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Postdoctoral Researcher — PNNL

Guta Wakbulcho
Abeshu

Computational Hydrologist

Pacific Northwest National Laboratory

Advancing global water sustainability by fusing AI / ML with physics-based hydrological models — from transboundary river management to climate-resilient water infrastructure.

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About Me

Bridging AI & Hydroscience

Welcome to the Hydrosystems Operations, Resilience, and Adaptation (HORA) Lab. I am a Postdoctoral Researcher at Pacific Northwest National Laboratory (PNNL), specializing in computational hydrology, machine learning, and water resources.

My research bridges artificial intelligence and hydrological science — developing cutting-edge frameworks that integrate deep learning, satellite remote sensing, and physics-based modeling to address global water challenges.

With expertise in large-scale hydrological processes, I focus on improving predictions of water availability, managing drought and flood risks, and building AI-driven solutions for transboundary water resource management under climate change. My current work includes potable water sustainability, adaptive resilience in water infrastructure, advanced hydrological modeling with the E3SM earth system model, and AI-driven solutions for contested transboundary river basins.

Explore My Research
  Affiliation
Pacific Northwest National Laboratory
Richland, WA, USA
  Research Lab
HORA Lab — Hydrosystems Operations,
Resilience & Adaptation
  Focus Areas
Computational Hydrology • AI/ML
Climate Science • Water Resources
  Role
Postdoctoral Researcher
Computational Hydrologist
  Academic Background

Education

Ph.D. — Civil Engineering (Hydrosystems)
  University of Houston
Houston, TX, USA2022
M.A.S. — Sustainable Water Resources
  ETH Zurich
Zürich, Switzerland2016
M.Sc. — Water Resources Engineering & Management
  Addis Ababa University
Addis Ababa, Ethiopia2013
B.Sc. — Hydraulic & Water Resources Engineering
  Arba Minch University
Arba Minch, Ethiopia2009
  Career Path

Professional Experience

Postdoctoral Research Associate 2024 – Present
  Pacific Northwest National Laboratory — Richland, WA
Atmospheric, Climate & Earth Sciences Division. Projects: GCIMS, ICoM, WACCEM. Advancing E3SM earth system model hydrology with AI/ML frameworks for global water sustainability.
Postdoctoral Research Fellow 2022 – 2023
  University of Houston — Houston, TX
Department of Civil & Environmental Engineering. Developed deep reinforcement learning frameworks for hydropower reservoir optimization and transboundary water management.
Graduate Research Assistant 2018 – 2022
  University of Houston — Houston, TX
PhD research on catchment ecohydrological processes across spatiotemporal scales; developed physics-informed deep learning models for global hydrological prediction.
Lecturer & Research Fellow 2009 – 2016
  Arba Minch University — Arba Minch, Ethiopia
Faculty of Water Technology Institute. Taught undergraduate courses in hydrology, hydraulics, and water resources engineering; conducted regional water resources research.
Full Curriculum Vitae
What I Do

Research Areas

Integrating AI, remote sensing, and physics-based modeling to tackle the most pressing global water challenges.

Catchment Hydrology

Catchment water balance, ecohydrology, vegetation-water interactions, sediment dynamics, and flood/drought processes across spatiotemporal scales.

Horton IndexEcohydrologyWater BalanceSediment

Large-Scale Modeling

Continental-to-global hydrological and earth system models coupling land, river, and reservoir components to simulate water, carbon, and sediment cycles.

E3SMMOSARTXanthosGCAM

AI / ML for Hydrology

Machine learning and deep learning for hydrological prediction, parameter estimation, and water systems optimization — from ML-derived datasets to reinforcement learning for reservoir operations.

Deep LearningReinforcement LearningPhysics-Informed ML
View All Research
Research Output

Selected Publications

Peer-reviewed contributions in hydrology, AI/ML, and computational hydrological science.

All Publications Google Scholar
Expertise

Skills & Tools

Technical depth across computation, modeling, remote sensing, and data science.

Programming

PythonRMATLABFortranBash / ShellJulia

AI / Machine Learning

TensorFlowPyTorchscikit-learnLSTMReinforcement LearningTransformers

Hydrological Models

VICMOSARTE3SMSWATHEC-HMSParFlow

Remote Sensing & GIS

GRACE / GRACE-FOMODISLandsatGoogle Earth EngineQGISArcGIS

HPC & Cloud

NERSCSlurmMPI / OpenMPAWSDockerGit / GitHub

Data Science

xarrayNetCDFPandasNumPyMatplotlibJupyter
Let's Connect

Get in Touch

I am always excited to connect with fellow researchers, potential collaborators, and students interested in hydrology, computational hydrological science, and AI/ML applications for water systems. Feel free to reach out!

Pacific Northwest National Laboratory

902 Battelle Blvd
Richland, WA 99354
United States

HORA Lab
Hydrosystems Operations, Resilience & Adaptation

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