Data Assimilation in Mike1D models for urban collection systems

Type of project

B.Sc., M.Sc.

Contact

Anne Katrine Vinther Falk (akf@dhigroup.com)

Topic

In its core, Data assimilation (DA) is "manipulate the calculated states of a numerical model, by using observations to guide the correction". Urban models have many structures as pumps, valves and orifices. Some of these structures are sources of discontinuities in the model - think of an on/off-pump, a valve which closes or a weir which diverts parts of the water in another direction, but only when its crest level is reached. When DA tinkers with the model states it will have adverse effects on a pump which for instance starts and stops at certain levels.

Mike1D has two implementations of a Kalman filter approach - one where the user specifies a stationary gain, and one where the gain is derived from an ensemble of simulations. The former is computationally cheap, because it only runs a single simulation - however, the user-specified gain may not reflect the system dynamics. The latter is computationally expensive, because it needs to run an ensemble of simulations - but has the advantage that the gain "stays true" to the model dynamics (in both space and time).

So far, we have some urban applications that use the stationary gain method, but only to inject/extract water at single points in the system. We would like to investigate if the use of ensemble methods can improve the corrections.

Relevance to DHI

DHI uses Data Assimilation in forecast systems to update the Mike1D model with observations during the hindcast period. This improves the state from which the models starts the forecast. If we are able to improve the state at time of forecast, the quality of the entire forecast is improved.

What is the student's contribution

A thorough review of what has been published on the Data Assimilation for models of urban collection systems during the past 20 years - with special focus on how the state of control structures are handled.

Is it possible to conclude on how states related to structures can be included in the update? What to do if the state is discrete (on/off)?

A collection of small Mike1D test setups, each of them targeted at investigating a specific challenge.