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

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 1.7$^o$C 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 1.1$^o$C 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 3$^o$C,  than those with clearer water, indicating that water emissitiviy must be revised for these cases.