Development of a Biodegradability Index for Urban Rivers Using Detergent Concentration: A Case Study from Tehran, Iran

Urban rivers are increasingly impacted by anthropogenic activities, leading to significant changes in water quality and pollutant levels. These rivers are subject to multiple environmental pressures, such as industrial discharge, urban runoff, and domestic wastewater, all of which affect the ecological health of the water systems and surrounding communities. To assess the impacts of these pollutants and to guide appropriate water management strategies, reliable and efficient indicators are required. This study introduces a novel Biodegradability Index (BI) designed specifically for urban rivers, based on the ratio of Biochemical Oxygen Demand (BOD₅) to Chemical Oxygen Demand (COD). The proposed BI allows for better monitoring and management of organic pollution by considering the biodegradability of pollutants, which is an important factor in assessing a water body’s self-purification potential. The index was developed using water samples collected across the metropolitan area of Tehran, Iran, and the relationship between the BI and various water quality variables (WQVs) was explored using statistical and machine learning techniques. The results show a strong correlation between detergent concentrations and the BI, with a Spearman correlation coefficient of 0.82 and an R² value of 0.63. A predictive model for BI was also developed using detergent concentrations, achieving an R² of 0.7, thus suggesting that detergent levels can serve as a reliable, low-cost predictor of biodegradability in urban rivers. This study offers a practical approach to estimating the BI, which could significantly improve water quality assessments in urban areas by providing a simpler and faster method for evaluating river health. The findings underscore the importance of using a dedicated biodegradability index tailored to urban rivers, which are subject to unique and complex pollutant profiles compared to natural water systems. The proposed method has potential applications for sustainable urban river management and pollution mitigation strategies.