Adaptability of the Hybrid-Maize Model and the Development of a Gridded Crop Modeling System for the Midwest US.

As a part of a USDA-NIFA U2U (USEFUL TO USABLE Climate Information) project, efforts are underway to simulate regional crop productivity as function of past and projected climate (and anomalous climatic conditions).  A decision support tool is envisioned to develop links between climatic information, crop yield ensembles, and potential economic impacts. Towards this end, different crop yield models of simple, intermediate to enhanced biophysical complexity and process scale representations are being tested and applied. This presentation will discuss the results from one such relatively simpler model - the Hybrid Maize model as tested over 20 different agroclimatic sites across the Midwest US using 30 year of climatic and long term yield data.  The results indicate that, under optimal water condition, the yields simulated by the crop model is highly sensitive to the prescription of potential kernels per ear, potential filling rate, upper temperature cutoff of growing degree days (GDD), and initial light use efficiency. Yields were also sensitive to the choice of plant density, planting date and GDD at maturity. The model results are also affected by the uncertainties of the input data, such as soil characteristics, planting date, and plant density.  The model outcome  for default/ optimal configuration were rescaled using regression analysis, and the resulting simulated crop yields highlight the good potential of using simpler models such as Hybrid Maize for predicting corn yields in the Midwest. The presentations will also provide an update on efforts underway to use remote sensing based biophysical parameters and a land data assimilation system (LDAS) to develop a 4 km gridded spatial product for soil moisture/temperature conditions and the potential for a gridded crop modeling system for the Midwest US.

Acknowledgement: Agriculture and Food Research Initiative Competitive Grant no. 2011-68002-30220 from the USDA National Institute of Food and Agriculture. Project website: http://www.AgClimate4U.org.