Dataset associated with "An Improved Rescaling Algorithm for Estimating Groundwater Depletion Rates using the GRACE Satellite"

Ukasha, Muhammad; Ramirez, Jorge; Niemann, Jeffrey

Dataset associated with "An Improved Rescaling Algorithm for Estimating Groundwater Depletion Rates using the GRACE Satellite"

dc.contributor.author	Ukasha, Muhammad
dc.contributor.author	Ramirez, Jorge
dc.contributor.author	Niemann, Jeffrey
dc.coverage.spatial	Sacramento and San Joaquin River Basins, California	en_US
dc.coverage.temporal	2006-01-2010-12	en_US
dc.date.accessioned	2022-07-15T18:45:06Z
dc.date.available	2022-07-15T18:45:06Z
dc.date.issued	2022
dc.description	Data in Figures 2 to 4.	en_US
dc.description	Department of Civil and Environmental Engineering
dc.description.abstract	The Gravity Recovery And Climate Experiments (GRACE) satellite mission has been instrumental in estimating large-scale groundwater storage changes across the globe. GRACE observations include significant errors, so pre-processing is normally required before the data are used. In particular, the regional observations of terrestrial water storage anomalies (TWSA) are usually filtered to reduce the effects of measurement errors and then rescaled to reduce the unintended impacts of the filtering. The rescaling is typically selected to maximize the Nash-Sutcliffe Efficiency (NSE) between the rescaled filtered TWSA and original TWSA from large-scale hydrologic models that represent an incomplete water budget. The objectives of this study are (1) to evaluate the use of NSE in the current GRACE rescaling methodology, (2) develop an improved methodology that incorporates a complete regional water budget, and (3) examine the impacts of the rescaling methodology on regional assessments of groundwater depletion. To evaluate the use of NSE as a performance metric, we implement an analytical solution to improve the relative variability between the filtered and original TWSA series. Improved relative variability produces more reliable estimates when comparing the results to TWSA estimates from global positioning systems (GPS) for the Sacramento and San Joaquin River basins (containing Central Valley) in California. Rescaling with the complete regional water budget based on observed hydrological fluxes results in a larger scale factor (3.18) than the scale factor from the large-scale hydrologic model outputs (1.97), and the new TWSA results are more consistent with those from GPS. The larger scale factor also suggests that regional groundwater depletion is more severe than previously estimated.	en_US
dc.format.medium	PDF
dc.format.medium	TXT
dc.identifier.uri	https://hdl.handle.net/10217/235434
dc.identifier.uri	http://dx.doi.org/10.25675/10217/235434
dc.language	English	en_US
dc.language.iso	eng	en_US
dc.publisher	Colorado State University. Libraries	en_US
dc.relation.ispartof	Research Data
dc.relation.isreferencedby	Ukasha, M., Ramirez, J. A., & Niemann, J. D. (2023). An Improved Rescaling Algorithm for Estimating Groundwater Depletion Rates using the GRACE Satellite. International Journal of Remote Sensing 44:3, 1069-1088. https://doi.org/10.1080/01431161.2023.2174387
dc.rights.license	The material is open access and distributed under the terms and conditions of the Creative Commons Public Domain "No rights reserved" (https://creativecommons.org/share-your-work/public-domain/cc0/).
dc.rights.uri	https://creativecommons.org/share-your-work/public-domain/cc0/
dc.title	Dataset associated with "An Improved Rescaling Algorithm for Estimating Groundwater Depletion Rates using the GRACE Satellite"	en_US
dc.type	Dataset	en_US