Scientists Develop Hourly Drought Monitoring Tool Using Satellite Data

Scientists have developed a high-resolution, hourly solar-induced chlorophyll fluorescence (SIF) dataset that provides unprecedented real-time monitoring of vegetation photosynthesis during drought conditions. The new method, published in the Journal of Remote Sensing, overcomes significant limitations in existing drought assessment techniques by capturing critical diurnal physiological changes in plants.

The research team from Chinese universities created the HC-SIFoco dataset using machine learning techniques, specifically the LightGBM model, which fuses data from OCO-2 and OCO-3 satellites. By integrating variables such as photosynthetically active radiation, temperature, vapor pressure deficit, soil moisture, and land cover types, researchers developed a tool with remarkable accuracy, demonstrating R² values of 0.89 for SIF and 0.94 for gross primary productivity.

Key findings reveal that drought stress rapidly decreases vegetation fluorescence efficiency, with vapor pressure deficit accounting for over 70% of SIF decline during drought conditions. The study specifically examined the Yangtze River Basin, demonstrating that midday photosynthesis depression increased by approximately 3% during the 2022 drought, with seasonal photosynthesis peaks occurring earlier than in previous years.

This innovative dataset holds significant potential for ecosystem management and climate change mitigation. By providing real-time insights into vegetation responses to extreme weather events, the research could help develop early warning systems for drought impacts on agriculture and biodiversity. The high-resolution approach allows scientists to observe subtle changes in plant physiology that were previously undetectable with traditional monitoring methods.

The breakthrough represents a critical advancement in understanding how global warming affects vegetation photosynthesis and the broader carbon cycle. As drought frequency and intensity increase worldwide, such precise monitoring tools become increasingly essential for predicting and managing environmental changes.