Résumé
This study introduces a novel method for analysing emitter clogging in drip irrigation systems by comparing optical tomography images (OCT) of clogging with hydrodynamic modelling (CFD) through statistical analysis. Utilising Principal Component Analysis (PCA) on data coming from modelling and images on a comparable format, turbulence kinetic energy was identified as the key hydrodynamic parameter influencing both kaolinite and biological clogging. The results indicate that turbulence kinetic energy is minimal at the inlet, correlating with the most severe clogging observed in this region. Two flow conditions were tested, with Reynolds numbers of 300 and 400. The higher Reynolds number (400) resulted in accelerated biofilm development and reduced kaolinite clogging compared to the lower Reynolds number (300), indicating a feeding effect correlated to flow speed and shear stress. This methodology offers new ways to study the relationship between modelling and images, leading to insights to understand mechanisms and optimise dripper designs. This method enables the determination of clogging localisation within drippers based on their geometry and can therefore be applied to various designs to enhance maintenance.