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Sensitivity analysis of the Chaohu Lake eutrophication model with a new index based on the Morris method
Author(s) -
Yulin Wang,
Zulin Hua,
Liang Wang
Publication year - 2017
Publication title -
water science and technology water supply
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 39
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2017.204
Subject(s) - eutrophication , sensitivity (control systems) , environmental science , biomass (ecology) , index (typography) , hydrology (agriculture) , nutrient , ecology , computer science , geology , biology , geotechnical engineering , electronic engineering , world wide web , engineering
Chaohu Lake is a large shallow lake in eastern China, and few eutrophication model studies have been conducted there. We present practical sensitivity indices based on the Morris method to compare the sensitivity of a parameter group on one model output with that of one parameter on multiple model outputs. The new sensitivity indices were employed to measure the parameter sensitivity of the Chaohu Lake eutrophication model. The results of the sensitivity analysis demonstrate that the most sensitive parameters on cyanobacteria biomass, NH 4 , NO 3 , and PO 4 were BMR, KDN, Nitm, and KRP, and the most sensitive parameter groups were algae-related, nitrogen-related, and phosphorus-related, which all directly participate in their cycles. Furthermore, Nitm, KRP, KDN, KHP, BMR, KTB, KTHDR, and KTCOD were the most important for the Chaohu Lake eutrophication model. The water environment characteristics, such as the cyanobacteria life stage in the simulated period, significantly affected parameter sensitivity. The power-law relationship between the new sensitivity index and the standard deviation of model variables in the Chaohu Lake model were also determined. This finding allows us to estimate the interactions between parameters using their sensitivity index. The results provide a basis for further improvement of the Chaohu Lake eutrophication model.

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