Application of Multivariate Statistical Methods to Optimize Water Quality Monitoring Network with Emphasis on the Pollution Caused by Fish Farms

By Tavakol, Mitra; Arjmandi, Reza et al. | Iranian Journal of Public Health, January 2017 | Go to article overview

Application of Multivariate Statistical Methods to Optimize Water Quality Monitoring Network with Emphasis on the Pollution Caused by Fish Farms


Tavakol, Mitra, Arjmandi, Reza, Shayeghi, Mansoureh, Monavari, Seyed Masoud, Karbassi, Abdolreza, Iranian Journal of Public Health


Introduction

In recent decades, population growth, increasing need for countries to protein, good quality of fish protein compared to other proteins, remarkable marine resources, job creation especially in rural communities, and have put a spotlight on aquaculture industry more than ever (1-4). Discharge of effluent from fish farms that contains a variety of pollutants can lead to direct and indirect risks to human health and the environment (5-9).

A large number of people through the use of contaminated water are prone to various kinds of diseases (10, 11).

The risk of surface water contamination makes inevitable measurement and monitoring of these resources. Monitoring Process includes programs and activities that checks the quality of water resources and performance of pollution reduction system within various time periods. Since quality monitoring requires the measurement of various parameters in the river course and requires spending much time and cost, therefore, the design of an optimal network that, can adequately determine the quality of river systems with minimum cost, would be of great importance. Surface water influenced by chemical, physical, and biological contaminations that eventually affects the receiving environment and human health (12, 13).

Surface water systems include rivers, lakes, reservoirs, estuaries, and coastal waters. Apart from the anthropogenic sources, the quality of surface water can be influenced by geology of areas under investigation (14).

Therefore, assessment of river water quality is of great importance because it directly influences public health (via drinking water) and aquatic life (via raw water). Water Quality Indices (WQI) has been developed in the recent years. These indices are based on parameters such as pH, DO, BOD, NO3, PO4, TDS, TSS, EC, coliform, etc. Nowadays, river pollution due to aquaculture activities and the resulting risks have made the design of optimal water monitoring networks as one of the important topics of research around the world. Long-term monitoring of the seabed in West Bay affected by aquaculture facilities using univariate and multivariate analyses, achieved an adaptive monitoring protocol.This protocol provided the possibility to monitor pollutants from aquaculture activities in the region with the lowest cost and with high efficiency.(15)

A remote monitoring system designed for aquaculture cages in the open ocean for real-time measurement of water quality parameters (16).

A biological warning system (BWS) monitored identified or unknown pollutants of aquaculture environments (17).

After extensive monitoring 21 fish farms in Italy, the remains of organ chlorine pesticides examined in fish species. According to those results, levels of pesticides were much lower than the standard limits (18).

Dissolved organic matters caused by aquaculture systems in the rivers of northern Patagonia, Chile. Large amounts of dissolved organic matters disposed from these systems could leave significant adverse effects on the riverine ecosystem in north of Patagonia (19).

Multivariate statistical analysis due to its characteristics can be an efficient and useful technique for understanding and analysis of river pollution. It is also useful in proper reasoning and decision making in the management of water quality.

Materials and Methods

Study area

Haraz Watershed with an area of 5100 km2 is situated in the northern part of the Alborz Mountains between the longitudes 35° 45'-36° 42' N and the latitudes 51° 27'-52° 42' E (20). Several streams join the Haraz River. The most important of which are Namarestaq with a flow rate of 3 m3/s and Nour with a flow rate of 3.5 m3/s. Average discharge of Haraz River is 940 MCM/yr (20).

The river length in the longest tributary is 148 km and the width varies from 50 m to 500 m along the river course. The narrowest part of the river is near the sea where the water depth increases. …

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