National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
ASSESSMENT OF IMPACT OF THE FLOOD CAUSATIVE FACTORS FOR FLOOD VULNERABILITY IN LOWER TAPI RIVER BASIN USING GIS AND REMOTE SENSING Mandviwala M. D1, Joshi G. S.2, Indra Prakash3 Former P.G. Student, Faculty of Technology & Engg, The M. S. University of Baroda, Vadodara Email:
[email protected] 2 Associate Professor, Faculty of Technology & Engg., The M. S. University of Baroda. Vadodara Email:
[email protected] 3 Faculty, Bhaskaracharya Institute for Space Application and Geo-Informatics, Department of Science and Technology, Government of Gujarat, Gandhinagar Email:
[email protected]
1
ABSTRACT The city of Surat situated in the lower Tapi river basin is affected by floods in the recent past. Lower part of the Tapi basin is prone to flood hazard due to its location between sea coast and Ukai dam. Also, sudden flood water releases from Ukai dam and Kakarapar weir results in the inundation of this part of the basin including low lying areas of Surat City. The methodology adopted in this study is to map the real flood affected areas in GIS environment (signals, alert, ready for evacuation, and immediate evacuation), considering various discharges at Kakarapar weir and gauge levels as per flood memorandum 2014-15 of the Government of Gujarat. The various flood causing factor maps have been developed for the Lower Tapi river basin using GIS and Remote Sensing. On comparison of real flood affected areas with the flood causing factors, it is found that the small size of the micro watershed followed by the land use, rainfall distribution, slope and type of soil results in the very high flood vulnerability in the downstream reaches of the lower Tapi river basin including Surat city. Keywords: Geographic Information, system, Remote sensing, Flood causative factors flood visualization map
1. INTRODUCTION The city of Surat situated in the lower Tapi river basin is affected by floods in the recent past. Lower part of the Tapi basin is prone to flood hazard due to its location between sea coast and Ukai dam. Also, sudden flood water releases from Ukai dam and Kakarapar weir results in the inundation of this part of the basin including low lying areas of Surat city. The methodology adopted in this study is to map the real flood affected areas in GIS environment (signals, alert, ready for evacuation, and immediate evacuation), considering various discharges at Kakarapar weir and gauge levels as per flood memorandum 2014-15 of the Government of Gujarat. The various flood causing factor maps have been developed for the Lower Tapi river basin using GIS and Remote Sensing. The objective of this study is to assess the impact of various flood causing factors in causing the flood in Lower Tapi River basin. The map of the Lower Tapi basin is shown in Figure 1. 2. REVIEW OF LITERATURE The Badilla and Elena (2002) assigned different degree of hazard to each Geomorphological unit, depending on slope, drainage pattern, grain size and permeability. In this way it is demonstrated that Turialba city is located in an area with high to medium flood hazard. Singh K. and Sharma A. K. (2009) developed floods typically occur during the monsoon season due to heavy tropical storm downpours and unregulated urban development. The floods during August 2006 in Tapi catchment caused great damage to people and property, WRF-20-1
National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
resulting in 300 people being killed and US$ 4.5 billion worth of property damage. The geospatial technologies such as remote sensing, GIS, and GPS have been utilised to prepare urban flood hazard maps and to handle entity-specific query and analysis. The research methodology employed is based on statistical probabilities of flood frequency, maximum discharge carrying capacity at river cross-section, mapping of inhabited areas based on highresolution images, and terrain mapping using global position system. Ishaya, I. B. Abaje et.al (2009) recognized that the integrated approach of Remote Sensing and GIS techniques in flood management with the goal of mapping areas vulnerable to flood hazard in Gwagwalada urban area.
Figure 1: Map of the Gujarat, including the study reach in the Lower Tapi river basin
Surji Singh saini and Kaushik S..(2012) developed risk and vulnerability assessment in middle parts of ghaggar river basin. Also included the hydrological analysis with a geographic information system (GIS) based on flood risk mapping. The study is to assess the risk and vulnerability based on multi-criteria assessment. Sinha et al. (2008) have conducted a study on flood risk assessment in the part of Kosi river basin, they have integrated hydrological with geomorphological, land cover, topographic and social (population density) parameters using GIS to propose a Flood Risk Index (FRI). Ajin. R.S. et al.(2014) developed Weighted Overlay Analysis method is adopted to prepare the Flood hazard risk zone map. The hazard map thus prepared will show the total areas subjected to the hazards, as very low, low, moderate, high and very high risk zones. Chandran R. and Joisy (2009) developed flood hazard map of Vamanapuram River basin, a number of contributing factors including annual rainfall, size of watershed, slope of watershed, gradient of river and stream, drainage density, type of soil, land use, communication line and infrastructures were considered for rating the degree of hazard by means of weighting. Sani Yahaya et al.(2010) developed flood risk area according to two main MCE approaches employed in GIS and MCE. In MCE, two methods, pairwise comparison method (Analytical Hierarchy Process-AHP) and Ranking method are used to calculate the flood prone area by weights of each factor. Lenka Ganvoka et al.,(2014) have conducted to assess flood hazard eastern slovakia area to describe and test approaches which combine MCA and GIS. WRF-20-2
National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
3. MODEL DEVELOPMENT The methodology includes following steps. 1) To develop the flood visualization map for lower Tapi river basin indicating the area under submergence for the various gauge levels and discharges at Kankarapar weir. 2) To develop the map for each of the flood causative factor namely, Rainfall distribution, Drainage density, slope, Type of soil, Landuse, and Size of micro-watershed and to assign the rating level to the classes of flood causing factor. 3) Comparison of each of the flood causative factor to the flood visualization map 4) Analyzing the impact of each of the flood causing factor to cause the flood in Lower Tapi river basin and in the area around Surat city, which is most affected by floods. 3.1 Development of the Flood Visualization Map On the basis of flood memorandum (Government of Gujarat 2014-2015), various villages affected from flooding under various discharge condition scenario at Kankarapar weir have been constructed in G.I.S environment as below in Figure 2 to Figure 7. It is considered that White signals are indicating for “Alert”, Blue signals are indicating for “Ready for Evacuation” and Red signals are indicating for “Immediate evacuation”.
Figure 2: Map of likely submerged villages in Lower Tapi area when discharge at Kakrapar weir is 3, 91,000 cusecs at Gauge level 53.15 m
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National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
Figure 3 Map of likely submerged villages in Lower Tapi area when discharge at Kakrapar weir is 4, 40,400 cusecs at Gauge level 53.40 m
Figure 4: Map of likely submerged villages in Lower Tapi area when discharge at Kakrapar weir is 4, 60,640 cusecs at Gauge level 53.66 m
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National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
Figure 5: Map of likely submerged villages in Lower Tapi area when discharge at Kakrapar weir is 5, 20,000 cusecs at Gauge level 54.04 m
Figure 6: Map of likely submerged villages in Lower Tapi area when discharge at Kakrapar Weir is 9, 50,000 cusecs at Gauge level 56.40 m
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National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
Figure 7: Map of likely submerged villages in Lower Tapi area when discharge at Kakrapar weir is 1200,000 cusecs at Gauge level 57.51 m
3.2 Development of maps for Flood causative factor The flood causative factors considered in this are : 1) rainfall distribution, 2) Type of soil, 3) Land use, 4) slope, 5) Drainage density, and 6) the Size of micro-wtershed (Joerin et.al.). The classes within each factor causing the flood have been shown in the section below. The satellite data of study area was collected from IRS-P6 (with sensors LISS-III) for the 3-D visualization through Bhaskarachya Institute of Space and Geo-informatics (BISAG), Gandhinagar.
3.2.1 Rainfall Distribution There are 3 rain gauge stations in the catchment area namely, Kakrapar, Ukai and Mandvi. The annual rainfall data from State Water Data Centre (SWDC), Gandhinagar from year 1990 to 2013 have been made available. The rainfall distribution is classified in to three classes as shown in Table 1. The rainfall distribution map in GIS environment have been developed as shown in Figure 8.The rating level is assigned from 1 to 3, for grading the high flood. . Table 1: Classification of Rainfall Distribution map
Parameter
No. of class
Sub class of criteria (mm) High - 1273.907
Rating level 1
Rainfall
3
Moderate - 1257.708
2
Low - 1160.971
3
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National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
Figure 8: Rainfall Distribution map
3.2.2 Drainage Density The micro-watershed map have been prepared at Bhaskaryacharya Institute of Space and Geoinformatics (BISAG), Gandhinagar. High drainage density values are favorable for runoff, and hence indicate low flood chance. In basin with smaller drainage density values are less favorable for runoff, and hence indicate high flood chance (Ajin.R.S. et al,2013). The length of the river/ tributaries have been measured by “Measure Tool” of the Arc GIS 9.3 software and subsequently, the drainage density of each micro watershed is calculated. The l Drainage Density is classified in to five classes as shown in Table 2. The Drainage Density map is as shown in Figure 9. The rating level is assigned from 1 to 5 for grading the high flood..
Figure 9: Drainage Density Map WRF-20-7
National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
Table 2: Classification of Drainage Density
Parameter
No. of class
Drainage Density l 5
Sub class of criteria 5.0
5
3.2.3 Slope The slope is classified in to 7 classes from 0 to 50%. Slope map has been prepared from DEM and analysis has been done to find out various categories of slopes and their percentage. In the present study area, it has been observed that about 99 % of land is having less than 0-1 percent slope, and remaining land of the beginning of Ukai dam contains higher slope ranges to 15-35 percent due to higher topography of Ukai dam. Classification of Slope map shown in Table 3. and slope map shown in Figure 10. The rating level is assigned from 1 to 7, grading the high flood. Table 3: Classification of Slope map
Parameter
No. of classes
Slope
7
Sub class of criteria 0 - 1% 1 - 3% 3 - 5% 5 - 10% 10 - 15% 15 - 35% 35 - 50%
Figure 10: Slope Map WRF-20-8
Rating level 1 2 3 4 5 6 7
National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
3.2.4 Landuse In the study area, Agriculture land, Built up (Urban & rural), water bodies (Reservoirs, River, canal, lake etc.), waste land (Land with Scrub, Land without Scrub) Prosophis, quarry have been identified and delineated in the land use/ land cover map. . Classification of Landuse in 8 classes is shown in Table 4 (K Subramanya, 2008), and the rating level is assigned from 1 to 7, grading the high flood. Landuse map is shown in Figure 11. Table 4: Classification of Landuse Map Parameter
Landuse
No. of classes
8
Sub class of criteria Water bodies Wetlands Built-up Wastelands Agriculture Grass Land Forest Other
Rating level 1 2 3 4 5 6 7 8
Figure 11: Land use Map 3.2.5 Type of soil The soil types in an area is important as it control the amount of water that can infiltrate into the soil, and hence the amount that turns into runoff. The soil (other than water) in Tapi river basin is mainly classified in to three classes: Clayey, Fine and Very fine sand. Type of clayey soil have more runoff as compare to fine sand and very fine sand, and thus the rating level is assigned accordingly. The classification of Type of Soil shown in Table 5 and the Soil map shown in Figure is shown in Figure 12.
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National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
Table 5: Classification of Type of Soil
Parameter
No. of classes
Type of soil
3
Sub class of criteria Clayey Fine Sand Very fine Sand
Rating level 1 2 3
Figure 12: Soil Map 3.2.6 Size of micro watershed Micro watersheds with larger drainage areas require runoff of longer duration for a significant increase in water level to become a flood. Therefore, the micro watersheds with smaller area (size) are greatly affected by floods. (Ajin. R.S. et al.,2013). The micro-watershed are digitized and the size of each watershed is computed, The maps are developed by classifying Micro watershed on the basis of size. The micro-watershed size categorized into 5 classes as shown in Table 6. Lower the size of the micro-watershed, larger is the possibility of the flow, gathered in the watershed. The rating level from 1 to 7 is assigned to the size of micro-watershed accordingly. The map of size of micro watershed is shown in Figure 12. Table 6: Classification of Size of Micro watershed Parameter
No. of classes
Size of microwatershed
5
Sub class of criteria 3-10 sq.km 10-15 sq.km 15-20 sq.km 20-25 sq.km 25-35 sq.km
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Rating level 1 2 3 4 5
National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
Figure 13: Size of Micro-Watershed
3.3 Comparison of map of each Flood Causative factor to the Flood Visualization map Figure 2 to 7 shows the area under submergence for the given gauge level and discharge (cusec) at Kankarapar weir. It is seen from Figure 2 that only area under submergence is falling in the most downstream end of the Lower Tapi basin. It is showing “Alert” signal to the area near the Surat city i.e. downstream of the Lower Tapi basin. From Figure 2 to Figure 7, it is seen that as the gauge level and discharge at Kankarapar weir increases, the extent of the area under submergence increases towards upstream of the basin. This is the indication of the fact that the all or any of the parameters such as Topography/Slope, Type of soil, Land use, Drainage density or Size of the micro-watershed of the downstream area of Lower Tapi river basin may be the prevalent causes of flooding in the area on the downstream of the Lower Tapi basin near Surat city. 4. RESULTS AND DISCUSSIONS Referring the map (Figure 2 to 7) and Table 1 to 6 for each of flood causative factor, it is evident that the parameters such as Size of micro-watershed shows rating level 1, out of total 5 classes; Rainfall distribution shows rating level 1, out of total 3 classes; Slope shows rating level 1, out of total 7 classes; Landuse shows rating level 3 out of total 8 classes; and Type of soil shows rating level 2 out of total 4 classes; while Drainage density is showing lowest rating for causing the flood in the area on the downstream reaches of Lower Tapi river basin near Surat city, which most flood affected. In brief, it is summarized that the size of micro-watershed, rainfall distribution, and slope are the prevalent factors followed by Land use, and Type of soil in Lower Tapi river basin. Further, it is evident that out of the total 3 prevalent flood causing factors, Rainfall distribution and Slope do not show the wide variation within the basin from most flood affected area located on downstream of the Lower Tapi river basin to other areas.
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National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
Thus, it is concluded that the small size of the micro watershed followed by the land use, rainfall distribution, slope and type of soil results in the very high flood vulnerability in the downstream reaches of the lower Tapi river basin including Surat city This results will provide the base for framing the rank or preferences in Ranking Sum method of Multi-criteria Evaluation for constructing the Flood Vulnerability map of Lower Tapi River basin. 5. CONCLUSIONS The following conclusions are derived from the present study: (i) (ii) (iii) (iv) (v)
(vi)
The area on the downstream reaches including Surat city is the most flood affected area in Lower Tapi river basin. The flood visualization maps for Lower Tapi basin have been developed for various scenario of gauge level and discharge at Kankarapar weir. The maps are developed in GIS environment using remotely sensed data for flood causing factors in a Lower Tapi river basin The classes are defined for each flood causing factor by assigning the rating level. it is concluded that the small size of the micro watershed followed by the land use, rainfall distribution, slope and type of soil results in the very high flood vulnerability in the downstream reaches of the lower Tapi river basin including Surat city The result of impact assessment of each factor in causing the flood in the Lower Tapi basin will provide the base for framing the rank or preferences in Ranking Sum method of Multi-criteria Evaluation for constructing the Flood vulnerability map of Lower Tapi river basin.
ACKNOWLEDGEMENT The authors are thankful to the BISAG authorities and State Water Data Centre, Gandhinagar for providing relevant data.
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National Conference on Water Resources & Flood Management with special reference to Flood Modelling October 14-15, 2016 SVNIT Surat
Sinha, R., G.V. Bapalu, G.V., Singh, L.K., and Rath, B., (2008), “Flood risk analysis in the Kosi River Basin, North Bihar using multi-parametric approach of AHP”, Indian Journal of remote sensing, 36, 293-307. Surjit Singh Saini, Kaushik. S.P (2012) “Risk and vulnerability assessment of flood hazard in part of Ghaggar Basin: A case study of Guhla block, Kaithal, Haryana, India” Imternational Journal of Geometics and Geosciences” 3(1), BOOKS: K subramanya ,2008 Engineering hydrology, The McGraw-Hill, New Delhi, Indian Flood Memorandum 2014-2015, Flood warning arrangements; Narmada, Water Resources, Water supply and kalpsar department.
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