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Summary
The need for more-efficient agricultural use of irrigation water arises out of the increased competition for water resources and the greater pressure on irrigation practices to be environmentally friendly. Here, we use a simple water-balance approach to model soil-water storage changes for the purpose of better estimating the irrigation requirements for a range of field crops growing in the Auckland region of New Zealand. In this humid, maritime climate irrigation requirements can very greatly in time and with crop type. Such information is needed by the local authorities, for planning purposes to determine appropriate water right allocations for local growers.
The model we have developed considers the root zone to be one dimensional, comprising a uniform soil of known hydraulic properties, and having plants with roots extending vertically to a known depth. Model output consists of daily values of the soil moisture stored in the root zone. Crop water use was calculated via the Penman-Monteith model, using a generalized coefficient for each crop. A threshold moisture level, which depends on a combination of soil and crop factors, is used trigger the irrigation events. Water drainage below the root zone is calculated from easily determined soil hydraulic properties, and the amount of water stored in the profile.
We use a statistical analysis based on 25 years of weather data to provide answers to the questions of “how much” and ‘how often”, at any level of given risk of exceedence. Irrigation requirements were considered for a wide range of crops that grow in the Auckland region. Variation in rainfall and drainage are described using a gamma probability density function (PDF), while the variation in irrigation requirement was found to be capable of description using a Gaussian PDF. This general model of irrigation requirements is easily parameterised, and can be run for any crop-soil combination using the historical weather data. It can be used to consider requirements for any level of prescribed risk. It could even be developed further to quantify specific water right allocations, and subsequently it could be turned into a Decision Support Tool for defining good irrigation practice, even in real time.