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Title: Calibration of CERES-Maize against precision weighing lysimeter data under semi-arid conditions of eastern Colorado

Author
item ANDALES, ALLAN - Colorado State University
item MA, CRISTINA CAPURR - Colorado State University
item SMITH, GARVEY E.B. - Colorado State University
item Gowda, Prasanna
item KISEKKA, ISAYA - Kansas State University

Submitted to: Miscellaneous Publishing Information Bulletin
Publication Type: Abstract Only
Publication Acceptance Date: 2/2/2017
Publication Date: 6/13/2017
Citation: Andales, A., Ma, C., Smith, G., Gowda, P.H., Kisekka, I. 2017. Calibration of CERES-Maize against precision weighing lysimeter data under semi-arid conditions of eastern Colorado[abstract]. 2017 UCOWR/NIWR Conference, June 13-15, 2018, Fort Collins, Colorado. Session 15, p. 43.

Interpretive Summary: Abstract only.

Technical Abstract: Alternative water management strategies in the Ogallala Aquifer Region (OAR) of the U.S. need to be explored to mitigate adverse effects of groundwater decline on agriculture. There is a need to evaluate impacts of various water conservation strategies on crop yield across the OAR. For the OAR portion in eastern Colorado, alternative irrigation management strategies can be evaluated across different locations using a calibrated cropping systems model. The objective of this study was to calibrate and evaluate the performance of the CERES-Maize crop model using water balance and corn growth data from a precision weighing lysimeter in southeast Colorado. The mass of an undisturbed soil monolith with an actively-growing corn crop contained in a steel tank (3 m x 3 m area; 2.4 m deep) was continuously monitored with a calibrated load cell to determine hourly and daily corn evapotranspiration (ET) and soil profile water balance. Corn was planted on the monolith and surrounding field (4 ha) in early May for two growing seasons (2013 – 2014). Irrigations on the monolith and surrounding field were applied through furrows spaced 76 cm apart. The CERES-Maize crop model integrated in two cropping system models [Decision Support System for Agrotechnology Transfer (DSSAT) and Root Zone Water Quality Model (RZWQM2)] was calibrated against weekly measurements of soil water content and corn growth; and daily measurements of evapotranspiration (ET) in 2013. The calibrated models were validated using 2014 growing season data. Comparative performance of DSSAT and RZWQM2 in simulating ET, growth, and soil water content are reported.