Variability of the Water Quality Characterizing High Andean Lagoons for Tourist Use Evaluated Through Multivariate Statistical Methods, Junín, Peru

Journal of Ecological Engineering

卷:20

María Custodio¹  Heidi De la Cruz¹  Richard Peñaloza¹  Fernán Chanmé¹  Gloria Miranda² 

[1] Universidad Nacional del Centro del Perú, Centro de Investigación en Alta Montaña, Av. Mariscal Castilla N° 3989-4089, Huancayo, Perú;

[2] Universidad de Guanajuato, Departamento de Estudios Culturales Demográficos y Políticos, División de Ciencias Sociales y Administrativas, México;

关键词: surface water quality;    high Andean lagoons;    tourist use;    indicators;    multivariate statistical methods;   

DOI  :  10.12911/22998993/109800

来源: DOAJ

【 摘 要 】

The spatial-temporal variability of the water quality of high Andean lagoons for tourist use was evaluated using multivariate statistical methods during 2017 and 2018. Water samples were collected from 14 sampling sites, with three replicates each. The water quality indicators determined were: pH, temperature, DO, COD, BOD5, P, N, Fe, Cu, Cr, Cd, Pb, Zn and chlorophyll-a. The flat cluster analysis (k R cluster) according to Ward's algorithm showed six significantly differentiated groups (α=0.01). While the real similarity profile (SIMPROF) moves markedly away from the obtained low permutation with a large excess of Euclidean similarity with a Pi value of 0.627. The PCA showed that the first two components recommended by the sedimentation analysis (Scree test) indicated 61.52% of the total variation of the observations. According to the Spearman range correlation selection criterion, the variables that best interpret the sample distributions are COD, DTS, P, Cd and Zn with a correlation of 0.893, the DTS being the most important variable with a correlation value of 0.795. The PERMANOVA analysis according to the flat cluster factor indicated that at least one of the groups is different from the others in relation to the levels of physical-chemical characteristics studied. Therefore, all the configured groups are statistically different, demonstrating that each lagoon of tourist use is different in relation to its physical-chemical indicators, according to the season in which it is found.

【 授权许可】

Unknown