Effects of vegetation restoration on soil organic carbon on the Loess Plateau, China using a combined remote sensing and process-based modeling approach
• A new model was developed to consider vertical SOC transfer along soil profiles. • Different restoration starting times in different grids were considered to calculate restoration effect. • It takes about 150 years for topsoil to reach a stable SOC after restoration. • Climate change had relatively small impacts on long-term SOC storage. • Restoration from cropland to forest had the highest effect on SOC than other types of restoration. A series of vegetation restoration programs (VRPs) have been implemented on the Loess Plateau, China to increase vegetation cover and soil organic carbon (SOC) content. Here, we used a Coupled Litter-Soil (CLS) model to estimate the spatiotemporal distribution of SOC change (0–100 cm) on the VRPs areas on the Loess Plateau from the vegetation restoration starting to 2100. The vertical transport process of SOC along the profile was considered in the model. Due to the starting time of VRPs varied across different areas on the Loess Plateau, we detected the implementation areas and starting times of VRPs from remote sensing data to constrain the model. Results indicate that between the restoration starting and the year 2022, VRPs areas increased a total of 0.8 Pg C of SOC (0–100 cm), showing an increasing trend of SOC from northwest to southeast on the Loess Plateau, China. Under the business-as-usual scenario (2022), our model predicts that SOC will reach a steady-state after 150 years of VRPs implementation, with a potential SOC storage of 2.9 Pg C (0–100 cm). The differences in SOC density among different future climate scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) were non-significant. Our study provides a platform for combining remote sensing techniques and a process-based model to better estimate and predict SOC change after the implementation of an ecological restoration program.
Authors
- Ying Qu (ORCID: https://orcid.org/0000-0001-9683-7136)
- Xianlei Fan (ORCID: https://orcid.org/0000-0001-8124-2260)
- Edith Bai (ORCID: https://orcid.org/0000-0003-0495-6504)
- Yunqiang Wang (ORCID: https://orcid.org/0000-0003-3380-549X)
Institutions
- Northeast Normal University (CN)
- Chinese Academy of Sciences (CN)
- Institute of Earth Environment (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- Geoderma
- Published
- 2025-03-18
- DOI
- https://doi.org/10.1016/j.geoderma.2025.117260
- Citations
- 3
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 5.15