Spatio-temporal analysis of surface temperature in a reservoir and its relation with water quality in a climate change context

FERRAL, ANABELLA; GERMAN, ALBA; BELTRAMONE, GIULIANA; BONANSEA, MATIAS; BURGOS, MAXIMILIANO; SAUNDERS DE CARVALHO, LINO; SHIMONI, MICHAL; ROQUÉ, MARIANA; SCAVUZZO, CARLOS MARCELO

Simposio; IEEE?s International Geoscience and Remote Sensing Symposium (IGARSS-2021); 2021

Remote sensing community is doing enormous efforts to implement early warning systems capable to follow spatiotemporal patterns of water quality and climate change risk indicators, being Horizon Eoxposure 2030 project one of then. This work presents first results of surface temperature Landsat 8 Level 2 Collection 2 analysis in San Roque reservoir against field data measurements. A Root Mean Square Error (RMSE) of 1.7 oC and a Mean Absolute Percentual Error (MAPE) of 7 % were obtained for these products but validation curve resulted not confident at a 95 % level. A semiempirical linear model with 94 % accuracy, RMSE of 1.1 o and a MAPE of 5 % is presented. It was successfully validated with a control group data set obtaining 94 % accuracy. A Water Surface Temperature temporal series is shown for the 2013-2020 period and spatio temporal patterns are analyzed and discussed. Differences found between warm and cool seasons are associated with physical and biological variables as river entrances, artificial aeration system, reservoir depth and high amount of biomass. Water surface temperature behavior in zones with algal bloom occurrence present greater significant values, up to 3 o, than those with clearer water, indicating that water emissitiviy must be revised for these cases.