Modeling the Spatio-Temporal Evolution of Chlorophyll- a in Three Tropical Rivers Comoé, Bandama, and Bia Rivers (Côte d’Ivoire) by Artificial Neural Network

摘要: Rivers and their watersheds play a key role in the global biogeochemical cycle of nitrogen phosphorus biosphere. They are also important economic resources for humans. However, little information is available on eutrophication West African coastal rivers due to costly analytical instruments socio-economic difficulties. In this study, spatial distributions chlorophyll-a biomass Comoe, Bandama, Bia (Cote d’Ivoire) were mapped during dry, rainy flood seasons, dynamics simulated using Artificial Neural Network (ANN) models. The results showed state advanced three sampling seasons. best generalizable models obtained from data collected 2 years covering hydrological seasons forecasted between 76% 85% present concentrations (static approach), 73% 84% future (both dynamic t t + 1 approaches). These achieved satisfactory accuracy with low relative mean errors (MRE) ranging 3.22% 7.71%. study suggest that ANN model could be an original less expensive tool monitoring river water developing countries.