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Assessment of the Flood Potential on a Lower Tapi Basin Tributary using SCS-CN Method integrated with Remote Sensing andamp; GIS data | OMICS International | Abstract
ISSN: 2167-0587

Journal of Geography & Natural Disasters
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Research Article

Assessment of the Flood Potential on a Lower Tapi Basin Tributary using SCS-CN Method integrated with Remote Sensing & GIS data

Sudhakar B Sharma1* and Anupam K Singh2

1Department of Civil Engineering, Nirma University Ahmedabad-382481, India

2Institute of Engineering & Technology, J.K Lakshmipat University, Jaipur-302026, India

*Corresponding Author:
Sudhakar B Sharma
Department of Civil Engineering
Nirma University, Ahmedabad-382481, India
Tel: 91-9376068099
E-mail:[email protected]

Received Date: June 06, 2014;Accepted August 08, 2014; Published Date: August 16, 2014

Citation:Sharma SB, Singh AK (2014) Assessment of the Flood Potential on a Lower Tapi Basin Tributary using SCS-CN Method integrated with Remote Sensing & GIS data. J Geogr Nat Disast 4:128. doi: 10.4172/2167-0587.1000128

Copyright: 2014 Sharma SB, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


The purpose of this research paper is to identify watersheds with high flood potential based on watershed characteristics for formation of surface runoff. The SCS-CN method relies on remote sensing and GIS data for obtaining watershed characteristics. A 30 m raster grid size digital elevation model (DEM) has been generated from field survey using Global Positioning System (GPS) of 3 m accuracy integrating with Survey of India topographical maps of 1: 50,000 scale having 10 m contour interval. The undisturbed soil samples from field have been collected and laboratory analysis was carried out using modified proctor compaction test as per ASTM D1557 and sieve analysis as per ASTM C136. This has helped in establishing hydrological soil map while land use map has been prepared using Landsat 7ETM+ image band 2, 3, 4 [30 m] merged with PAN band 8 [15 m] for classification. The supervised classification approach using maximum likelihood classifier has been employed for preparation of land use map for Varekhadi catchment having 442 km2 of geographical coverage. The major land use categories classified on 10 Nov 2001 Landsat 7ETM+ image have been agriculture (32%), forest (29%), wasteland (20%), fallow land (14%), built-up (4%) and water bodies (2%). The hydrological soil groups generated in GIS environment have identified two soil groups viz. group B and group C that exist under study area. The Varekhadi catchment has been delineated into five watersheds viz. Amli, Zankhwaw, Visdaliya, Godsambha and Wareli delineated using DEM and stream network. The SCS-CN model was applied for estimating of daily run-off for each sub-watershed. The results obtained on the flood potential analysis shows that Wareli watershed has highest flood potential while the Amli watershed lowest. It should be noted that highest value of flood potential belongs to lowest part of watershed, where high population density can be found. This analysis reflects an increased vulnerability and risks to floods and inundations for Wareli watershed. Stream gauge data has been used for result validation with a common event of 2010 and it shows good fit with the model. The flood potential analysis within the lower Tapi basin tributary suggests that the SCS-CN method with hydrological parameters derived using remote sensing and GIS data can be applied to predict run-off in poorly gauged watersheds


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