Water temperature regulates many processes in lakes; therefore, evaluating it is essential to understand its ecological status and functioning, and to comprehend the impact of climate change. Although few studies assessed the accuracy of individual sensors in estimating lake-surface-water temperature (LSWT), comparative analysis considering different sensors is still needed. This study evaluated the performance of two thermal sensors, MODIS and Landsat 7 ETM+, and used Landsat methods to estimate the SWT of a large subtropical lake. MODIS products MOD11 LST and MOD28 SST were used for comparison. For the Landsat images, the radiative transfer equation (RTE), using NASA’s Atmospheric Correction Parameter Calculator (AtmCorr) parameters, was compared with the single-channel algorithm in different approaches. Our results showed that MOD11 obtained the highest accuracy (RMSE of 1.05 ° C), and is the recommended product for LSWT studies. For Landsat-derived SWT, AtmCorr obtained the highest accuracy (RMSE of 1.07 ° C) and is the recommended method for small lakes. Sensitivity analysis showed that Landsat-derived LSWT using the RTE is very sensitive to atmospheric parameters and emissivity. A discussion of the main error sources was conducted. We recommend that similar tests be applied for Landsat imagery on different lakes, further studies on algorithms to correct the cool-skin effect in inland waters, and tests of different emissivity values to verify if it can compensate for this effect, in an effort to improve the accuracy of these estimates.

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In three-dimensional simulations of free-surface flow where the vertical velocities are relevant, such as in lakes, estuaries, reservoirs, and coastal zones, a nonhydrostatic hydrodynamic approach may be necessary. Although the nonhydrostatic hydrodynamic approach improves the physical representation of pressure, acceleration and velocity fields, it is not free of numerical diffusion. This numerical issue stems from the numerical solution employed in the advection and diffusion terms of the Reynolds-averaged Navier–Stokes (RANS) and solute transport equations. The combined use of high-resolution schemes in coupled nonhydrostatic hydrodynamic and solute transport models is a promising alternative to minimize these numerical issues and determine the relationship between numerical diffusion in the two solutions. We evaluated the numerical diffusion in three numerical experiments, for different purposes: The first two experiments evaluated the potential for reducing numerical diffusion in a nonhydrostatic hydrodynamic solution, by applying a quadratic interpolator over a Bilinear, applied in the Eulerian–Lagrangian method (ELM) step-ii interpolation, and the capability of representing the propagation of complex waves. The third experiment evaluated the effect on numerical diffusion of using flux-limiter schemes over a first-order Upwind in solute transport solution, combined with the interpolation methods applied in a coupled hydrodynamic and solute transport model. The high-resolution methods were able to substantially reduce the numerical diffusion in a solute transport problem. This exercise showed that the numerical diffusion of a nonhydrostatic hydrodynamic solution has a major influence on the ability of the model to simulate stratified internal waves, indicating that high-resolution methods must be implemented in the numerical solution to properly simulate real situations.

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<p>Climate change impacts on lake surface water temperature (LSWT) have been mostly investigated in deep northern lakes, and are less understood in southern hemisphere shallow lakes. We evaluated the seasonal warming rates of a large (surface area c.a. 10000 km²) shallow choked lagoon in southern Brazil, with a 22 yr time series of MODIS-derived LSWT, and meteorological data. We found high LSWT warming, with a rate of 0.6°C dec<sup>-1</sup> in spring and of 0.3°C dec<sup>-1 </sup>in summer. We also found a high correlation between water and mean air temperature trends, as well as a substantial shortening of the cold season. Spatially, there was some homogeneity in the warming rates but prominent point spatial differences, which may result from the variability of the tributaries’ temperature or discharge or decreased water transparency. The high warming rates found here are comparable to those found in deep northern lakes although the changes and processes of heating differ. The stronger warming in early spring can result in accelerated process rates and an earlier start of the phytoplankton growing season.</p>

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