Abstract:
Eutrophication of lentic water bodies have
significant impact on the natural environment and human life.
The quantities of nitrogen, phosphorous and other biologically
useful nutrients are the primary determinants of a water
body’s Trophic State Index (TSI). The artificial intelligence
(AI) methods have enhanced the estimation of Eutrophication
status of lentic systems like fresh water lakes. This study uses
three artificial intelligence methods such as M5 Model Tree,
Support Vector Machine (SVM) for the prediction of Trophic
states of Sasthamcotta fresh water Lake, Kerala. Four
different cases were considered in the study via prediction of
individual trpohic status (TSI-Ph, TSI-Ch1-a and TSI-Sechi
Depth) along with the classical Carlson’s Trophic State Index
(CTSI). Several statistical measures were used to quantify the
performance of the three AI methods. Both the tree based
algorithms were found to be successful in accurate prediction
of TSI with Random Forest method as the best among them.
