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

Abstract

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 of water for agriculture, addressing the water shortage problem in the region. The irrigation water quality is evaluated based on the Water Quality Index (WQI) using a fuzzy inference system, a mathematical tool that converts complex statements into mathematical terms and simplifies them into outputs. The centroid defuzzification technique is applied to convert the fuzzy results into crisp numbers. The output of the FIS score is used to determine the suitability of water for irrigation. The study utilized six different samples: groundwater (GW), wastewater (WW), sedimented wastewater (SW), filtered sedimented wastewater (FSW), diluted sedimented wastewater (DSW), and filtered diluted sedimented wastewater (FDSW). The samples were analyzed for their physical and chemical properties, including pH, electrical conductivity (EC), total suspended solids (TSS), turbidity (TUR), total nitrogen (TN), total phosphate (TP), cations (Ca, Na), anions (Cl and SO4), and heavy metals (Mn, Fe, Co, Ni, Zn, Cu). The study found that the WQI FIS-I values for wastewater increased with each treatment step, with the final step of passing the DSW through a biochar filter resulting in an FIS WQI-I value of 61.59, indicating good water quality. The deterministic method also showed improved levels for TP, TN, TSS, and turbidity. Mean TN and TP values decreased to 8.9 mg L-1 and 3.62 mg L-1, respectively, in the FDSW, with turbidity and TSS also decreasing to 0.37 NTU and 21 mg L-1. The resulting FDSW was of the best quality among the treated waters, making it suitable for drip irrigation.