Irrigation strategies for different crops and varying soil and climatic conditions can be determined using longterm data representing average weather conditions or short-term predictions based on real-time information. Irrigation scheduling methods are set out below, focusing on their applicability and limitations. Aspects peculiar to the different irrigation methods are dealt with in Section 5.4. However, the challenge to agricultural research is to develop successful methods that are simple to implement and easy to understand from the farmer's and the project management's standpoints . Most of the practiced applications can be found in the literature [1,7]. Common approaches generally include measurement of soil water, plant-stress indicators, and soil water balance.
Methods based on soil water measurements and on plant-stress indicators present some difficulties, particularly for farmers, related to improper handling, malfunctioning, or miscalibration of instrumentation, or lack of understanding of equipment functioning principles. Methods that follow the soil water balance also are not readily adoptable by the farmers because of difficulties in obtaining quality weather data, appropriate information about soils and crops, or about updating schedules.
Trained staff can apply these procedures on a real-time basis to produce irrigation scheduling calendars based on fixed intervals for long-term usage and adoption of very simple rules . In more complicated situations, these can be based on sophisticated models. Irrigation scheduling models currently are used worldwide since microcomputer capability has improved and the required input variables are better defined [7, 9, 10]. Water-balance models consider that irrigation should start when a threshold value of water content is reached. Some models neglect water fluxes that are more difficult to determine, such as the capillarity rise. The effects of weather conditions on plant growth, combined with models predicting seasonal yields as influenced by soil water content, usually are simulated using mechanistic models [10, 11]. A review of crop-water-yield models for water management is given in Section 5.5.
Irrigation models can be used for large areas that include a variety of crops, providing farmers with the daily information needed to make timely decisions. Although these models seem to be difficult to implement in small-scale farming or in developing countries, irrigation scenarios originating from them could be easier to use for definition of irrigation strategies, choosing crops, planning crop according to farm constraints, and allocation of irrigation water supplies. However, the best use of these models is realtime irrigation scheduling .
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