TY - JOUR
T1 - Fusion of Time-Lapse Gravity Survey and Hydraulic Tomography for Estimating Spatially Varying Hydraulic Conductivity and Specific Yield Fields
AU - Tsai, Jui Pin
AU - Yeh, Tian Chyi Jim
AU - Cheng, Ching Chung
AU - Zha, Yuanyuan
AU - Chang, Liang Cheng
AU - Hwang, Cheinway
AU - Wang, Yu Li
AU - Hao, Yonghong
N1 - Publisher Copyright:
© 2017. American Geophysical Union. All Rights Reserved.
PY - 2017/10
Y1 - 2017/10
N2 - 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.
AB - 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.
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U2 - 10.1002/2017WR020459
DO - 10.1002/2017WR020459
M3 - Article
AN - SCOPUS:85034448186
SN - 0043-1397
VL - 53
SP - 8554
EP - 8571
JO - Water Resources Research
JF - Water Resources Research
IS - 10
ER -