Time series precipitation data generated by the Tropical Rainfall Measuring Mission (TRMM) have been used as a possible solution for providing rainfall information for ungauged regions. We evaluated the quality of TRMM Multi‐satellite Precipitation Analysis (TMPA) Version 6 (3B42V6) and Version 7 (3B42V7) products on a daily and monthly basis for a 14 year time series by comparing with gridded ground‐based rainfall data from ~3625 rain gauges distributed throughout Brazil. The results show that daily estimates are inaccurate for both Versions 6 and 7 (the refined index of agreement, d_r, was less than 0.6 in most of the analyzed pixels). In general, both versions perform well on monthly basis (d_r > 0.75), but no significant improvement between them could be identified with the exception of local areas. TMPA performed poorly in the northwest region, where rainfall depths are higher in Brazil; however, the quality of the ground‐based data is poor in this region because of low gauge density. Based on a seasonal analysis, we found that TMPA performed better during the dry seasons and that some improvements, although not significant, between successive versions took place over the northeast, southeast, and south regions. This study shows the value of remote sensing precipitation for providing reliable, spatiotemporally continuous precipitation at monthly timescales.

Droughts are particularly critical for Brazil because of impacts on water supply and because most (70 %) of its electricity is derived from hydroelectric generation. The Paraná basin (PB), a major hydroelectric producing region with 32 % (60 million people) of Brazil's population, recently experienced the most severe drought since the 1960s, compromising the water supply for 11 million people in São Paulo. The objective of this study is to quantify linkages between meteorological and hydrological droughts based on remote sensing, modelling, and monitoring data using the Paraná River basin in south-eastern Brazil as a case study. Two major meteorological droughts were identified in the early 2000s and 2014, with precipitation 20–50 % below the long-term mean. Total water storage change estimated from the Gravity Recovery and Climate Experiment (GRACE) satellites declined by 150 km³ between April 2011 and April 2015. Simulated soil moisture storage declined during the droughts, resulting in decreased runoff into reservoirs. As a result, reservoir storage decreased by 30 % relative to the system's maximum capacity, with negative trends ranging from 17 (May 1997–April 2001) to 25 km³ yr⁻¹ (May 2011–April 2015). Storage in upstream reservoirs is mostly controlled by natural climate forcing, whereas storage in downstream reservoirs also reflects dam operations. This study emphasizes the importance of integrating remote sensing, modelling, and monitoring data to evaluate droughts and to establish a preliminary understanding of the linkages between a meteorological and hydrological drought for future management.

Many remote sensing‐based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT‐JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM‐MOD), and Penman–Monteith Nagler model (PM‐VI). was predicted satisfactorily by all four models, with correlations consistently higher () for GLEAM and PT‐JPL, and PM‐MOD and PM‐VI presenting overall better responses in terms of percent bias (%). As for PM‐VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land‐use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America.

Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of the surface-groundwater interaction, have not yet been investigated. Here, we assess long-term trends in the streamflow and baseflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through a trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that, on average, over 86% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend along the SFR, with a spatial agreement between the decreased baseflow, increased ET, and irrigated agricultural land in the Middle SFB. We also noted a decreasing trend in TWS across the SFB exceeding –20 mm year⁻¹. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) are providing the observed reduction in the total SFR flow. A lack of significant P trends and the strong TWS depletion indicate that a P variability only has likely not caused the observed baseflow reduction, in mainly the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may likely be a driver of baseflow reduction in some regions of the SFB.

In-situ hydrological monitoring is essential for a proper decision-making process and modelling. Efforts have been made in Brazil to carry out field activities at the basin scale, but how complete and comprehensive are those studies? Where are they located? How long have they been carried out? What are the main findings? To answer these questions, an overview of experimental monitoring basins in Brazil is presented, listing their geographical locations, monitored variables, operational status, monitoring periods and main publications. We identified 60 monitored sites, spread across most Brazilian biomes, with an average monitoring period of 12 years. However, some publications from these monitoring studies are not fully accessible to the international community. Field hydrology activities in Brazil contribute to a better understanding of hydrological processes in humid and semi-arid regions and inform us about the impacts of land-use change on water quality and quantity.