Khandappa et al. (2025) Improving Irrigation Scheduling through Deep Learning-Based Reference Evapotranspiration Estimation

Identification

• Journal: Engineering Technology & Applied Science Research
• Year: 2025
• Date: 2025-12-08
• Authors: Praveen Kumar Khandappa, Manjula Sunkudkatte Haladappa
• DOI: 10.48084/etasr.15002

Research Groups

[Information not extractable due to corrupted input.]

Short Summary

[Information not extractable due to corrupted input.]

Objective

• [Information not extractable due to corrupted input.]

Study Configuration

• Spatial Scale: [Information not extractable due to corrupted input.]
• Temporal Scale: [Information not extractable due to corrupted input.]

Methodology and Data

• Models used: [Information not extractable due to corrupted input.]
• Data sources: [Information not extractable due to corrupted input.]

Main Results

• [Information not extractable due to corrupted input.]

Contributions

• [Information not extractable due to corrupted input.]

Funding

• [Information not extractable due to corrupted input.]

Citation

@article{Khandappa2025Improving,
  author = {Khandappa, Praveen Kumar and Haladappa, Manjula Sunkudkatte},
  title = {Improving Irrigation Scheduling through Deep Learning-Based Reference Evapotranspiration Estimation},
  journal = {Engineering Technology & Applied Science Research},
  year = {2025},
  doi = {10.48084/etasr.15002},
  url = {https://doi.org/10.48084/etasr.15002}
}