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SUMMARY

akes and reservoirs provide was obtained for each day from January on chlorophyll-a time series data from
multiple ecosystem services to 2009 to September 2019. A time series modis. In 2017 IEEE International
Lsociety, such as energy generation, was generated for the reservoir under Geoscience and Remote Sensing
provision of water for human and animal study (German et al. 2017). A clear Symposium (IGARSS) (pp. 4008-
consumption, and irrigation, flood seasonal behavior was observed in the 4011). IEEE.
attenuation, recharge of underground series, with peaks in the summer months Khan, I.; Zhao, M. (2019). Water resource
waters, and provision of habitat for and valleys in winter. This trend is to be management and public preferences
animal and plant species (Ledesma et expected due to temperature-limited for water ecosystem services: a choice
al. 2019). In recent years, contamination primary production processes (Li et al. experiment approach for inland river
and eutrophication of water resources 2017). In recent years, the dispersion basin management. Science of the
has become one of the world’s most of the data has increased and, also, Total Environment, 646, 821-831.
important environmental problems, as the values of Cl-a (Ferral et al. 2017). Ledesma, M.M.; Bonansea, M.; Ledesma,
it puts both the quantity and quality of This work is a relevant contribution to C.R.; Rodríguez, C.; Carreño, J.; Pinotti,
water for human consumption at risk study the temporal evolution of water L. (2019). Estimation of chlorophyll-a
(Khan and Zhao, 2019). Remote sensing pollution in reservoirs. concentration using Landsat 8 in the
has proven to be a fundamental tool Cassaffousth reservoir. Water Supply,
dynamics of eutrophication. The MODIS REFERENCIAS Li, Y.; Zhang, Y.; Shi, K.; Zhu, G.; Zhou, Y.;
for capturing the spatial and temporal
19(7), 2021-2027.
onboard sensor (launched in 1999) Zhang, Y.; Guo, Y. (2017). Monitoring
has high daily global coverage, as well Bonansea, M.; Rodriguez, M.C.; Pinotti, spatiotemporal variations in nutrients
as appropriate spatial resolutions L.; Ferrero, S. (2015). Using multi- in a large drinking water reservoir and
for the analysis of large lakes. The temporal Landsat imagery and linear their relationships with hydrological
concentration of Chlorophyll-a (Cl-a) mixed models for assessing water and meteorological conditions based
is a good indicator of water quality quality parameters in Río Tercero on Landsat 8 imagery. Science of the
(Bonansea et al. 2015). The objective reservoir (Argentina). Remote Sensing Total Environment, 599, 1705-1717.
of this work was to generate a time of Environment, 158, 28-41. Li, Z.; Ma, J.; Guo, J.; Paerl, H.W.; Brookes,
series from a statistical model based Ferral, A.; Solis, V.; Frery, A.; Orueta, A.; J.D.; Xiao, Y.; ...; Lunhui, L. (2019).
on field data and satellite information Bernasconi, I.; Bresciano, J.; Scavuzzo, Water quality trends in the Three
from MODIS, to determine and predict C.M. (2017). Spatio-temporal changes Gorges Reservoir region before and
the temporal distribution of Cl-a in the in water quality in an eutrophic lake after impoundment (1992–2016).
Río Tercero reservoir. A linear regression with artificial aeration. Journal of Ecohydrology & Hydrobiology, 19(3),
model was obtained (R2 = 0.66), which Water and Land Development, 35(1), 317-327.
takes into account the relationship 27-40.
between bands 1 and 2 of the MODIS Germán, A.; Tauro, C.; Scavuzzo, M.C.; Ferral,
satellite (Li et al. 2017; Ledesma et al. A. (2017, July). Detection of algal
2019). With this algorithm, a Cl-a value blooms in a eutrophic reservoir based

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