Flood hazard measures through vulnerability indexing in GIS at Cochin city, Kerala.

1. Presentation
on
Flood hazard measures through vulnerability
indexing in GIS
Presented by
AMIT KUMAR SAHA(2017GI12)
M.Tech
GIS Cell, MNNIT Allahabad
Under the supervision of
Dr. Sonam Agrawal
Assistant Prof., GIS Cell
MNNIT Allahabad

2. OBJECTIVE
• To have a primary look over the basic factors as the cause of flood
• Having the effective working methods to analyse and determine
places with different vulnerability to flooding

3. Usual causes of flooding
• Climate conditions changing
• Regional environment destruction
• Deforestation
• Illegal constructions
• Clogging of storm water
• Poor drainage systems

4. How GIS can be helpful?
In such case GIS ..
• Can form a map on areas where flooding occurs
• Using geographical aspects can rebuild a sewage drains to ensure
smooth water flow
• Can allow the creation of flood simulation models
• Can allow mapping of evacuation routes by use of imageries
• Can allow the vulnerability indexing of flood hazards

5. Important data to be considered
• DEM
• Land use
• Soil type
• Rainfall data
• Map of drainage system

6. A methodology for Trivandrum City, India
Source: Reference #1

7. Important factors in hazard mapping
Part-A
• Runoff factor
• Soil map
• Surface slope
• Surface roughness
• Flow accumulation
• Distance to main channel
• Land cover
Part-B
• Alignment of drains

8. Part A: Priority based decision making example
Factor
criteria
Runoff Soil Type Slope Roughness Drainage
density
Distance
to main
channel
Land Use Priority
Runoff 1 2 3 4 5 6 7 0.355
Soil Type 0.5 1 2 3 4 5 6 0.240
Slope 0.33 0.5 1 2 3 4 5 0.159
Roughness 0.25 0.33 0.5 1 2 3 4 0.104
Drainage
density
0.20 0.25 0.33 0.5 1 2 3 0.068
Distance
to main
channel
0.17 0.20 0.25 0.33 0.5 1 2 0.045
Land Use 0.14 0.17 0.20 0.25 0.33 0.5 1 0.030
Table: Analytical Hierarchical process

9. Priority based decision making example
Factor Weight
Runoff 7
Soil type 6
Slope 5
Roughness 4
Drainage density 3
Distance to main channel 2
Land use 1
Table: Drainage factors and their corresponding weights

10. Flood hazard indexing calculation and mapping
• Flood Hazard Index, FHI=Runoff x .355+Soil type x 0.240+Slope x
0.159+Roughness x 0.104+Flow accumulation x 0.068 + Distance to
main channel x 0.045+Landuse x 0.030 (Reference#1 )
Flood hazard zoning map
(source:https://pdfs.semanticscholar.org/64d7/4c7abaf79
8864f7e117b97049ff431439f9c.pdf)

11. Part B: Alignment of Drains

12. A type of methodology for Cochin City
Flow chart of methodology
(Source: Reference #2)

13. Data sources for case study
• Basic thematic layers from Survey of India toposheets at 1:50,000
scale, corporation map, satellite images and field study
• Elevation data from SRTM DEM(from GLCF website)
• Remotely sensed image acquired by LISS-III sensor of IRS-P6
satellite
• Drainage block sites mapped using GPS receiver with help of
reference drainage map of the city
• ArcGIS generated .dbf file for demographic data
• Density of drainage block site to be derived from ArcGIS

14. Multi-criteria evaluation (MCE) approach
• For vulnerability indexing, thematic raster layers can be
reclassified to a score inn scale 0-10
• The relative weight are fixed for themes and added to layers
• Higher weight indicates higher influence and vulnerability

15. Cumulative vulnerability
Represented in a sum of product fashion as,
Cumulative vulnerability = (F1*W1)+(F2*W2)+……+
(Fn*Wn)
where, F =each contributory factor reclassed with vulnerability
score, W = relative weight applied to each influencing factor

16. Some other data to be considered
• Rainfall intensity data (of at least 10 years)
• Specific data required for run-off calculation
• Some other geology related data(according to its influence)

17. Analysis of Chennai flood 2015
The study area map
Source: Reference #3

18. Methodology of case study
Detailed methodology flow chart
Source: Refence #3

19. Data source of case study
• Rainfall data provided by NASA
• The integrated Multi-satellite retrievals for GPM (IMERG) to fetch
rainfall precipitation data
• Indian Remote Sensing (Cartosate-1 SRTM) satellite image of
April 2005 and Survey of India toposheets are used to prepare
contour and Drainage Map
• GPS, was used for field survey
• Geological map from GSI
• Soil map from Soil Survey of India
• Area rainfall collected in PWD chennai

20. Considered analysis aspects of flood
• Geographical and meteorological reasons
• Annual rainfall
• Drainage system
• Types of soils
• Geology of the study area
• Slope and size of watershed
• Spatial analysis

21. Generated hazard map
Source: Reference #3

22. Conclusion
• More researches to be studied for more developed insight about
indexing factor consideration
• Reliable data sources according to flood prone areas are necessary
• More improved factor analysis needed for appropriate weightage
assigning

23. References
• GIS-Based Urban Flood Management: A Case Study of
Trivandrum City, India(authors: Catherin R Sebastian, Sheeja
Ramakrishnan Vimala, Mesapam Shashi)
• Urban flood vulnerability zoning of Cochin City,
southwest coast of India, using remote sensing and GIS
(authors: K. Sowmya, C. M. John, N. K. Shrivasthava)
• Study and Analysis of Chennai Flood 2015
Using GIS and Multicriteria Technique(authors:Muthusamy
Seenirajan, Muthusamy Natarajan, Ramasamy Thangaraj,
Murugesan Bagyaraj)

24. THANK
YOU