地磁1年周期变化的响应函数

用通日月均值减去夜均值计算的月均值资料和Ｓｏｍｐｉ谱分析法分析了１４个台站的北向分量１年周期变化的振幅向相位，时段为１９８４－１９８８年。分析结果显示用Ｐ＾０ｎ（ｄｎｄ＝１，…，６）复合模式的估算的Ｃ值较合理。各台的Ｃ值比较一致。     

盖县─析木城地区盖县亚岩群的划分与对比

阐述了盖县亚岩群建立的依据。将盖县亚岩群划分为3个岩组（汤家沟岩组、江还山岩组和太平岭岩组）6个岩性段。在讨论了各岩组、岩段基本岩性特征基础上进行了区域对比。     

利用相关分析划分重力异常

本文从理论上对相关分析法区分重力异常的可行性进行了论述，并从一元线性回归方程着手，对大地水准面上的重力值与相应的地形高程作了相关分析，通过分析，认为在区域性小比例主均衡补偿基本完善的条件下，重力值与高程有极好的线性相关关系；当计算窗口较大时，地下的局部不均匀体，不足以破坏重力值与高程的相头发一，所以，在实际工作中，利用相关分析处理重力资料的叠加场，可以收到较好的效果，且方法简单易行。     

膨胀土判别与分类的灰关联分析法

基于灰色系统理论，给出一种用于膨胀土判别与分类的新方法—灰关联分析法。实际算例表明，该法具有简单方便、结果客观可靠等优点。     

A Study on Sequence Stratigraphy of Mesoproterozoic and Neoproterozoic in Southern North China Platform

INTRODUCTIONThestrataofMesoprotCrozoicandNeoproterozoicaredevelopedcompletelyinthesouthpartoftheNorthetnaplatformandconsistofthreesystems,inasCendingorder,Jixiaulan,QingbaikouanandSlman.BasedonadetailedinvestigationontheolltcropandthecomprehenSiveanalysis,wediscussthecharaCterofsequencestratigraphyandthecorrelationoftheMemo--Neoproterozoicinthearea.FnThRrsor~unCrsANDPARA~unCrsMeSO--NooprotffezoicRadonalfortigraphyThesouthernpartofNorthChinaplatformherereferstotheareasincluding…     

海南同安岭-牛腊岭火山地层划分与对比

将同安岭—牛腊岭火山地层划分为六罗村组、汤他大岭组、岭壳村组，总厚度达５４２９ｍ。六罗村组下部以玄武安山质火山岩为主，上部为流纹质火山碎屑岩、熔岩；汤他大岭组主要为英安岩类火山岩，岭壳村组为流纹岩类的岩石，构成２个喷发旋回。根据同位素年龄，确定火山岩的时代为早白垩世，与海南岛下白垩统鹿母湾组为同期产物，相当于我国东南沿海白垩纪火山岩。     

一种基于二次灰关联分析的数列预测法

数列预测一直是评价决策中最常见而又信于把握的问题之一。本文在总结现有预测方法的基础上，结合前铛预报思想和灰色预测理论，依据数据求同原则，提出了运用二次灰关联分析，建立组合模型的预测方法，该方法易于计算机实现，并已实际应用于油气储量预测研究中。     

RILL EROSION PROCESS ON STEEP SLOPE LAND OF THE LOESS PLATEAU

IntheLoessPlateau,alongtheslopelengthfromthetoptothebottom,soilerosionischaracterizedbyobviousverticalzonaldivision,thatis,sheeterosionzone,sheeterosionandrillerosionzone,rillerosionandshallowgullyerosionzoneandgullyerosionzone.Inthesheetandrillero..sionzone,rillerosionamounttakesup70%ofthetotalsoilloss[TANGKenetal.,1983,ZHENGFenlietal.,19871;intherillandshallowgullyerosionzone,rillerosionamountaccountsfor30--40%ofthetotalsoilloss.Sorillerosionisamajorerosionpatternonsteepslopeland.Riller…     

Estimation of groundwater evaporation and salt flux from Owens Lake, California, USA

Groundwater evaporation and subsequent precipitation of soluble salts at Owens Lake in eastern California have created one of the single largest sources of airborne dust in the USA, yet the evaporation and salt flux have not been fully quantified. In this study, we compare eddy correlation, microlysimeters and solute profiling methods to determine their validity and sensitivity in playa environments. These techniques are often used to estimate evaporative losses, yet have not been critically compared at one field site to judge their relative effectiveness and accuracy. Results suggest that eddy correlation methods are the most widely applicable for the variety of conditions found on large playa lakes. Chloride profiling is shown to be highly sensitive to thermal and density-driven fluxes in the near surface and, as a result, appears to underestimate yearly groundwater evaporation. Yearly mean groundwater evaporation from the playa surface estimated from the three study areas was found to range from 88 to 104 mm year⁻¹, whereas mean evaporation from the brine-covered areas was 872 mm year⁻¹. Uncertainties on these mean rates were estimated to be ±25%, based on comparisons between eddy correlation and lysimeter estimates. On a yearly basis, evaporation accounts for approximately 47 × 10⁶ m³ of water loss from the playa surface and open-water areas of the lake. Over the playa area, as much as 7.5 × 10⁸ kg (7.5 × 10⁵ t) of salt are annually concentrated by evaporation at or near the playa surface, much of which appears to be lost during dust storms in area.     

A bivariate meta-Gaussian density for use in hydrology

Convenient bivariate densities found in the literature are often unsuitable for modeling hydrologic variates. They either constrain the range of association between variates, or fix the form of the marginal distributions. The bivariate meta-Gaussian density is constructed by embedding the normal quantile transform of each variate into the Gaussian law. The density can represent a full range of association between variates and admits arbitrarily specified marginal distributions. Modeling and estimation can be decomposed into i) independent analyses of the marginal distributions, and ii) investigation of the dependence structure. Both statistical and judgmental estimation procedures are possible. Some comparisons to recent applications of bivariate densities in the hydrologic literature motivate and illustrate the model.