Prof. Dr. Husam Baalousha

Main tasks

English

Husam Baalousha is a Professor of Hydrogeology at the Department of Geosciences, College of Petroleum and Geosciences (CPG), at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. He has his Habilitation Degree from the University of Strasbourg, his PhD from Aachen University of Technology (RWTH), and his MSc degree from IHE-Delft, The Netherlands. 

Prof. Baalousha has worked in several countries, including Germany, New Zealand, Qatar, and Saudi Arabia. His research and professional experience cover a broad range of hydrogeological and environmental topics, particularly groundwater hydrology, groundwater modeling, managed aquifer recharge, carbon sequestration, geothermal energy, and the application of machine learning methods in the geosciences.

Deutsch

Husam Baalousha ist Professor für Hydrogeologie am Fachbereich Geowissenschaften des College of Petroleum and Geosciences (CPG) der King Fahd University of Petroleum and Minerals in Saudi-Arabien. Er besitzt die Habilitation der University of Strasbourg, promovierte an der RWTH Aachen University und erwarb seinen Masterabschluss am IHE Delft Institute for Water Education.

Prof. Baalousha hat in mehreren Ländern gearbeitet, darunter Deutschland, Neuseeland, Katar und Saudi-Arabien. Seine Forschungs- und Berufserfahrung umfasst ein breites Spektrum hydrogeologischer und umweltbezogener Themen, insbesondere Grundwasserhydrologie, Grundwassermodellierung, künstliche Grundwasseranreicherung, Kohlenstoffspeicherung, Geothermie sowie den Einsatz von Methoden des maschinellen Lernens in den Geowissenschaften.

Selected publications

• Abbasov, Rashad, Marwan Fahs, Vincent Fontaine, Husam Musa Baalousha, Anis Younes, and Renaud Toussaint. 2026. “Assessing Simplified Approaches in Modeling Rainfall-Induced Landslides Using Richards’ Equation with Biot Poroelasticity.” Engineering Geology 360 (January): 108481. https://doi.org/10.1016/j.enggeo.2025.108481.
• Alshammari, Bashayer, Rashad Abbasov, Anis Younes, et al. 2026. “Modeling Seawater Intrusion with Multiple Sources of Uncertainty: Application to Kuwait City.” Hydrogeology Journal, ahead of print, March 30. https://doi.org/10.1007/s10040-026-03051-0.
• Baalousha, Husam Musa. 2025. “Machine Learning Approaches for Groundwater Vulnerability Assessment in Arid Environments: Enhancing DRASTIC with ANN and Random Forest.” Groundwater for Sustainable Development 30 (August): 101496. https://doi.org/10.1016/j.gsd.2025.101496.
• Fahs, Marwan, Behshad Koohbor, Qian Shao, Joanna Doummar, Husam M. Baalousha, and Clifford I. Voss. 2022. “Effect of Flow‐Direction‐Dependent Dispersivity on Seawater Intrusion in Coastal Aquifers.” Water Resources Research 58 (8): e2022WR032315. https://doi.org/10.1029/2022WR032315.
• Kanito, Dawit, Mohammed Benaafi, and Husam Musa Baalousha. 2025. “Machine Learning Models for Groundwater Level Prediction and Uncertainty Analysis in Ruataniwha Basin, New Zealand.” Hydrology 12 (11): 282. https://doi.org/10.3390/hydrology12110282.
• Khan, Md Shaibaz, Marwan Fahs, Ahmed Hadidi, and Husam Musa Baalousha. 2026. “Physics-Informed Bayesian Neural Network for Groundwater Recharge Estimation in Data-Scarce Arid Regions.” Frontiers in Water 8 (March): 1787659. https://doi.org/10.3389/frwa.2026.1787659.