The crop water production function (WPF), representing the relationship between crop yield and seasonal irrigation water, is a useful tool for irrigation planning purposes. The objective of the paper is to propose a methodology to evaluate the optimal seasonal irrigation depth based on the crop production function, the field distribution uniformity, and economic considerations. An extended unpublished database experimentally obtained on the onion crop on the island of Kula, Hawaii, was initially used to assess the crop WPF. The combination between the crop WPF and the model representing the field distribution uniformity allowed determining the area subjected to underirrigation and overirrigation, as well as the corresponding yield, that were finally averaged across the field. An economic comparison was also carried out in order to evaluate the optimal seasonal water depth aimed at maximizing the farmer's gross margin under different irrigation system distribution uniformities and water prices. According to the experimental data, it was observed that the onion crop is more sensitive to deficit than overirrigation, as well as that a quadratic model, valid for the entire range of the seasonal applied irrigation depths fitted better than a two-slope linear model, representing separately the conditions of deficit and over-irrigation. Moreover, the maximum yield, as well as maximum gross margin, can be obtained by applying average irrigation depths lower than those which correspond to the maximum yield, with percentages that declined at decreasing of water distribution coefficient and at increasing of water price. The proposed methodology can be applied even for other crops once the corresponding WPFs aree known, thus providing interesting evaluations that are useful for irrigation planning.
|Number of pages||9|
|Journal||JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING|
|Publication status||Published - 2016|
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Water Science and Technology
- Agricultural and Biological Sciences (miscellaneous)