Bewuket Tefera

Focus Areas:

Country of Origin: Ethiopia

Degree Program: PhD

Entered Program: Fall 2022

Expected Graduation: Fall 2026

Dissertation Topic: Integrating Artificial Intelligence and Hydrological Models for Hydrological Process Analysis: Case Studies in Stellenbosch, South Africa, and Upper Awash River Basin, Ethiopia

Research Statement: My research interests lie in human-environment interactions, with a focus on understanding both natural and human-induced impacts on environmental systems. I specialize in Geospatial Science, particularly in the areas of Hydrological Sciences, Remote Sensing, Spatial Sciences, Agriculture Science, and Land-Use/Land-Cover (LULC) analysis. My work integrates advanced AI techniques and Physical-based models to analyze and model complex spatial and temporal datasets. Through this interdisciplinary approach, I aim to enhance our understanding of environmental processes and support sustainable management of land and water resources.

Adviser: Dr. Jane Southworth

Recent Publications

Alemu, A. M., Addisu, T., Tolosa, D., Abduro, S., Fetene, S., & Bekele, B. (2026). Reliability, functionality, and governance of community-managed rural water points in Ginir district, Ethiopia. Utilities Policy, 101, 102205.

Safaei, M., Southworth, J., Gibbes, C., Herrero, H. V., Rahaman, M., Tefera, B. B., & Blackburn, J. K. (2025). Land-cover classification in Addo Elephant National Park: Analyzing the impact of variables, classifiers, and object-based approach. Ecological Informatics, 90, 103279.

Tefera, B. B., Southworth, J., Mossa, J., Rahaman, M., Safaei, M., Yang, D., & Karuppannan, S. (2025). Predictive groundwater quality responses to land cover and lithology in the upper Awash River basin (Ethiopia) with stacking ensembles. Journal of Environmental Management, 394, 127572.

Rahaman, M., Southworth, J., Amanambu, A. C., Tefera, B. B., Alruzuq, A. R., Safaei, M., ... & Smith, A. C. (2025). Combining deep learning and machine learning techniques to track air pollution in relation to vegetation cover utilizing remotely sensed data. Journal of Environmental Management, 376, 124323.

Southworth, J., Smith, A. C., Safaei, M., Rahaman, M., Alruzuq, A., Tefera, B. B., ... & Herrero, H. V. (2024). Machine learning versus deep learning in land system science: A decision-making framework for effective land classification. Frontiers in Remote Sensing, 5, 1374862.

Educational Background

  • M.S. in Agricultural and Biological Engineering, University of Florida, 2023
  • M.S. in Water Science and Engineering, UNESCO-IHE Institute for Water Education, Delft, 2016
  • B.S. in Agricultural Engineering and Mechanization, Hawassa University, 2010