1. Three-dimensional hydraulic tomography analyses to investigate commingling issues of reproducibility, data density, and geological prior models.
- Author
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Ning, Zeren, Luo, Ning, Inaba, Kaoru, Nakashima, Tomohiro, Shimizu, Takaaki, and Illman, Walter A.
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GEOLOGICAL modeling , *GEOLOGICAL statistics , *HYDRAULIC conductivity , *TOMOGRAPHY , *GROUNDWATER flow , *DENSITY , *ACQUISITION of data - Abstract
• HT surveys in 2019 and 2020 to test the reproducibility of estimated K and S s. • 3D K and S s fields are reproducible even when boundary conditions are varied. • Improved reproducibility observed when inverting with higher data density. • Accurate geological information included as initial guess improved reproducibility. • HT has the potential for mapping changes in K and S s heterogeneity over time. Over the past two decades, geostatistics-based hydraulic tomography (HT) has been proven to be a robust method for subsurface heterogeneity characterization. However, the reproducibility of estimated parameter fields, namely the hydraulic conductivity (K) and specific storage (S s), obtained over different data collection periods and under different flow scenarios have been rarely studied. In this study, we investigate the reproducibility and predictivity of HT estimates using data collected in 2019 and 2020 at a field site of varying boundary conditions underlain by sedimentary units in Japan, with different data density and prior geological information. Model performance of each case is evaluated qualitatively and quantitatively by examining results from model calibration, self-validation and cross-validation, in terms of parameter fields comparison, drawdown matches and cross-correlation distributions. Results of this study reveal that: 1) overall, the parameter fields for 2019 and 2020 HT estimates are generally reproducible, while fine-scale discrepancy exists; 2) they are also found to be reproducible in terms of consistency of estimated geostatistical parameters; 3) higher levels of reproducibility and predictivity associated with estimated K and S s fields are obtained when higher data density is included for geostatistical inverse modeling with more accurate prior geological information; and 4) the different spatial distributions of cross-correlation between head and parameter fields induced through the significant variation of the groundwater flow field from 2019 to 2020 strengthen the notion of reproducibility of HT results. These results collectively suggest that HT has the potential for mapping changes to K and S s heterogeneity over time broadening its future applications to various practical problems. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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