黑龙江省与呼伦贝尔盟土地类型的划分及其分布规律

本文就土地研究的几个主要概念,即土地、土地分类、土地分级作了简要讨论,并结合黑龙江省及呼伦贝尔盟的具体条件,对为农、林、牧业服务的土地分类原则进行了初步探讨,还拟订了该区土地分级系统——土地类和土地型,及适合于大比例尺制图的土地组。在此基础上,将全区分为18个土地类、71个土地型。文章还从水平带性、垂直带性和土地结构三个方面,介绍了该区土地类型分布的一般规律。     

中国大陆第四纪地壳运动时程

本文从中国大陆有代表性的青藏高原、黄土高原、三峡地区着手,进行了新构造运动剖析。并结合全国火山活动期次,总结出中国大陆第四纪地壳运动的时程变化。从而为进一步探讨新构造运动特点和规律,为国民经济建设及人类生存环境提供了一定的地质背景资料。     

冀西北长城纪宣龙式铁矿层中微体植物化石的发现及其意义

本文研究的是笔者等在冀西北长城系串岭沟组宣龙式铁矿层中发现的微体植物化石,这些化石都保存在铁质叠层石(肾状赤铁矿)和铁质核形石(鲕状赤铁矿)的基本层中。微化石以丝状体为主,部分为球状体。归属于原核生物蓝藻门颤藻科的两个属和色球藻科的一个属。化石层同位素年龄约在1800—1757Ma。这些化石与北美冈弗林特组微化石比较,既有些相似,又有些区别。该化石的发现为研究铁矿的成因,指示沉积环境及层位对比都很有意义。     

De nouveaux éléments structuraux du complexe aquifère profond du bassin du Rharb (Maroc) : implications hydrogéologiques

The Rharb basin is located in northwestern Morocco. It is a part of one of the most important hydrogeological basins of Morocco, and extends over some 4000 km². The nature of its Plio-Quaternary sedimentary fill and its structural and palaeoenvironmental contexts are reflected by great variations in aerial and temporal facies distribution. This distribution, in turn, is a direct cause of the observed complexity in the geometry of potentially water-bearing beds. In the present work, we present an image of potential new hydrogeological reservoirs and define new structures that partially explain their architecture. To cite this article: M. Kili et al., C. R. Geoscience 338 (2006).     

Application of back-propagation networks in debris flow prediction

Debris flows have caused serious loss of human lives and a lot of damage to properties in Taiwan over the past decades. Moreover, debris flows have brought massive mud causing water pollution in reservoirs and resulted in water shortage for daily life locally and affected agricultural irrigation and industrial usages seriously. A number of methods for prediction of debris flows have been studied. However, the successful prediction ratio of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for occurrence predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 178 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 93.82% demonstrates that the presented ANN model with seven significant factors can provide a stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.