Gemechu et al. (2025) Assessing the Impact of Multi-Decadal Land Use Change on Agricultural Water–Energy Dynamics in the Awash Basin, Ethiopia: Insights from Remote Sensing and Hydrological Modeling

Identification

• Journal: Agronomy
• Year: 2025
• Date: 2025-12-05
• Authors: Tewekel Melese Gemechu, Huifang Zhang, Jialong Sun, Baozhang Chen
• DOI: 10.3390/agronomy15122804

Research Groups

• State Key Laboratory of Resource and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
• University of Chinese Academy of Sciences, Beijing, China
• Department of Natural Resource Management, Ambo University, Ambo, Ethiopia
• School of Marine Technology and Surveying, Jiangsu Ocean University, Lianyungang, China

Short Summary

This study assesses the impact of multi-decadal land use and land cover (LULC) changes on agricultural water–energy dynamics in Ethiopia's Awash Basin using the WRF-Hydro/Noah-MP modeling framework, revealing that early agricultural expansion increased surface runoff while later woodland recovery promoted subsurface flow and groundwater recharge.

Objective

• To assess the impact of decadal LULC changes (2001–2020) on hydrologic processes governing irrigation water supply using the coupled WRF-Hydro/Noah-MP model.
• To evaluate the associated trade-offs in water fluxes between different land use trajectories.
• To derive implications for sustainable agricultural water management and land use policy in the Awash Basin, providing actionable insights for initiatives like Ethiopia’s Green Legacy Initiative.

Study Configuration

• Spatial Scale: Awash Basin, approximately 110,000 square kilometers (8–12° N, 38–43° E). Model routing grid size of 600 meters, domain grid size of 6 kilometers × 6 kilometers.
• Temporal Scale: Multi-decadal LULC scenarios for 2001, 2010, and 2020. Simulations cover 2000–2024. Streamflow validation for Metehara (2000–2014) and Adaitu (2000–2001). Evapotranspiration (ET) validation against GLEAM (2003–2022) and GLDAS (2000–2024). Precipitation data from 1990–2021.

Methodology and Data

• Models used: WRF-Hydro/Noah-MP modeling framework, Markov transition matrices (for LULC change analysis).
• Data sources:
  • Meteorological Forcing: Global Land Data Assimilation System (GLDAS-2.1) (3-hour intervals, 0.25° × 0.25° resolution).
  • Land Use/Land Cover (LULC): ESA Climate Change Initiative (ESA CCI) Land Cover dataset (2001, 2010, 2020 snapshots, 300 meters spatial resolution).
  • Evapotranspiration (ET) Validation: GLEAM ET data, GLDAS-derived ET data.
  • Precipitation Validation: ERA5 reanalysis data.
  • Streamflow Validation: In situ observed streamflow data from Metehara and Adaitu stations.
  • Other: MODIS IGBP classification scheme, WRF Preprocessing System (WPS), Earth System Modeling Framework (ESMF), ArcGIS 10.4, Python 3.12, SAGA-GIS.

Main Results

• The WRF-Hydro/Noah-MP model effectively simulated streamflow dynamics, with R² values of 0.80 at Metehara and 0.89 at Adaitu stations.
• LULC analysis (2000–2020) showed a persistent increase in Woodland (from 3.2% to 4.6%) and Urban areas, alongside a near-total disappearance of Wetlands (from 0.9% to 0.0%). Cropland and Grassland areas remained relatively stable in overall percentage but underwent dynamic internal transitions.
• Markov analysis (2010–2020) revealed significant cropland encroachment into woodlands (13.9%) and grasslands (7.3%), and urbanization fragmenting grasslands (26.4% of urban transitions).
• Hydrological response to LULC changes:
  • The 2001–2010 period (agricultural and urban expansion) led to increased surface runoff, potentially enhancing reservoir storage for large-scale irrigation.
  • The 2010–2020 period (substantial woodland recovery) resulted in decreased surface runoff and a pronounced increase in subsurface flow, indicating enhanced infiltration and groundwater recharge for small-scale and well-based irrigation.
• Evapotranspiration (ET) trends:
  • The model demonstrated strong temporal agreement with GLEAM (R² = 0.75–0.88) and GLDAS (monthly R² = 0.88–0.96, annual R² = 0.80–0.90) for ET, but systematically underestimated absolute ET magnitudes.
  • Yearly ET declined from 2001–2010 (−0.323) and most steeply from 2010–2020 (−0.637) due to urbanization and cropland/shrubland losses. By 2020, the yearly ET decline softened (−0.111), suggesting woodland recovery began to counteract urban impacts.
• Latent Heat Flux (LH) analysis showed strong seasonal fidelity with GLDAS (monthly R² = 0.75–0.83) but lower interannual agreement (yearly R² = 0.25–0.47). Spatially, LH declined from 2001–2010 but increased robustly from 2010–2020, reflecting vegetation recovery.
• A strong positive correlation (R² = 0.850) was found between elevation and average annual precipitation (1990–2021) in the Awash Basin.

Contributions

• Introduces a novel framework that dynamically integrates multi-decadal LULC scenarios (2001, 2010, and 2020) directly into the fully coupled, process-based WRF-Hydro/Noah-MP modeling system.
• Provides the first dynamic, process-based attribution of changes in water partitioning (surface runoff for reservoirs vs. subsurface flow for groundwater) to specific land transitions in the Awash Basin.
• Quantifies the critical trade-offs in water fluxes between different land use trajectories (e.g., agricultural expansion boosting surface water vs. afforestation enhancing groundwater sustainability).
• Offers actionable insights for designing sustainable land and water management strategies, particularly for initiatives like Ethiopia’s Green Legacy Initiative, by providing a quantitative evidence base for spatially targeted land use planning.

Funding

• Science and Technology Project of Jiangsu Provincial Department of Natural Resources (No. JSZRKJ202421)
• National Natural Science Foundation of China (No. 4245000217)
• Strategic Priority Research Program of the Chinese Academy of Sciences (Category B, Geographic Intelligence, No. XDB0740300)
• Jiangsu Province’s Special Fund for Carbon Peak and Carbon Neutrality Technological Innovation for the year 2023 (No. BE2023855)
• Lianyungang Key R&D Program (Industrial Foresight and Key Core Technologies, No. 22CY080)

Citation

@article{Gemechu2025Assessing,
  author = {Gemechu, Tewekel Melese and Zhang, Huifang and Sun, Jialong and Chen, Baozhang},
  title = {Assessing the Impact of Multi-Decadal Land Use Change on Agricultural Water–Energy Dynamics in the Awash Basin, Ethiopia: Insights from Remote Sensing and Hydrological Modeling},
  journal = {Agronomy},
  year = {2025},
  doi = {10.3390/agronomy15122804},
  url = {https://doi.org/10.3390/agronomy15122804}
}

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