Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In-Situ and Remote Sensing Analysis for an Urban Lake in Chile

Version 1 : Received: 15 November 2023 / Approved: 15 November 2023 / Online: 16 November 2023 (15:19:03 CET)

A peer-reviewed article of this Preprint also exists.

Yépez, S.; Velásquez, G.; Torres, D.; Saavedra-Passache, R.; Pincheira, M.; Cid, H.; Rodríguez-López, L.; Contreras, A.; Frappart, F.; Cristóbal, J.; Pons, X.; Flores, N.; Bourrel, L. Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile. Remote Sens. 2024, 16, 427. Yépez, S.; Velásquez, G.; Torres, D.; Saavedra-Passache, R.; Pincheira, M.; Cid, H.; Rodríguez-López, L.; Contreras, A.; Frappart, F.; Cristóbal, J.; Pons, X.; Flores, N.; Bourrel, L. Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile. Remote Sens. 2024, 16, 427.

Abstract

This study aims to develop and implement a methodology for retrieving bio-optical parameters in a lagoon located in the Biobío region, in south-central Chile by analyzing time series of Landsat-8 satellite images, specifically using the multispectral OLI sensor. The bio-optical parameters, i.e., chlorophyll-a (mg·m-3) and turbidity (NTU) were also measured in-situ synchronized with the satellite passes to minimize the impact of atmospheric distortions. To calibrate the satellite images, various atmospheric correction methods (including ACOLITE, C2RCC, iCOR, and LaSRC) were evaluated during the image preprocessing phase. Spectral signatures obtained from the scenes for each atmospheric correction method were then compared with spectral signatures acquired in-situ on the water surface. In short, the ACOLITE model emerged as the best fit for the calibration process. Subsequently, we harnessed the reflectance data derived from the ACOLITE model to establish correlations between various spectral indices and the in-situ data. The empirical retrieval models (based on band combinations) that showed superior performance, as indicated by higher R2 values, were subjected to rigorous statistical validation and optimization by applying a bootstrapping approach. Our analysis covered a spectrum of dates, seasons, and years, which allowed us to search deeper into the evolution of the trophic state associated with the lake. We identified a striking eight-year period (2014-2022) characterized by a decline in chlorophyll-a concentration in the lake possibly attributable to governmental measures in the region for the protection and conservation of the lake. The results of this initial study serve as the basis for the creation of a modern monitoring system that enhances traditional point-based methods, offering a holistic view of the ongoing processes within the lake.

Keywords

eutrophication; landsat; Chl-a; turbidity; spectral signatures; OLI; Chile

Subject

Environmental and Earth Sciences, Remote Sensing

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