Abstract
Forecasting the movement and growth of algae in river systems as particularly important for operational managers responsible for the distribution and supply of potable water. Algae affect the taste and smell of water and pose considerable filtration problems at water treatment plants. In a collaborative study with the Thames Water Authority, algal models have been developed for the River Thames. The non-linear processes controlling algal growth are examined using a generalized sensitivity analysis technique and the dominant parameters controlling system behaviour are identified. The extended Kalman filter (EKF) is then used to estimate these important parameters. The technique of using generalized sensitivity analysis prior to EKF estimation is suggested as a pragmatic approach to the problem of identifying the subset of physically, chemically or biologically meaningful parameters controlling system behaviour in mechanistic models.
Published Version
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