Surface Water Transitions 1984-2022: A Global Dataset at Annual Resolution

Area of Science:

• Earth and Environmental Sciences
• Remote Sensing
• Hydrology

Background:

• Global surface water dynamics are complex, influenced by seasonal variations and climate events, challenging accurate long-term monitoring.
• Satellite technology and cloud computing advancements facilitate large-scale surface water change detection.
• Existing datasets often struggle to differentiate persistent changes from seasonal fluctuations.

Purpose of the Study:

• To introduce the first global dataset detailing the annual timing of surface water advance and recession from 1984 to 2022.
• To provide a tool for analyzing persistent changes in various surface water features.
• To support research and water management by offering insights into the drivers of water dynamics.

Main Methods:

• Development of a novel algorithm to identify persistent surface water changes by filtering seasonal fluctuations.
• Global mapping of surface water transitions at an annual resolution using satellite data.
• Creation of a dataset where each 30m x 30m pixel records the year of water advance or recession.

Main Results:

• A comprehensive global dataset identifying the timing of surface water transitions (advance/recession) annually from 1984 to 2022.
• The dataset covers diverse water bodies including rivers, lakes, reservoirs, flooded agriculture, and coastal regions.
• Pixel-level data provides the specific year of transition for each 30m x 30m area.

Conclusions:

• The dataset offers unprecedented insights into the timing and drivers of global surface water dynamics.
• Its focus on persistent changes overcomes limitations of seasonal variability in previous monitoring efforts.
• Accessible data supports scientific research, NGOs, policymakers, and water managers in addressing critical water resource challenges.