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dc.contributor.authorTsai, Jui-Pinen_US
dc.contributor.authorYeh, Tian-Chyi Jimen_US
dc.contributor.authorCheng, Ching-Chungen_US
dc.contributor.authorZha, Yuanyuanen_US
dc.contributor.authorChang, Liang-Chengen_US
dc.contributor.authorHwang, Cheinwayen_US
dc.contributor.authorWang, Yu-Lien_US
dc.contributor.authorHao, Yonghongen_US
dc.date.accessioned2018-08-21T05:53:07Z-
dc.date.available2018-08-21T05:53:07Z-
dc.date.issued2017-10-01en_US
dc.identifier.issn0043-1397en_US
dc.identifier.urihttp://dx.doi.org/10.1002/2017WR020459en_US
dc.identifier.urihttp://hdl.handle.net/11536/144290-
dc.description.abstractHydraulic conductivity (K) and specific yield (S-y) 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.en_US
dc.language.isoen_USen_US
dc.titleFusion of Time-Lapse Gravity Survey and Hydraulic Tomography for Estimating Spatially Varying Hydraulic Conductivity and Specific Yield Fieldsen_US
dc.typeArticleen_US
dc.identifier.doi10.1002/2017WR020459en_US
dc.identifier.journalWATER RESOURCES RESEARCHen_US
dc.citation.volume53en_US
dc.citation.spage8554en_US
dc.citation.epage8571en_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.identifier.wosnumberWOS:000418736000025en_US
Appears in Collections:Articles