Hierarchical Inverse Modeling of Complex Groundwater Systems Across Multiple Scales  

 

Investigators

Shu-Guang Li, Qun Liu, Phanikumar Mantha

Research Assistants

Soheil Afshari, David Ni, Yu-Hui Sun

Funding Agency:

National Science Foundation


Physical phenomena in GW modeling tend to line up, approximately, along the diagonal direction in the space-time  scale diagram [after Bonnet, 1982, NASA 1988]

 


A fundamental problem in the analysis of complex ground-water systems is the interplay of data and modeling. Improving how data and models are used, especially across a multitude of scales, has proven to be exceedingly difficult. The prevalent ways of groundwater modeling today do not properly account for scale interactions and the significant disparity between model, measurement, and management scales and are unable to make effective use of the available data, resulting in a significant loss of valuable information.

In this project, we will address systematically these fundamental difficulties in large scale, 3D groundwater modeling.  In particular, we will take advantage of the new “forward” hierarchical patch dynamic paradigm (HPDP) for groundwater modeling (under development in another NSF project CISE 0430987) and further develop an important hierarchical inverse modeling capability. The inverse HPDP environment will be based on the popular inverse modeling engine – PEST – a general, model independent nonlinear parameter estimation program [Doherty, 1994]. The PEST program will be adapted and seamlessly embedded in the hierarchical modeling environment. It will communicate with the entire model hierarchy dynamically, obviating the need for offline processing, I/O, and file storage.  The hierarchical inverse environment will allow integrated, simultaneous calibration of flow and/or transport processes within one or more patches across any combination of scales.

The hierarchical patch dynamic approach to inverse modeling will provide a systematic and efficient scaling ladder to link data and models across multiple spatial scales and is expected to significantly enhance our ability to make maximal use of the field information and to identify and characterize complex groundwater systems and fluxes at surface water interfaces.

 

Publications:



Shu-Guang Li, http://www.egr.msu.edu/~lishug

Department of Civil and Environmental Engineering
A133 Engineering Research Complex
Michigan State University
East Lansing, MI 48824-1226

Phone: (517)432-1929
Fax: (517)335-0250
E-mail: lishug@egr.msu.edu