IAHR, founded in 1935, is a worldwide independent member-based organisation of engineers and water specialists working in fields related to the hydro-environmental sciences and their practical application. Activities range from river and maritime hydraulics to water resources development and eco-hydraulics, through to ice engineering, hydroinformatics, and hydraulic machinery.
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You are here : eLibrary : IAHR World Congress Proceedings : 36th Congress - The Hague (2015) ALL CONTENT : Hydro-environment : Assimilation for a numerical eutrophication model using ensemble kalman filter
Assimilation for a numerical eutrophication model using ensemble kalman filter
Author : ZHIJIE LI (1), QIUWEN CHEN (1)(2)
Data assimilation techniques have been developed for assimilating observations into various models by coupling
measured data and model simulations together to enhance the model reliability and reduce forecast uncertainties. The Ensemble Kalman filter (EnKF) which is one of the most widely used data assimilation techniques for complex nonlinear numerical models has been applied to a eutrophication model for predicting dynamics of phytoplankton biomass in Taihu Lake. In this study both of the model parameter and state variable are updated using the observations available.
The simulation results show that the fitness between model simulation and observation was improved when the state variable and parameter were updated by measured data. It demonstrates that EnKF is an effective method for improving the simulation accuracy of complex dynamic eutrophication models, which provides a solid foundation for the use of the model predictions.
File Size : 626,129 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 36th Congress - The Hague (2015) ALL CONTENT
Article : Hydro-environment
Date Published : 30/09/2015
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