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Articles by Keiji Takase
Total Records ( 2 ) for Keiji Takase
  Bin He , Osamu Kaino , Yi Wang and Keiji Takase
  To analyze and evaluate the environmental self-purification function of river water, the chemical and hydro-meteorological data have been collected over the past 6 years in the Shigenobu river of Shikoku island, Japan. Generally, the problems of an adequate understanding and description of complex processes of pollutant circulation and water quality dynamics in rivers can be effectively solved by applying the water quality mathematical models. This approach allows taking into account, analyzing and ranking numerous interacting hydrological, meteorological and biological factors, impact of natural and anthropogenic sources of pollution. But in some cases the hydrological, meteorological and biological information are unavailable or incomplete. Thus this study presents the results of a study that examined the application of Artificial Neural Network (ANN) model to simulate the river chemical mass transport using the indicator of dissolved oxygen. Artificial Neural Network model is proved to behave well with the measured data. This study demonstrated that it was feasible to assemble and deploy ANN model to predict the dissolved oxygen under the condition of incomplete information.
  Abu Farah Md. Anisur Rahman , Hiromasa Hiura , Kazuo Shino and Keiji Takase
  Single catchment experiment was used to assess the effects of thinning on direct runoff and peak runoff properties in a small mountainous watershed of Kochi prefecture, Japan. The watershed is covered with commercial plantations of Japanese cedar (Cryptomeria japonica), Japanese cypress (Chamaecyparis obtusa), red pine (Pinus densiflora) and oak (Quercus spp.). Following an initial pre-thinning period (1996-1999), stream flow measurements were continued over a comparable post-thinning period (2000-2003) and linear regression models were developed for the two periods to assess the effects of a thinning operation conducted during December 1999 to January 2000. We hypothesized that the regression model for the pre-thinning period is still valid for the post-thinning period and tested this utilizing the Chow`s F Test. A 95% prediction interval was calculated for the pre-thinning regression models to evaluate changes in individual observations of the post-thinning period. The results suggest that the thinning, carried out on 19.25% of the watershed area removing only 6.35% of total timber volume, did not cause noticeable effects on direct runoff and peak runoff. Concentration time was found to be decreased after thinning for some storm events. The study revealed that hydrometric method is not enough for detecting noticeable effects of a small thinning operation on direct runoff and peak runoff properties.
 
 
 
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