SMAP-HydroBlocks, a 30-m satellite-based soil moisture dataset for the conterminous US.

Area of Science:

• Earth Science
• Hydrology
• Remote Sensing

Background:

• Soil moisture is critical for land-atmosphere interactions, influencing water resources, agriculture, climate, and ecosystems.
• Current soil moisture monitoring relies on coarse satellite data and limited in-situ networks, failing to capture landscape variability.

Purpose of the Study:

• Introduce SMAP-HydroBlocks (SMAP-HB), a novel 30-m resolution satellite-based surface soil moisture dataset for the conterminous US (2015-2019).
• Enhance the spatial detail and accuracy of soil moisture monitoring to better support critical applications.

Main Methods:

• Developed a scalable cluster-based merging scheme integrating land surface modeling, radiative transfer modeling, and machine learning.
• Combined Soil Moisture Active Passive (SMAP) satellite microwave data with in-situ observations.
• Validated the dataset using 1,192 observational sites.

Main Results:

• SMAP-HB demonstrated superior performance compared to existing SMAP products, with a median temporal correlation of 0.73 and Kling-Gupta Efficiency of 0.52.
• Achieved significantly improved spatial detail and accuracy in representing soil moisture variability.
• The dataset provides high-resolution soil moisture data across the conterminous United States.

Conclusions:

• SMAP-HB represents a significant advancement in high-resolution soil moisture data availability and accuracy.
• The dataset offers enhanced capabilities for studying land-atmosphere interactions and managing water resources.
• SMAP-HB is publicly accessible for research and application purposes.