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 journalArticlepeer-review

10 Scopus citations


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 languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalJournal of Computational and Applied Mathematics
Issue number1
StatePublished - Jan 2013

Bibliographical 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).

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics


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