MONITORING THE SEASONAL WATER QUALITY VARIATIONS BASED ON REMOTE SENSING IN URBAN LAKES, SRI LANKA

Abstract

Due to rapid urbanization, lakes water face many challenges in present. Therefore, it become an important phenomenon and identifying the spatial distribution of water quality (WQ), including the seasonally is important. But providing accurate WQ data using situ methods, it’s are time-consuming, expensive, and provides lacks of spatiotemporal details. To overcome these issues, remote sensing (RS) has been recognized as an ideal solution. This study is aimed to assess the seasonal WQ distribution using RS in Beira and Diyawanna Lake. Seasonal based Landsat8 satellite data were collected from US Geological Survey in 2020 and observed WQ data obtained from Sri Lanka Land Development Corporation. In methodological terms image preprocessing, empirical methods, regression analysis, and spatial analysis used to estimate the parameters. (Chlorophyll-a, Turbidity, Secchi disk, Nitrate, phosphate, EC, Ammonia, pH, Surface Water Temperature (SWT)). The analysis was carried out using ArcGIS 10.5 and SPSS 23. The findings reveal that the estimated data significantly correlated with observed data with R2 >0.50 and p values< 0.05 mostly. According to the seasonal distribution, the highest chlorophyll-a (442.22mg/L) was recorded in NEM and the lowest (85.65mg/L) was recorded in the SWM. Northern and eastern banks of the Beira Lake showed higher EC in the SWM. The pH of Beira Lake was more Alkaline than Diyawanna Lake during all these seasons. Nitrate and Ammonia have shown higher values in Diyawanna Lake in the SIM (3.1, 1.8mg/L, respectively). The highest phosphate, and Sacchi disk values reported in the SIM (0.9mg/L, 3.1m respectively). The SWT of both lakes fluctuated within four seasons, and the FIM (Appendix 1b) reported the highest value of SWT (42.01oC) and the lowest value (14.69oC) reported in the SWM. Finally, this study showed that Beira Lake WQ was lower than Diyawanna Lake. These analytical results will undoubtedly lead to enhanced WQ improvement strategies in the future.