Improving Soil Water Content and Surface Flux Estimation Based on Data Assimilation Technique
Land surface model is a powerful tool for estimating continuous soil water content (SWC) and surface fluxes. However, simulation error tends to accumulate in the process of model simulation due to the inevitable uncertainties of forcing data and the intrinsic model errors. Data assimilation techniqu...
Main Authors: | He Chen, Rencai Lin, Baozhong Zhang, Zheng Wei |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-07-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/14/13/3183 |
Similar Items
-
Coupled Calculation of Soil Moisture Content and PML Model Based on Data Assimilation in the Hetao Irrigation District
by: Hao Duan, et al.
Published: (2024-03-01) -
An Improved Approach of Winter Wheat Yield Estimation by Jointly Assimilating Remotely Sensed Leaf Area Index and Soil Moisture into the WOFOST Model
by: Wen Zhuo, et al.
Published: (2023-03-01) -
Data Assimilation in Spatio-Temporal Models with Non-Gaussian Initial States—The Selection Ensemble Kalman Model
by: Maxime Conjard, et al.
Published: (2020-08-01) -
Assimilation of Wheat and Soil States into the APSIM-Wheat Crop Model: A Case Study
by: Yuxi Zhang, et al.
Published: (2021-12-01) -
Assimilation of LAI Derived from UAV Multispectral Data into the SAFY Model to Estimate Maize Yield
by: Xingshuo Peng, et al.
Published: (2021-03-01)