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| Using an example for Malawi, first it will be established which water balance parameters are good predictors for yield. Then the multiple linear regression will be performed. | Using an example for Malawi, first it will be established which water balance parameters are good predictors for yield. Then the multiple linear regression will be performed. | ||
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| - | |width="225"| ||[[Image:graph92.jpg|400px|]] | + | |width="225"|The input data file for Malawi contains multiple lines for stations and years. In every line, besides yield, all possibly relevant water balance output parameters are stored. The file can be downloaded [http://www.hoefsloot.com/downloads/sample.csv here]||[[Image:graph92.jpg|400px|]] |
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Revision as of 12:04, 15 September 2006
Calibrating Yield
The yield function is a statistically derived function relating the water balance parameters (which constitute the outputs of the water balance model) and the other factors (farm inputs, trend) or NDVI with station yield. Once this function has been established, it can be used for early crop yield forecasting.
Although many different equations are possible, the most widely used one is the outcome of a multiple linear regression procedure:
Y = a + b1X1 + b2X2 + b3X3where b1 to b3 are the corresponding X coefficients.
Using an example for Malawi, first it will be established which water balance parameters are good predictors for yield. Then the multiple linear regression will be performed.
The input data file for Malawi contains multiple lines for stations and years. In every line, besides yield, all possibly relevant water balance output parameters are stored. The file can be downloaded here 
