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Reduced order emulation of distributed hydraulic models

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Reduced order emulation of distributed hydraulic models. / Young, Peter; Leedal, David; Beven, Keith; Szczypta, Camille.

15th IFAC Symposium on System Identification, 2009 . Vol. 15 1. ed. IFAC, 2009.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Young, P, Leedal, D, Beven, K & Szczypta, C 2009, Reduced order emulation of distributed hydraulic models. in 15th IFAC Symposium on System Identification, 2009 . 1 edn, vol. 15, IFAC. https://doi.org/10.3182/20090706-3-FR-2004.00293

APA

Young, P., Leedal, D., Beven, K., & Szczypta, C. (2009). Reduced order emulation of distributed hydraulic models. In 15th IFAC Symposium on System Identification, 2009 (1 ed., Vol. 15). IFAC. https://doi.org/10.3182/20090706-3-FR-2004.00293

Vancouver

Young P, Leedal D, Beven K, Szczypta C. Reduced order emulation of distributed hydraulic models. In 15th IFAC Symposium on System Identification, 2009 . 1 ed. Vol. 15. IFAC. 2009 https://doi.org/10.3182/20090706-3-FR-2004.00293

Author

Young, Peter ; Leedal, David ; Beven, Keith ; Szczypta, Camille. / Reduced order emulation of distributed hydraulic models. 15th IFAC Symposium on System Identification, 2009 . Vol. 15 1. ed. IFAC, 2009.

Bibtex

@inproceedings{0dedb0bbbf174021a9a15f835ed6084b,
title = "Reduced order emulation of distributed hydraulic models",
abstract = "Water level predictions made with hydraulic models are uncertain and evaluatingthis uncertainty using Monte Carlo ensemble prediction is computationally very expensive. In this paper we show how a reduced order Dynamic Model Emulator (DME) can be used to reproduce, with high accuracy, the outputs of a large and complex 1-D hydraulic model (HEC-RAS) at specied cross-sections along the Montford to Buildwas reach of the River Severn in the U.K, together with estimates of uncertainty in the predictions. This emulation model is obtained by the application of Dominant Mode Analysis (DMA), involving the identication and estimation of nonlinear State-Dependent Parameter (SDP) transfer function models, using data generated by dynamic experiments conducted on the HEC-RAS model. The paper shows how this `nominal' DME is able to emulate the distributed hydraulic model for a nominal set of its physically-dened parameters and it presents initial results from a complete DME that emulates the HEC-RAS model over a user-dened region of its parameter space.",
keywords = "nonlinear systems, system identification, Time series",
author = "Peter Young and David Leedal and Keith Beven and Camille Szczypta",
year = "2009",
month = jul,
day = "6",
doi = "10.3182/20090706-3-FR-2004.00293",
language = "English",
volume = "15",
booktitle = "15th IFAC Symposium on System Identification, 2009",
publisher = "IFAC",
edition = "1",

}

RIS

TY - GEN

T1 - Reduced order emulation of distributed hydraulic models

AU - Young, Peter

AU - Leedal, David

AU - Beven, Keith

AU - Szczypta, Camille

PY - 2009/7/6

Y1 - 2009/7/6

N2 - Water level predictions made with hydraulic models are uncertain and evaluatingthis uncertainty using Monte Carlo ensemble prediction is computationally very expensive. In this paper we show how a reduced order Dynamic Model Emulator (DME) can be used to reproduce, with high accuracy, the outputs of a large and complex 1-D hydraulic model (HEC-RAS) at specied cross-sections along the Montford to Buildwas reach of the River Severn in the U.K, together with estimates of uncertainty in the predictions. This emulation model is obtained by the application of Dominant Mode Analysis (DMA), involving the identication and estimation of nonlinear State-Dependent Parameter (SDP) transfer function models, using data generated by dynamic experiments conducted on the HEC-RAS model. The paper shows how this `nominal' DME is able to emulate the distributed hydraulic model for a nominal set of its physically-dened parameters and it presents initial results from a complete DME that emulates the HEC-RAS model over a user-dened region of its parameter space.

AB - Water level predictions made with hydraulic models are uncertain and evaluatingthis uncertainty using Monte Carlo ensemble prediction is computationally very expensive. In this paper we show how a reduced order Dynamic Model Emulator (DME) can be used to reproduce, with high accuracy, the outputs of a large and complex 1-D hydraulic model (HEC-RAS) at specied cross-sections along the Montford to Buildwas reach of the River Severn in the U.K, together with estimates of uncertainty in the predictions. This emulation model is obtained by the application of Dominant Mode Analysis (DMA), involving the identication and estimation of nonlinear State-Dependent Parameter (SDP) transfer function models, using data generated by dynamic experiments conducted on the HEC-RAS model. The paper shows how this `nominal' DME is able to emulate the distributed hydraulic model for a nominal set of its physically-dened parameters and it presents initial results from a complete DME that emulates the HEC-RAS model over a user-dened region of its parameter space.

KW - nonlinear systems

KW - system identification

KW - Time series

U2 - 10.3182/20090706-3-FR-2004.00293

DO - 10.3182/20090706-3-FR-2004.00293

M3 - Conference contribution/Paper

VL - 15

BT - 15th IFAC Symposium on System Identification, 2009

PB - IFAC

ER -