A method for increasing accuracy of digital models of crop growth based on nutrient values in a computing system, the method comprising: storing, in the computing system, a digital model of crop growth, the digital model of crop growth being configured to compute nutrient requirements in soil to produce particular yield values based, at least in part, on data unique to an agricultural field; receiving agronomic field data for a particular agronomic field, the agronomic field data comprising one or more input parameters for each of a plurality of locations on the agronomic field, nutrient application values for each of the plurality of locations, and measured yield values for each of the plurality of locations; using the digital model of crop growth computing, for each location of the plurality of locations, a required nutrient value indicating a required amount of nutrient to produce the measured yield values; identifying a subset of the plurality of locations where the computed required nutrient value is greater than the nutrient application value; computing, for each of the subset of the plurality of locations, a residual value comprising a difference between the required nutrient value and the nutrient application value; generating a residual map comprising the residual values at the subset of the plurality of locations; generating, from the residual map and the one or more input parameters for each of the plurality of locations, particular model correction data for the particular agronomic field; storing the particular model correction data with an identifier of the particular agronomic field, further comprising: storing model correction data for a plurality of different agricultural fields; receiving particular input parameter data for the particular agricultural field; identifying the model correction data with the identifier of the particular agronomic field and, in response, using the digital model and the model correction data stored with the identifier of the particular agronomic field to compute recommended nutrient values for the particular field; generating a script which, when executed by one or more processors, causes an agricultural implement to release the nutrient at the recommended nutrient values onto the particular agronomic field. storing, in the computing system, a digital model of crop growth, the digital model of crop growth being configured to compute nutrient requirements in soil to produce particular yield values based, at least in part, on data unique to an agricultural field; receiving agronomic field data for a particular agronomic field, the agronomic field data comprising one or more input parameters for each of a plurality of locations on the agronomic field, nutrient application values for each of the plurality of locations, and measured yield values for each of the plurality of locations; using the digital model of crop growth computing, for each location of the plurality of locations, a required nutrient value indicating a required amount of nutrient to produce the measured yield values; identifying a subset of the plurality of locations where the computed required nutrient value is greater than the nutrient application value; computing, for each of the subset of the plurality of locations, a residual value comprising a difference between the required nutrient value and the nutrient application value; generating a residual map comprising the residual values at the subset of the plurality of locations; generating, from the residual map and the one or more input parameters for each of the plurality of locations, particular model correction data for the particular agronomic field; storing the particular model correction data with an identifier of the particular agronomic field, further comprising: storing model correction data for a plurality of different agricultural fields; receiving particular input parameter data for the particular agricultural field; identifying the model correction data with the identifier of the particular agronomic field and, in response, using the digital model and the model correction data stored with the identifier of the particular agronomic field to compute recommended nutrient values for the particular field; generating a script which, when executed by one or more processors, causes an agricultural implement to release the nutrient at the recommended nutrient values onto the particular agronomic field. storing model correction data for a plurality of different agricultural fields; receiving particular input parameter data for the particular agricultural field; identifying the model correction data with the identifier of the particular agronomic field and, in response, using the digital model and the model correction data stored with the identifier of the particular agronomic field to compute recommended nutrient values for the particular field; generating a script which, when executed by one or more processors, causes an agricultural implement to release the nutrient at the recommended nutrient values onto the particular agronomic field.