A simplified modelling framework for real-time assessment of conservative pollutants in ungauged rivers during cloudy periods

Recently, the optical remote sensing technique is effectively applied to monitor real-time water quality parameters at finer spatiotemporal scales that are mostly based on the surface reflectance of satellite images. However, during the rainy season due to cloudy or hazy satellite images, it is a great challenge to obtain the surface reflectances and to estimate the pollutant concentration. This study is specially focused on developing a novel approach to estimate the daily-scale pollutant concentrations in ungauged rivers during cloudy days. The developed approach integrates the simplified physically-based VPMM-AD(ΨDc) solute transport model with the remote sensing (RS)-based approach for assessing the non-reactive river pollutants in real-time. This integrated VPMM-AD(ΨDc)-RS approach is tested for simulating the in-situ heavy metal (Fe, Zn, Cu, Cr, Pb, and Cd) and total suspended solid (TSS) concentrations in the Brahmani River during the tropical monsoon (rainy) seasons of the typical years 2010–2013. The study results reveal that the proposed integrated approach performed reasonably well with acceptable accuracy for real-time estimation of pollutant concentrations in the considered ungauged river reach during the cloudy period. •Devised a novel VPMM-AD(ΨDc)-RS framework for assessing conservative pollutants in ungauged river reaches.•VPMM-AD(ΨDc) routes both streamflow and contaminants downstream as an embedded system.•RS framework uses the spatiotemporal adaptive fusion of MODIS and Landsat images.•This addresses the limitations of optical remote sensing due to cloud contamination.