Ishag et al. (2025) Using Remote Sensing and Machine Learning to Determine Past, Current and Future Crop Water Use From the Nubian Sandstone Aquifer

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: JAWRA Journal of the American Water Resources Association
• Year: 2025
• Date: 2025-12-01
• Authors: Moaz N. Ishag, Aaron R. Mittelstet, Derek M. Heeren, R. H. Wang
• DOI: 10.1111/1752-1688.70076

Research Groups

Not specified in abstract.

Short Summary

This study quantifies the increase in irrigated land and associated crop water use from the Nubian Sandstone Aquifer System (NSAS) between 2000 and 2024, revealing a significant doubling of total irrigated area and a substantial increase in water abstraction, with critical implications for sustainable water management.

Objective

• Quantify the increase in irrigated hectares (both pivot and non-pivot) during the last decade.
• Identify major irrigated crop types and their water requirements.
• Quantify the increase in crop water use from the NSAS from 2000 to 2024.

Study Configuration

• Spatial Scale: Nubian Sandstone Aquifer System (NSAS), spanning Egypt, Sudan, Libya, and Chad.
• Temporal Scale: "Last decade" (for irrigated area increase), and 2000 to 2024 (for crop types, water requirements, and crop water use increase).

Methodology and Data

• Models used: Not explicitly detailed in abstract.
• Data sources: Long-term satellite remote sensing observations.

Main Results

• The overall irrigated area under the NSAS has increased significantly over time.
• The total irrigated area nearly doubled from 14,635 km² in 2000 to 24,811 km² in 2024.
• The area irrigated directly from the NSAS increased from 1257 km² to 3268 km² over the same period.
• Crop water use from the NSAS increased from an estimated 1.4 km³ in 2000 to 3.64 km³ in 2024.

Contributions

• Provides quantitative insights into the expansion of irrigated agriculture and associated water consumption from the NSAS, a critical transboundary aquifer.
• Offers crucial data for policymakers to develop strategies for sustainable water and land use management in the NSAS region for present and future generations.

Funding

Not specified in abstract.

Citation

@article{Ishag2025Using,
  author = {Ishag, Moaz N. and Mittelstet, Aaron R. and Heeren, Derek M. and Wang, R. H.},
  title = {Using Remote Sensing and Machine Learning to Determine Past, Current and Future Crop Water Use From the Nubian Sandstone Aquifer},
  journal = {JAWRA Journal of the American Water Resources Association},
  year = {2025},
  doi = {10.1111/1752-1688.70076},
  url = {https://doi.org/10.1111/1752-1688.70076}
}