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Automatic flushing valve (AFV) can improve the anti-clogging ability of the drip fertigation system. The minimum inlet pressure (<i>H</i>_amin) required for automatic closing and the maximum flushing duration (FD_max) are two important performance indexes of AFV. The existing AFV products have the problem of larger <i>H</i>_amin and smaller FD_max, which result higher investment and operating cost, and poor flushing efficiency. Based on the mechanical analysis of the AFV elastic diaphragm and the derivation of the FD, elastic diaphragm hardness (<i>E</i>), ascending channel offset distance (<i>D</i>), and drain hole width (<i>W</i>) were selected as the experimental factors, and nine AFVs were designed by L₉(3³) orthogonal test method to investigate the influence of elastic diaphragm hardness and structural parameters on the hydraulic performance of AFVs. The hydraulic performance test results showed that the <i>H</i>_amin of the nine AFVs ranged from 0.026 to 0.082 MPa and FD_max ranged from 36.3 to 95.7 s. <i>H</i>_amin was positively correlated with <i>E</i> and <i>D</i> and negatively correlated with <i>W</i>. FD_max was negatively correlated with <i>E</i> and <i>W</i> and tended to increase and then decrease with <i>D</i>. All elastic diaphragm hardness and structural parameters had a significant effect on <i>H</i>_amin, and <i>E</i> and <i>W</i> had a significant effect on FD_max. Based on the range analysis, two new combinations of AFV elastic diaphragm hardness and structural parameters with minimum <i>H</i>_amin (<i>E</i> = 40 HA, <i>D =</i> 0 mm, <i>W</i> = 2 mm) and maximum FD_max (<i>E</i> = 40 HA, <i>D</i> = 2 mm, <i>W</i> = 1.68 mm) were determined, and the corresponding <i>H</i>_amin was 0.022 MPa, 63.3% lower than that of the existing product, and FD_max was 116.4 s, 71.2% higher than that of the existing product. In this study, two ternary nonlinear mathematical regression models of <i>H</i>_amin and FD_max with elastic diaphragm hardness and structural parameters was constructed. The simulation accuracy of the models is good and can be used to quickly predict the optimal combination of AFV parameters to satisfy the actual engineering-required <i>H</i>_amin and FD_max.