Satellite-based detection of agricultural flash droughts and their ecosystem impacts in southeastern South America

Flash droughts are rapid-onset events that develop within weeks, imposing severe and often unexpected impacts on agriculture. Their monitoring remains challenging due to several factors, including the scarcity of root-zone soil moisture (RZSM) observations and the lack of methodological consensus. This study has two main objectives: (1) to evaluate the applicability of the European Space Agency Climate Change Initiative Combined Root-Zone Soil Moisture product (ESA CCI COM RZSM) for detecting agricultural flash droughts (AFDs) across southeastern South America (SESA), and (2) to assess how satellite-based indicators obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) capture their physical evolution and agricultural impacts.

We apply two complementary AFD detection frameworks to ESA CCI COM and ERA5 RZSM data for 1979–2022: a statistical percentile-based approach and a physically based formulation derived from the Soil Water Deficit Index (SWDI). The percentile method detects AFDs as rapid transitions from above-normal to below-normal soil moisture. The SWDI identifies events through shifts from near-optimal water availability to physiological stress based on soil hydraulic properties. To evaluate agricultural impacts, we analyze satellite-derived evapotranspiration (EVT) and vegetation indicators from MODIS for two representative events in central-eastern and northern SESA. Vegetation indicators include the Land Surface Water Index (LSWI), fraction of absorbed Photosynthetically Active Radiation (fPAR), and Gross Primary Productivity (GPP).

Our results suggest that AFD detection is strongly conditioned by both methodological framework and dataset characteristics. The percentile-based approach tends to overestimate AFD occurrence in persistently wet or dry regimes, where small fluctuations are amplified after percentile transformation. In contrast, the SWDI-based approach preserves regional hydroclimatic gradients and provides a physically consistent representation of plant water stress. Regarding the dataset, ESA CCI COM RZSM captures the main spatial patterns and seasonal cycles of soil moisture depicted by ERA5 across SESA. However, it exhibits smoother short-term variability, delayed drying, and lower absolute soil moisture than ERA5, which could be attributed to the empirical filtering used to propagate surface signals into deeper layers.

Satellite-derived indicators effectively capture the evolution of AFDs across SESA. Soil moisture depletion is followed by reductions in EVT as ecosystems transition from energy- to water-limited conditions. Vegetation indicators respond shortly thereafter: LSWI reveals declining canopy water content, fPAR shows reduced photosynthetic activity, and GPP reflects suppressed ecosystem productivity. The magnitude and spatial extent of these impacts depend on antecedent soil moisture and land-cover type, highlighting the importance of background conditions in modulating drought severity.

Overall, the results demonstrate that ESA CCI COM RZSM provides valuable information for regional AFD monitoring when its physical limitations are considered. The coherence among soil moisture, surface fluxes, and biological responses highlights the potential of satellite observations to track the onset, intensification, and agricultural consequences of AFDs. These results strengthen the use of multi-sensor satellite systems for operational early-warning applications and impact assessment across climate-sensitive agricultural regions such as SESA.