Identification of temporal and spatial variations of water quality in Sanya Bay, China by three-way principal component analysis

Abstract

A large data set obtained by a 1-year monthly determination of water quality from Sanya Bay, South China Sea, was treated by three-way principal component analysis aimed at exploring the spatial and temporal patterns of water quality in Sanya Bay. Tucker3 model of optimum complexity (2, 2, 1) explaining 33.18% of the data variance, allowed interpretation of the data information in three modes. The model explained spatial and temporal variation trends in terms of water quality variables during the study period. Water quality in sampling station (S2) Sanya River was mainly influenced by Sanya River, and water quality in other stations (S1, S3-S10) were mainly influenced by the waters in South China Sea. The results delineated the mouth of Sanya River as critical from pollution point of view. The dry season from October to the next April and rainy season from May to September have different influences on water quality in Sanya Bay. The information extracted by the three-way models would be very useful to regional agencies in developing a strategy to carry out scientific plans for resource use based on marine system functions.