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

Victor M. Calo; Nathan Collier; Matthias Gehre; Bangti Jin; Hany G. Radwan; Mauricio Santillana

doi:10.1016/j.cam.2012.08.004

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

Victor M. Calo, Nathan Collier, Matthias Gehre, Bangti Jin, Hany G. Radwan, Mauricio Santillana

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	1-13
Number of pages	13
Journal	Journal of Computational and Applied Mathematics
Volume	238
Issue number	1
DOIs	https://doi.org/10.1016/j.cam.2012.08.004
State	Published - Jan 2013

ASJC Scopus subject areas

Computational Mathematics
Applied Mathematics

Access to Document

10.1016/j.cam.2012.08.004

Cite this

@article{144e0415d2a14a918f6db2806a77aac3,

title = "Gradient-based estimation of Manning's friction coefficient from noisy data",

abstract = "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. {\textcopyright} 2012 Elsevier B.V. All rights reserved.",

author = "Calo, {Victor M.} and Nathan Collier and Matthias Gehre and Bangti Jin and Radwan, {Hany G.} and Mauricio Santillana",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): KUS-C1-016-04 Acknowledgements: This work was initiated while V.M.C. was a Visiting Professor at the Institute for Applied Mathematics and Computational Science (IAMCS), Texas A&M University, College Station. The work of M.G. was carried out during his visit at IAMCS. They would like to thank the institute for the kind hospitality and support. The work of B.J. is supported by Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST).",

year = "2013",

month = jan,

doi = "10.1016/j.cam.2012.08.004",

language = "English (US)",

volume = "238",

pages = "1--13",

journal = "Journal of Computational and Applied Mathematics",

issn = "0377-0427",

publisher = "Elsevier B.V.",

number = "1",

}

TY - JOUR

T1 - Gradient-based estimation of Manning's friction coefficient from noisy data

AU - Calo, Victor M.

AU - Collier, Nathan

AU - Gehre, Matthias

AU - Jin, Bangti

AU - Radwan, Hany G.

AU - Santillana, Mauricio

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): KUS-C1-016-04 Acknowledgements: This work was initiated while V.M.C. was a Visiting Professor at the Institute for Applied Mathematics and Computational Science (IAMCS), Texas A&M University, College Station. The work of M.G. was carried out during his visit at IAMCS. They would like to thank the institute for the kind hospitality and support. The work of B.J. is supported by Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST).

PY - 2013/1

Y1 - 2013/1

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10754/562559

UR - http://arxiv.org/abs/arXiv:1204.1709v1

UR - http://www.scopus.com/inward/record.url?scp=84867070691&partnerID=8YFLogxK

U2 - 10.1016/j.cam.2012.08.004

DO - 10.1016/j.cam.2012.08.004

M3 - Article

SN - 0377-0427

VL - 238

SP - 1

EP - 13

JO - Journal of Computational and Applied Mathematics

JF - Journal of Computational and Applied Mathematics

IS - 1

ER -

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

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this