2 resultados para Landscape indicators : assessing and monitoring landscape quality

em Aquatic Commons


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The results reported on were from a monitoring survey No. 9 undertaken between 9th and 12th September 2011 during construction period of the Bujagali Hydropower Project (BHPP). Two pre-construction, baseline surveys in April 2000 and April 2006 were conducted and so far, during construction phase of the project, eight monitoring surveys have been undertaken i.e. in September 2007, April 2008, April 2009, October 2009, April 2010, September 2010, April 2011 and the present one, in September 2011. Since 2009 biannual monitoring surveys have been conducted at an upstream and a downstream transect of the BHPP with emphasis on the following aspects: water quality determinants biology and ecology of fishes and food webs fish stock and fish catch including economic aspects of catch and sanitation/vector studies (bilharzias and river blindness)in addition to the above mentioned studies, a soil pH survey was undertaken on 15th October 2011 in the area behind the reservoir whose filling started a week earlier. The findings of pH status in the catchment of the dam are also contained in this report.

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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.