Geospatial distribution and machine learning algorithms for assessing water quality in surface water bodies of Morocco.

ABSTRACT: Surface waterbodies being primary source of water for human consumption are being investigated for its quality globally. This study evaluated water quality in three rivers (River Nfifikh, Hassar and El Maleh) of Mohammedia prefecture, Morocco in terms of heavy metals occurrence during two seasons of winter and spring. The heavy metals analyzed were cadmium, iron, copper, zinc, and lead. Heavy metal pollution index was derived to quantify water quality and pollution. Hazard quotient and carcinogenic risk were calculated to determine possible health risk. Modelling and prediction were performed using random forest, support vector machine and artificial neural network. The heavy metal concentration was lower in the winter season than in the spring season. Heavy metal pollution index (H.P.I.)

SUBMITTER: El Morabet R 

PROVIDER: S-EPMC10667218 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature