Civil Engineering Department
عنوان البريد الإلكتروني هذا محمي من روبوتات السبام. يجب عليك تفعيل الجافاسكربت لرؤيته.
I am working as an associate professor at the University of Technology- Civil Engineering Department. I hold a PhD degree in Water Resources Engineering from TU Freiberg in Germany
Ph.D Water Resources Engineering and Management.
M.Sc Building and Construction Engineering- Water Resources Engineering.
B.Sc. Building and Construction Engineering- Sanitary Engineering .
My research interests mainly focus on hydrological modelling and the impacts of climate changes on water resources. Also, I am interested in the machine learning modelling methods i.e. Artificial Intelligence methods
Al-Mukhtar, M. & Qasim, M. (2019) Future predictions of precipitation and temperature in Iraq using the statistical downscaling model. Arabian Journal of Geosciences. 2 (12). https://doi.org/10.1007/s12517-018-4187-x
Al-Mukhtar, M., Al-Yaseen, F. (2019) Modeling Water Quality Parameters Using Data-Driven Models, a Case Study Abu-Ziriq Marsh in South of Iraq. Hydrology 6(1), 24; https://doi.org/10.3390/hydrology6010024
Al-Mukhtar, M. (2019) Random forests, support vector machine, and neural networks to modelling suspended sediment in Tigris River-Baghdad. Environ Monit Assess 191: 673. https://doi.org/10.1007/s10661-019-7821-5
Al-Mukhtar M. (2016) Modelling the root zone soil moisture using artificial neural networks, a case study. Environmental Earth Sciences. 75 (15):1124. DOI 10.1007/s12665-016-5929-2
Al-Mukhtar M. (2018) Integrated approach to forecast future suspended sediment load by means of SWAT and artificial intelligence models, a case study. Freiberg Online Geoscience. Jun (51). 52-77
Water Resources Management
Jun-September 2017. Fulbright Visiting Scholar. Civil and Environmental Engineering Department, University of Delaware, USA