Artificial intelligence model based on grey systems to assess water quality from Santa river watershed

Abstract

Water resources quality assessment is a topic very complex, as it demands a great variety of parameters to be analyzed. In this context, the grey clustering method, which is based on grey systems theory, offers an interesting alternative to assess water quality using artificial intelligence criteria. In this study, we assess water quality from Santa river watershed according to parameters stablish by MINAM-Peru (DS N° 015-2015). In addition, we analyze monitoring data from water national authority from Peru (ANA), which was collected, in the study area, in 2013. Twenty-one monitoring points from Santa river watershed were analyzed. The results showed that 47.6% of the monitoring points presented good water quality to consumption of the population, which indicated that could be purified by applying disinfection; 33.3% of the monitoring points presented moderate water quality to consumption of the population, which indicated that could be purified by applying conventional treatment; and 19.1% of the monitoring points presented low water quality to consumption of the population, which indicated that could be purified by applying special treatment. The grey clustering method showed interesting results and could be applied to others studies on water quality or environmental quality in general.