Retrieving Soil Moisture in the First-Level Tributary of the Yellow River–Wanchuan River Basin Based on CD Algorithm and Sentinel-1/2 Data
Author:
Liu Xingyu1ORCID, Liu Xuelu2, Li Xiaodan3, Zhang Xiaoning1ORCID, Nian Lili1, Zhang Xinyu2, Wang Pengkai2, Ma Biao2, Li Quanxi2, Zhang Xiaodong2, Hui Caihong2, Bai Yonggang2, Bao Jin2, Zhang Xiaoli2, Liu Jie2, Sun Jin2, Yu Wenting2, Luo Li3
Affiliation:
1. College of Forestry, Gansu Agricultural University, Lanzhou 730070, China 2. College of Resources and Environment, Gansu Agricultural University, Lanzhou 730070, China 3. College of Management, Gansu Agricultural University, Lanzhou 730070, China
Abstract
Lanzhou is the only provincial capital city in Northwest China where the main stream of the Yellow River and its tributaries flow through the city. Due to its geographical location and the influence of various factors, it is difficult to evaluate and simulate the climatic, hydrological, and ecological processes of the main stream of the Yellow River and its tributaries in the region. In this study, the Wanchuan River basin, currently undergoing ecological restoration, was selected as the study area. Seasonal backscatter differences generated using Sentinel-1/2 (S1/S2) data and the CD algorithm were used to reduce the effects of surface roughness; vegetation indices, soils, and field measurements were used to jointly characterize the vegetation contribution and soil contribution. Then, SM maps with a grid spacing of 10 m × 10 m were generated in the Wanchuan River basin, covering an area of 1767.78 km2. To validate the results, optimal factors were selected, and a training set and validation set were constructed. The results indicated a high level of the coefficient of determination (R2) of 0.78 and the root mean square error (RMSE) of 0.08 for the comparison of measured and inverted water contents, indicating that the algorithm retrieved the SM values of the study area well. Furthermore, Box line plots with ERA5-Land and GLDAS confirmed that the algorithm is in good agreement with current SM products and feasibility for soil water content inversion work in the Wanchuan River basin.
Funder
Research on Ecological Land Reclamation and Ecological Barrier Function in the Context of Multi-regulation
Subject
Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry
Reference50 articles.
1. Tebbs, E., Gerard, F., Petrie, A., and De Witte, E. (2016). Satellite Soil Moisture Retrieval: Techniques and Applications, Elsevier. 2. Baghdadi, N., El Hajj, M., Zribi, M., and Bousbih, S. (2017). Calibration of the water cloud model at C-Band for winter crop fields and grasslands. Remote Sens., 9. 3. Assessment of vegetation change on the Mongolian Plateau over three decades using different remote sensing products;Bai;J. Environ. Manag.,2022 4. Study on the spatial differences and its time lag effect on climatic factors of the vegetation in the Longitudinal Range-Gorge Region;Bao;Chin. Sci. Bull.,2007 5. Moghaddam, M.A., Ferre, T., Chen, X., Chen, K., and Ehsani, M.R. (2022). Application of Machine Learning Methods in Inferring Surface Water Groundwater Exchanges using High Temporal Resolution Temperature Measurements. arXiv.
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