The role of freshwater lakes in providing water resources and supporting ecosystems is essential. Monitoring water quality using remote sensing (RS) technologies is crucial for sustainable management practices. A study on Loktak Lake was done using RS algorithms to predict post-monsoon water quality. The multiplication band model (B1 × B6) demonstrated a moderate correlation with dissolved oxygen (DO) values (mg/l) with (coefficient of determination, R2 = 0.47, root mean square error, RMSE = 0.23, and standard error of estimation, SEE = 0.23). The band combination (B2/B4) was strongly correlated with electrical conductivity (EC) values (μs/cm) (R2 = 0.60, RMSE = 9.44, and SEE = 9.69). For total dissolved solids (TDS) (mg/l), with an R2 = 0.61, RMSE = 5.95, and SEE = 6.09, Band 2 demonstrated a strong correlation between field values and satellite imagery. The post-monsoon water quality map of the lake indicates lower concentrations of DO, EC, and TDS on the western side and elevated values on the eastern side. The research concluded that RS algorithms can be effectively used to predict water quality parameters in Loktak Lake, specifically DO, EC, and TDS. The findings suggest that effective pollution management is needed on the western side of the lake.

  • Frequent and continuous water quality monitoring has been problematic in Loktak Lake, Manipur.

  • A linear regression can be used to develop algorithms for retrieving water quality data.

  • Water quality prediction model for DO, EC, and TDS.

  • Remote sensing (RS) and GIS provide rapid information on water quality and spatial variability.

  • Spatial water quality map can be generated using RS and GIS.

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