Gradient-based estimation of Manning's friction coefficient from noisy data

We study the numerical recovery of Manning's roughness coefficient for the diffusive wave approximation of the shallow water equation. We describe a conjugate gradient method for the numerical inversion. Numerical results for one-dimensional models are presented to illustrate the feasibility of...

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Main Authors: Calo, Victor, Collier, N., Gehre, M., Jin, B., Radwan, H., Santillana, M.
Format: Journal Article
Published: Elsevier 2013
Online Access:http://hdl.handle.net/20.500.11937/51358
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author Calo, Victor
Collier, N.
Gehre, M.
Jin, B.
Radwan, H.
Santillana, M.
author_facet Calo, Victor
Collier, N.
Gehre, M.
Jin, B.
Radwan, H.
Santillana, M.
author_sort Calo, Victor
building Curtin Institutional Repository
collection Online Access
description We study the numerical recovery of Manning's roughness coefficient for the diffusive wave approximation of the shallow water equation. We describe a conjugate gradient method for the numerical inversion. Numerical results for one-dimensional models are presented to illustrate the feasibility of the approach. Also we provide a proof of the differentiability of the weak form with respect to the coefficient as well as the continuity and boundedness of the linearized operator under reasonable assumptions using the maximal parabolic regularity theory. © 2012 Elsevier B.V. All rights reserved.
first_indexed 2025-11-14T09:47:48Z
format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T09:47:48Z
publishDate 2013
publisher Elsevier
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-513582017-09-13T15:35:35Z Gradient-based estimation of Manning's friction coefficient from noisy data Calo, Victor Collier, N. Gehre, M. Jin, B. Radwan, H. Santillana, M. We study the numerical recovery of Manning's roughness coefficient for the diffusive wave approximation of the shallow water equation. We describe a conjugate gradient method for the numerical inversion. Numerical results for one-dimensional models are presented to illustrate the feasibility of the approach. Also we provide a proof of the differentiability of the weak form with respect to the coefficient as well as the continuity and boundedness of the linearized operator under reasonable assumptions using the maximal parabolic regularity theory. © 2012 Elsevier B.V. All rights reserved. 2013 Journal Article http://hdl.handle.net/20.500.11937/51358 10.1016/j.cam.2012.08.004 Elsevier unknown
spellingShingle Calo, Victor
Collier, N.
Gehre, M.
Jin, B.
Radwan, H.
Santillana, M.
Gradient-based estimation of Manning's friction coefficient from noisy data
title Gradient-based estimation of Manning's friction coefficient from noisy data
title_full Gradient-based estimation of Manning's friction coefficient from noisy data
title_fullStr Gradient-based estimation of Manning's friction coefficient from noisy data
title_full_unstemmed Gradient-based estimation of Manning's friction coefficient from noisy data
title_short Gradient-based estimation of Manning's friction coefficient from noisy data
title_sort gradient-based estimation of manning's friction coefficient from noisy data
url http://hdl.handle.net/20.500.11937/51358