Por: Carlos López Mendoza, Universidad Nacional de Cajamarca y Alexi Delgado Villanueva, Pontificia Universidad Católica del Perú.

Abstract

Mining environmental liabilities (PAM in its acronym in Peru), constitute one of the biggest problems in Peru, since they are the cause of social conflicts due to the impact they generate on the environment, especially on water quality. The methodology chosen for the research was Grey Clustering, which provides an alternative to evaluate water quality in an integral manner considering uncertainty within the analysis. 

The Center-Point Triangular Whitenization Weight Functions (CTWF), which is a gray clustering approach, was used as an assessment mechanism to determine the water quality of the Llaucano River watershed. 

The study was carried out taking into account eleven monitoring points established by the National Water Authority (ANA) and analyzed on the basis of five parameters (pH, aluminum, iron, lead and zinc). The results showed that 36.6% of the points belong to category A1, which requires disinfection to be purified, 36.6% belong to category A2, which requires conventional treatment to be purified, and 27.28% belong to category A3, which requires advanced treatment. 

These results can be useful for organizations in charge of remediating mining environmental liabilities, such as knowing the water quality of the Llaucano river basin and implementing a remediation plan for the affected areas.