Abstract
The rapidly changing economic, technical and regulatory context of irrigated agriculture, coupled with seasonal variation in precipitation, presents a problem for irrigation management, especially in sub-humid regions. During years of drought, frequent irrigation bans may be applied and shortage of water for crops becomes a critical problem. Simulation models offer the opportunity to optimise production strategies, such as optimal irrigation scheduling. But few biophysical models are designed for decision making. MODERATO is a management oriented cropping system model developed for use at a strategic level by irrigation advisors confronted with the question: ‘How to irrigate maize with a limited amount of irrigation water?’. It includes the main constraints specifically related to irrigation (work time, available amount of water, flow rate, blackout days), simulates the plant-soil system with a dynamic biophysical model (parametrized on a large database) and takes into account within-field variability that results from sequentially irrigating the plots in a block of irrigation. Five elementary irrigation rules are distinguished: (1) a rule to irrigate to facilitate plant emergence; (2) a rule to decide when to start the main irrigation period; (3) a rule to determine when to start a new irrigation cycle; (4) a rule to decide when to stop irrigation; and (5) a rule to delay irrigation due to weather conditions. The elementary rules consist of two boolean conditions which depends respectively on development stage and soil water availability. The details of the rules are input using a graphic user interface. The dynamic biophysical model is based on the well-known interception–conversion process. The model outputs allow one to analyse the consequences of the decision rules for various climatic series and context. MODERATO is the result of 3 years of collaborative research between scientists and irrigation advisors and has been used to calculate optimized starting and ending rules for irrigation on a specific pedoclimate.
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