International Journal of Environmental Sciences

Volume 3 Issue 1 2012- July 2012        Pages: 62- 74               <<Previous    Next>>

Integrated remote sensing and GIS approach for water quality analysis of Gomti river, Uttar Pradesh

Author Information:

Somvanshi.S1, Kunwar.P2, Singh.N.B3, Shukla.S.P3, Pathak.V3
1- Amity Institute of Environmental Sciences, Amity University, Sector-125, Noida, India.
2- Forest Resources and Ecology Division, Remote Sensing Applications Centre, U.P., Sector-G, Jankipurm, Kursi Road, Lucknow, Uttar Pradesh, India
3-  Department of Civil Engineering, Institute of Engineering and Technology, Gautam Budha Technical University,  Lucknow, Uttar Pradesh, India.

ABSTRACT

This paper deals with development of decision making tool for mapping of water quality parameters of Gomti River in parts of Lucknow, Sitapur and Barabanki districts of Uttar Pradesh, India. Mapping was done using IRS LISS III data combined with measurement of selected sample points. Water quality data was collected for both pre-monsoon and post-monsoon seasons. Radiance value of each band of IRS LISS III data has been calculated and observed radiance value on those sample points of each band along with band ratios and principal components were compared with in situ measurements of water quality parameters. The water quality parameters included, TS, DS, SS, pH, COD, BOD, DO, Chloride and TH. Using radiance data of pre-monsoon images and in situ measurement data of water quality parameters correlation and multiple linear regression models were developed and selected most appropriate band combinations which were having highest R2 value. With the help of these multiple linear regression water quality parameters were predicted which were then compared with the values obtained through laboratory analysis of water quality. These appropriate band combinations and principal components of pre-monsoon satellite data were used in estimation of water quality parameters. The all these water quality parameters were significantly correlated with LISS III radiance data except SS. The same band combinations of post-monsoon satellite data were also used for estimation of water quality parameters in post-monsoon. Subsequently, multiple linear regression equations models were used in estimation of water quality parameters and preparation of digital cartographic maps depicting the water quality over the entire study area for both the seasons respectively..

Keywords: Gomti River, Water Quality Parameters, Remote Sensing, Satellite Data, GPS, LISS III, PC, Regression Models, Water Quality Maps.

DOI: 10.6088/ijes.2012030131008

© 2012 Copyright by the authors, licensee Integrated Publishing Association.This is an open access article distributed under the Creative Commons Attribution License (3.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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