Robust groundwater management is necessary to maintain long-term aquifer sustainability. Temporally and spatially inconsistent in situ data prevents robust groundwater resource evaluation. Data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission has been used to evaluate long-term, large-scale groundwater trends. However, the spatial resolution of GRACE data presents challenges for groundwater management in medium-sized aquifers like the Central Valley of California (CV). Other researchers have utilized GRACEderived data to evaluate groundwater storage in the CV, but they often make corrections due to what is referred to as the "leakage effect." We demonstrate a method for imputing gaps in groundwater time series that uses in situ data, Earth observations, and machine learning that provides an independent estimate of groundwater storage change. Using imputed data from this method, we calculate a storage depletion curve and use it to rescale GRACE-derived groundwater data in the CV. Our results demonstrate a method for calculating groundwater storage change, providing a direct solution for calibrating GRACE at a variety of aquifer scales.
| Identifer | oai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-10985 |
| Date | 17 June 2022 |
| Creators | Stevens, Michael David |
| Publisher | BYU ScholarsArchive |
| Source Sets | Brigham Young University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | https://lib.byu.edu/about/copyright/ |
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