Water quality management plans are an indispensable strategy for conservation and utilization of water resources in a sustainable manner. One common industrial use of water is aquaculture. The present study is an attempt to use statistical analyses in order to prepare an environmental water quality monitoring program for Haraz River, in Northern Iran. For this purpose, the analysis of a total number of 18 physicochemical parameters was performed at 15 stations during a 1-year sampling period. According to the results of the multivariate statistical methods, the optimal monitoring would be possible by only 3 stations and 12 parameters, including NH, EC, BOD, TSS, DO, PO, NO, TDS, temperature, turbidity, coliform, and discharge. In other words, newly designed network, with a total number of 36 measurements (3 stations × 12 parameters = 36 parameters), could achieve exactly the same performance as the former network, designed based on 234 measurements (13 stations × 18 parameters = 234 parameters). Based on the results of cluster, principal component, and factor analyses, the stations were divided into three groups of high pollution (HP), medium pollution (MP), and low pollution (LP). By clustering the stations, it would be possible to track the water quality of Haraz River, only by one station at each cluster, which facilitates rapid assessment of the water quality in the river basin. Emphasizing on three main axes of monitoring program, including measurement parameters, sampling frequency, and spatial pattern of sampling points, the water quality monitoring program was optimized for the river basin based on natural conditions of the study area, monitoring objectives, and required financial resources (a total annual cost of about US $2625, excluding the overhead costs).

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