Fusion of Time-Lapse Gravity Survey and Hydraulic Tomography for Estimating Spatially Varying Hydraulic Conductivity and Specific Yield Fields

Jui Pin Tsai, Tian Chyi Jim Yeh, Ching Chung Cheng, Yuanyuan Zha, Liang Cheng Chang, Cheinway Hwang, Yu Li Wang, Yonghong Hao

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Hydraulic conductivity (K) and specific yield (SY) are important aquifer parameters, pertinent to groundwater resources management and protection. These parameters are commonly estimated through a traditional cross-well pumping test. Employing the traditional approach to obtain detailed spatial distributions of the parameters over a large area is generally formidable. For this reason, this study proposes a stochastic method that integrates hydraulic head and time-lapse gravity based on hydraulic tomography (HT) to efficiently derive the spatial distribution of K and (SY) over a large area. This method is demonstrated using several synthetic experiments. Results of these experiments show that the K and (SY) fields estimated by joint inversion of the gravity and head data set from sequential injection tests in unconfined aquifers are superior to those from the HT based on head data alone. We attribute this advantage to the mass constraint imposed on HT by gravity measurements. Besides, we find that gravity measurement can detect the change of aquifer's groundwater storage at kilometer scale, as such they can extend HT's effectiveness over greater volumes of the aquifer. Furthermore, we find that the accuracy of the estimated fields is improved as the number of the gravity stations is increased. The gravity station's location, however, has minor effects on the estimates if its effective gravity integration radius covers the well field.

Original languageEnglish
Pages (from-to)8554-8571
Number of pages18
JournalWater Resources Research
Volume53
Issue number10
DOIs
Publication statusPublished - 2017 Oct

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

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