Abstract
Data assimilation optimally merges model forecasts with observations taking into account both model and observational uncertainty. This paper presents a new data assimilation framework that enables the many Open Model Interface (OpenMI) 2.0.NET compliant hydrological models already available, access to a robust data assimilation library. OpenMI is an open standard that allows models to exchange data during runtime, thus transforming a complex numerical model to a 'plug and play' like component. OpenDA is an open interface standard for a set of tools, filters, and numerical techniques to quickly implement data assimilation. The OpenDA OpenMI framework is presented and tested on a synthetic case that highlights the potential of this new framework. MIKE SHE, a distributed and integrated hydrological model is used to assimilate hydraulic head in a catchment in Denmark. The simulated head over the entire domain were significantly improved by using an ensemble based Kalman filter. (C) 2014 Elsevier Ltd. All rights reserved.
| Original language | English |
|---|---|
| Journal | Environmental Modelling & Software |
| Volume | 57 |
| Pages (from-to) | 76-89 |
| ISSN | 1364-8152 |
| DOIs | |
| Publication status | Published - 2014 |
| Externally published | Yes |
Keywords
- OpenDA
- OpenMI
- Data assimilation
- Hydrological modeling
- Kalman filter
- Uncertainty
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