Monte Kietpawpan, Parichart Visuthismajarn, and Chatchai Ratanachai

pp. 359 - 365

Abstract

The classification of trophic conditions of water bodies may often face contradictory cases where a
given lake is classified into a trophic category from a trophic variable, whereas it is classified into another
trophic category from other trophic variables. To solve this problem, this paper proposes a new methodology
based on the concepts of squared Euclidean distance and the boundary values recommended by the OECD
(Organization for Economic Cooperation and Development). This methodology requires that a trophic variable data set of a water body under consideration and such boundary values be compared by a measure of
similarity computed by using basic statistical techniques to determine the trophic condition of a given water
body. The methodology has been tested by applying it to two sample data sets: the Pattani Dam Reservoir
and the North Adriatic Sea data sets, which were taken from Kietpawpan (2002) and Zurlini (1996), respectively. The squared Euclidean distance analysis were then applied to the above data sets in order to classify
trophic conditions, based on four trophic variables comprising total nitrogen, total phosphorus, chlorophyll-a, and Secchi depth. Our results show that the squared Euclidean distance analysis is a useful methodology
for preliminarily classifying trophic conditions and solving contradictory classifications, which often arise
when applying the present OECD methodology alone.