Water and Irrigation Managment Specialist
University of Nebraska Panhandle Research and Extension Center
4502 Avenue I, Scottsbluff, NE 69361
308-632-1240
Email: xin.qiao@unl.edu
EDUCATION:
- B.S. 2009, Water and Wastewater Engineering, South China University of Technology
- M.S. 2012, Biosystems Engineering, Clemson University
- Ph.D. 2015, Plant and Environmental Sciences, Clemson University
AREA OF INTEREST:
- Deficit irrigation, variable rate irrigation, sensor technology, modeling, remote sensing
AWARDS AND HONORS:
- Simpson experiment station field day graduate student poster contest, 1st place, 2014.
- Beltwide Cotton Conference student presentation contest, 3rd place, January 7 – 10, San Antonio, TX, 2013.
PROFESSIONAL SOCIETY MEMBERSHIPS:
- American Society of Agricultural and Biological Engineers
RESEARCH INTERESTS:
- Promote the beneficial and efficient use of water resources for agricultural production systems using technologies such as sensor-based irrigation, modeling, and remote sensing images.
EXTENSION INTERESTS:
- Provide farmers and stakeholders with timely and relevant information/tools to assist them to improve yields and profits while conserving limited water resources. Provide educational material through fact sheets, presentations, workshops, and online resources for irrigation management.
MAJOR PROJECT ACTIVITIES:
- TBD
RECENT PUBLICATIONS:
- Qiao, X., Khalilian, A., Payero, J.O., Maja, J.M., Privette, C.V. and Han, Y.J. 2016 Evaluating Reflected GPS Signal as a Potential Tool for Cotton Irrigation Scheduling. Advances in Remote Sensing, Vol. 5 No. 3 pp. 157-167, http://dx.doi.org/10.4236/ars.2016.53013
- Qiao, X., H. J. Farahani, A. Khalilian, E. M. Barnes. 2016. Cotton Water Productivity and Growth Parameters in the Humid Southeast – Experimentation and Modeling. Transactions of the ASABE, 59(3): 949-962
- Privette III, C.V., Khalilian, A., Bridges, W., Katzberg, S., Torres, O., Han, Y.J., Maja, J.M. and Qiao, X. 2016 Relationship of Soil Moisture and Reflected GPS Signal Strength. Advances in Remote Sensing, 5, 18-27. http://dx.doi.org/10.4236/ars.2016.51002