Gradient-based estimation of Manning's friction coefficient from noisy data
AuthorsCalo, Victor M.
Radwan, Hany G.
KAUST DepartmentApplied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Earth Science and Engineering Program
Environmental Science and Engineering Program
Numerical Porous Media SRI Center (NumPor)
Physical Science and Engineering (PSE) Division
KAUST Grant NumberKUS-C1-016-04
Preprint Posting Date2012-04-08
Permanent link to this recordhttp://hdl.handle.net/10754/562559
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AbstractWe 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.
CitationCalo, V. M., Collier, N., Gehre, M., Jin, B., Radwan, H., & Santillana, M. (2013). Gradient-based estimation of Manning’s friction coefficient from noisy data. Journal of Computational and Applied Mathematics, 238, 1–13. doi:10.1016/j.cam.2012.08.004
SponsorsThis 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).