A Daily Reference Crop Evapotranspiration Forecasting Model Based on Improved Informer

Junrui Pan, Long Yu (), Bo Zhou and Junhong Zhao
Additional contact information
Junrui Pan: College of Electronic Engineering & College of Artificial Intelligence, South China Agricultural University, Guangzhou 510642, China
Long Yu: College of Electronic Engineering & College of Artificial Intelligence, South China Agricultural University, Guangzhou 510642, China
Bo Zhou: Tea Research Institute, Guangdong Academy of Agricultural Sciences & Guangdong Provincial Key Labora-tory of Tea Plant Resources Innovation and Utilization, Guangzhou 510640, China
Junhong Zhao: Institute of Facility Agriculture, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China

Agriculture, 2025, vol. 15, issue 9, 1-21

Abstract: Daily reference crop evapotranspiration (ET 0 ) is crucial for precision irrigation management, yet traditional prediction methods struggle to capture its dynamic variations due to the complexity and nonlinearity of meteorological conditions. To address this, we propose an Improved Informer model to enhance ET 0 prediction accuracy, providing a scientific basis for agricultural water management. Using meteorological and soil data from the Yingde region, we employed the Maximal Information Coefficient (MIC) to identify key influencing factors and integrated Residual Cycle Forecasting (RCF), Star Aggregate Redistribute (STAR), and Fully Adaptive Normalization (FAN) techniques into the Informer model. MIC analysis identified total shortwave radiation, sunshine duration, maximum temperature at 2 m, soil temperature at 28–100 cm depth, and surface pressure as optimal features. Under the five-feature scenario (S3), the improved model achieved superior performance compared to Long Short-Term Memory (LSTM) and the original Informer models, with MAE reduced to 0.065 (LSTM: 0.637, Informer: 0.171) and MSE to 0.007 (LSTM: 0.678, Informer: 0.060). The inference time was also reduced by 31%, highlighting the enhanced computational efficiency. The Improved Informer model effectively captures the periodic and nonlinear characteristics of ET 0 , offering a novel solution for precision irrigation management with significant practical implications.

Keywords: crop evapotranspiration; prediction models; maximal information coefficient; precision irrigation; periodicity (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/15/9/933/pdf (application/pdf)
https://www.mdpi.com/2077-0472/15/9/933/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:15:y:2025:i:9:p:933-:d:1642062

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().