TY - JOUR
T1 - Stochastic analysis of oscillatory hydraulic tomography
AU - Wang, Yu Li
AU - Yeh, Tian Chyi Jim
AU - Xu, Dong
AU - Li, Kuangjia
AU - Wen, Jet Chau
AU - Huang, Shao Yang
AU - Wang, Wenke
AU - Hao, Yonghong
N1 - Funding Information:
This research is in part by the U.S. Civilian Research and Development Foundation ( CRDF ) under the award number DAA2-15-61224-1: Hydraulic tomography in shallow alluvial sediments: Nile River Valley, Egypt. The second author also acknowledges the support of the U.S. NSF grant EAR1931756. The program and the data used in this study are available from the corresponding author on reasonable request. The authors thank the editors and reviewers for their helpful and insightful comments which have significantly improved this work.
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/5
Y1 - 2021/5
N2 - This paper investigates the effectiveness of different oscillatory hydraulic tomography (OHT) frequencies for estimating heterogeneous fields. The analysis first formulates the effects of uncharacterized aquifer responses, T, and S fields as the ensemble mean residual flux and residual storage terms in the stochastic unconditional and conditional mean equations. These terms persist unless the T, S, or head fields are specified everywhere. We then conducted OHT to estimate the T and S fields using Monte Carlo experiments. The experiments show that using the heads in response to periodic pumping with different frequencies or multifrequency, the estimates' performance metrics vary from one realization to others. The mean performance metrics over many realizations are, however, indistinguishable, despite the frequency. We attribute the variation in the performance metrics to the lack of parameter or state variable ergodicity. Lastly, we emphasize the importance of dense monitoring networks and a cost-effective data collection strategy to improve the resolution of characterizing aquifer heterogeneity.
AB - This paper investigates the effectiveness of different oscillatory hydraulic tomography (OHT) frequencies for estimating heterogeneous fields. The analysis first formulates the effects of uncharacterized aquifer responses, T, and S fields as the ensemble mean residual flux and residual storage terms in the stochastic unconditional and conditional mean equations. These terms persist unless the T, S, or head fields are specified everywhere. We then conducted OHT to estimate the T and S fields using Monte Carlo experiments. The experiments show that using the heads in response to periodic pumping with different frequencies or multifrequency, the estimates' performance metrics vary from one realization to others. The mean performance metrics over many realizations are, however, indistinguishable, despite the frequency. We attribute the variation in the performance metrics to the lack of parameter or state variable ergodicity. Lastly, we emphasize the importance of dense monitoring networks and a cost-effective data collection strategy to improve the resolution of characterizing aquifer heterogeneity.
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U2 - 10.1016/j.jhydrol.2021.126105
DO - 10.1016/j.jhydrol.2021.126105
M3 - Article
AN - SCOPUS:85102070766
SN - 0022-1694
VL - 596
JO - Journal of Hydrology
JF - Journal of Hydrology
M1 - 126105
ER -