Persone PhD CandidatesXL ciclo Abderrahman El Farchouni

XL ciclo Abderrahman El Farchouni

2nd year

Curriculum: Agricultural and Forest Engineering

Supervisors: Abdessamad Hadri (UM6P), Giulio Castelli (UNIFI), Elena Bresci (UNIFI), Azzouz KCHIKACH (UM6P)

Email: abderrahman.elfarchouni@unifi.it

Office address: Via di San Bonaventura, 13, 50145, Firenze (FI)

Mobile phone: 

Profile

I am Abderrahman El Farchouni, born on December 4, 1999, in Chefchaouen, Morocco. I hold a bachelor’s degree in applied Geosciences from the Faculty of Science and Technology of Tangier (Morocco) and a Master’s degree in Hydroinformatics and Hydrosystems Management from Ibn Tofail University in Kenitra (Morocco).

I am currently a PhD candidate in cotutelle between Mohammed VI Polytechnic University (UM6P International Water Research Institute, Morocco) and University of Florence (UNIFI Department of Agricultural, Food, Environmental and Forestry Sciences and Technologies, DAGRI, Italy).

Research interests and PhD project

My PhD research focuses on integrated surface–groundwater modeling and recharge assessment in semi-arid environments. I am developing a SWAT–MODFLOW coupled modeling framework to quantify groundwater recharge and evaluate the impacts of land use/land cover dynamics and climate variability on water resources in the Haouz–Mejjate aquifer system (Morocco).

Research interests include hydrogeophysics, Major ion chemistry and isotopic tracing of groundwater recharge, and the integration of remote sensing and artificial intelligence for sustainable water resource management.

Papers

• El Mezouary, L., Hadri, A., Kharrou, M. H., Fakir, Y., Elfarchouni, A., Bouchaou, L., & Chehbouni, A. A. (2024). Machine Learning and Deep Learning Guided Assessment of Groundwater Reservoir Hydrodynamic Parameters: A Case Study of The El Haouz Aquifer. E3S Web of Conferences, 489, 1–5. https://doi.org/10.1051/e3sconf/202448904005
• El Mezouary, L., Hadri, A., Kharrou, M. H., Fakır, Y., Elfarchouni, A., Bouchaou, L., & Chehbouni, A. (2024). Contribution to advancing aquifer geometric mapping using machine learning and deep learning techniques: a case study of the AL Haouz-Mejjate aquifer, Marrakech, Morocco. Applied Water Science, 14(5). https://doi.org/10.1007/s13201-024-02162-x

Conference talks and seminars

• IAHR Africa Congress (Dec 9–12, 2024): Mapping Groundwater Recharge Potential Zones Using Remote Sensing, GIS, and AHP Techniques: A Case Study of the Tensift Basin, Morocco.