Soil Moisture Prediction Using the VIC Model Coupled with LSTMseq2seq
Soil moisture (SM) is a key variable in agricultural ecosystems and is crucial for drought prevention and control management. However, SM is influenced by underlying surface and meteorological conditions, and it changes rapidly in time and space. To capture the changes in SM and improve the accuracy...
Saved in:
Main Authors: | Xiuping Zhang, Xiufeng He, Rencai Lin, Xiaohua Xu, Yanping Shi, Zhenning Hu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-07-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/17/14/2453 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Estimation of recharge from soil water profiles under dryland agriculture, eucalypt plantation, and natural woodland in the Wimmera district of Victoria /
by: Kennett-Smith, A. K., (Ashleigh Kenneth)
Published: (1992) -
Application of Seq2Seq models for predicting the development of thunderstorm activity to enhance the pilot’s situational awareness in flight
by: G. V. Kovalenko, et al.
Published: (2025-03-01) -
A PatchTST-GRU based heterogeneous seq2seq model with numerical weather prediction refinement for multi-step wind power forecasting
by: Shiwei Xu, et al.
Published: (2025-06-01) -
Combined Analysis of BSA-Seq and RNA-Seq Reveals Candidate Genes for <i>qGS1</i> Related to Sorghum Grain Size
by: Qi Shen, et al.
Published: (2025-06-01) -
Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX.
by: P. A. Vyaznikov, et al.
Published: (2022-01-01)