Published January 1, 2022 | Version v1
Conference paper Open

Spatio-Temporal Analysis of Water Surface Temperature in a Reservoir and its Relation with Water Quality in a Climate Change Context.

Creators

  • 1. Instituto Gulich, Universidad Nacional de Córdoba & CONICET

Description

Remote sensing community is making enormous efforts  to implement  early warning  systems capable for following spatio-temporal  patterns of water quality and climate change risk indicators, being Horizon 2030 EOXPOSURE project one of them. This work presents first results of surface temperature Landsat 8 Level 2 Collection 2 products analysis  for a  reservoir and compare them with field data measurements.  A Root Mean Square Error  (RMSE) of 1.7oC and a Mean Absolute Percentage 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 1.1oC 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.   Water surface temperature behavior in zones with algal bloom occurrence  present greater significant values, up to 3oC,  than those with clearer water, indicating that water emissitiviy must be revised for these cases. 

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