| Sumario: | The East Kolkata Wetlands (EKW) is a globally recognized Ramsar site, where municipal wastewater is sustainably recycled through several aquaculture ponds. This study focuses on a prominent aquaculture pond, Boro Gopeshwar Bheri, within EKW, to assess surface water turbidity, a critical indicator for the health and functioning of that ecosystem. The study aims to develop a multivariate regression model (MRM) to predict turbidity using satellite-derived spectral reflectance and indices as independent variables. High-resolution imagery from Sentinel-2A MSI was correlated with in-situ turbidity measurements collected using a calibrated turbidimeter. A combination of the key spectral bands was used to understand their strong sensitivity to suspended particulate matter. The model was statistically calibrated using ground-truth turbidity and showed satisfactory predictive performance (R² =0.99; RMSE < 10 NTU), validating it for estimating turbidity in wetland waters. The MRM generates a turbidity image as a continuous raster layer showing predicted turbidity levels (NTU) across the area of interest, enabling spatial and temporal comparisons and helping to identify consistent turbidity patterns and potential zones of elevated turbidity. This hybrid approach of combining remote sensing data and geostatistical analysis offers a high-throughput, cost-effective monitoring framework and a decision-support tool for sustainable wetland management.
|
|---|