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Integration of GRACE Data for Improvement of Hydrological Models

Banerjee, C and Kumar, DN (2019) Integration of GRACE Data for Improvement of Hydrological Models. [Book Chapter]

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Official URL: https://doi.org/10.1007/978-3-030-02197-9_1


Terrestrial Water Storage (TWS) data, now available for more than 15Â years, as furnished by the Gravity Recovery and Climate Experiment (GRACE) satellite mission provided remarkable insights into the hydrological cycle. An expanding volume of scientific literature bears testimony to this. Besides identifying the alarming rate of both global groundwater storage depletion and polar ice cap melt, which are considered as its major accomplishments, the GRACE dataset also provided an exceptional resource for the improvement of the hydrological models. Such studies, although large in number, can be broadly classified into two categories: (1) Model evaluation studies, comparing regional or global model outputs with GRACE-derived hydrological parameters and (2) data assimilation techniques, where GRACE data is incorporated into the modeling framework. Model evaluation techniques vary in terms of the choice of hydrologic parameter, which in most cases is TWS or groundwater. On the other hand, data assimilation strategies in most of the studies use ensemble Kalman filter or its variant to incorporate the information derived from GRACE data into the models. This chapter reviews the integration methodologies highlighting the different aspects of model improvement such as the hydrologic parameter of interest, complexity of the model framework, and representation of hydrological processes. However, the present discussion is restricted to conceptual hydrological models and do not include statistical or GRACE-based water balance models.

Item Type: Book Chapter
Publication: Springer Water
Publisher: Springer Nature
Additional Information: The copyright for this article belongs to Springer Nature
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Date Deposited: 01 Dec 2022 05:55
Last Modified: 01 Dec 2022 05:55
URI: https://eprints.iisc.ac.in/id/eprint/78118

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