The Pointwise Double Constraint Methodology

Wouter Zijl, Florimond De Smedt, Mustafa El-Rawy, Okke Batelaan

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter deals with the basic elements of the double constraint methodology (DCM). Since the DCM is an imaging method, while most parameter estimation methods are calibration methods, the difference is introduced in Sect. 3.1 and worked out in much greater depths in Sect. 3.9. Section 3.2 introduces the DCM in its most simple, intuitive form. To avoid presentation of three times the same equation for the three conductivity components in anisotropic media, we introduce the “voxel notation” in Sect. 3.3. Sections 3.4 and 3.5 present the theoretical justifications for the “intuitive DCM” presented in Sect. 3.2, while Sect. 3.6 discusses convergence and termination of the iterations. Section 3.7 presents some different approaches to handling anisotropy. Since the DCM is based on two models—the flux model and the head model—the rules for posing the correct boundary conditions for the two models are dealt with in Sect. 3.8.

Original languageEnglish
Title of host publicationThe Double Constraint Inversion Methodology
Subtitle of host publicationEquations and Applications in Forward and Inverse Modeling of Groundwater Flow
PublisherSpringer
Chapter3
Pages35-55
Number of pages21
Edition9783319713410
ISBN (Print)978-3-319-71341-0
DOIs
Publication statusPublished - 2018

Publication series

NameSpringerBriefs in Applied Sciences and Technology
Number9783319713410
ISSN (Print)2191-530X
ISSN (Electronic)2191-5318

Bibliographical note

Copyright Springer

Keywords

  • imposed fluxes
  • imposed heads
  • linear conductivity
  • groundwater flow equation

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    Zijl, W., De Smedt, F., El-Rawy, M., & Batelaan, O. (2018). The Pointwise Double Constraint Methodology. In The Double Constraint Inversion Methodology: Equations and Applications in Forward and Inverse Modeling of Groundwater Flow (9783319713410 ed., pp. 35-55). (SpringerBriefs in Applied Sciences and Technology; No. 9783319713410). Springer. https://doi.org/10.1007/978-3-319-71342-7_3