Estimation of water quality profiles in deep lakes based on easily measurable constituents at the water surface using artificial neural networks coupled with stationary wavelet transform

This study proposes a novel framework to accurately estimate water quality profiles in deep lakes based on parameters measured at the water surface, considering Boulder Basin of Lake Mead as a case study. Hourly-measured meteorological data were used to compute heat exchange between lake and atmosphere. Heat fluxes combined with every 6-hour measured water temperature, conductivity, and dissolved oxygen (DO) profiles, from the water surface to a...