Comparative Investigation of Water Quality Parameters of Aerial & Rangat Bay, Andaman Islands Using In-Situ Measurements and Spatial Modelling Techniques

Springer Science and Business Media LLC - Tập 5 - Trang 57-67 - 2013
Dilip Kumar Jha1, Marimuthu Prashanthi Devi2, N. V. Vinithkumar1, Apurba Kumar Das1, P. S. Dheenan1, P. Venkateshwaran1, R. Kirubagaran3
1Andhaman and Nicobar Centre for Ocean Science and Technology, National Institute of Ocean Technology (Ministry of Earth Sciences, Govt. of India), Port Blair, India
2Department of Environmental Management, Bharathidasan University, Tiruchirapalli, India
3National Institute of Ocean Technology (Ministry of Earth Sciences), Pallikaranai Chennai, India

Tóm tắt

Aerial Bay and Rangat Bay witness extensive and diverse activities such as tourism, shipping and fisheries. These activities along with domestic discharge may significantly affect the seawater quality in the bays. Therefore seawater samples were analyzed to comprehend the physicochemical and biological variables and its sources that affected the seawater quality at both the bays. The land-use/land cover data was studied to understand the source of pollution and to classify the areas into various categories relating to prevailing environment adjoining these bays. Difference between sites and the variables responsible for variation were analyzed using one-way analysis of variance (ANOVA). Pearson correlation was used to find the relationship between variables and degree of dependency towards the other. Agglomerative hierarchical cluster analysis grouped the sampled sites, which helped to identify the similarity/dissimilarity within and between sites at both high and low tides. Moreover, inverse distance weighted interpolation technique was used to develop comparative potential mapping using Arc GIS software (ver. 9.3.1), generated a model for spatial changes at both sites. The results indicate the increase of pollution level at Aerial Bay due to anthropogenic activities, whereas Rangat Bay showed less variance due to frequent open sea water exchange. The combination of both statistical and GIS modeling techniques have proven to be excellent methods for spatial analysis and integration of these data to derive useful outputs and visual modeling.

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