Estimating the quality of treated wastewater is a complex, nonlinear challenge that traditional statistical methods struggle to address. This study introduces a hybrid machine learning approach to predict key effluent parameters from an advanced biological wastewater treatment plant and assesses the reuse potential of treated wastewater for irrigation. Three artificial intelligence (AI) models, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Fuzzy Logic-Mamdani (FLM), were applied to three years of daily inlet and outlet water quality data. Fuzzy Logic was employed to predict the usability potential of treated wastewater, with ANFIS categorizing quality parameters and ANN-based high-performance models (low MSE, 74–99% R²) applied in the fuzzy inference system. The qualitative reuse potential of treated wastewater for agricultural irrigation ranged from 69% to 72% based on the best-performing model. It was estimated that treated wastewater could irrigate approximately 35% of a 20,000-hectare agricultural area. By integrating machine learning models, this research enhances the accuracy and interpretability of wastewater quality predictions, providing a reliable framework for sustainable water resource management. The findings support the optimization of wastewater treatment processes and highlight AI’s role in advancing water reuse strategies in agriculture, ultimately contributing to improved irrigation efficiency and environmental conservation.

Fruit growing is more important in terms of agricultural cultivation. Pear is a valuable kind of fruit species that supported to economy in Turkey. Pear trees need to irrigation in the period of growing/cultivation. Irrigation is more important factor for pear. Generally, application of irrigation recommend from the beginning of May until the end of September. Irrigation methods change according to orchard’s soil characteristic and climatic conditions depend on research area. For this reason, a project for a pear orchard of 1 da to be drip irrigated was prepared and put into operation. Monitoring and evaluation efforts were made in the field and were compared with those for the non-irrigated areas. In this study, irrigation methods and water resources were investigated in orchard of pear in the vicinity of Hisareyn/Kocaeli in Turkey. So, double ring infiltrometer test has been done for the determination of soil infiltration rate and the infiltration value of the soil has been calculated as 8 mm h -1 . After the some soil characteristics were determined, drip irrigation system set up in the area for orchard irrigation. With irrigation time scheduling, it has been proposed that 10-12 hours of irrigation once a week or 6-7 hours of irrigation every 4 days can be applied. Keywords: Drip irrigation, infiltration, irrigation project, productivity, water management