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Browsing by Author "Hong, HJ"

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    NPS model parameter uncertainty analysis for an off-stream reservoir
    (1996-10-01)
    Kao, JJ
    ;
    Hong, HJ
    ;
    環境工程研究所
    ;
    Institute of Environmental Engineering
    Parameter uncertainties exert a significant effect on nonpoint source pollution (NPS) modeling results. A decision made on the basis of such results may thereby be inappropriate. In this work, the parameter uncertainty is analyzed to explore an improved modeling procedure. Drainage patterns generated from digital elevation data and rainfall are the major parameters examined. A case study for the watershed of the Posan off-stream reservoir is implemented. A significant spatial variation of NPS distribution simulated with a drainage pattern generated from varied methods is observed. The effects of rainfall randomness on the spatial loading distribution are assessed and computed based on a Monte Carlo simulation. The proposed procedure is capable of improving the quality of modeling results and the decision for an appropriate control strategy.
  • Thumbnail Image
    Item type:Item,
    NPS model parameter uncertainty analysis for an off-stream reservoir
    (1996-10-01)
    Kao, JJ
    ;
    Hong, HJ
    ;
    交大名義發表
    ;
    環境工程研究所
    ;
    National Chiao Tung University
    Parameter uncertainties exert a significant effect on nonpoint source pollution (NPS) modeling results. A decision made on the basis of such results may thereby be inappropriate. In this work, the parameter uncertainty is analyzed to explore an improved modeling procedure. Drainage patterns generated from digital elevation data and rainfall are the major parameters examined. A case study for the watershed of the Posan off-stream reservoir is implemented. A significant spatial variation of NPS distribution simulated with a drainage pattern generated from varied methods is observed. The effects of rainfall randomness on the spatial loading distribution are assessed and computed based on a Monte Carlo simulation. The proposed procedure is capable of improving the quality of modeling results and the decision for an appropriate control strategy.