The financially difficult and highly uncertain circumstances surrounding agriculture place a premium on management. A key to successful crop management is being able to integrate data from a variety of sources into a format that provides useful information for decision making. The purpose of this paper is to illustrate the use of crop models in linking information about the response of crops to irrigation with economic analysis and risk assessment. The intent is to provide an integrated information base for making irrigation management decisions. Example applications include use of the CERES‐Maize model to evaluate corn ( Zea mays L.) irrigation strategies in Michigan and use of the SOYGRO model to evaluate soybean [ Glycine max (L.) Merr.] irrigation strategies in Florida. Stochastic dominance is used to evaluate the risks associated with the alternative strategies. Two general relationships are exhibited by the results. First, profit maximizing strategies call for significantly less water than maximum yield strategies. This relationship underscores the need to analyze a wide range of strategies in order to provide producers with information on how to cut back on costs during tough times. Second, irrigation is unique as a production input, in that increasing rates of application actually reduce the weather related variability in yield. This relationship underscores the need to evaluate strategies over a wide range of uncertain conditions in order to adequately assess the risk implications. The crop simulation models and the strategy evaluation procedures of this study can be generalized to look at other variables that affect irrigation decisions or to look at other types of production decisions.
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Boggess et al. (1988) studied this question.