Flood vulnerable zones in the rural blocks of Thiruvallur district, South India

• Main Authors: Punitha Periyasamy, Mohamed Mohamed Yagoub, Mahalingam Sudalaimuthu
• Format: Article
• Language: English
• Published: SpringerOpen 2018-11-01
• Series: Geoenvironmental Disasters
• Subjects: DEM; IRS p6; Flood; Lineament; Vulnerable zones
• Online Access: http://link.springer.com/article/10.1186/s40677-018-0113-5

Abstract Background Flooding is not simply the flow of water from higher topography to lower topography. Rather, it is the interface dynamics between geo-terrain system parameters; viz., lithology, geological structures, geomorphology, soil, drainage conditions, slope, land use and land cover etc., and flood. Hence the flood vulnerability mapping requires the understanding and mapping of all terrain parameters. With this in mind, an attempt has been made to delineate flood vulnerable zones in the rural blocks of Thiruvallur District, Tamil Nadu, covering an area of 1557.07 Sq. Km that consists of 7 blocks from RK Pet to Thiruvallur fall in the study area. Results The thematic maps such as drainage, geology, geomorphology, landuse, and landcover, tectonic map with special reference to lineaments and detection of zones of land subsidence on the basis of drainage anomalies along them were prepared using Resourcesat-2 LISS IV - 2014 data. The collateral data includes rainfall for a period of 40 years collected from 1974 to 2014 from 5 rain-gauge stations collected and the Rainfall Isohyet Map was prepared. The digital elevation model (DEM) was generated using Shuttle Radar Topographic Mission (SRTM) and the slope of the study area was obtained. ArcGIS 10.3 acts as a powerful spatial analysis tool to find out the flood vulnerable zones in the study area by means of weighted overlay analysis. Each individual parameter of the thematic maps are ranked and weighted in accordance with their vulnerability to flood in the study area are classified; viz., highly vulnerable, moderately vulnerable, less vulnerable and no vulnerable with their aerial extent of 426.47, 181.57, 832.25 and 116.78 Sq.Km respectively. The GIS-based output result is then validated by obtaining the list of flood-affected villages in real time. Conclusion The multi-criteria analysis allowed the integration of several elements for mapping the flood vulnerable zones. Results revealed that about 40% of the study area is exposed to high and medium flood vulnerability. The structural and non-structural measures recommended in this research will help the decision makers and planners to effectively develop strategies for future flood occurrences within the rural blocks of the district.