Digital twin-enabled intelligent irrigation-drainage system for precision water-salt management in saline agroecosystems
Soil salinization and freshwater scarcity are widely recognized as persistent constraints on sustainable agricultural intensification, especially in arid and semi-arid regions. This study presents a targeted approach by developing an integrated intelligent irrigation-drainage platform that combines Internet of Things (IoT)-based multi-layer environmental sensing, Long Short-Term Memory (LSTM) deep learning for predictive modeling, and digital twin-assisted management. A closed-loop irrigation-drainage infrastructure was concurrently implemented, incorporating multi-source water reuse pipelines, subsurface drainage networks, and photovoltaic-powered units for brackish water purification. Field deployment in saline-affected agricultural plots in northwestern China enabled high-frequency monitoring of soil moisture, temperature, and salinity dynamics under complex soil stratification conditions. The Long Short-Term Memory (LSTM) model demonstrated high predictive accuracy (R² = 0.97 for soil electrical conductivity and R² = 0.92 for water content), while feature importance analysis identified soil moisture, temperature, and groundwater depth were the dominant factors driving water-salt interactions. Coordinated irrigation and drainage scheduling significantly reduced soil salinity across permeable soil profiles, while closed-loop water reuse strategies enhanced water-use efficiency without increasing salinity risks. This study highlights the potential of intelligent irrigation-drainage systems integrating real-time monitoring, predictive modeling, and closed-loop water reuse to enhance salt leaching efficiency, optimize water utilization, and stabilize crop production across heterogeneous saline agroecosystems. • A digital twin-based irrigation-drainage system was developed for saline farmlands. • Real-time monitoring and Long Short-Term Memory (LSTM) prediction enabled adaptive water-salt control. • A closed-loop reuse system improved leaching efficiency and reduced salinity. • Field experiments demonstrated significant salt reduction across soil profiles.
Authors
- Chuansong Zhang
- Feng Xiong (ORCID: https://orcid.org/0000-0001-6029-0204)
- Mei Qin (ORCID: https://orcid.org/0000-0003-4261-2075)
- Guorong Ma (ORCID: https://orcid.org/0000-0003-3308-8021)
- Yongcheng Ma (ORCID: https://orcid.org/0000-0001-5498-8040)
- Peijie Li (ORCID: https://orcid.org/0000-0003-1026-0925)
- Kepeng Feng
Institutions
- Shihezi University (CN)
- Ningxia University (CN)
- Ningxia Water Conservancy (CN)
Publication Details
- Journal
- Agricultural Water Management
- Published
- 2025-11-06
- DOI
- https://doi.org/10.1016/j.agwat.2025.109957
- Citations
- 2
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 3.50