Calibration coefficient stability and influence on climate impact predictions on potato

Authors: Fleisher, David; Haynes, Kathleen; Timlin, Dennis

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 6/10/2019
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Crop model calibration refers to the process where values for a set of parameters, usually referred to as genetic or cultivar coefficients, are obtained. Because model predictions are inherently biased due to simplifications in the system of equations that represent real-world phenomenon, these calibrated parameters are just as likely to compensate for limitations in model structure as well as reflecting true phenotypic characteristics. This confounding of genetics with components of the production environment limits model accuracy when conducting assessments including climate change impacts. We tested the extent of this confounding by evaluating changes in calibration parameters and model prediction results when calibration was conducted cross- versus within- locations. The potato model SPUDSIM was selected along with data from two cultivars grown in two contrasting locations in the U.S.. Calibration methods, location specific (R1) or cross location (R2), were used. Differences between phenology coefficients under the R1 method ranged from 4 to 17 percent between the two locations depending on cultivar. A wider range was observed for growth coefficients, which likely reflected over-coupling of canopy expansion rate within the model structure as well as an over-sensitivity with to temperature and photoperiod. R2 method results for phenology coefficients gave values within the range for that obtained in R1. However, canopy expansion rate was almost 50 percent larger for one cultivar. Still, independent validation year results were similar for R1 and R2 with respect to end-of-year yields (17 percent error or less) and yield-RMSE (less than 36.1 grams per plant). Projected climate change impacts for 2030, 2040, 2050, and 2080 decades indicated R2 over-predicted yields by 5 percent or less as compared with R1, with a maximum discrepancy of 4.4 grams per plant. Consistent differences between R1 and R2 calibrated models in rates of yield decline per decade were not observed for cultivar, location, or climate scenario, but averaged -0.59 grams per plant per year for R1 and -0.67 for R2. These results suggest calibration for these cultivars and locations was relatively stable for the SPUDSIM model.