Inverse modeling of different stimuli and hydraulic tomography: A laboratory sandbox investigation

Liqun Jiang, Ronglin Sun, Tian Chyi Jim Yeh, Xing Liang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


The limited area of influence in highly permeable aquifers hampers hydraulic tomography (HT) surveys with traditional pumping tests. Few have suggested that flow data under natural stimuli could complement HT. Verifying this conjecture in controlled laboratory sandbox experiments does not exist. Similarly, many have employed independent pumping events to validate inverse modeling results, but few have explored the validation uncertainty. This study first conducted sandbox experiments to investigate the effectiveness of head data from HT, natural gradient (NG), and precipitation/infiltration (PI) events for estimating hydraulic conductivity (K) field. Conditional Monte Carlo simulation of independent pumping tests then addresses the uncertainty of validating these estimated K fields. The effectiveness of the estimates from NG and PI as prior information for HT was investigated next. Cross-correlation analysis, exploring the relationship between the observed heads and K heterogeneity under different stimuli, then assesses the usefulness of flow data under different stimuli and their possibility for complementing HT as prior information. Estimates from NG and PI events as the mean of the prior probability distribution for HT then corroborate the cross-correlation analysis. Conditional Monte Carlo simulation of twelve independent pumping tests further confirms that a decent NG's K estimate as the mean for the prior probability distribution for HT inversion yields the highest resolution of K estimates.

Original languageEnglish (US)
Article number127108
JournalJournal of Hydrology
StatePublished - Dec 2021


  • Conditional effective hydraulic conductivity
  • Conditional realizations
  • Hydraulic tomography
  • Natural gradient flow
  • Precipitation/infiltration events
  • Prior information

ASJC Scopus subject areas

  • Water Science and Technology


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