AI SearchMulti-site streamflow generation with the view of preserving the higher order moments
Call Number: AIT Thesis no. 1348 Material type:
TextSeries: Asian Institute of Technology. Thesis ; no. 1348Publication details: Bangkok : Asian Institute of Technology, 1979Description: 101 pSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 1979 Summary: The present research deals with two station streamflow generation schemes, in the attempt to preserving the moments of the historical sequences up to the third order. For this purpose, three ten day streamflow generation models are presented and their applicability is investigated by means of case studies. These models are: Stepwise model, Fiering two station model and Multiple Regression model. In addition, the Stepwise model is also used for monthly streamflow generation and a disaggregation model is employed to transfer generated monthly sequences into ten day sequences. The method for estimates the related parameters of these models are described and their use is judged when necessary by means of typical statistical tests. Through comparison between the generated sequences and the historical sequences in terms of the mean, the standard deviation, the serial and cross correlation coefficients, and the skewness coefficient, The most suitable model is recommended for use in the case of the Tachia River basin in Taiwan.
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A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering of the Asian Institute of Technology, Bangkok, Thailand
Thesis (M.Eng.) - Asian Institute of Technology, 1979
The present research deals with two station streamflow generation schemes, in the attempt to preserving the moments of the historical sequences up to the third order. For this purpose, three ten day streamflow generation models are presented and their applicability is investigated by means of case studies. These models are: Stepwise model, Fiering two station model and Multiple Regression model. In addition, the Stepwise model is also used for monthly streamflow generation and a disaggregation model is employed to transfer generated monthly sequences into ten day sequences. The method for estimates the related parameters of these models are described and their use is judged when necessary by means of typical statistical tests. Through comparison between the generated sequences and the historical sequences in terms of the mean, the standard deviation, the serial and cross correlation coefficients, and the skewness coefficient, The most suitable model is recommended for use in the case of the Tachia River basin in Taiwan.
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