Karra et al. (2026) Digital twin–based adaptive irrigation management framework for enhancing water use efficiency and drought resilience in the Kaleshwaram Lift Irrigation System

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Identification

• Journal: Journal of Applied and Natural Science
• Year: 2026
• Date: 2026-09-20
• Authors: Rahul Karra, Majji Kiranmai Reddy
• DOI: 10.31018/jans.v18i3.7717

Research Groups

• Indian Institute of Technology (IIT) Hyderabad
• Water Resources Engineering Laboratory
• Department of Civil Engineering

Short Summary

This study introduces an Adaptive GDD framework based on a Digital Twin approach to enhance water use efficiency, supply security, spatial equity, and drought resistance in large-scale irrigation systems. The adaptive operation reduced losses by 60% to 65%, augmented water use efficiency by 52% – 73%, and increased supply reliability by 62% – 88%.

Objective

• Investigate the effectiveness of an Adaptive GDD framework based on a Digital Twin approach in improving the performance of large-scale irrigation systems.

Study Configuration

• Spatial Scale: Large multi-stage lift irrigation system (KLIS) in urban semi-arid regions.
• Temporal Scale: Seasonal variations in hydrology and evapotranspiration.

Methodology and Data

• Models used: Digital Twin approach with physics-based simulation.
• Data sources: Boundary conditions, energy consumption data under conventional (rule-based) operation and adaptive operation.

Main Results

• Adaptive operation reduced losses by 60% to 65% in the dry season.
• Water use efficiency increased by 52% – 73%.
• Supply reliability raised by 62% – 88%.
• Losses in total drought season reduced by approximately 51%.
• Recovery time shortened from 8 – 9 months to 4 – 5 months.

Contributions

The study provides a measurable increase in efficiency, equity, and drought-resilience of large lift irrigation systems without the need for additional infrastructure or water extraction. The incorporation of forecasting, physics-based simulation, and adaptive control showcases the effectiveness of the Adaptive GDD framework.

Funding

• This research was funded by the [project name] (reference code: [code]) and supported by the Department of Science and Technology (DST) under the [program name].

Citation

@article{Karra2026Digital,
  author = {Karra, Rahul and Reddy, Majji Kiranmai},
  title = {Digital twin–based adaptive irrigation management framework for enhancing water use efficiency and drought resilience in the Kaleshwaram Lift Irrigation System},
  journal = {Journal of Applied and Natural Science},
  year = {2026},
  doi = {10.31018/jans.v18i3.7717},
  url = {https://doi.org/10.31018/jans.v18i3.7717}
}