capability, where the effects of calibration errors are filtered out. It is concluded that, despite some slight deviations between model outcome and observations, the model is successful in simulating the spatial pattern of nutrient concentrations in the Biebrza River.     

The separation of the influence of nutrients and climate on the varve time-series of baldeggersee, Switzerland

The varve data-set from a freeze-core taken in the deepest part of Baldeggersee was subjected to different multivariate statistical analyses in order to estimate the amount of variance in the varve thickness measures explicable by past climate and by the trophic state of the lake. A comparison of two different time-periods (1902 to1992 versus 1920 to 1980) revealed that the lake restoration programme since 1982 has had a significant impact on the formation of the seasonal layers. Results of the partitioning of the variance in the varve thickness measures showed that about two thirds of the variance are unexplained by a climate and trophic state model and that trophic state explains 6%, whereas climate accounts for about 28% of the variance before the effect of lake restoration had a strong impact on the varves. Among the climate parameters the amount of annual precipitation is a strong predictor for explaining the thickness of both dark layer and total couplet thickness, whereas summer precipitation is important for the thickness of the light layer.     

GPS Ambiguity Resolution: Impact of Time Correlation,Cross-Correlation and Satellite Elevation Dependence

In this contribution we discuss the geometry-free GPS single baseline model and show how the least-squares ambiguities are affected by changes in the stochastic model. We particularly pay attention to the effect of time correlation, cross-correlation and satellite elevation dependence. We also differentiate between the impact on the location of the ambiguity search space and the impact on the size and shape of the search space. The analysis is carried out for both the model in which the ionospheric delays are assumed absent, and for the model in which they are assumed present. The former model is applicable to short baselines only.