Professional Summary
Dr. Ing. Bereket Geberselassie Assa is a hydrologist, computational geospatial scientist, and Earth Observation specialist whose work integrates hydrology, GIS, remote sensing, machine learning, spatial statistics, and environmental system modeling. He is affiliated with Wolaita Sodo University and completed his Ph.D. in Geo-information and Earth Observation for Hydrology at Arba Minch University. His doctoral and research work focuses on downstream surface and groundwater nitrate contamination from fertilizer loss in the Bilate Sub-Watersheds, using coupled Earth Observation, machine learning, nitrogen balance modeling, and watershed-scale hydrological analysis. His expertise bridges academic research and applied environmental decision support, with strong emphasis on water quality dynamics, hydrological connectivity, rainfall-driven nutrient transport, climate-resilient agriculture, sustainable watershed management, and data-driven environmental monitoring. Through teaching, graduate supervision, peer-reviewed publications, and interdisciplinary research, he contributes to strengthening African capacity in computational hydrology, water resources management, agricultural water systems, climate adaptation, and evidence-based environmental planning.
Key Expertise
Major Projects and Contributions
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Faculty Member – Hydrology and Geospatial Engineering, Wolaita Sodo University
Conducts teaching, graduate supervision, research, and academic leadership in hydrology, GIS, Earth observation, geospatial engineering, watershed modeling, environmental monitoring, and climate-water-agriculture systems. -
Ph.D. Research on Bilate Sub-Watershed Nitrate Contamination
Completed doctoral research assessing downstream surface and groundwater nitrate levels from fertilizer loss in upper croplands of the Bilate Sub-Watersheds using coupled Earth Observation and Machine Learning approaches. -
Computational Watershed Modeling and Environmental Monitoring
Develops computational and geospatial workflows that integrate satellite observations, field datasets, spatial statistics, and hydrological models to support watershed-scale environmental monitoring and decision-making. -
Earth Observation and Machine Learning for Water Quality Assessment
Applies Earth Observation, GIS, remote sensing, machine learning, and Geographically Weighted Regression to investigate water quality dynamics, nitrate contamination processes, and agricultural watershed vulnerability. -
Nitrogen Balance Modeling for Surface and Groundwater Nitrate Risk
Published research on modeling nitrogen balance for pre-assessment of surface and groundwater nitrate contamination from fertilizer application loss in the Bilate downstream watershed croplands. -
Canopy Water Content and Rainfall-Induced Nitrate Contamination Research
Conducted research on canopy water content and its role in assessing rainfall-induced surface and groundwater nitrate contamination in the Bilate cropland sub-watershed. -
Seasonal Crop Biomass, Nitrate Leaching, and Runoff Coefficient Assessment
Investigated nitrate leaching and runoff coefficients in relation to seasonal crop biomass dynamics, supporting improved understanding of surface and groundwater nitrate contamination in agricultural watersheds. -
Geomorphological Analysis of Seasonal Nitrate Contamination Dynamics
Contributed to research on seasonal nitrate contamination dynamics in cropland sub-watersheds using geomorphological analysis of the Bilate agricultural watershed. -
Climate-Resilient Agricultural Water and Environmental Decision Support
Works on data-driven and computational approaches that support climate-resilient agriculture, sustainable watershed management, water quality protection, environmental monitoring, and evidence-based policy development. -
Geospatial Analytical Workflow Development
Develops spatial data fusion and geospatial analytical workflows using MODIS, Landsat, Sentinel, Google Earth Engine, ArcGIS Pro, QGIS, Python, R, SPSS, SWAT, HEC-HMS, and environmental modeling tools.