Brief Summary of Minutes of Annual Meeting

Accomplishments Objective 1. Coordinate the documentation of crop coefficients used in irrigation scheduling. The crop coefficients used with North Dakota's irrigation scheduling programs were developed based on research performed over 30 years ago. Current research using eddy covariance has the potential to provide updated Kc curves for corn. The Kc formulas for 10 crops grown in ND were sent to the chair of a subcommittee of this committee (Peters) who is assembling a national database. The Kc curves are polynomial equations based on days past emergence (DPE) for use with the Jensen-Haise reference ET equation. Currently, research on water use in tile drainage has produced some estimates of crop coefficients. Research efforts continue on the development of crop coefficients (Kcs) in the Texas High Plains for sunflowers at the USDA-ARS lysimeter facility at Bushland, TX. Agreement with previous literature values validates the derived Kcs for regional applications (production and modeling). Additionally, Kcs for spinach have been determined and published; Kcs for cabbage and artichokes in the Wintergarden region of Texas are being derived. This information will be contributed to support WERA 1022 subcommittee to compile a database of Kc values and their attributes (derivation and application). Objective 2. Coordinate efforts to promote adoption of improved irrigation scheduling technology, including computer models based on crop coefficients and ETref, remote sensing and instrumentation that will help producers more efficiently apply irrigation water. Daily crop water use values are available on the North Dakota Agricultural Weather Network (NDAWN) website, http://ndawn.ndsu.nodak.edu/ or in the irrigation scheduling Extension bulletin AE-792 Checkbook Irrigation Scheduling. Analysis of the web access logs for 2012 show that 65 irrigators used the NDAWN based irrigation scheduling program. The NDAWN based program was used to schedule irrigations on over 120 fields containing a variety of crops. This represents about 15,000 to 18,000 acres or about 7 percent of the irrigated acreage in ND. The NRCS requires irrigators to use the web-based irrigation-scheduling program to support the irrigation water management portion of their Environmental Quality Incentive Program (EQIP). Methods of interpolation were evaluated for use in developing interpolated daily ET maps for the Texas High Plains. Commonly used interpolation (inverse weighted, spline, and kriging) methods and one new method (machine learning with optimization algorithm(s)) were evaluated for mapping reference ET in the Texas High Plains. Machine learning increased accuracy of the daily ET maps using optimization algorithms. Decommissioning of several weather stations of the network during the course of the project added challenge and urgency to the task. Machine learning applied to alternative data sources were compared with interpolation techniques in order to help fill spatial gaps in the data. A basic irrigation scheduling tool was created to help farmers evaluate viable options to conserve water in terms of selecting crop types and irrigation systems. I have attached a report on the tool that was developed. This accomplishment aligns with Objective 2. Farmers associated with Central Colorado Water Conservancy District (CCWCD) were educated on the use of the tool to promote its use. CCWCD is now collaborating in another project to demonstrate the tool in conjunction with the use of soil moisture sensors (SMS) to improve irrigation scheduling. In the past they funded a project to evaluate irrigation scheduling using SMS.

Saleh Taghvaeian, José L Chávez, and Neil C Hansen. (2012). Infrared Thermometry to Estimate Crop Water Use and Stress Index of Irrigated Maize in Northeastern Colorado. Remote Sensing Journal. Special issue: Advances in Remote Sensing of Crop Water Use Estimation. Remote Sens. 2012, 4(11), 3619-3637; doi:10.3390/rs4113619 Chávez, J.L., Gowda, P.H., Howell, T.A., Garcia, L.A., Copeland, K.S., and Neale, C.M.U. 2012. ET mapping with high resolution airborne remote sensing data in an advective semi-arid environment. Journal of Irrigation and Drainage Engineering. ASCE. Vol. 138, No. 5, May 1, 2012. Pp. 416-423. Abhinaya Subedi, José L. Chávez, and Allan A. Andales. (2013). Preliminary performance evaluation of the Penman-Monteith evapotranspiration equation in southeastern Colorado. In Proceedings of 33rd Annual American Geophysical Union (AGU) Hydrology Days 2013 Conference. Fort Collins, CO. March 25 - 27, 2013. Rijal, I., and X. Jia. 2012. Reference evapotranspiration and actual evapotranspiration measurements in North Dakota. ND Water Resources Research Institute Technical Report No: ND12-02. http://www.ndsu.edu/wrri/ Fargo, ND. p30. Rijal, I., X. Jia, X. Zhang, D. D. Steele, T. F. Scherer, and A. Akyuz. 2012. Effects of subsurface drainage on evapotranspiration for corn and soybean in Southeastern North Dakota. J. of Irrigation and Drainage 138(12): 1060-1067. Holman, Daniel, Mohan Sridharan, Prasanna Gowda, Dana Porter, Thomas Marek, Terry Howell, and Jerry Moorhead. 2013. Accurate Estimates of Reference Evapotranspiration for Irrigation Management in the Texas High Plains. [Peer Reviewed] Proceedings of the International Joint Conference on Artificial Intelligence, Beijing, China, August 3-9, 2013. Porter, Dana, Prasanna Gowda, Thomas Marek, Terry Howell, Jerry Moorhead, and Suat Irmak. 2012. Sensitivity of Grass- and Alfalfa-Reference Evapotranspiration to Weather Station Sensor Accuracy. Applied Engineering in Agriculture. 28(4):543-549. Samui, P., P.H. Gowda, T. Oommen, T.A. Howell, T.H. Marek, and D.O. Porter. 2012. Statistical learning algorithms for identifying contrasting tillage practices with Landsat Thematic Mapper data. International Journal of Remote Sensing, 33 (18):5732-5745.