Technical Note on the Dynamic Changes in Kalman Gain when Updating Hydrodynamic Urban Drainage Models

Morten Borup*, Henrik Madsen, Morten Grum, Peter Steen Mikkelsen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

To prevent online models diverging from reality they need to be updated to current conditions using observations and data assimilation techniques. A way of doing this for distributed hydrodynamic urban drainage models is to use the Ensemble Kalman Filter (EnKF), but this requires running an ensemble of models online, which is computationally demanding. This can be circumvented by calculating the Kalman gain, which is the governing matrix of the updating, offline if the gain is approximately constant in time. Here, we show in a synthetic experiment that the Kalman gain can vary by several orders of magnitude in a non-uniform and time-dynamic manner during surcharge conditions caused by backwater when updating a hydrodynamic model of a simple sewer system with the EnKF. This implies that constant gain updating is not suitable for distributed hydrodynamic urban drainage models and that the full EnKF is in fact required.
Original languageEnglish
Article number416
JournalGeosciences
Volume8
Issue number11
Number of pages8
ISSN2076-3263
DOIs
Publication statusPublished - 2018

Keywords

  • backwater
  • data assimilation
  • distributed urban drainage models
  • Ensemble Kalman Filter
  • Kalman gain
  • sewer surcharge
  • Geology
  • QE1-996.5

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