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فارسی
Mohammad Ali Mahmoodi
Academic rank:
Assistant Professor
ORCID:
0000-0002-1513-869X
Education:
PhD.
ScopusId:
54612
HIndex:
Faculty:
Faculty of Agriculture
Address:
Department of Soil Science, University of Kurdistan, Pasdaran St., Sanandaj, Kurdistan, Iran. P. O. Box: 416, Postal Code: 66177-15175, Fax: 08733620553
Phone:
08733620552
E-mail:
a.mahmoodi [at] uok.ac.ir
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Education
Courses
Research activities
Research interests
Students
Executive activities
Education
PhD. in Soil Physics , University of Tehran , Iran
(2005 - 2011)
Thesis title: Predicting Solute Transport Parameters Using Soil Hydraulic Data
MSc. in Soil Science , University of Tehran , Iran
(2002 - 2005)
Thesis title: Simulation of Cadmium Transport in Soil
BSc. in Soil Science , University of BU-Ali Sina , Iran
(1998 - 2002)
Thesis title:
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Courses
Bachelor Of Science
Soil Erosion and Conservation
Soil and Plant Water Relationships
Soil Physics
General Soil Science
Master Of Science
Geostatistics
Advanced Soil and Plant Water Relationships
Advanced Soil Physics
Research activities
Journal Papers
Satellite-Based Estimation of Soil Moisture Content in Croplands: A Case Study in Golestan Province, North of Iran
Soraya Bandak, Seyed Ali Reza Movahedi Naeini, Chooghi Bairam Komaki, Jochem Verrelst, Mohammad Kakooei, Mohammad Ali Mahmoodi (2023)
The possibility of preparing soil texture class map by artificial neural networks, inverse distance weighting, and geostatistical methods in Gavoshan dam basin, Kurdistan Province, Iran
Lnaz Khanbabakhani, Ali Mohammadi Torkashvand, Mohammad Ali Mahmoodi (2020)
Research interests
Data Mining and Pedotransfer Functions
Monitoring of Spatial Variability of Soil Properties
Parameter Estimation and Scaling
Water and Solute Transport Modeling in Soil
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Students
Name:
Serveh Aghayari
AcademicLevel:
Master
Field:
Soil Physics and Conservation
Thesis:
Evaluation of pedotransfer function for predicting soil moisture retention curve in Ghorve soils
Name:
Molood Mirzaii
AcademicLevel:
Master
Field:
Soil Physics and Conservation
Thesis:
Prediction of soil organic matter based on soil characteristics, topography and remote sensing data using artificial neural networks
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Executive activities
Head of Department of Soil Science
(1398 - 1400)
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