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Abstract
The Alqueva reservoir (South of Portugal) in the Guadiana river basin constitutes the most important water resource in southern Portugal for domestic and agricultural consumption. We present a methodology developed to characterize spatial and temporal variations of Secchi depth and diffuse attenuation coefficient (both related to dissolved/suspended particles and to water transparency), using high spatial resolution satellite images from Sentinel-2 Multi-Spectral Instrument (MSI). Empirical relations between satellite retrievals of surface reflectances and in situ measurements of water parameters were defined and applied to the entire reservoir for spatial and temporal analysis in the period July 2017–June 2019, useful in the identification of microalgae blooms and rapid variations in water characteristics, which allowed us to differentiate five zones. Water estimates with lower transparency and higher attenuation of radiation were found in the northern area of Alqueva reservoir during the months characterized by higher water temperatures, with Secchi depth monthly averages near 1.0 m and diffuse attenuation coefficient near or above 1.5 m-1. Satellite retrievals of water with greater transparency in the reservoir were obtained in the southern area in months with low water temperature and atmospheric stability, presenting some monthly Secchi depth averages above 3 m, and diffuse attenuation coefficient below 0.8 m-1. January 2018 presented great transparency of water with a Secchi depth of 7.5 m for pixels representing the 95th percentile and diffuse attenuation coefficient of 0.36 m for pixels representing the 5th percentile in the Southern region.
Highlights
Lake ecosystems are vital resources for aquatic wildlife and human needs, representing 98% of the liquid surface freshwater on the Earth’s surface
The results showed the high reliability of the Water Vapour (WV) estimates, with normalized root mean square errors (NRMSE) of 5.33% and R2 of 0.99
In the validation of the Secchi depth (SD) algorithm, it is verified that the absolute value of the Bias (0.36 m) is practically equal to the mean absolute error (MAE) (0.4 m), meaning that deviations to the observed data are practically all of underestimation satellite retrievals in relation to the observed data
Summary
Lake ecosystems are vital resources for aquatic wildlife and human needs, representing 98% of the liquid surface freshwater on the Earth’s surface. Lakes are sensitive to the impacts of climate change, and the impacts include a wide range of negative consequences, such as changes in thermal stratification, an acceleration of the eutrophication which favors periodic proliferation by cyanobacteria in many freshwaters, increased turbidity, and changes in salinity [8,9,10]. In this context, many studies have been carried out regarding the deterioration of water quality due to human influence, and its spatial and temporal variations in rivers or water reservoirs [11,12,13,14]
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