• Sorted by Date • Sorted by Last Name of First Author •
Singh, Alka, Seitz, Florian, Eicker, Annette, and Güntner, Andreas, 2016. Water Budget Analysis within the Surrounding of Prominent Lakes and Reservoirs from Multi-Sensor Earth Observation Data and Hydrological Models: Case Studies of the Aral Sea and Lake Mead. Remote Sensing, 8(11):953, doi:10.3390/rs8110953.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2016RemS....8..953S,
author = {{Singh}, Alka and {Seitz}, Florian and {Eicker}, Annette and {G{\"u}ntner}, Andreas},
title = "{Water Budget Analysis within the Surrounding of Prominent Lakes and Reservoirs from Multi-Sensor Earth Observation Data and Hydrological Models: Case Studies of the Aral Sea and Lake Mead}",
journal = {Remote Sensing},
keywords = {GRACE, water budget, reservoir, water fluxes, GLDAS, WGHM, Aral Sea, Lake Mead},
year = 2016,
month = nov,
volume = {8},
number = {11},
eid = {953},
pages = {953},
abstract = "{The hydrological budget of a region is determined based on the
horizontal and vertical water fluxes acting in both inward and
outward directions. These integrated water fluxes vary, altering
the total water storage and consequently the gravitational force
of the region. The time-dependent gravitational field can be
observed through the Gravity Recovery and Climate Experiment
(GRACE) gravimetric satellite mission, provided that the mass
variation is above the sensitivity of GRACE. This study
evaluates mass changes in prominent reservoir regions through
three independent approaches viz. fluxes, storages, and gravity,
by combining remote sensing products, in-situ data and
hydrological model outputs using WaterGAP Global Hydrological
Model (WGHM) and Global Land Data Assimilation System (GLDAS).
The results show that the dynamics revealed by the GRACE signal
can be better explored by a hybrid method, which combines remote
sensing-based reservoir volume estimates with hydrological model
outputs, than by exclusive model-based storage estimates. For
the given arid/semi-arid regions, GLDAS based storage
estimations perform better than WGHM.}",
doi = {10.3390/rs8110953},
adsurl = {https://ui.adsabs.harvard.edu/abs/2016RemS....8..953S},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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