Land Hydrology Studies in North America Using GRACE and Hydrology Models

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dc.contributor.advisorSideris, Michael G.
dc.contributor.authorPiretzidis, Dimitrios
dc.contributor.committeememberKim, Jeong-woo
dc.contributor.committeememberRangelova, Elena V.
dc.contributor.committeememberHe, Jianxun
dc.contributor.committeememberHuang, Jianliang
dc.date2020-11
dc.date.accessioned2020-04-27T18:18:53Z
dc.date.available2020-04-27T18:18:53Z
dc.date.issued2020-04-22
dc.description.abstractThe need for a reliable land hydrology model that can monitor the amount of water stored on and beneath the Earth’s surface on a regional and global scale has become very important, especially in overpopulated areas or regions that already suffer from shortage of freshwater. The main objective of this thesis is to examine the hydrology signal in North America using a combination of land hydrology models and satellite gravimetry products coming from the GRACE satellite mission. Our analysis emphasizes on the post-processing of GRACE data. More specifically, we define a detailed framework for the extraction of hydrological signals from GRACE data by removing the contribution of non-hydrologic geophysical components and using advanced processing techniques. In order to carry out this objective, we improve the most frequently-used filtering methods for the suppression of correlated errors from GRACE data, and develop more refined algorithms for their implementation. We formulate a selective decorrelation of GRACE data using machine learning and show that our new approach mitigates the over-filtering effects of the conventional decorrelation. We also solve the instability and inaccuracy problems related to the calculation of isotropic Gaussian filter coefficients and develop new expressions that simplify their evaluation. We assess the GRACE data and the hydrology models, and find a satisfactory level of agreement between them, with an averaged RMS difference of 3.9 cm in terms of equivalent water height. We then combine these independent datasets and develop two combined hydrology models for the monitoring of monthly terrestrial water storage and groundwater storage variations. We examine their seasonal and long-term variations and provide useful insights for the spatiotemporal evolution of water masses in North America from 2003 to 2014. For the most part, North America is affected by negative long-term trends of terrestrial and ground water changes that are more evident in Hudson Bay and southern North America, whereas strong accumulation of water masses is observed in central North America. The combined models developed in this study provide a basis for the continuous satellite-based monitoring of land hydrology in North America and can be used for the improved management of water resources.en_US
dc.identifier.citationPiretzidis, D. (2020). Land Hydrology Studies in North America Using GRACE and Hydrology Models (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/37727
dc.identifier.urihttp://hdl.handle.net/1880/111902
dc.language.isoengen_US
dc.publisher.facultySchulich School of Engineeringen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectSatellite gravimetryen_US
dc.subjectGRACEen_US
dc.subjectGLDASen_US
dc.subjectFilteringen_US
dc.subject.classificationGeodesyen_US
dc.subject.classificationGeophysicsen_US
dc.subject.classificationHydrologyen_US
dc.subject.classificationRemote Sensingen_US
dc.titleLand Hydrology Studies in North America Using GRACE and Hydrology Modelsen_US
dc.typedoctoral thesisen_US
thesis.degree.disciplineEngineering – Geomaticsen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameDoctor of Philosophy (PhD)en_US
ucalgary.item.requestcopyfalseen_US
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