Estimativa da evaporação do açude Quixeramobim, Ceará, utilizando sensoriamento remoto

Abstract

Studies on water loss through evaporation are becoming increasingly strategic in water resource management. With this in mind, the aim of this study was to estimate evaporation in a reservoir located in the semi-arid region of Ceará, using remote sensing - the Quixeramobim reservoir. This required the use of images from the Landsat 8 satellite (OLI) in conjunction with an evaporation estimation method based on the energy balance: AquaSEBS. The model integrates satellite data and hydrometeorological data to estimate the latent heat rate and thus determine daily evaporation. For the climatic and hydrological data, two climatological stations were used, Quixeramobim and Morada Nova, with the Piché evaporimeter being used as the reference evaporation method. The model estimated minimum and maximum values of 0.17 mm and 7.44 mm, respectively, showing high spatial variability over the period analyzed (2013-2022), with higher evaporation rates on the banks of the reservoir, as well as in the central region of the dam. The surface temperature of the water mirror showed high values in the aforementioned areas, with a higher surface albedo. The highest average evaporated value was observed in 2016, when there was also an increase in the values for water heat flow and net radiation. The model's performance was moderate, according to the statistical data obtained from the comparison between the Piche evaporimeter at the Morada Nova climatological station and the AquaSEBS model, with R² equal to 0.5 and RMSE of 1.06 mm/day. Meteorological variables such as relative humidity, air temperature and wind speed have been shown to contribute to the reservoir's evaporation processes. The average annual relative humidity in 2017 rose to 63.87% and evaporation reached its minimum average in the same year at 1.22 mm/day, making the relationship between humidity and evaporation inversely proportional. As for air temperature, as it rises, evaporation also tends to increase, with both peaking in November 2016 at 28.9°C and 6.2 mm, respectively. Finally, it can be seen that in June 2018, as the wind speed decreases, evaporation follows the same line, as well as increasing as the winds intensify. Thus, the results show the relevance of combining the energy balance with remote sensing to estimate reservoir evaporation, making it a viable alternative for monitoring and managing the water balance.