American Journal of Geophysics, Geochemistry and Geosystems
Articles Information
American Journal of Geophysics, Geochemistry and Geosystems, Vol.5, No.3, Sep. 2019, Pub. Date: Nov. 21, 2019
Identification of Vulnerable Areas to Natural Hazards along Rapti River System in U.P. (India) using Satellite Remote Sensing Data and GIS
Pages: 91-103 Views: 162 Downloads: 74
[01] Kuldeep Pareta, Department of Water Resource, DHI (India) Water & Environment Pvt. Ltd., Delhi, India.
[02] Upasana Pareta, Department of Mathematics, PG College, District Sagar (Madhya Pradesh), India.
This paper illustrates the case of Rapti river system in U.P. of India. The main purpose of this study is to identify the vulnerable areas to natural hazards by using multi-criteria model integrated with remote sensing and GIS is to provide more flexible and more accurate decisions to the decision makers. Based on this principle, the study aims to utilize space tools to extract physical data in a comprehensive approach as well as analyse and manipulate these datasets in GIS, thus determining the vulnerable areas to natural hazards. More specifically, the study aims to produce thematic maps for each type of existing natural hazards, among which geographic zones can be classified with respect to different risk levels. For this study, ten different criteria i.e. settlement, cultivated area, soil, geology, slope, erosional area, morphologically active river bankline reaches, embankments, spurs / studs, bridge, and barrages have been considered. The criteria for each of components were determined based on expert opinions and literature review. The result obtained from multi-criteria analysis has been classified in 5 categories i.e. very-highly sensitive, highly sensitive, highly-moderate sensitive, moderate sensitive, and not sensitive. Total 273 vulnerable areas to natural hazards have been identified, out of these vulnerable areas, total 98 vulnerable areas are very-highly sensitive, 69 vulnerable areas are highly sensitive, and 106 vulnerable areas are highly-moderate sensitive. Out of 98 very-highly sensitive vulnerable areas to natural hazards, we have visited 46 vulnerable areas to verify the vulnerability of the areas, and significant observations have been noted.
Vulnerable Areas, Natural Hazards, Remote Sensing, GIS, Rapti River
[01] Zwenzner H, and Voigt S. 2008. Improved estimation of flood parameters by combining space-based SAR data with very high-resolution digital elevation data. Hydrology and Earth System Sciences (HESS) Discussion. Vol. 5, pp. 2951-2973.
[02] Guha-Sapir D, Vos F, Below R, and Ponserre S. 2011. Annual disaster statistical review - 2011, The numbers and trends. Centre for Research on the Epidemiology of Disasters (CRED), Brussels, Belgium. pp. 18-19.
[03] Edwards J, Gustafsson M, and Näslund-Landenmark B. 2007. Handbook for vulnerability mapping. EU Asia Pro Eco Project, Disaster Reduction through Awareness, Preparedness and Prevention Mechanisms in Coastal Settlements in Asia. pp. 3-4.
[04] Yoon DK. 2012. Assessment of social vulnerability to natural disasters: A comparative study. Natural Hazards. Vol. 63, pp. 823-843.
[05] Uitto JL. 1998. The geography of disaster vulnerability in megacities: A theoretical framework. Applied Geography. Vol. 18, pp. 7-16.
[06] Malczewski J. 1999. Spatial multicriteria decision analysis, In: J-C Thill (Ed.). Multicriteria decision making and analysis: a geographic information sciences approach, Brookfield, VT. Ashgate Publishing. pp. 11-48.
[07] Heywood I, Oliver J, and Tomlinson S. 1993. Building an exploratory multi criteria modelling environment for spatial decision support. International Journal of Geographical Information Science. Vol. 7 (4), pp. 13-23.
[08] Daves R. 2018. India - floods affect 2 million in Uttar Pradesh as west Rapti river reaches record high, 2017.
[09] Pareta K. 2003. Morphometric analysis of Dhasan river basin, India. Uttar Bharat Bhoogol Patrika, Gorakhpur. Vol. 39, pp. 15-35.
[10] Pareta K, and Pareta U. 2014. New watershed codification system for Indian river basins. Journal of Hydrology and Environment Research. Vol. 2 (1), pp. 31-40.
[11] SRTM. 2007. NASA, & USGS EROS Data Centre.
[12] Landsat-8 OLI. 2019. U.S. Geological Survey (USGS), Earth Explorer.
[13] Survey of India Toposheets, 2005.
[14] Pareta K, and Pareta U. 2012a. Integrated watershed modeling and characterization using GIS and remote sensing techniques. Indian Journal of Engineering. Vol. 1 (1), pp. 81-91.
[15] Pareta K, and Pareta U. 2012c. Quantitative geomorphological analysis of a watershed of Ravi river basin, H.P. India. International Journal of Remote Sensing and GIS. Vol. 1 (1), pp. 47-62.
[16] Murthy SRN, and Mukhopadhyay PK. 1966-67. Geological Quadrangle Map, 63 M / 15 - 1: 50,000 Scale. Geological Survey of India (GSI), Uttar Pradesh and Bihar.
[17] Pandey BN, and Bisaria BK. 1986-87. Geological Quadrangle Map, 62J / 3, 4, 7, 8, 11, 12 - 1: 50,000 Scale. Geological Survey of India (GSI), Uttar Pradesh.
[18] Prasad LM, Verma SK, and Sinha M. 1988-89. Geological Quadrangle Map, 63 N / 14 - 1: 50,000 Scale. Geological Survey of India (GSI), Uttar Pradesh and Bihar.
[19] Jain V, and Sinha R. 2003. River Systems of the Ganga plains and their comparison with Siwaliks: a review, Current Science. Vol. 84 (8), pp. 1025-1033.
[20] Geological Survey of India (GSI). 1974.
[21] Pareta K, and Pareta U. 2015. Geomorphological interpretation through satellite imagery and DEM data. American Journal of Geophysics, Geochemistry and Geo-systems. Vol. 1 (2), pp. 19-36.
[22] Biswajit N, Sultana N, and Paul A. 2013. Trends analysis of river bank erosion at Chandpur, Bangladesh: A remote sensing and GIS approach. International Journal of Geometrics and Geosciences. Vol. 3 (4), pp. 454-464.
[23] Pareta K, and Pareta U. 2012b. Landslide modelling and susceptibility mapping of Giri river watershed, H. P. (India). International Journal of Science & Technology. Vol. 1 (2), pp. 91-104.
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