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Gómez, Edna Luc\'ıa Espinosa, Rodr\'ıguez, Leticia, and Thalmeier, Maria Belén, 2025. Spatio-Temporal Analysis of Water Dynamics of a Large-Scale Plain Region Using Remote Sensing and Proxy Variables. Earth Systems and Environment, .
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025ESE...tmp..153G,
author = {{G{\'o}mez}, Edna Luc{\'\i}a Espinosa and {Rodr{\'\i}guez}, Leticia and {Thalmeier}, Maria Bel{\'e}n},
title = "{Spatio-Temporal Analysis of Water Dynamics of a Large-Scale Plain Region Using Remote Sensing and Proxy Variables}",
journal = {Earth Systems and Environment},
keywords = {MNDWI, MODIS images, SPI, Surface water detection, Threshold method, Bajos Submeridionales plain-Argentina},
year = 2025,
month = jun,
abstract = "{Monitoring the spatio-temporal dynamics of water-covered surfaces is
relevant for both natural ecosystems and socio-productive
activities. This is challenging in plains, where the flat
terrain, poorly-defined drainage networks, and extensive flood-
prone areas lead to complex hydrological patterns. The main goal
of this study was to investigate the spatio-temporal dynamics of
flooded areas in large plains within temperate climates, which
remain among the least studied globally. A multi-variable
approach was applied to map the dynamics of inundation extent,
and identify relationships between key hydrological variables. A
16-year time series of GRACE-derived Total Water Storage-TWS,
precipitation, Standardized Precipitation Index-SPI, and
available river height data were evaluated. Open water and mixed
water areas were identified from MODIS images using the Modified
Normalized Difference Water Index thresholding method, to
construct a Water Occurrence Frequency map. The correlation
between hydrological variables and water-covered areas was
explored. About 57 \% of the study basin can be affected by
water, 92 \% of which only ephemerally. Frequently flooded areas
constitute 0.31 \% while permanent waters cover 0.57\%. The
spatial pattern of mixed/open water relates to the topographic
position both at regional and local scales. The linear
correlation between TWS and SPI strengthens as the time scale
increases. Water storage controls water surface dynamics and the
intensity of flooding events. River height relates exponentially
to both the flooded area and TWS. A multiple-variable analysis
approach is essential for understanding water dynamics in data-
scarce, remote regions, offering crucial insights both for flood
risk assessment and management, and wetlands mapping.}",
doi = {10.1007/s41748-025-00673-4},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025ESE...tmp..153G},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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