Dr. Xin Qiao

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