Dan-Thuy Lam


With the observed tendency towards more complex conceptual models in hydrogeology, the parameter estimation of high-dimensional systems has become an even more challenging task mathematically and computationally. My current work focuses on the application of existing iterative Ensemble Kalman algorithms as an inverse approach to calibrate a transient groundwater flow model. Because of the strong assumptions of gaussianity and linearity made by such algorithms, it is necessary in a suboptimal context to reflect on proper parameterization strategies so as to leverage these methods in a way that they would still yield meaningful results. 

More info on RG and GitHub  


2015 - 2019 : PhD at Centre of Hydrogeology and Geothermics (CHYN), University of Neuchâtel, Switzerland.

2011 - 2014 : Master's degree at School of Engineering Geophysics (EOST), University of Strasbourg, France.


  • Lam, D.‐T., Renard, P., Straubhaar, J., & Kerrou, J. (2020). Multi‐resolution approach to condition categorical multiple‐point realizations to dynamic data with iterative ensemble smoothing. Water Resources Research, 56, 1-29.​ ​​https://doi.org/10.1029/2019WR025875