Determining Multivariate Analysis Sampling Frequency for Monitoring Contamination Caused by Trout Farms Publisher



Tavakol M¹ ; Arjmandi R¹ ; Shayeghi M² ; Monavari SM¹ ; Karbassi A³
Source: Polish Journal of Environmental Studies Published:2017

Abstract

Recent rapid growth of the aquaculture industry and the necessity to comply with environmental standards suggest the need for studies on the possible negative effects of this type of industry. One of the most devastating effects of aquaculture is water pollution caused by the discharge of untreated effluent from fish farms into aquatic ecosystems. Assessment of the pollutants requires an optimal design of a water monitoring network in a way to demonstrate changes in aquatic environments. Accordingly, the present study used multivariate statistical analysis to determine sampling frequency for optimal monitoring of the contaminants resulting from trout farms in the Haraz River in northern Iran. For this purpose, a total number of 17 physical and chemical water quality parameters were sampled monthly over a one-year period based on the instructions recommended in the standard method (2005) [1]. The results showed that changes in biochemical oxygen demand (BOD) during the warm months of summer were very high and reached its peak in August and September. This may be attributed to the increased fish production in fish farms, increased food intake to feed the fish, and higher rate of discharge from fish farms containing waste feed and fish faeces. The nitrate also reached its maximum level in June due to the same reasons. Conversely, dissolved oxygen (DO) level was the lowest in the warm months (August and September). The reason would be increased consumption of DO due to higher production rate in the fish farms and increased metabolism of fish in warm months. Overall, the findings confirmed the applicability of multivariate techniques in determining temporal frequency of the measurements during the monitoring period. By which it would be possible to recognize the reality of changes in water quality, with fewer measurements, and in less time and cost. © 2017, HARD Publishing Company. All rights reserved.