4.7 Article

3-D transient hydraulic tomography in unconfined aquifers with fast drainage response

期刊

WATER RESOURCES RESEARCH
卷 47, 期 -, 页码 -

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AMER GEOPHYSICAL UNION
DOI: 10.1029/2010WR010367

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资金

  1. NSF [EAR-0710949, DMS-0934680]
  2. US Army RDECOM ARL Army Research Office [W911NF-09-1-0534]
  3. Division Of Mathematical Sciences
  4. Direct For Mathematical & Physical Scien [0934680] Funding Source: National Science Foundation

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We investigate, through numerical experiments, the viability of three-dimensional transient hydraulic tomography (3DTHT) for identifying the spatial distribution of groundwater flow parameters (primarily, hydraulic conductivity K) in permeable, unconfined aquifers. To invert the large amount of transient data collected from 3DTHT surveys, we utilize an iterative geostatistical inversion strategy in which outer iterations progressively increase the number of data points fitted and inner iterations solve the quasi-linear geostatistical formulas of Kitanidis. In order to base our numerical experiments around realistic scenarios, we utilize pumping rates, geometries, and test lengths similar to those attainable during 3DTHT field campaigns performed at the Boise Hydrogeophysical Research Site (BHRS). We also utilize hydrologic parameters that are similar to those observed at the BHRS and in other unconsolidated, unconfined fluvial aquifers. In addition to estimating K, we test the ability of 3DTHT to estimate both average storage values (specific storage S-s and specific yield S-y) as well as spatial variability in storage coefficients. The effects of model conceptualization errors during unconfined 3DTHT are investigated including: (1) assuming constant storage coefficients during inversion and (2) assuming stationary geostatistical parameter variability. Overall, our findings indicate that estimation of K is slightly degraded if storage parameters must be jointly estimated, but that this effect is quite small compared with the degradation of estimates due to violation of structural'' geostatistical assumptions. Practically, we find for our scenarios that assuming constant storage values during inversion does not appear to have a significant effect on K estimates or uncertainty bounds.

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