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New Methodology to Evaluate Flow Rates in On-Demand Irrigation Networks |
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| Authors: | Miguel A. Moreno Patricio Planells José F. Ortega José Tarjuelo |
| Affiliation: | 1Researcher, Agricultural Engineering, Centro Regional de Estudios del Agua, Castilla-La Mancha Univ., Campus Universitario, s/n. E02071, Albacete, Spain. E-mail: miguelangel.moreno@uclm.es 2Professor, Industrial Engineering, Centro Regional de Estudios del Agua. Castilla-La Mancha Univ., Campus Universitario, s/n. E02071, Albacete, Spain. E-mail: patricio.planells@uclm.es 3Researcher, Agricultural Engineering, Centro Regional de Estudios del Agua. Castilla-La Mancha Univ., Campus Universitario, s/n. E02071, Albacete, Spain. E-mail: jose.ortega@uclm.es 4Professor, Agricultural Engineering, Centro Regional de Estudios del Agua. Castilla-La Mancha Univ., Campus Universitario, s/n. E02071, Albacete, Spain. E-mail: jose.tarjuelo@uclm.es |
| Abstract: | Although Clément methodology is the most commonly used model for obtaining the design flow rate in on-demand irrigation networks, studies have shown that the Clément methodology does not always fit properly. A new stochastic methodology is proposed in this paper [random daily demand curve (RDDC)], in order to achieve a more accurate design flow. Results from Clément and the proposed RDDC methodology are compared to measured flow data in an on-demand irrigation network located in Tarazona de La Mancha (Albacete, Spain). RDDC is shown to have a better fit with the measured data compared to the Clément methodology, which underestimated the design flow by 35%–40%. RDDC methodology avoids the problem of using average opening hydrant probability, resulting in a better estimation of the network behavior. |
| Keywords: | Irrigation Hydraulic network Pipe flow Stochastic models |