New Methodology to Evaluate Flow Rates in On-Demand Irrigation Networks

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.