Water scarcity is a global concern, with irrigation of food crops contributing significantly to freshwater depletion. Drip irrigation technology reduces water consumption but faces issues like clogging in narrow discharge sections, diminishing efficiency, and increasing costs. Accurate prediction of flow characteristics and understanding pa- rameters affecting biofilm growth and particle deposition is crucial for effective anti-clogging strategies. Computational fluid dynamics (CFD) using turbulence models can be a valuable tool. This study evaluated the accuracy and efficiency of different turbulence models (standard k-ε, Reynolds Stress Model, and Large Eddy Simulation) in predicting the flow characteristics of a commercial emitter in a drip irrigation system. Results showed the standard k-ε model as a preferred choice for simulating mean flow characteristics and emitter discharge due to its balance between accuracy and computational efficiency. However, the Large Eddy Simu- lation model provided the most accurate results, considering the emitter discharge, unsteady flow behavior, wall shear stress distribution, and oscillatory index, despite requiring more computational resources. This model is valuable for understanding hydrodynamic effects on emitter clogging. The study also investigated the impact of velocity fluctuations, wall shear stress, and oscillatory shear index on biofilm growth and deposition in the emitter. Low shear stress in inlet and return zones reduced self-cleaning ability, leading to particle and micro- organism attachment. Maintaining appropriate wall shear stress values in other regions proved crucial for improving anti-clogging ability. High oscillatory shear index values enhanced mass transfer, nutrient mixing, diffusion within the biofilm, and self-cleaning capacity. In summary, this study greatly enhances our under- standing of how flow dynamics and biofilm management impact drip irrigation systems. It provides practical insights for engineers and practitioners, aiding in the creation of more efficient and clog-resistant systems. By optimizing these dynamics and strategies, this research promotes sustainable water use in agriculture, while also minimizing maintenance costs and maximizing crop yields.