Evaluation of Water Quality in the Lower Huallaga River Watershed using the Grey Clustering Analysis Method

Currently, the evaluation of water quality is a topic of global interest, due to its socio-cultural, environmental and economic importance, but in recent years this quality is deteriorating due to inadequate management in the conservation, disposal and use of water by the competent authorities, private-state entities and the population itself. An alternative to determine the quality of a water body in an integrated manner is the Grey Clustering Method, which was used in this study taking as an indicator the Prati Quality Index, with the objective of making an objective analysis of the quality of the water bodies under study. The case study is the Lower Watershed of the Huallaga River, located between the region of Loreto and San Martin, along which 12 monitoring stations were established to evaluate its surface water quality, through the analysis of 7 parameters: pH, BOD, COD, Total Suspended Solids (TSS), Ammonia Nitrogen, Substrates and Nitrates. Finally, it was determined that the water quality of eleven monitoring stations in the Lower Huallaga River Watershed are within the "Uncontaminated" category, while one monitoring station is within the "Highly Contaminated" category of the Prati Index, this due to its proximity to a landfill. The results obtained in this study, could be useful for the authorities responsible for the protection and sustainable conservation of the Huallaga River Watershed, in order to propose appropriate measures to improve its quality, additionally, this study could be a reference for future studies since the proposed method allowed to prioritize the quality level of the water bodies and identify critical areas.

@article{Delgado2021,
  title     = {Evaluation of Water Quality in the Lower Huallaga River Watershed using the Grey Clustering Analysis Method},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {1},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Alexi Delgado and Diego Cuadra and Karen Simon and Katya Bonilla and Katherine Tineo and Enrique Lee Huamaní},
  doi       = {10.14569/IJACSA.2021.0120156},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120156}
}