Thermistor Chain Data Assimilation to Improve Hydrodynamic Modeling Skill in Stratified Lakes and Reservoirs
Publication: Journal of Hydraulic Engineering
Volume 134, Issue 8
Abstract
Results from a three-dimensional hydrodynamic model of a stratified lake show that the computed structure of the pycnocline changed rapidly due to numerical diffusion, thus altering the vertical mixing dynamics and introducing a positive feedback that quickly drives model predictions off course. To negate the numerical diffusion a pycnocline filtering method is proposed that assimilates high-resolution thermistor chain data and adaptively adjusts to minimize the discrepancy between observed and computed temperatures. The adaptive pycnocline filter ensures that the computed temperature gradients in the metalimnion at the position of the thermistor chain remain within the bounds of the measured values so the computation preserves the spectrum of internal wave motions that trigger diapycnal mixing events in the deeper reaches of the lake.
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Acknowledgments
The writers thank the staff of the Field Operations Group at the Centre for Water Research (CWR) for installing the Lake Diagnostic Systems (LDS) in Lake Kinneret, and the staff at the Kinneret Limnological Laboratory, Israel, for maintaining the LDSs. Many thanks to Arthur Simanjuntak from CWR for his input into ELCOM development. The writers also thank the reviewers and editor for their comments. This is CWR reference ED1642PY.
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Published In
Journal of Hydraulic Engineering
Volume 134 • Issue 8 • August 2008
Pages: 1123 - 1135
Copyright
© 2008 ASCE.
History
Received: Dec 11, 2006
Accepted: Nov 21, 2007
Published online: Aug 1, 2008
Published in print: Aug 2008
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