Abstract:
Reservoirs are essential natural assets and sustaining them demands a full knowledge of the factors that affect their water quality. Traditional analysis methods for water parameter mapping on a wide scale are expensive and time-consuming. Current research looks at how merging remote sensing data with hyperspectral spectroradiometer data enhances the accuracy of water quality monitoring. Fifteen samples were taken from Rawal Lake, Islamabad on 6th June 2023. The research aims to perform laboratory analysis of water quality parameters (pH, turbidity, EC, nitrates, and phosphates) and then predict the model of the laboratory analysis with Landsat 8 with seven bands (430-2290nm) and Field Spec ASD (350-2500nm) data. Laboratory analysis indicates that pH (7.61) and EC (41.56 S/m) are within the permissible limit while turbidity (36.21 NTU), nitrates (0.75 mg/L), and phosphates (1.23 mg/L) exceed the limit described by WHO. The results of NDCI range from -0.51 to 0.42 for 2013 and from -0.05 to 1.81 for 2023. The results of NDTI range from -0.06 to 0.04 for 2013 and from -0.08 to 0.24 for 2023. The results of regression models for water quality prediction reveal that ASD ratio R530/R620 yields R2=0.75 with RMSE4 of 0.15 for predicting turbidity. In comparison, applying the ratio B4-B3/B4+B3 within the spectral range had an RMSE of 0.27 and R2=0.62. For phosphates prediction, the ASD ratio R506/R861 resulted in an RMSE of 0.03 and an R2 of 0.77, while the ratio B2/B4 within the corresponding spectral range shows an RMSE of 0.05 and R2 of 0.67. Furthermore, for nitrates prediction, the ASD ratio R550/R750 yielded R2 = 0.72 and an RMSE of 0.34, whereas the B2/B4 ratio produced R2 = 0.56 and an RMSE of 0.49. In a nutshell, the findings show that for all three water quality criteria, ASD ratios consistently performed better than OLI ratios.
