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NPS MODEL PARAMETER UNCERTAINTY ANALYSIS FOR AN OFF‐STREAM RESERVOIR 1
Author(s) -
Kao JehngJung,
Hong HongJyh
Publication year - 1996
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1996.tb04074.x
Subject(s) - randomness , watershed , monte carlo method , digital elevation model , environmental science , nonpoint source pollution , water quality , drainage , uncertainty analysis , hydrology (agriculture) , elevation (ballistics) , computer science , statistics , mathematics , simulation , geology , geotechnical engineering , remote sensing , ecology , geometry , machine learning , biology
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.