Using different multivariate approaches to assess water quality of qanats in arid zones of Southern Central Mexico.

Qanats in the aquifer of the Tehuacán Valley (Mexico) represent an ancient way of using groundwater that is still practiced today. They are used mainly for agricultural irrigation. However, anthropogenic activities have jeopardized the use of these aquifers. We analyzed 24 qanats in the Tehuacán Valley to assess water quality. Based on 24 physicochemical variables, a water quality index (WQI) was constructed on a zero-to-100 scale, divided into five water quality classes. A decision-tree analysis was applied to identify the parameters with the highest influence on the WQI, considering the water quality classes as categorical responses and the values of physicochemical variables as drivers of these categories. We produced interpolation maps to identify trends. The relationship between the WQI and the normalized difference indices of vegetation and salinity (NDVI and NDSI, respectively) was analyzed using a ternary diagram. WQI scores showed that 12.5% of the qanats have very good quality; 25%, good quality; and the remaining (62.5%) range from moderate to unacceptable quality. The CHAID classification-tree method correctly explained 83.3% of the categories, with sulfates, alkalinity, conductivity, and nitrates as the main parameters that explain water quality. WQI was inversely related to NDVI and NDSI, showing seasonal differences. Interpolation maps suggest a better water quality in the northern zone of the aquifer.