Posterior assessment of parameters in a time domain random walk model of partitioning tracer tests in two-phase flow scenarios

Supplementary material associated with the manuscript : "Posterior assessment of parameters in a time domain random walk model of partitioning tracer tests in two-phase flow scenarios" by Emanuela Bianchi Janetti, Alberto Guadagnini and Monica Riva. The folder '1. Input Data' contains the set of experimental observations of Dwarakanath et al. (1999) analysed in the manuscript. The folder '2. Classical ML inversion' inlcudes the breakthrough curves obtained with the Time Domain Random Walk (TDRW) particle tracking methodology considering the parameters estimated via classical Maximum Likelihood (ML) approach. The folder '3. Stochastic inversions' inlcudes the key results of the stochastic inverse modeling technique.