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dc.contributor.advisorYeh, Tian-Chyi Jim
dc.contributor.authorWang, Yu-Li
dc.creatorWang, Yu-Li
dc.date.accessioned2020-02-06T19:32:21Z
dc.date.available2020-02-06T19:32:21Z
dc.date.issued2020
dc.identifier.urihttp://hdl.handle.net/10150/636974
dc.description.abstractGroundwater is one of important water resources for the socio-economic development of a community. Its reserve, distribution, and movement are mainly controlled by the subsurface hydraulic characteristics. For management of the groundwater resources, mathematical models of groundwater dynamics have been used for estimation, prediction, and scenario analysis. The accuracy of these analyses relies on the detailed knowledge of the subsurface hydraulic characteristic distributions. However, a reliable evaluation of groundwater resources remains intractable due to multi-scale variability of the subsurface characteristics and our limited ability to characterize it over a large groundwater basin. This difficulty thus hinders adequate assessments of water sustainability, and in turn, impedes the development of community. In order to overcome this difficulty, a new generation of basin-scale aquifer characterization method must be developed. My dissertation is to explore and develop the new generation of basin-scale aquifer characterization approach. The dissertation is composed of three parts. In, the first part, we investigate the feasibility of utilizing river stage fluctuation as spatial and temporal varying excitation sources to characterize the basin-scale aquifers. The wavelet analysis is first conducted to investigate the temporal characteristics of groundwater level, precipitation, and stream stage. The results of the analysis show that variations of groundwater level and stream stage are highly correlated over seasonal and annual periods while that between precipitation is less significant. Subsequently, spatial cross-correlation between seasonal variations of groundwater level and river stage data is analyzed. It is found that the correlation contour map reflects the pattern of sediment distribution of the fan. This finding is further substantiated by the cross-correlation analysis using both noisy and noise-free groundwater and river stage data of a synthetic aquifer, where aquifer heterogeneity is known exactly. The ability of river stage tomography is then tested with these synthetic data sets to estimate hydraulic diffusivity (D) distribution. Finally, the river stage tomography is applied to the alluvial fan. The results of the application reveal that the apex and southeast of the alluvial fan are regions with relatively high D and the D values gradually decrease toward the shoreline of the fan. In addition, D at northern alluvial fan is slightly larger than that at southern. These findings are consistent with the geologic evolution of this alluvial fan. In the second part of the dissertation, we investigate the effects of different types of river stage variation and the monitoring network design on the large-scale aquifer characterization. It evaluates the spatiotemporal cross-correlation between the observed head and D parameters in heterogeneous aquifers under static and migrating periodic excitations with different frequencies and other factors, and a moving single excitation along a river boundary. Results of the cross-correlation analysis are verified by estimating the parameters in a synthetic heterogeneous aquifer under these excitations. For assuring the statistical significance of the results based on a single realization, Monte Carlo experiments of estimating the parameters with these excitations are conducted. The experiments also explore the relationship between the resolution of the estimated parameters and the distance from the excitation to the observation wells, the frequency, and amplitude of the excitation, and the mean diffusivity of the aquifer. In addition, the relationship between the resolution of the estimates and monitoring network spatial density is investigated. Finally, the usefulness of moving single excitations, effects of frequencies of the periodic excitations under different situations, the density of monitoring network in term of correlation scale, and the ergodicity issue corresponding to the number of observation and size of simulation domain are discussed. In the third part, we evaluate the capability of periodic excitations with different frequencies and multi-frequency to estimate hydraulic transmissivity and storage coefficient fields in heterogeneous aquifers. The residual flux and residual storage presented in the stochastic groundwater flow model are examined by the unconditional and conditional effective approaches. Afterward, the first order approximation and the singular value decomposition are substantiated to quantify the similarity and dissimilarity of amplitude and phase shift of unconditional flux and storage under different pumping frequencies. The result of the cross-correlation analysis is verified by estimating the parameters in a set of synthetic heterogeneous aquifers. The Monte Carlo experiment is required for assuring the statistical significance of the results. These resulting data and the reanalyzing data from previous studies lead us to a conclusion that the heads induced by pumping with different frequencies or multi-frequency carry the same information about the heterogeneity. Finally, the parameter (e.g., hydraulic conductivity and specific storage) and state variable (e.g., water level and flow fields) ergodicities emphasize the importance of dense monitoring network and cost-effective data collection procedure on the resolution of delineating heterogeneity.
dc.language.isoen
dc.publisherThe University of Arizona.
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
dc.titleBasin-Scale Aquifer Characterization: Theory and Application
dc.typetext
dc.typeElectronic Dissertation
thesis.degree.grantorUniversity of Arizona
thesis.degree.leveldoctoral
dc.contributor.committeememberFerre, Paul A.
dc.contributor.committeememberGuo, Bo
dc.description.releaseRelease after 01/22/2022
thesis.degree.disciplineGraduate College
thesis.degree.disciplineHydrology
thesis.degree.namePh.D.


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