Combining water quality variables with landsat ETM+ data for remote sensing of chlorophyll-a concentration

BONANSEA, MATIAS; LEDESMA, CLAUDIA; RODRIGUEZ, CLAUDIA; PINOTTI, LUCIO

BIOCELL

INST HISTOL EMBRIOL-CONICET

Lugar: Mendoza; Año: 2015 vol. 39 p. 58 - 59

0327-9545

Río Tercero reservoir is considered the largest artificial reservoir in Córdoba province (Argentina). This multipurpose reservoir has experienced toxin-producing blooms of the cyanobacterium Microcystis on a number of occasions over the past decades. Conventional monitoring of lakes and reservoirs is time consuming and expensive. Satellite imagery is another source of information with great potential to be used for the study of water quality variables including chlorophyll-a concentration (Chl-a), among others. Different studies propose reliable relationships between remote sensing data and Chl-a, however, their procedures rely solely on spectral data and do not consider additional factors that potentially affect Chl-a. In this study, we developed a model to estimate Chl-a of Río Tercero reservoir (Córdoba, Argentina) from Landsat ETM+ data, and we improved model performance by including different water quality parameters to explain variability in Chl-a. Water quality samples were taken coinciding with the passage of ETM+ by the study area. Pearson correlation and backward multiple regression analyses were used to investigate the relationship between Chl-a, ETM+ bands and different water quality parameters. Results suggested that visible ETM+ bands (band 1-3), water surface temperature and water clarity were reliable predictors of Chl-a (R2=0.84). The procedure presented here could become a low cost measurement tool for water management authorities and decision makers, obtaining simpler and practical results for estimation of Chl-a variable, which is considered a reliable indicator of lake productivity and an ideal metric of water quality.