Analysis of 'black box' relationship between sediment discharge, rainfall and runoff
Call Number: AIT Thesis no. 458 Material type:
TextSeries: Asian Institute of Technology. Thesis ; no. 458Publication details: Bangkok : Asian Institute of Technology, 1972Description: 118 pSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 1972 Summary: In the present study an attempt was made to find a relationship between sediment discharge, rainfall and runoff. A 'Black Box' method of analysis was used. The relationship was assumed to be nonlinear and time variant. A decomposition model was devised which consisted of a linear filter combinations connected in series with a nonlinear filter. The data for the study was obtained from twelve plots in the evergreen forests of Northern Thailand. Two different models were compiled after testing eighteen different models. The memory of the system was processed by using linear low pass and Laguerre filter combination. The nonlinearity was accounted for by using second degree terms and cross product terms. The effect of number of linear and nonlinear filters on the model sensitivity and stability were also studied. Two models gave fairly good results. The use of more than one linear and nonlinear filters resulted in system instability and damping the sensitivity of the model. The nonlinearity was found to be overestimated by second degree term.
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Asian Institute of Technology Library Archives | AIT Thesis no. 458 (Browse shelf(Opens below)) | Available | 30050160108030 |
A thesis submitted in partial fulfillment 0f the requirements of the degree of Master of Engineering of the Asian Institute of Technology, Bangkok Thailand.
Thesis (M.Eng.) - Asian Institute of Technology, 1972
In the present study an attempt was made to find a relationship between sediment discharge, rainfall and runoff. A 'Black Box' method of analysis was used. The relationship was assumed to be nonlinear and time variant. A decomposition model was devised which consisted of a linear filter combinations connected in series with a nonlinear filter. The data for the study was obtained from twelve plots in the evergreen forests of Northern Thailand. Two different models were compiled after testing eighteen different models. The memory of the system was processed by using linear low pass and Laguerre filter combination. The nonlinearity was accounted for by using second degree terms and cross product terms. The effect of number of linear and nonlinear filters on the model sensitivity and stability were also studied. Two models gave fairly good results. The use of more than one linear and nonlinear filters resulted in system instability and damping the sensitivity of the model. The nonlinearity was found to be overestimated by second degree term.
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