Variabilidade da umidade do solo nos biomas brasileiros a partir do uso de dados de satélites e reanálise: uma análise com a precipitação

Abstract

Soil water storage is essential for understanding hydrological dynamics and the sustainability of water resources. While in situ monitoring data are limited, remote sensing has proven to be crucial, with satellites such as SMOS and SMAP providing global information on soil moisture, contributing to the understanding of ecosystem behavior, especially at the macroscale. Products like ERA5-Land have shown significant advances in the analysis of moisture in relation to precipitation and evapotranspiration. The aim of this study was to analyze the variability of the soil moisture index in parallel with precipitation data from the IMERG V07 product, considering the Brazilian biomes: Pampa, Pantanal, Caatinga, Cerrado, Amazon, and Atlantic Forest, over the period from 2000 to 2024. Data were extracted from the ERA5-Land and IMERG V07 platforms, both made available through Google Earth Engine (GEE). The analysis revealed distinct patterns among the biomes over the 2000–2024 time series. In the Amazon and Atlantic Forest, high precipitation rates maintained elevated soil moisture levels at all depths, with stability over the years. The Pantanal showed a reduction in moisture in deeper layers from 2020 onwards, associated with an increase in wildfires. In the Cerrado, a decline in surface moisture and stability at depth was observed, reflecting strong seasonality and the impacts of drought. The Caatinga exhibited low moisture levels and a decreasing trend in the series, with high sensitivity to drought events. The Pampa, in turn, showed hydrological stability, with low surface values and higher levels at depth, attributed to the clayey texture of the soils. The correlation between moisture and climatic variables is vital for improving forecasting models and identifying areas susceptible to desertification and biodiversity loss. Furthermore, it is important to emphasize the need for validation of these estimates, both for precipitation and soil moisture, in order to strengthen the reliability of analyses at regional and national scales.