Surface irrigation methods are the oldest, and are those that use the soil surface to conduct and infiltrate the applied water. Traditionally, the design and operation of surface irrigation systems are based on experience as well as on historically successful designs.
The enormous variability of the parameters involved in design (such as soil infiltration, soil surface roughness, soil water holding capacity, field slope, and channel geometry) make field tests slow, tedious, and expensive. To improve the design of furrow and border irrigation systems (as well as contour irrigation for its similar application form), physically based simulation models have been developed in the last 30 years. Model selection and use are based on sustain-ability, data availability, and prediction precision for the advance and recession phases of the irrigation, which determine the water volume or depth to be applied at each point.
Development of optimization models for surface irrigation design generally requires a relationship between the design variables and crop/orchard production. To identify those relations, the following variables are required: frequency and timing of irrigation, critical water application depth, design variables, crop or orchard production, costs associated with the irrigation, and a relationship between the design variables and revenues.
Surface irrigation design variables include: water discharge, furrow or border length, irrigation cutoff time, distance between furrows or border width, and minimum area to be irrigated. These variables should establish a relation between production, costs, and net benefits. Methodologies have been developed to relate production and irrigation costs with irrigation decision variables, using irrigation quality parameters. The most important decision variables in the design are furrow length and time of irrigation since these have a greater impact in the costs and benefits than other variables.
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