Fuzzy Inference System in Assessing the Improved Wastewater Quality for Irrigation through Sedimentation, Dilution, and Biochar Filtration in Sulaymaniyah City, Iraq

Abstract The study aims to improve the quality of wastewater in Sulaymaniyah city, Iraq, which has been facing drought problems, by using sedimentation, dilution (1:1), and biochar filtration. It provides an alternative source water for agriculture, addressing shortage problem region. irrigation is evaluated based on Water Quality Index (WQI) a fuzzy inference system, mathematical tool that converts complex statements into terms simplifies them outputs. centroid defuzzification technique applied convert results crisp numbers. output FIS score used determine suitability irrigation. utilized six different samples: groundwater (GW), (WW), sedimented (SW), filtered (FSW), diluted (DSW), (FDSW). samples were analyzed their physical chemical properties, including pH, electrical conductivity (EC), total suspended solids (TSS), turbidity (TUR), nitrogen (TN), phosphate (TP), cations (Ca, Na), anions (Cl SO 4 ), heavy metals (Mn, Fe, Co, Ni, Zn, Cu). found WQI FIS-I values increased with each treatment step, final step passing DSW through filter resulting WQI-I value 61.59, indicating good quality. deterministic method also showed improved levels TP, TN, TSS, turbidity. Mean TN TP decreased 8.9 mg L -1 3.62 , respectively, FDSW, TSS decreasing 0.37 NTU 21 . FDSW was best among treated waters, making it suitable drip