Drought Identification and Prediction for Cold Climate Regions

Mohammad Hadi Bazrkar a Ph.D. student, I have started working on my Ph.D. dissertation research in Water Resources Engineering in the Department of Civil and Environmental Engineering at North Dakota State University since Summer 2017. In addition, teaching CE 310 Fluid Mechanics Laboratory class has not only helped me gain valuable experience, but also encouraged me to do my best in both research and teaching.

I graduated in Water Engineering (B.Sc.) from Isfahan University of Technology (Iran) in 2008. Ranked the 10th among 1710 participants in the Nation-wide University Entrance Exam, I got a full scholarship from Iran Ministry of Science and Education to continue my education as a Master student in Water Resources Engineering at Tarbiat Modares University. The title of my Master thesis was “SWAT model application in simulation of nutrients to identify pollutant sources contribution in Chamgordalan reservoir watershed in wet seasons.” After my graduation in 2011, I received three scholarships from German Academic Exchange Service (DAAD) and United Nations to attend “Freshwater Ecosystems in Urban Systems – ecotoxicology, ecology and biology” at University of Duisburg Essen, “Water and Environment in Time of Global Change” at Ostfalia University of Applied Sciences (Germany) and “Survey to Planning: New Technologies and Land Protection (H2O:Life) at Polytechnic University of Bari (Italy). In addition, I have 5-year experience in two main projects: “Farhzad River Restoration” and “Water Quality Monitoring and Modeling in Taham, Kinevars, Golabar Rivers and Reservoirs” in Ray Ab and Tarhe Noandishan Consulting Engineers Companies, Tehran, Iran. These research experiences promoted me to pursue my doctoral degree in Water Resources Engineering.

Drought Identification and Prediction for Cold Climate Regions

Drought as a destructive disaster is associated with a great number of socio-economic damages and losses. Thus, identification and prediction of droughts are crucial to mitigation of their impacts. Drought indices are common tools in drought identification. Although many studies have been conducted to develop new indices, more efforts are still needed to develop new indices to achieve more accurate drought identification. In addition to identification, drought prediction is necessary to prevent the high level of damages to the society. Despite the fact that there are many studies related to drought identification, few studies have focused on cold-climate regions. The main objective of this proposed study is to modify the canonical correlation analysis (CCA) in drought prediction based on hydroclimatic data and drought indices in cold climate. Then, the new method will be applied to predict drought in the Red River Basin of the North (RRB), a typical cold climate region. Finally, the root weighted mean square error (RWMSE) will be used to evaluate the model performance. This study will provide valuable drought information especially for the stakeholders and decision makers in North Dakota.

Dr. Xuefeng (Michael) Chu
Director, ND Water Resources Research Institute & Civil and Environmental Engineering
Office: CIE 201K
Phone: (701) 231-9758
Email: xuefeng.chu@ndsu.edu

Top of page