In the heart of Ethiopia’s Tekeze Basin, a critical study is shedding light on how changes in land use and land cover (LULC) are significantly impacting peak flood levels in the Babur Watershed. Led by Kahsu Hubot from the Department of Hydraulic and Water Resources Engineering at Aksum University, this research, published in the ‘Journal of Flood Risk Management’ (translated as ‘Journal of Flood Risk Management’), is not just an academic exercise but a vital tool for policymakers, urban planners, and the energy sector.
Using a combination of remote sensing, Geographic Information Systems (GIS), and advanced hydrologic modeling, Hubot and his team have painted a vivid picture of the watershed’s evolution over the past two decades. “We’ve seen a substantial increase in cropland, built-up areas, and vegetation,” Hubot explains, “while forestland, shrubland, and bareland have been on the decline.” These changes, though seemingly gradual, have profound implications for the region’s hydrology.
The study employed the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) to simulate the impact of these LULC changes on peak stream flow. The model’s performance was rigorously evaluated through sensitivity analysis, calibration, and validation, with impressive results. “The calibration and validation periods showed a strong match between measured and simulated flow data,” Hubot notes, highlighting the model’s reliability.
The findings are stark: peak flow has increased by 19.33% from 1996 to 2016, and is projected to rise by a further 45.91% from 2016 to 2036 due to continued LULC changes. These increases in peak flow can have significant commercial impacts, particularly for the energy sector. Hydropower plants, which rely on consistent water flow, may face challenges in managing increased peak flows, potentially leading to infrastructure damage and operational disruptions.
Moreover, the study’s methodology offers a replicable framework for other regions grappling with similar issues. By integrating Quantum GIS (QGIS) with the MOLUSCE plugin for LULC prediction and using the Statistical Downscaling Model (SDSM) for future rainfall prediction, the research provides a robust toolkit for understanding and mitigating flood risks.
As the world grapples with climate change and its attendant challenges, studies like Hubot’s are invaluable. They not only highlight the urgent need for sustainable land use practices but also offer practical solutions for managing flood risks. For the energy sector, this research underscores the importance of integrating hydrologic modeling into infrastructure planning and management strategies.
In an era of increasing environmental uncertainty, such insights are not just academic—they’re essential for building a more resilient future. As Hubot’s work demonstrates, understanding the past and present can help us navigate the challenges of tomorrow.