Satellite assessment of eutrophication hot spots and algal blooms in small and medium-sized productive reservoirs in Uruguay's main drinking water basin

Abstract

Intensive agricultural activities favor eutrophication and harmful phytoplankton blooms due to the high export of nutrients and damming of rivers. Productive watersheds used for water purification can have multiple reservoirs with phytoplankton blooms, which constitutes a high health risk. In general, water quality monitoring does not cover small and medium-sized reservoirs (0.25–100 ha) of productive use due to their large number and location in private properties. In this work, the in-situ trophic state of fourteen reservoirs was simultaneously assessed using Sentinel-2 images in the Santa Lucía River Basin, the main drinking water basin in Uruguay. These reservoirs are hypereutrophic (0.18–5.22 mg total P L-1) with high phytoplankton biomasses (2.8–4439 µg chlorophyll-a L-1), mainly cyanobacteria. Based on data generated in-situ and Sentinel-2 imagery, models were fitted to estimate satellite Chl-a and transparency in all the basin reservoirs (n = 486). The best fits were obtained with the green-to-red band ratio (560 and 665 nm, R2 = 0.84) to estimate chlorophyll-a and reflectance at 833 nm (R2 = 0.73) to determine transparency. The spatial distribution of the trophic state was explored by spatial autocorrelation and hotspot analysis, and the variation in spatial patterns could be determined prior and subsequent to a maximum cyanobacteria value in water treatment plant intakes. Therefore reservoirs with greater potential for phytoplankton biomass export were identified. This work provides the first fitted tool for satellite monitoring of numerous reservoirs, and strengthens the country's ability to respond to harmful phytoplankton blooms in its main drinking water basin.

Zoning the risk of transporting phytoplankton blooms from multiple reservoirs to the primary drinking water intake in Uruguay

“…Subsequently, the average surface re ectance of each reservoir was extracted using polygons positioned over the water surface. Using this information, Chl-a concentration was estimated using the satellite estimation model calibrated by Zabaleta et al, (2023). The estimation equation employed was Chl-a (µg L − 1 ) = 10 ^ (1.6218 + 6.0575 * VR), with VR being calculated as (Rrs 560 nm -Rrs 665 nm) / (Rrs 560 nm + Rrs 665 nm).…”

“…Chlorophyll-a (Chl-a) stands out as the pigment most commonly used in remote sensing, serving as an indicator of total phytoplankton biomass (Giardino et al, 2019;Watanabe et al, 2017). In particular, the Sentinel-2 satellite's Multi Spectral Instrument sensor, with its frequent revisit interval (5 days) and 10-meter pixel resolution, has proven effective in monitoring Chl-a concentration, even in small and turbid reservoirs (Zabaleta et al, 2023;Ansper, 2018).…”