Nafyad Kawo
University of Nebraska-Lincoln, Class of 2024
From Adama, Oromia
From Adama, Oromia
I am Nafyad Serre Kawo, a recent Ph.D. graduate in Natural Resource Sciences with a specialization in Hydrological Sciences from the University of Nebraska-Lincoln. My academic journey includes two M.Sc. degrees: one in Water Science and Engineering from UNESCO-IHE, and another in Physical Land Resources from Vrije Universiteit Brussels, along with a B.Sc. in Applied Geology from Mekelle University, Ethiopia.
With extensive research experience in hydrogeology, I have collaborated on projects across multiple countries and published numerous peer-reviewed articles. My expertise spans hydrostratigraphic modeling, machine learning, groundwater management, and aquifer heterogeneity, groundwater and hydrological modelling. I have been honored with several awards and scholarships, including the Skala Fellowship Award, the Widaman Distinguished Graduate Assistant Award, the Milton E. Mohr Award, the Netherlands Fellowship Programmes (NFP) scholarship, and the Flemish Interuniversity Council (VLIR-UOS) scholarship.
Professionally, I have served as a research assistant at the University of Nebraska-Lincoln and as a lecturer in Ethiopia at Adama Science and Technology University and Haramaya University. In these roles, I have contributed to both academic and practical advancements in groundwater resources management. My passion lies in developing innovative solutions for sustainable water resource management and protection.

Nafyad Kawo of Adama earns University of Nebraska-Lincoln degree
Nafyad Serre Kawo of Adama was among 3,484 graduates who received degrees from the University of Nebraska-Lincoln during commencement exercises May 3, 17 and 18. Kawo earned a Doctor of Philosophy...
May, 20 2024 - Verified by University of Nebraska-Lincoln
Nafyad Kawo was recognized for earning a scholarship
Awards and Scholarships
Skala Fellowship Award (2022): Received a prestigious fellowship for outstanding academic and research performance at the University of Nebraska Lincoln.
Widaman Distinguished Graduate Assistant Award (2021): Awarded for exceptional contributions as a graduate assistant, reflecting strong research capabilities and dedication.
Milton E. Mohr Award (2021)
Added by Nafyad
Multiple‑point statistical modeling of three‑dimensional glacial aquifer heterogeneity for improved groundwater management
This study used a combination of soft data, a cognitive training image, and hard data to generate 100 three-dimensional (3D) conditional aquifer heterogeneity realizations. The most probable model (probability of hydrofacies) was then computed at node spacing of 200 × 200 × 3 m and validated using groundwater-level hydrographs. The resulting hydrofacies probability grids revealed variations in aquifer geometry, locally disconnected aquifer systems, recharge pathways, and hydrologic barriers
June 2023 -
Articles
Hydrogeology Journalology Journal – Editors’ Choice article
“Editors’ Choice” articles are selected for special attention by the Hydrogeology Journal editorial team, for any of
several good reasons including: outstanding science, innovative approach, potentially important conclusions,
interesting field area or phenomenon, unusual topic, political/social/historical/philosophical interest, etc. At the
conclusion of each publishing year, the Editors select several articles from among the year’s crop of about 150
peer-reviewed published articles.
Others
Three-dimensional Probabilistic Hydrofacies Modeling using Machine Learning
Water Resources Research, Accepted for publications
We used machine learning and data from airborne geophysics and boreholes to generate high-resolution, 3D models of a glacial aquifer in Nebraska, USA. We compare and contrast five different machine learning models, showing that there are differences in the models’ performance and ability to construct geologically plausible results. These models help estimate the aquifer properties, locate aquifer boundaries, and provide a basis for constructing numerical models of groundwater flow.
Articles
Comparisons of Machine Learning-based 3D Probabilistic Hydrofacies Models for Improved Groundwater Flow Model Parameterizations
2023, Daugherty Water for Food Global Conference
Conferences
Streambed and aquifer connectivity revealed by 3D MPS modeling of AEM resistivity data: A glacial aquifer case study
AGU 2021 Fall Meeting
Conferences