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. 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. 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.

中文翻译：

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印度南部蒂鲁瓦卢尔地区农村地区的脆弱地区

洪水不仅仅是从较高地形到较低地形的水流。而是地理系统参数之间的接口动态。即岩性，地质结构，地貌，土壤，排水条件，坡度，土地利用和土地覆盖等，以及洪水。因此，洪水脆弱性映射需要了解和映射所有地形参数。考虑到这一点，已尝试划定泰米尔纳德邦蒂鲁瓦卢尔县农村地区的洪水脆弱地区，面积为1557.07平方英尺。从RK Pet到Thiruvallur的7个街区组成的Km处在研究区域内。专题图，例如排水，地质，地貌，土地利用和土地覆盖，使用Resourcesat-2 LISS IV-2014数据，绘制了特别参照地貌的构造图和基于沿途排水异常的地面沉降区域的检测。附带数据包括从1974年至2014年收集的5个雨量计站收集的40年期间的降雨，并编制了降雨Isohyet地图。使用航天飞机雷达地形任务（SRTM）生成了数字高程模型（DEM），并获得了研究区域的坡度。ArcGIS 10.3是一种功能强大的空间分析工具，可通过加权叠加分析来找出研究区域中的洪水易感区域。根据专题图在研究区域的易受灾性，对专题图的每个参数进行排序和加权。即高度脆弱，中度脆弱，脆弱程度较低，没有脆弱性，其空中范围分别为426.47、181.57、832.25和116.78Sq.Km。然后，通过实时获取受洪水影响村庄的清单来验证基于GIS的输出结果。多标准分析允许整合多个要素以绘制易受洪灾地区的地图。结果表明，约40％的研究区域处于高中洪水脆弱性环境中。本研究中建议的结构性和非结构性措施将帮助决策者和计划者有效地制定该地区农村地区未来洪水发生的策略。然后，通过实时获取受洪水影响村庄的清单来验证基于GIS的输出结果。多标准分析允许整合多个要素以绘制易受洪灾地区的地图。结果表明，约40％的研究区域处于高中洪水脆弱性环境中。本研究中建议的结构性和非结构性措施将帮助决策者和计划者有效地制定该地区农村地区未来洪水发生的策略。然后，通过实时获取受洪水影响村庄的清单来验证基于GIS的输出结果。多标准分析允许整合多个要素以绘制易受洪灾地区的地图。结果表明，约40％的研究区域处于高中洪水脆弱性环境中。本研究中建议的结构性和非结构性措施将帮助决策者和计划者有效地制定该地区农村地区未来洪水发生的策略。