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ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Wind Erosion and Water Conservation Research » Research » Publications at this Location » Publication #98910


item Wanjura, Donald

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Proceedings
Publication Acceptance Date: 1/6/1999
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Crop simulation models are useful tools for evaluating the relationship between production inputs and crop responses. The Agricultural Research Service is developing a cotton model using the object-oriented programming language C++. Special emphasis is placed on maintaining independence between personnel and data bases used in model development from that of model validation. The purpose is to provide an objective evaluation that i unbiased by common data being used in both modeling activities. The intent is to provide a model whose capabilities have been accurately evaluated so that subsequent users can proceed based on documented rigorous testing. Model validation work in Texas during 1998 included assembly and formatting of validation data sets from the Texas area and preliminary calibration and validation of the model. A sequence for calibrating plant parameters was set up, and acceptable differences between simulated and observed plant parameters were established. The sequence for calibrating plant factors is first square, first bloom, number of main stem nodes, plant height, leaf area, fruiting, and yield. The levels of acceptable deviation between predicted and observed plant factors are within two days for the first square and bloom events and within 15% for all other plant factors. From 33 data sets, two groups were identified to represent multiple water levels at the same location and another for different years and locations. After optimizing the calibration factors for each plant parameter, initial simulations indicate that the model is correctly predicting plant factors on a relative basis. We are now starting comparisons between pre- dicted and observed factors to determine accuracy of the model.