Next Article in Journal
A Method for Choosing an Initial Time Eigenstate in Classical and Quantum Systems
Next Article in Special Issue
Probabilistic Forecasts: Scoring Rules and Their Decomposition and Diagrammatic Representation via Bregman Divergences
Previous Article in Journal / Special Issue
Entropy of Shortest Distance (ESD) as Pore Detector and Pore-Shape Classifier
Open AccessArticle

On the Use of Information Theory to Quantify Parameter Uncertainty in Groundwater Modeling

Black and Veatch, 5750 Castle Creek Pkwy N Dr, Indianapolis, Indiana 46250, USA
Department of Geosciences, University of Missouri, Kansas City, 5100 Rockhill Road, Kansas City, Missouri, 64110, USA
Author to whom correspondence should be addressed.
Entropy 2013, 15(6), 2398-2414;
Received: 16 February 2013 / Revised: 3 June 2013 / Accepted: 5 June 2013 / Published: 13 June 2013
(This article belongs to the Special Issue Applications of Information Theory in the Geosciences)
We applied information theory to quantify parameter uncertainty in a groundwater flow model. A number of parameters in groundwater modeling are often used with lack of knowledge of site conditions due to heterogeneity of hydrogeologic properties and limited access to complex geologic structures. The present Information Theory-based (ITb) approach is to adopt entropy as a measure of uncertainty at the most probable state of hydrogeologic conditions. The most probable conditions are those at which the groundwater model is optimized with respect to the uncertain parameters. An analytical solution to estimate parameter uncertainty is derived by maximizing the entropy subject to constraints imposed by observation data. MODFLOW-2000 is implemented to simulate the groundwater system and to optimize the unknown parameters. The ITb approach is demonstrated with a three-dimensional synthetic model application and a case study of the Kansas City Plant. Hydraulic heads are the observations and hydraulic conductivities are assumed to be the unknown parameters. The applications show that ITb is capable of identifying which inputs of a groundwater model are the most uncertain and what statistical information can be used for site exploration. View Full-Text
Keywords: information theory; groundwater modeling; parameter uncertainty information theory; groundwater modeling; parameter uncertainty
Show Figures

Figure 1

MDPI and ACS Style

Noronha, A.; Lee, J. On the Use of Information Theory to Quantify Parameter Uncertainty in Groundwater Modeling. Entropy 2013, 15, 2398-2414.

Show more citation formats Show less citations formats

Article Access Map by Country/Region

Only visits after 24 November 2015 are recorded.
Back to TopTop