Evapotranspiration (ET) is an important component of the hydrological cycle. Understanding the ET process has become of fundamental importance given the scenario of global change and increasing water use, especially in the agricultural sector. Determining ET over large agricultural areas is a limiting factor due to observational data availability. In this regard, remote sensing data has been used to estimate ET. In this study, we evaluated the Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface ET product estimates (hereafter MOD16 ET – MODIS Global Terrestrial Evapotranspiration Product) over two rice paddy areas in Southern Brazil, through the ET measured using the eddy covariance technique (hereafter EC). The energy balance components were evaluated during fallow and flooded seasons showing latent heat flux dominates in both seasons. The results showed that MOD16 ET underestimated EC measurements. Overall, the RMSE (root mean square error) ranged between 13.40 and 16.35 mm 8-day⁻¹ and percent bias (PBIAS) ranged between −33.7% and −38.7%. We also assessed the ET (measured and estimated) main drivers, with EC yielding higher correlation against observed net radiation (R_n) and global radiation (R_g), followed by air temperature (Temp) and vapor pressure deficit (VPD), whilst MOD16 ET estimates yielded higher correlation against leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR). The MOD16 algorithm was forced with meteorological measurements but the results did not improve as expected, suggesting a low sensitivity to meteorological inputs. Our results indicated when a water layer was present over the soil surface without vegetation (LAI around zero), the largest differences between EC measurements and MOD16 ET were found. In this period, the expected domain of soil evaporation was not observed in MOD16 ET physical processes partition, indicating the algorithm was not able to detect areas with high soil moisture. In general, the MOD16 ET product presented low accuracy when compared against experimental measurements over flooded rice paddy, suggesting more studies are necessary, in order to reduce uncertainties associated to the land cover conditions.

The application of Nondestructive Testing methods (NDT) may be an interesting strategy to monitor the condition state of reinforced concrete structures, especially when there are problems related to mixing, conveying or placing the concrete. Among the NDT methods, the Ultrasonic Pulse Velocity (UPV) has been one of the most used in various fields of civil engineering, due to the ease of operation, low cost, test velocity and low level of damage to the surface analyzed. This work aims to study the influence of certain technological variables in the results obtained through UPV tests. With this aim two large blocks were cast at the laboratory, with dimensions close to real concrete elements. One of the elements was reinforcement with steel meshes on both sides while the other was cast without reinforcement. Inside these elements objects were introduced to reproduce internal concrete flaws. To facilitate the analysis the results were represented by means of a surface mapping image technique and were also subjected to statistical analysis. Through the study it was demonstrated that the correct choice of test parameters is crucial to obtain a right interpretation of UPV results from real structures.

This study aims to evaluate the performance of MOD16 and GLEAM evapotranspiration (ET) datasets in nine eddy covariance monitoring sites. Data from both ET products were downloaded and its daily means calculated. Evapotranspiration estimations were then compared to the observed ET in the eddy covariance monitoring sites from the Large-Scale Biosphere-Atmosphere Experiment in the Amazon (LBA). We performed a statistical analysis using the correlation coefficient (R), the root mean square error (RMSE) and BIAS. Results indicate that, in general, both products can represent the observed ET in the eddy covariance flux towers. MOD16 and GLEAM showed similar values to the calculated statistics when ET estimates were compared to observed ET. Model estimates and eddy covariance flux towers are subject to uncertainties that influence the analysis of remotely-sensed ET products.