Emulation of a process-based estuarine hydrodynamic model

ABSTRACT

Emulation modelling can be an effective alternative to traditional mechanistic approaches for complex environmental systems and, if carefully conceived, can offer significantly reduced run times and user expertise requirements. We present a case study of dynamic emulation for the domain of estuarine water quality modelling, by reporting the development and evaluation of a one-dimensional hydrodynamic model emulator. The proposed “neuroemulator” retains the dynamic nature of the process-based model utilizing a set of artificial neural networks. The underlying hydrodynamic model is routinely used for analysis and management of the northern reach of the San Francisco Bay-Delta estuary, a large complex region of strategic importance for water supply and ecosystem services on the Pacific coast of California, USA. The reduced computational expense of the emulator affords opportunities for direct use, as well as embedded use within other modelling frameworks such as those developed for reservoir operations and socio-hydrology.

KEYWORDS:

• estuarine water quality
• artificial neural network
• neuroemulation
• San Francisco Bay-Delta

Editor R. Woods; Associate editor A. Efstratiadis

Editor R. Woods; Associate editor A. Efstratiadis

Acknowledgements

The authors wish to thank Deanna Sereno (Contra Costa Water District) for her review of an earlier version of the emulation model described in this paper, and Ms Carrie Munill for preparing Figures 1 and 3. We appreciate the constructive review comments of K. W. Chau, S. N. Londhe and Associate Editor, Andreas Efstratiadis.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplementary data for this article can be accessed here.

Additional information

Funding

This work was funded by State Water Project Contractors Authority (SWPCA).