Introduction to catastrophic disaster flood. Its impact on environment and human lives. GIS and Remote Sensing based solutions that can provide key approaches to mitigate flood related hazard as well as vulnerablities.

1. Seminar Presentation
on
Application of GIS and Remote Sensing in Flood Risk Management
by
Amit Kumar Saha
2017GI12
M.Tech IIIrd Sem
GIS Cell
Under the supervision of
Dr. Sonam Agrawal
Assistant Professor
GIS Cell
GIS Cell
Motilal Nehru National Institute of Technology Allahabad

2. • Introduction
• Literature review
• Conclusion
• References
Contents

3. • Flood is an overflow of water.
• Flood is a form of natural disaster.
• Flood usually occurs when there is too much rain.
• There is an overflow of water bodies by high precipitation and snow melt.
• There are different types of floods as flash flood,catastrophic flood,river
flood , coastal flood, urban flood, muddy flood.
• Flood is one of the most the most re-occurring natural hazard in the
different states of India and Bangladesh.
• Usually both natural and manmade factors are associated with floods.
Introduction

4. • Major causes of floods (categorized)…
Introduction
Physical
• Intense precipitation
• Prolonged rainfall
• Snow melt or ice thaw
• Storm surges
• Landslides
• Volcanic eruptions
Human
• Changes in land use
• Urbanization
• Climate change
• Poor dam construction
• Poverty

5. • Benefits of floods…..
• Floods recharges ground water.
• Fresh water flood help in maintaining flood plain ecosystem.
• Floods make boost in food production for birds.
• Facilitation of weather fish to grow new habitat.
• Soils become more fertile with nutrients.
Introduction

6. • Consequences of floods….
Introduction
Primary Effects
• Physical Damage
[Structural Damage]
• Casualties[Deaths]
Secondary Effects
• Contaminated Water
Supplies
• Diseases
• Cease of food supply
• Cease of communication
and other amenities

7. • What have been done?
• Coastal defenses have been made as sea walls, beach nourishment.
• Barriers were built several times.
• Flood gates were constructed.
Introduction

8. • Scope of the study…
• Floods in every monsoon makes people study about its risks and
management.
• Unplanned urban development makes scope for vulnerability
assessment.
• Improper drainage management causes flood situation.
• Health and housing concerns are incorporated with flood.
• Economic damages are major issue for flood related studies.
• Disruption of transportation also makes a reason for flood risk
management study.
Introduction

9. • Under catastrophic conditions, the gauge stations located along the river to
record the water level may be swept away or damaged(Bhatt and Rao
2014)
• Satellite remote sensing technology has emerged as one of the most
important means of capturing disastrous flood events, providing
information in real time and space (Sharma et al. 1996; Jain et al. 2005)
• Satellite images provide near real-time, comprehensive, synoptic and multi-
temporal coverage of inaccessible areas at frequent intervals, which is
required for quick response and planning of emergency operations((Bhatt
and Rao 2014))
• there is a strong need to explore remote sensing and GIS simulation
techniques which are useful to represent complex systems in a sensible
way(Ahmad and Simonovic 2000)
Literature Review

10. • Risk may be defined as a real or existing threat to a system (life, health,
property, infrastructure, economy and environment) given its existing
exposure and vulnerability (Tsakiris et al. 2009)
• Increased urbanization with intensified vertical growth of cities has led to
the liquid waste disposal along the storm water drains making the run-off
models unpredictable(Prasad and Narayanan, 2016)
• Chennai flood was basically claimed to occur due to improper drainage
system and underlying strata which was found to be landfill over the ponds
and lakes(Seenirajan et al., 2017)
• Rapid flood information retrieval and 3D flood mapping is vital for
effective flood Hazard and risk management (Schumann et al. 2008)
• It is always better to understand the weather condition in advance and the
data collected should be of great accuracy so that there won’t be any havoc
created afterwards(Seenirajan et al., 2017)
Literature Review

11. • A study conducted over lower Tapi basin and Surat district used DEM,
toposheets of 1:50000 from SOI along with Google earth imges.
• This study used georeferenced contour maps over earth imge and applied
spatial adjustment for better accuracy. 3D analyst is then used to convert
digitized contours into TIN model of the study area. The above
methodology is applied to prepare a flood Hazards map for Surat city.
shape files of the whole city with zonal boundaries and contour maps are
digitized and then used to find out submerged areas integrated with town
planning scheme.
• DEM of the Surat city was generated by collecting and estimating the
contour map of 0.5 m interval.
• Result of TIN-DEM shows that areas of Surat city having reduced level
above 12.50 m are safe and can survive under the same flood conditions as
happened in 2006.
Literature Review

12. Literature Review
Source= Patel et al. 2013

13. • Another GIS study about Ganga floods 2010 in UP used Resourcesat-2,
AWiFS (Advanced Wide Field Sensor) satellite images. SRTM (Shuttle
Radar Topographic Mission) digital elevation model (DEM) had been used
for analysing the river valley profile and the lateral spreading of inundation.
• Daily water level data obtained from CWC from 5 September 2010 to 5
October 2010 is used to generate flood hydrograph for the five gauge
stations (Kannauj, Ankinghat, Kanpur, Dalamau and Phaphamau)
• These data can be used for developing of library of flood inundation layers
by geotagging water level to inundation layer, multi-temporal satellite data
from Radarsat-2 (Scan SAR wide beam).
• Flood hydrograph for the Ganga River at Kannauj, Ankinghat and Kanpur
gauge stations from 5 September 2010 to 5 October 2010 had been
obtained as a result as a measure of WL and DL.
• At Dalamau River crossed the DL towards the end of September and was
flowing above the DL for four days (29 September 2010 to 2 October
2010).
Literature Review

14. Literature Review
Source= Sharma et al. 2017

15. • Remotely sensed images and geographical information system (GIS) can be
very effective in identifying the spatial component of flood for
management through MCDM(Lowry et al. 1995)
• Thus hazard identification, vulnerability assessment, monitor and forecast
has become easy through GIS (Roy et al. 2001)
• Multi-criteria evaluation (MCE) methods have been applied in several
studies since usually 80 % of the data used by decision makers are
geographical (Malczewski 1999)
• GIS allows the decision maker to identify a list meeting a predefined set of
criteria with the overlay process (Heywood et al. 1993)
• the multi-criteria decision analysis within GIS may be used to develop and
evaluate alternative plans that may facilitate compromise among interested
parties (Malczewski 1996)
Literature Review

16. • For a general case of vulnerability assessment, several geographical and
anthropogenic related parameters can be used as thematic layers.
• These criteria may include elevation, population density, population density
of children, female, drainage block density, distance from drainage block
sites, distance from water bodies and etc.(Shrivasthava et al. 2014)
• Such analysis identified more than 8.5% of cochin as highly vulnerable
areas.(Shrivasthava et al. 2014)
• In such scenario of multi-criteria approach result can be Represented in a
sum of product fashion as,(Seenirajan et al. 2017)
Cumulative vulnerability = (F1*W1)+(F2*W2)+……+ (Fn*Wn)
where, F =each contributory factor reclassified with vulnerability
score, W = relative weight applied to each influencing factor.
Literature Review

17. • On the basis of alternatives many spatial decision problems has given rise
to the GIS-based multi-criteria decision analysis (GIS-MCDA). (Church et
al. 1992, Banai 1993)
• Even some vulnerability assessment may include flood hazard
classification as FHI.(Roy et al.)
Literature Review
Source= Roy et al. 2017

18. • social vulnerability index parameters may include household density, sc/st
population, illiteracy population.
Literature Review
Source= Roy et al. 2017

19. • For the case of last recorded hazards, the flood risk assessment is
calculated as follows, (Xiao et al. 2017)
Risk = Hazard x Vulnerability
• This is further mentioned as
Flood Risk Assessment = function of {Hazard Assessment, Vulnerability
Assessment, Elements at risk and Risk Analysis} (Westen et al. 2009).
• The most commonly used aggregation method in MCA is linear weighted
combination which is applicable as Ordered Weighted Averaging
method.(Xiao et al. 2017)
• Yager (1998) has provided a OWA method incorporating criteria attribute
values along with vulnerability scores where OWA operator F can be
defined as follows,
F(a1, a2…. an) = v1*b1 + v2*b2 +….+ vn*bn
Literature Review
Source= Tang et al. 2017

20. • Previously mentioned methods may have some issues with the risk attitude
taken towards risk factors.
• The AHP is a decision support tool, which is used to solve complex
decision problems.
• In GIS analysis AHP has become a popular trending factor.
• Usually regional geographic sub-factors are considered for risk assessment.
• These sub-factors may include criteria such as slope, roughness, soil type,
distance to main channel, land use and the list goes on.
• The AHP method includes 3 crucial steps as:
• (1) Developing a hierarchical structure with a goal at top level, Criteria
at second level .
• (2) Determine relative importance of attribute of different criteria with
respect to goal .
• (3) Calculation of consistency with the help of Consistency Index.
Literature Review

21. • Sometimes ordered weightage assigning is done for factors considered in
the Multi-Criteria Approach (MCA).
•
Literature Review
Factor Weight
Runoff 7
Soil type 6
Slope 5
Roughness 4
Drainage density 3
Distance to main channel 2
Land use 1
Source= Seenirajan et al. 2017

22. •
Literature Review
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
SUM 2.59 4.45 7.28 10.08 15.83 21.5 28
Source= Seenirajan et al. 2017

23. •
Literature Review
Factor
criteria
Runoff Soil Type Slope Roughness Drainage
density
Distance
to main
channel
Land Use Row Sum
Runoff 2.816 8.33 18.867 38.46 73.529 133.33 233.33 508.66
Soil Type 1.408 4.17 12.578 28.846 58.82 111.11 200.0 416.93
Slope 0.929 2.085 6.289 19.23 44.117 88.889 166.66 328.19
Roughness 0.704 1.376 3.144 9.615 29.41 66.667 133.33 244.24
Drainage
density
0.563 1.042 2.075 4.807 14.708 44.444 99.999 167.64
Distance
to main
channel
0.479 0.834 1.572 3.173 7.353 22.222 66.666 102.29
Land Use 0.394 0.709 1.258 2.408 4.853 11.111 33.333 54.06
WEIGHTED
SUM
1822.0

24. •
Literature Review
Factor
criteria
Runoff Soil Type Slope Roughness Drainage
density
Distance
to main
channel
Land Use WS/CW
Runoff 2.816 8.33 18.867 38.46 73.529 133.33 233.33 3.582
Soil Type 1.408 4.17 12.578 28.846 58.82 111.11 200.0 4.370
Slope 0.929 2.085 6.289 19.23 44.117 88.889 166.66 5.551
Roughness 0.704 1.376 3.144 9.615 29.41 66.667 133.33 7.459
Drainage
density
0.563 1.042 2.075 4.807 14.708 44.444 99.999 10.868
Distance
to main
channel
0.479 0.834 1.572 3.173 7.353 22.222 66.666 17.812
Land Use 0.394 0.709 1.258 2.408 4.853 11.111 33.333 33.699
WEIGHTED
SUM
1822.0

25. • λmax can be calculated as average of the ratios.
• In the third step Consistency index (CI) is calculated by,
• CI =
• Then comes Consistency Ratio (CR), where…
• CR =
Literature Review
max
1
n
n
 

CI
RI
Source= Xiao et al. 2017

26. • A table of RI for the validation of Consistency Ratio(CR) is so important
for the testing of reliability.
•
Literature Review
Source= Seenirajan et al. 2017

27. • GIS is a lot helpful for flood risk assessment.
• 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
from expert opinion
Conclusion

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