Generating high accuracy multi-layer soil moisture at daily scale in the black soil region of China
The black soil region of China is one of the four major black soil regions in the world and is an important grain production base. High-accuracy soil moisture data are therefore crucial for understanding the mechanisms of drought and waterlogging on crop yields. Here, we present a 16 years (2008-2023) soil moisture dataset (DMSN) with both high spatiotemporal resolution and multi-layer spatiotemporal consistency (2 km, daily, 0-10, 10-20, 20-50, 50-100 cm),using Community Land Model 3.5 (CLM3.5). The DMSM showed excellent performance, with validation at seven field monitoring sites in the black soil region, the correlation coefficient (R) was generally greater than 0.7, the RMSE varied between 0.035 and 0.07, the MAE ranged from 0.03 to 0.06, and the bias remained between -0.02 and 0.02. The DMSM effectively captured daily, inter-annual, and seasonal soil moisture variations, providing important insights into soil moisture dynamics in this critical black soil region. These results help in understanding the potential drivers of drought and waterlogging and their impact on crop yields.
Authors
- Haiqing Song
- Jingxuan Sun (ORCID: https://orcid.org/0000-0003-1130-1354)
- Yangguang Wang
- Jia Mu
- Jingquan Ren
- Guangxin Zhang (ORCID: https://orcid.org/0000-0001-5339-0426)
- Lijun Wang (ORCID: https://orcid.org/0000-0001-8712-1275)
- Liwen Chen (ORCID: https://orcid.org/0000-0002-8432-9406)
- Cong Liu (ORCID: https://orcid.org/0000-0003-2470-4160)
- Mei-Yu Wang
Institutions
- Chinese Academy of Sciences (CN)
- Banner Health (US)
- Jilin Jianzhu University (CN)
- Northeast Institute of Geography and Agroecology (CN)
- Inner Mongolia Autonomous Region Meteorological Bureau (CN)
- Jilin Meteorological Bureau (CN)
Publication Details
- Journal
- Scientific Data
- Published
- 2025-10-28
- DOI
- https://doi.org/10.1038/s41597-025-05986-7
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chinese Academy of Sciences
- China Meteorological Administration
- People's Government of Jilin Province
- Education Department of Jilin Province