Characterization of Yamuna River water quality and its remediation by Phytoremediation technique

The Yamuna River in Delhi faces a critical environmental crisis due to escalating pollution levels. As per recent Delhi Pollution Control Committee reports, Delhi has 37 STPs with a combined treatment capacity of 566.3 MGD. However, with sewage generation reaching 792 MGD, approximately 225.7 MGD of untreated sewage is discharged directly into the river. This effluent significantly degrades water quality and poses a severe threat to aquatic ecosystems. The study assesses seasonal variations in the river's water quality, utilizing Box-and-Whisker plots and Hierarchical Agglomerative Clustering Analysis (HACA) to characterize spatiotemporal dynamics. In addition, the study explores the potential of phytoremediation techniques for restoring the health of the Yamuna River. Water samples were collected in three different seasons from eight sampling stations and nine parameters were determined viz., pH, temperature, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), ammonia, and chloride. This study unveils the severe impact of pollution in the Yamuna River as drains mix into its water, causing zero DO levels. Box plots showed significant water quality degradation during dry seasons, with improvement in the rainy season. HACA optimized monitoring by identifying similar stations. Additionally, phytoremediation by Canna indica reduced TDS, ammonia, BOD, and COD levels, increasing DO from 0 ppm to 7.78 ppm, with over 95 % efficiency in removing BOD and COD when paired with aeration. The study introduces a cost-effective approach for remediating polluted stretches, emphasizing the critical role of multivariate statistical techniques in identifying key pollutants.