Water Quality in Areas Surrounding Mining: Las Bambas, Peru
Alexi Delgado1, Alvaro Espinoza2, Patrick Quispe3, Pablo Valverde4, Ch. Carbajal5

1Alexi Delgado*, Department of Engineering, Mining Engineering Section, Pontificia Universidad Católica del Perú, Lima, Peru.
2Alvaro Espinoza, Mining Engineering Section, Pontificia Universidad Católica del Perú, Lima, Peru.
3Patrick Quispe, Mining Engineering Section, Pontificia Universidad Católica del Perú, Lima, Peru.
4Pablo Valverde, Mining Engineering Section, Pontificia Universidad Católica del Perú, Lima, Peru.
5Ch. Carbajal, Administration Program, Universidad de Ciencias y Humanidades, Lima, Peru.

Manuscript received on September 18, 2019. | Revised Manuscript received on 28 September, 2019. | Manuscript published on October 10, 2019. | PP: 4427-4432 | Volume-8 Issue-12, October 2019. | Retrieval Number: L38071081219/2019©BEIESP | DOI: 10.35940/ijitee.L3807.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Nowadays, it is known that water is a critical issue for human life. For this reason, research in this category is a complex subject. The case chosen for this work is in the district of Tambobamba, Cotabambas province, in the region of Apurimac. This is where Las Bambas mine is operating and the area of influence includes the Challhuahuacho and Ferrobamba rivers. Based on six monitoring points, carried out between February 2017 and March 2019 by ANA, it was possible to know if these rivers would have a low or high degree of contamination. Therefore, the methodology used in this work was the Grey Clustering Method. This method includes vital water parameters established by Peruvian D.S. N° 004-2017-MINAM. The results of these studies show that the Ferrobamba River has a high water quality while the Challhuahuacho River has a poor water quality, which could be associated with spills in the area.
Keywords:  Grey Clustering, Mining Project, River Water Quality, Water Quality
Scope of the Article: Clustering