Deriving a practical form of IDF formula using transformed rainfall intensities

A general form of formula is presented for the rainfall Intensity–Duration–Frequency (IDF) relationship. This formula is derived from the nearly normal probability distribution function of transformed intensities. In order to transform the raw intensities, a correcting non‐constant spread technique, the Kruskal–Wallis statistic, and the Box–Cox transformation are adopted. These transformations enable to express a simpler model for the IDF formula that agrees well with traditional IDF relationships. Since the proposed method allows the estimation of any percentile value of intensities with a single equation, the intensity percentile at arbitrary duration can be generated easily. The validity of the formula derived by means of the proposed method is assessed using data from major weather stations in Korea. The results show that the percentile intensities produced using the proposed method are in good agreement with those of traditional frequency analysis. Copyright © 2013 John Wiley & Sons, Ltd.     

The Application of Artificial Neural Networks to Landslide Susceptibility Mapping at Janghung, Korea

The purpose of this study was to develop techniques for landslide susceptibility using artificial neural networks and then to apply these to the selected study area at Janghung in Korea. Landslide locations were identified from interpretation of satellite images and field survey data, and a spatial database of the topography, soil, forest, and land use. Thirteen landslide-related factors were extracted from the spatial database. These factors were then used with an artificial neural network to analyze landslide susceptibility. Each factor's weight was determined by the back-propagation training method. Five different training sets were applied to analyze and verify the effect of training. Then the landslide susceptibility indices were calculated using the back-propagation weights, and susceptibility maps were constructed from Geographic Information System (GIS) data for the five cases. Landslide locations were used to verify results of the landslide susceptibility maps and to compare them. The artificial neural network proved to be an effective tool for analyzing landslide susceptibility.     

中国东北地区中生代火山岩的大地构造意义

中国东北地区中生代火山岩可划分为西部大兴安岭环状火山岩带、南部火山岩带和东部火山岩带,它们是古亚洲洋构造域向太平洋构造域转换时期不同构造环境的产物。西部大兴安岭环状火山岩带的形成与古亚洲洋闭合过程中壳幔相互作用引起的深部热地幔柱的上升有关,南部火山岩带与构造域转换时期走滑拉伸构造有关,而东部火山岩带则是太平洋板块斜向俯冲作用的产物。     

Geophysical Surveys in the Jebel Hamrat Fidan,Jordan

The Jebel (Jebel is mountain in Arabic) Hamrat Fidan marks the “gateway” to the Feinan district of southern Jordan—one of the largest sources of copper during the prehistoric and Early Bronze Ages in the eastern Mediterranean. Preliminary excavations and surveys at sites along the Wadi Fidan have revealed a long history of settled occupation extending from the Pre‐Pottery Neolithic (ca. 6,500 B.C.) to early medieval times. Because of this long history of occupation, and the fact that this area was a regional center for the production of copper, the study of this area is important for understanding early metallurgy, craft specialization, and social evolution. During the summer of 1997, geophysical investigations at a series of Neolithic and Bronze Age sites identified specific areas within Wadi Fidan for future intensive excavations. Three geophysical techniques (electromagnetic induction, ground‐penetrating radar, and magnetometry) were used to help locate buried architectural and industrial features remaining from early mining and metallurgical operations, including copper ore bodies or voids. Geophysics was not used at the actual mining sites because of scheduling constraints; however, geophysics did delineate buried stone walls at three distinct Wadi Fidan sites. Magnetometry and ground penetrating radar provided little useful information. Buried stone walls were apparently “masked” by numerous magnetic stones on the ground surface making magnetometry useless. Reflections from known strata demonstrated that radar penetrated the ground adequately; however, known shallowly buried walls were not recognizable. Electromagnetic induction produced maps of linear and rectilinear features that suggested spatial distribution of widespread buried stone walls suitable for future excavation. A significant and unexpected finding was that electromagnetic induction proved capable of delineating buried stone walls. © 2000 John Wiley & Sons, Inc.