부산대학교 도서관

Lakes are versatile ecosystems which perform valuable functions such as recycling nutrients, attenuating floods, recharging ground water and also serve the water needs of the human populace. Now-a-days the quality of surface water is getting deteriorating at a rapid pace due to excess water withdrawal and various anthropogenic activities. In this study the eutrophication status of Sasthamkotta lake, a fresh water wetland in the South western part of India which is also a Ramsar site is determined in terms of Carlson's Trophic State Index and thereafter the same is modeled using Geographical Information System and Remote Sensing. The study was carried out from the month of October 2018 to the month of September 2019 and parameters namely Chlorophyll-a and total phosphorus were analysed and in-situ secchi depth was measured to determine the eutrophication status of the lake and the same was mapped using Geographical Information System. It was found that major portion of the lake comes under the lower mesotrophic category (Carlson's Trophic State Index ranging from 30 to 40). Localised moderate mesotrophic condition was observed at sampling stations namely Ambalakadavu, Vettolikadavu and Mynagappaly pump house and oligotrophic condition was found at the sampling station near sayippu house during the post-monsoon, pre-monsoon and monsoon season of the said period. Densely populated catchment area of the lake, physical setting of the lake characterised by steep slopes on three sides and excess nutrient flow from the agricultural fields surrounding the lake during rainfall could be attributed to the lower mesotrophic trophic state of the lake. Remote sensing data (Landsat OLI satellite images) was used to model and validate the parameter chlorophyll-a and the statistical analysis showed a high correlation between satellite-based normalized difference vegetation index (NDVI) and in- situ measured parameter chlorophyll a (Chl-a) concentration. Two linear regression models with high determination coefficients of 0.935 (Post-monsoon) and 0.99 (Pre-monsoon) and correlation coefficient of 0.967 (Post-monsoon) and 0.995 (Pre-monsoon) were obtained from the regression analysis. Therefore it can be concluded that remote sensing data was used effectively to model the eutrophication status of Sasthamkotta lake. [ABSTRACT FROM AUTHOR]