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Title: Definition and solution of a stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models

Abstract

The uncertainty in spatially heterogeneous Manning’s n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented in this paper. Technical details that arise in practice by applying the framework to determine the Manning’s n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of “condition” for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. Finally, this notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning’s n parameter and the effect on model predictions is analyzed.

Authors:
 [1];  [2];  [3];  [2];  [4]
  1. Univ. of Colorado, Denver, CO (United States)
  2. Univ. of Texas, Austin, TX (United States)
  3. Colorado State Univ., Fort Collins, CO (United States)
  4. Univ. of Notre Dame, South Bend, IN (United States)
Publication Date:
Research Org.:
Colorado State Univ., Fort Collins, CO (United States); Univ. of Colorado, Denver, CO (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1343755
Alternate Identifier(s):
OSTI ID: 1249698
Grant/Contract Number:  
SC0009279; FG02-04ER25620; FG02-05ER25699; FC02-07ER54909; SC0001724; SC0005304; DGE-1110007; INL00120133; DE0000000SC9279; PO672TO001; 00069249; 00115474; B573139; B584647; B590495
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Advances in Water Resources
Additional Journal Information:
Journal Volume: 78; Journal ID: ISSN 0309-1708
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; Manning’s n coefficient; measure theory; parameter estimation; set-valued inverse solutions; shallow water equations; stochastic inverse problems

Citation Formats

Butler, Troy, Graham, L., Estep, D., Dawson, C., and Westerink, J. J. Definition and solution of a stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models. United States: N. p., 2015. Web. doi:10.1016/j.advwatres.2015.01.011.
Butler, Troy, Graham, L., Estep, D., Dawson, C., & Westerink, J. J. Definition and solution of a stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models. United States. https://doi.org/10.1016/j.advwatres.2015.01.011
Butler, Troy, Graham, L., Estep, D., Dawson, C., and Westerink, J. J. 2015. "Definition and solution of a stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models". United States. https://doi.org/10.1016/j.advwatres.2015.01.011. https://www.osti.gov/servlets/purl/1343755.
@article{osti_1343755,
title = {Definition and solution of a stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models},
author = {Butler, Troy and Graham, L. and Estep, D. and Dawson, C. and Westerink, J. J.},
abstractNote = {The uncertainty in spatially heterogeneous Manning’s n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented in this paper. Technical details that arise in practice by applying the framework to determine the Manning’s n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of “condition” for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. Finally, this notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning’s n parameter and the effect on model predictions is analyzed.},
doi = {10.1016/j.advwatres.2015.01.011},
url = {https://www.osti.gov/biblio/1343755}, journal = {Advances in Water Resources},
issn = {0309-1708},
number = ,
volume = 78,
place = {United States},
year = {Tue Feb 03 00:00:00 EST 2015},
month = {Tue Feb 03 00:00:00 EST 2015}
}

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Cited by: 17 works
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Works referenced in this record:

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Works referencing / citing this record:

A research on the estimation of coefficient roughness in open channel applying entropy concept
journal, September 2018


Specification of Additional Information for Solving Stochastic Inverse Problems
journal, January 2019