Preparation of environmental monitoring plan pattern for surface water quality in Iran (Case study: Gharehsou River)

Using water quality management programs is a necessary and inevitable way for preservation and sustainable use of water resources. One of the important issues in determining the quality of water in rivers is designing effective quality control networks, so that the measured quality variables in these stations are, as far as possible, indicative of overall changes in water quality. One of the methods to achieve this goal is increasing the number of quality monitoring stations and sampling instances. Since this will dramatically increase the annual cost of monitoring, deciding on which stations and parameters are the most important ones, along with increasing the instances of sampling, in a way that shows maximum change in the system under study can affect the future decision-making processes for optimizing the efficacy of extant monitoring network, removing or adding new stations or parameters and decreasing or increasing sampling instances. This end, the efficiency of multivariate statistical procedures was studied in this thesis. Multivariate statistical procedure, with regard to its features, can be used as a practical and useful method in recognizing and analyzing rivers’ pollution and consequently in understanding, reasoning, controlling, and correct decision-making in water quality management. This research was carried out using multivariate statistical techniques for analyzing the quality of water and monitoring the variables affecting its quality in Gharasou river, in Ardabil province in northwest of Iran. During a year, 28 physical and chemical parameters were sampled in 11 stations. The results of these measurements were analyzed by multivariate procedures such as: Cluster Analysis (CA), Principal Component Analysis (PCA), Factor Analysis (FA), and Discriminant Analysis (DA). Based on the findings from cluster analysis, principal component analysis, and factor analysis the stations were divided into three groups of highly polluted (HP), moderately polluted (MP), and less polluted (LP) stations Thus, this study illustrates the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and in water quality assessment, identification of pollution sources/factors and understanding spatial variations in water quality for effective river water quality management. This study also shows the effectiveness of these techniques for getting better information about the water quality and design of monitoring network for effective management of water resources. Therefore, based on the results, Gharasou river water quality monitoring program was developed and presented.

An investigation on benthic macro-invertebrates species diversity as bio-indicators of environmental health in Bahrekan Bay

The purpose of this study was to evaluate benthic macro-invertebrates species diversity as bio-indicators of environmental health in Bahrekan bay (in the Northwest of Persian gulf). Seasonal sediments sampling along 5 transects, 15 stations at 4 replicates (3 replicates for macrobenthos and 1 replicate for sediment analysis) was done from November 2008 to August 2009 by 0.025 m2 Van Veen grab sampler. Physical and chemical parameters of water, grain size analysis, %TOM and Ni and Va concentrations of sediments were assessed through four seasons. Macrobenthic communities after staining and sorting, using stereomicroscope have been identified. Their density in every station and every season calculated. For using of AMBI index, identified macrobenthos according to their sensitivity to stressors and pollutants, categorized into 5 ecological groups and for using of Bentix index categorized into 3 ecological groups. The diversity indices and indicators that showing ecological status were calculated. Also, the differences between physiochemical parameters of sea water, sediments TOM% and grain size, diversity indices in stations and seasons were recorded (P=0.05). The correlation coefficient determined for all parameters. According to the results of grain size analysis, bottom grain size categorized as clay. Highest percent of TOM was belong to autumn (36.39±.075) and lowest was belong to summer (19.01±0.51). Also there was positive correlation (p=0.01) between %TOM and %Clay that showing sediments with lowest size containing highest amounts of organic matters. Ni concentrations in sediments (87.80±21.25)mg/kg showed the amounts over than standards levels but Va concentrations in sediments (53.54±17.60)mg/kg showed the amounts lower than standards level. The highest density of macrobenthos was recorded for summer (8254±485) N/m2 and the lowest density was recorded for spring (3775±172)N/m2. The highest annual density was belong to mollusca (81%) and then polycheates (13%), Others (4%) and crustaceae (2%). The highest diversity was recorded for winter (Simpson index: 0.13±0.01, H':3.47±0.06) and the lowest diversity recorded for autumn (Simpson index: 0.16±0.01, H':3.17±0.06). in all stations, the highest amount of Shanon index was belong to T2S3 station in summer (4.11± 0.32) and the lowest amount was belong to T1S1 station in autumn (2.42± 0.41). The annual mean of Simpson diversity index: (0.15 ±0.04) and Shanon diversity index (3.36±0.03), illustrated that macrobenthos in Bahrekan bay have a good variation. The results of Brilluin and N1 (Number of equally common species) indices confirm the results of Simpson index. For study on the regions that diversity has a little difference between stations, with use of Ni index, the degree of differences could be better ono recognizable. According to the results of AMBI index in all seasons (autumn: 0.46±0.03; summer: 0.22±0.01; annual mean:0.31±0.01) and standards (0.0of Bentix index in all seasons (autumn: 5.07±0.07; summer: 5.57±0.02; annual mean: 5.40±0.02) and standards (4.5of AMBI and Bentix indices, highest amount of species diversity was belong to the summer and the lowest amount of species diversity was belong to the autumn. With regarding to high species diversity in Bahrekan Bay, AMBI index present accurate assessment rather to Bentix index. AMBI can be used successfully in ecosystems like to study area for detecting the pollutant and disturbance recourses.