Eshetie et al. (2026) High-resolution root-zone soil moisture for agricultural drought assessment using Sentinel-2 and hybrid modeling in the Lake Tana Basin, Ethiopia

Identification

• Journal: Remote Sensing Applications Society and Environment
• Year: 2026
• Date: 2026-01-01
• Authors: Habtamu Abay Eshetie, Tena Alamirew, Abebech Abera, Dejene Sahlu, Ayenew Desalegn Ayalew
• DOI: 10.1016/j.rsase.2026.101900

Research Groups

• Faculty of Civil and Water Resources Engineering, Bahir Dar Institute of Technology, Bahir Dar University, Ethiopia.
• Department of Water Resource and Irrigation Engineering, Kombolcha Institute of Technology, Wollo University, Ethiopia.
• Water and Land Resource Centre (WLRC), Addis Ababa, Ethiopia.
• Institute of Disaster Risk Management and Food Security Studies, Bahir Dar University, Ethiopia.
• Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, Germany.

Short Summary

This study develops a high-resolution framework for estimating root-zone soil moisture (RZSM) in the Lake Tana Basin by integrating Sentinel-2A data with hybrid modeling. The research identifies significant agricultural drought patterns and contrasting trends between pre-rainy (antecedent) and post-rainy (residual) soil moisture levels from 2016 to 2024.

Objective

• To estimate antecedent and residual root-zone soil moisture (RZSM) and evaluate agricultural drought severity across the Lake Tana Basin using high-resolution satellite data and hybrid statistical modeling.

Study Configuration

• Spatial Scale: Lake Tana Basin, Ethiopia (High-resolution basin-wide analysis).
• Temporal Scale: 2016–2024 (covering Belg/spring and Tsedey/autumn seasons).

Methodology and Data

• Models used: Optical Trapezoid Model (OPTRAM), Multiple Linear Regression (MLR), and Soil Moisture Deficit Index (SMDI).
• Data sources: Sentinel-2A satellite imagery (optical indices), in-situ soil moisture measurements, and auxiliary environmental variables.

Main Results

• Residual (post-rainy) RZSM was consistently higher than antecedent (pre-rainy) RZSM across the study period.
• Temporal analysis revealed a significant increasing trend in residual RZSM, while antecedent RZSM exhibited a declining trend.
• Spatial distribution showed higher soil moisture in northern, northeastern, and central districts, whereas southern and southwestern areas faced persistent moisture deficits.
• Severe agricultural drought events impacted more than 55% of the basin during the spring (Belg) of 2016 and 2024.
• A peak drought extent was recorded in autumn (Tsedey) 2018, affecting up to 93% of the basin area.

Contributions

• Establishes a scalable hybrid modeling framework (OPTRAM-MLR) for high-resolution RZSM estimation in complex agro-ecological landscapes.
• Provides a detailed assessment of the roles of antecedent and residual soil moisture in driving agricultural drought severity.
• Offers actionable spatial data for precision irrigation, drought risk mitigation, and sustainable water resource management in the Ethiopian highlands.

Funding

• Not specified in the provided text.

Citation

@article{Eshetie2026Highresolution,
  author = {Eshetie, Habtamu Abay and Alamirew, Tena and Abera, Abebech and Sahlu, Dejene and Ayalew, Ayenew Desalegn},
  title = {High-resolution root-zone soil moisture for agricultural drought assessment using Sentinel-2 and hybrid modeling in the Lake Tana Basin, Ethiopia},
  journal = {Remote Sensing Applications Society and Environment},
  year = {2026},
  doi = {10.1016/j.rsase.2026.101900},
  url = {https://doi.org/10.1016/j.rsase.2026.101900}
}

Generated by BiblioAssistant using gemini-3-flash-preview (Google API)