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Information theory approach to quant...

Noronha, Alston Marian.

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Information theory approach to quantifying parameter uncertainty in groundwater modeling.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Information theory approach to quantifying parameter uncertainty in groundwater modeling./
Author:	Noronha, Alston Marian.
Description:	101 p.
Notes:	Adviser: Jejung Lee.
Contained By:	Masters Abstracts International44-04.
Subject:	Engineering, Civil. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1430516
ISBN:	9780542458552

Information theory approach to quantifying parameter uncertainty in groundwater modeling.
Noronha, Alston Marian.

Information theory approach to quantifying parameter uncertainty in groundwater modeling. - 101 p.

Adviser: Jejung Lee.

Thesis (M.S.)--University of Missouri - Kansas City, 2005.

The complexity of geologic and hydrologic subsurface structures often makes it difficult to formulate an accurate groundwater model. To improve the accuracy of a model, many studies have focused on optimizing unknown parameters without considering their uncertainty. The Information Theory (IT) approach uses entropy as a measure of uncertainty for the most probable state of a system. We maximize entropy when the groundwater model is optimized, by imposing normalization constraint and error constraint with observation data. A three-dimensional synthetic model is simulated using MODFLOW-2000 to demonstrate the effectiveness of the IT approach. With hydraulic heads as the observed data, hydraulic conductivities are chosen as the parameters to be optimized. The IT approach calculates variance, covariance and correlation coefficients for multiple unknown parameters. The Kansas City Plant case study shows that the IT approach is able to direct site exploration to detect the unknown structure that may affect the remediation performance.

ISBN: 9780542458552Subjects--Topical Terms:

783781
Engineering, Civil.

Information theory approach to quantifying parameter uncertainty in groundwater modeling.
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020 $a 9780542458552
035 $a (UnM)AAI1430516
035 $a AAI1430516
040 $a UnM $c UnM
100 1 $a Noronha, Alston Marian. $3 1296020
245 1 0 $a Information theory approach to quantifying parameter uncertainty in groundwater modeling.
300 $a 101 p.
500 $a Adviser: Jejung Lee.
500 $a Source: Masters Abstracts International, Volume: 44-04, page: 1915.
502 $a Thesis (M.S.)--University of Missouri - Kansas City, 2005.
520 $a The complexity of geologic and hydrologic subsurface structures often makes it difficult to formulate an accurate groundwater model. To improve the accuracy of a model, many studies have focused on optimizing unknown parameters without considering their uncertainty. The Information Theory (IT) approach uses entropy as a measure of uncertainty for the most probable state of a system. We maximize entropy when the groundwater model is optimized, by imposing normalization constraint and error constraint with observation data. A three-dimensional synthetic model is simulated using MODFLOW-2000 to demonstrate the effectiveness of the IT approach. With hydraulic heads as the observed data, hydraulic conductivities are chosen as the parameters to be optimized. The IT approach calculates variance, covariance and correlation coefficients for multiple unknown parameters. The Kansas City Plant case study shows that the IT approach is able to direct site exploration to detect the unknown structure that may affect the remediation performance.
590 $a School code: 0134.
650 4 $a Engineering, Civil. $3 783781
650 4 $a Hydrology. $3 545716
690 $a 0388
690 $a 0543
710 2 0 $a University of Missouri - Kansas City. $3 1021712
773 0 $t Masters Abstracts International $g 44-04.
790 $a 0134
790 1 0 $a Lee, Jejung, $e advisor
791 $a M.S.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1430516