In a groundbreaking development for Earth observation and water resource management, researchers have harnessed near real-time land cover data to create a dynamic, high-resolution map of global surface water extents. This innovative approach, detailed in a study led by Arushi Khare from the Hydrology & Hydroinformatics Innovation Lab at the University of Texas at Arlington, promises to revolutionize how we understand and respond to global water dynamics. The research was published in the journal ‘Environmental Research Letters’, which translates to ‘Letters on Environmental Research’ in English.
The study builds upon traditional methods of mapping global surface water extents (GSWE), which have typically relied on static estimates or annual averages. By leveraging the Sentinel-2 satellite’s Dynamic World (DW) land cover products, Khare and her team have produced a first-of-its-kind dataset with a resolution of 10 meters, covering the years 2015 to 2023. This dataset estimates 2.5 million square kilometers of permanent waters and 8 million square kilometers of seasonal waters worldwide.
One of the most intriguing findings from this research is the discrepancy observed when comparing the Sentinel-2 based data with contemporary Landsat-based GSWE. “Our data mapped less water within the >50% probability of occurrence range, suggesting a lower presence of open permanent water, especially in high latitudes,” Khare explained. This deviation from previously understood patterns opens new avenues for research and could significantly impact water resource management strategies.
The implications for the energy sector are substantial. Accurate and timely data on surface water dynamics are crucial for hydropower generation, thermal power plant cooling, and water resource management for oil and gas operations. “This research provides a prototype Open Science operational framework that extracts routinely available DW products, runs geospatial analytics, and creates actionable water information,” Khare noted. This framework can be invaluable for energy companies looking to optimize their water usage and mitigate risks associated with water scarcity or excess.
The study also highlights the practical applications of this technology through real-world examples. Instant mapping of floods in Spain, drought monitoring in Lake Urmia in Central Asia, and frequent monitoring of river extent changes at the Ganges–Brahmaputra confluence demonstrate the versatility and immediacy of this approach. “Our key contribution is the interoperability with other existing GSWE applications, making it a powerful tool for educators, researchers, and stakeholders at any scale of practical interest,” Khare added.
This research not only advances our understanding of global surface water dynamics but also sets the stage for future developments in Earth observation and water resource management. As Khare and her team continue to refine their methods and expand their dataset, the energy sector and other industries stand to benefit from more accurate, timely, and actionable water information. The study, published in ‘Environmental Research Letters’, marks a significant step forward in the integration of remote sensing and open science capabilities for global water monitoring.