Abstract:Exploring qualitative measures of any waterbody is as vital as quantitative analysis for the sustainability of our water resources. Thus, examining the dynamics of spatiotemporal behaviour of dominant Water Quality Parameters (WQPs) along any waterbody is indeed critical for proposing the appropriate water resource management. This study aims to create a Machine learning model for mapping the dominant optical and non-optical WQPs such as Electrical Conductivity (EC), pH, Temperature (Temp), Total Dissolved Sol… Show more
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