Tian-Chyi Yeh

Professor, Hydrology / Atmospheric Sciences

Member of the Graduate Faculty

  Dr. Yeh presently holds a Professor in the Department of Hydrology and Water Resources at the University of Arizona (number 1 ranking in Hydogeology by US News) and an Adjunct Professor at the Department of Resources Engineering, National Cheng Kung University, Taiwan, Republic of China. Department of Soil, Water, and Environmental Science, The University of Arizona, Tucson, Arizona; Department of Earth & Environmental Sciences, University of Waterloo. Professor Yeh is also an outstanding lecturer of Department of Education, China to Jilin University, China.       Professor Yeh is an internationally renowned leader in stochastic/numerical analysis and laboratory/field investigations, as applied to heterogeneity effects on flow and solute transport in the saturated and unsaturated geologic media.  He pioneered stochastic analysis of the effects of spatial variability on flow in unsaturated geologic media; he discovered and developed the theory of moisture-dependent anisotropy for unsaturated hydraulic conductivity, which has significantly advanced our understanding, characterization, and prediction of unsaturated and saturated zone processes.  His three classic papers on this subject have been referenced 624 times since their publications.  Dr. Yeh also was the first to explore the conditional simulations and inverse modeling of flow and transport processes in variably saturated geologic media.  He recently invented the sequential successive linear estimation technique as an innovation that overcomes difficulties of the traditional inverse modeling technique.  This innovation has led to the development of robust hydraulic, tracer, electrical resistivity tomography, and stochastic fusion methods to image the subsurface heterogeneity.  The impact of his innovation is well-documented by the number of citations of his two recent papers:  Hydraulic tomography: development of a new aquifer test method (147 citations since 2000, 9.8/yr) and characterization of aquifer heterogeneity using transient hydraulic tomography (95 times since 2005, 9.5/yr). These two papers revolutionize the way we collect and analyze data for characterization of hydraulic properties the subsurface.   Success of the stochastic fusion method brings about his concept of exploiting naturally occurring stimuli (storm, earthquake, river stage, lightning, etc.) as energy sources for basin-scale subsurface tomographic surveys. He believes this new concept is the future of hydrologic sciences and other disciplines of environmental sciences and engineering.  

Offering Research Opportunities?


Prerequisite Courses

numeric, fluid mechanics, hwr516, hwr535, hwr 645

Majors Considered

subsurface hydrology

Types of Opportunities

Description of Opportunity

No description given

Start Date

August 2016

Primary Department

Affiliated Departments

Research Location