Training Course on‘Coastal Vulnerability Mapping and Analysis’

August 26-30, 2019

International Training Centre for operational Oceanography(ITCO),

INCOIS, Hyderabad, India

Dr. P C Mohantymohanty@incois.gov.in

RISK= HAZARDS X VULNERABILITY

Hazard : potential threat to humans and their welfare

+

vulnerability : exposure and susceptibility to losses

=

risk : probability of hazard occurrence

disaster : realization of a risk

Vulnerability is an internal risk factor of the subject or system that is exposed to a hazardand corresponds to its intrinsic predisposition to be affected, or to be susceptible todamage.

VULNERABILITY = RISK/HAZARDS

Basics and concept Basics and concept

Vulnerability of the Indian CoastlineVulnerability of the Indian Coastline26 % of Indian Population live 26 % of Indian Population live within 100 Km from the within 100 Km from the shorelineshoreline

Most of the coastal areas are Most of the coastal areas are low lying and vulnerable to low lying and vulnerable to oceanogenicoceanogenic disasters such as disasters such as Tsunamis, Storm Surges, SeaTsunamis, Storm Surges, Sea--level riselevel rise

Dec 26, 2004 Tsunami Dec 26, 2004 Tsunami resulted in a loss of 18, 045 resulted in a loss of 18, 045 deaths and 6,47,599 persons deaths and 6,47,599 persons displaceddisplaced

Increased frequency and Increased frequency and intensity of the disasters intensity of the disasters ((PhailinPhailin Cyclone Cyclone --2013 (2013 (helenhelen, Lehar), Lehar)

26 % of Indian Population live 26 % of Indian Population live within 100 Km from the within 100 Km from the shorelineshoreline

Most of the coastal areas are Most of the coastal areas are low lying and vulnerable to low lying and vulnerable to oceanogenicoceanogenic disasters such as disasters such as Tsunamis, Storm Surges, SeaTsunamis, Storm Surges, Sea--level riselevel rise

Dec 26, 2004 Tsunami Dec 26, 2004 Tsunami resulted in a loss of 18, 045 resulted in a loss of 18, 045 deaths and 6,47,599 persons deaths and 6,47,599 persons displaceddisplaced

Increased frequency and Increased frequency and intensity of the disasters intensity of the disasters ((PhailinPhailin Cyclone Cyclone --2013 (2013 (helenhelen, Lehar), Lehar)

13% of World’s cyclones in the Seas around IndiaAnnual; Frequent phenomenonInundation of Coastal areas

Oceanogenic DisastersOceanogenic Disasters

Tsunami in Indian OceanA few events in the pastInundation of Coastal areas (Large stretches)Highly devastative Tsunami on December 26, 2004

Tsunami, Cyclones, Storm surge, Sea level rise, Coastal erosion, High Waves, etc.

CoastalInundation

Damage

OceanogenicOceanogenic DisastersDisasters

*Source: UNESCO/IOC Report on Coastal Vulnerability

Marine Hazard Tsunami* Storm Surge* Long-term Sea

Level*

Coastal Erosion

Likely Frequency Decade to Millennia

depending on

regional tectonic

regime

Months to decade,

depending on the

regional climate

regime

Ongoing, a

consequence of

global warming and

local factors

Ongoing due to

natural coastal

processes and

anthropogenic

intervention

Limits are Likely to

be affected

Local run-up limit for

specified wave

amplitude predicted

by modelling

Flood limit for

specified surge level

predicted by terrain

modelling

Mean high waterline

mark predicted by

terrain modelling

with allowance of

extreme events

Shoreline position

marked based on the

temporal satellite

observations and

coastal modelling

Cyclone tacks during1970-2005Source: en.wikipedia.org

2004 indian ocean Tsunami Threat maphttp://academic.evergreen.edu/

Cyclones13% of World’s cyclones in the Seas around IndiaAnnual; Frequent phenomenonInundation of Coastal areas

TsunamisA few events in the pastInundation of Coastal areas (Large stretches)Highly devastative Tsunami on Dec 26, 2004

His

tory

Ch

arac

teri

stic

s

Mapping of Coastal Vulnerability Indices

Parameter Data

Geomorphology IRS LISS-IV

Slope GEBCO

Elevation SRTM

Tidal Range Astronomical tides

Shoreline Change Rate Landsat data (1972-2000)

Historical Sea Level PSMSL data from GLOSS

Significant Wave Height Simulated data from Mike model

Dat

a U

sed

“Vulnerability is an internal risk factor of the subject or system that is exposed to a hazard and corresponds to itsintrinsic predisposition to be affected, or to be susceptible to damage”

Me

tho

do

logy

INCOIS, (2012). Coastal Vulnerability Atlas of India. INCOIS-ASG-CGAM-CV-2012-01, Pages 212, Maps 156, INCOIS, Hyderabad, India. ISBN 978-81-923474-0-0.

SHORELINE CHANGE RATE

Landsat, MSS, TM, ETM, IRS(1972, 1990, 2000, 2010)

Sea

Land

117 m

Shoreline Change Rate=117/39=3 m/y

User-specified output parameters include transect spacing and transect length using DSAS.

SEA LEVEL CHANGE RATE

Long-term sea-level observations from Indian Tide Gauges

Mumbai Apallo Bandar

y = 0.0619x + 6977.9

R2 = 0.1408

6800

6850

6900

6950

7000

7050

7100

7150

7200

7250

7300

18

78

18

83

18

88

18

94

18

99

19

04

19

09

19

14

19

19

19

25

19

30

19

35

19

40

19

45

19

50

19

56

19

61

19

66

19

71

19

76

19

81

19

87

19

92

Year

Se

a L

ev

el

(mm

)

Sea-level change along the Indian Coast

COASTAL SLOPE

General Bathymetric Chart of the Ocean (GEBCO)

Deg.

SIGNIFICANT WAVE HEIGHT

Wave simulation in the Mike-21 using the forecasted winds from NCMWF

TIDAL RANGE

Astronomical tides used to asses the tidal amplitude (WX-Tide)

COASTAL ELEVATION

Shuttle Radar Topographic Mission (SRTM)

GEOMORPHOLOGY

Coastal geomorphology interpreted within 500m from the coast using the IRS-P6, LISS-IV

ParameterPercentile

1 2 3 4 5

Shoreline Change Rate

<0(Accretion)

0-25

(No Change)25-50

Low Erosion50-75

Moderate erosion75-100

(High Erosion)

Coastal Slope

80-100(Gentle slope)

60-80 40-60 20-40 0-20(Steep slope)

Elevation

80-100(low elevation)

60-80 40-60 20-40 0-20(high elevation)

Geomorphology Cliffs, , Gullied lands, Barren

lands

Dense Mangroves,

Dense Vegetation, Wetlands,

Mudflats, Tidal Flats, Marsh Vegetation

Sparsely vegetated

coastal plains,

Sparse/Degraded

Mangrove, Open/Vacant Lands, wide

lagoons

Aquaculture,, Salt Pans, Backwaters, Bays, Inundated Coasts, Narrow

Lagoons, Creeks, Estuaries,

Inundated Coasts

Sandy Beach, Spit, Delta and

Inhabited Coastal Plains

Sea level Change Rate

0-20(Sea level fall)

20-40

(very low Rise)40-60

(Low Rise)60-80

(Moderate Rise)80-100

(high rate of Rise)

Mean Significant Wave Height 0-20 20-40 40-60 60-80 80-100

Tidal Range 0-20 20-40 40-60 60-80 80-100

Percentage of Data Ranking

State wise CVI Maps

20m

5m

10m

Coastline in 1950

Coastline in 2005

Predicted erosion in 100 yrs

Predicted 100 year flood level

Composite 100 year hazard line

Sea Level Trend(GLOSS & SoI)

Shoreline Change Rate(Landsat and IRS)

Long Term Sea Level Data (Tide gauges)

Satellite data

DEM data(Carto-DTM)

Return periods (T)Extreme water level (Hmax)

Future Sea Level after T (A) Future Shoreline after T (B) Contours

Multi-hazard Line=union of A, B & C

Contour of Hmax (C)

MHVM Methodology

Multi-hazard Map

Digital Shoreline Analysis System

Sea Level Trend(GLOSS & SoI)

Shoreline Change Rate(Landsat and IRS)

Long Term Sea Level Data (Tide gauges)

Satellite data

DEM data(Carto-DTM)

Return periods (T)Extreme water level (Hmax)

Future Sea Level after T (A) Future Shoreline after T (B) Contours

Multi-hazard Line=union of A, B & C

Contour of Hmax (C)

MHVM Methodology

Multi-hazard Map

Digital Shoreline Analysis System

“The Multi-Hazard Map is a “composite, synthesized and overlay of multiple hazards”

Inputs Source

Extreme Water level Hourly Mean SOI Tide Data and events from published data sources

Sea-level Change Monthly Mean from PSMSL

Shoreline Change Landsat/IRS

Topography ALTM/Carto DTM

Data Used

Coastal Multi-hazard Vulnerability Assessment

High Resolution Topographic data

The Mike 21 has been used to calculate the predicted data to estimate the residuals

Extreme Water level return period was estimated for the above stations based on the Grigorton probability distribution method

Assessment of extreme water level from historical tide data

2

2.2

2.4

2.6

2.8

3

3.2

3.4

5 15 25 35 45 55 65 75 85 95

Wate

r Leve

l (m

)

Return Periods (Y)

Return Period of the extreme water levels for the Mumbai

RP for 100 year for the survey of India tide gauge data

-- No data or negative values

Station

From Year

To

Year

Range

(Y)

Availablity

(y)

Gap

(Y)

Extreme WL

100 Y RP (m)

Future

SL Rise -

100

(m)

Tide

Gauge

Data

Tide

Gauge

Data +

other

obs (m)

Chennai 1880 2007 127 101 26 1.28 3.49 0.11

Cochin 1886 2007 121 71 50 0.92 1.29 0.2

Diamond Harbour 1874 2007 133 62 71 4.63 4.63 0.55

Gangra 1974 2006 32 31 1 2.69 6.05 0.28

Garden Reach 1949 2007 58 53 5 3.45 3.55 0.3

Haldia 1970 2007 37 33 4 3.23 3.44 0.51

Kandla 1952 2006 54 46 8 6.02 7.58 0.31

Karwar 1878 2006 128 34 94 1.8 1.8 0.08

Mangalore 1961 2006 45 39 6 1.69 2.48 0.28

Marmagao 1969 2007 38 30 8 1.82 3.57 0.01

Mumbai 1876 2006 130 120 10 3.37 3.41 0.76

Nagapattinam 1971 1990 19 18 1 1.87 7.81 --

Okha 1974 2006 32 32 0 2.63 2.63 0.15

Paradip 1966 2007 41 40 1 1.58 5.27 0.18

Port Blair 1880 2007 127 61 66 3.36 5.65 0.22

Sagar 1951 1988 37 28 9 3.2 4.44 0.17

Tangachchimadam 1969 1982 13 10 3 0.82 4.63 0.03

Tuticorin 1871 2007 136 36 100 0.63 2.61 --

Vadinar 1981 2006 26 26 -1 3.96 6.49 --

Veraval 1959 1983 24 18 6 2.39 2.58 --

Visakhapatnam 1879 2007 128 50 78 1.63 3.26 0.09

-1.00

0.00

1.00

2.00

3.00

4.00

5.006

/9/2

006

19:1

2

6/1

0/20

06 0

:00

6/1

0/20

06 4

:48

6/1

0/20

06 9

:36

6/1

0/2

006

14:2

4

6/1

0/2

006

19:1

2

6/1

1/20

06 0

:00

Obs

Prd

res

Composite Multi-hazard line

Shoreline Change Rate

Composite Multi-hazard Line

Coastal Multi-hazard Vulnerability Assessment

Sea-level Change RateMumba i Apal lo Bandar

y = 0.0619x + 6977.9

R 2 = 0.1408

6800

6850

6900

6950

7000

7050

7100

7150

7200

7250

7300

1878

1883

1888

1894

1899

1904

1909

1914

1919

1925

1930

1935

1940

1945

1950

1956

1961

1966

1971

1976

1981

1987

1992

Yea r

Sea

Leve

l (m

m)

High Resolution Topography

Extreme Water Level and return periods

Hourly Mean Tide Data from SOI Published data

Sea-level data from PSMSL

IRS and Landsat

Carto DTMALTM

INPUTS

Case Studies

Nellore Cuddalore, Pondicherry and Vellupuram

Mahendra R.S., Prakash C. Mohanty, Srinivasa Kumar T., and Nayak, S. (2011) Assessment and Management of Coastal Multi-hazard Vulnerability along theCuddalore-Villupuram, East Coast of India using Geospatial Techniques. Ocean and Coastal Management, 54(4), 302-311.

Mahendra R.S., Prakash C. Mohanty, Srinivasa Kumar T., Shenoi S. S. C., and Nayak, S. (2010) Coastal Multi-hazard Vulnerability Mapping: A Case Study along thecoast of the Nellore District, Andhra Pradesh, East Coast of India. Italian Journal of Remote Sensing: Vol. 42, Issue 3, pp. 67-76.

3DVAS

3D GIS Mapping3D GIS Mapping

MHVM High Vulnerable Areas

High Vulnerable Areas

KakinadaMachilipatnam

Nizampatnam-Vatapalem

Chennai

Cuddalore-Pondicherry

Tuticorin

Alleppey- Chevara

RameshwaramRameshwaram

PuriPuri

3D Buildings of 3D Buildings of MachilipatnamMachilipatnam3D Buildings of 3D Buildings of MachilipatnamMachilipatnam

3D Buildings of Pondicherry3D Buildings of Pondicherry

3D Buildings with Socio3D Buildings with Socio--economic data of Pondicherryeconomic data of Pondicherry3D Buildings with Socio3D Buildings with Socio--economic dataeconomic dataOf Of MachilipatnamMachilipatnam

Area 433Buildings 661564SE Data 1690831

Area(km2) 96

Buildings 140552

SE Data 127973

Area 18

Buildings 20111

SE Data 22606

Area 1655

Buildings 218385

SE Data 169517Area 781

Buildings 166758

SE Data 25156

Areaj 55

Buildings 48333

SE Data 109393

Area 20

Buildings 51057

SE Data 53805

Area(km2) 947

Buildings 509104

SE Data 37549

Area(km2) 528

Buildings 204650

SE Data 45038

Area 270

Buildings 103810

SE Data 196576

3D GIS Mapping Areas

Area(km2) 18

Buildings 20111

SE Data 22606

Coastal Risk Assessment at Building levelCoastal Risk Assessment at Building level

3m

2m

1m

InundationDepth

Socio-Economic Risk for Tsunami

Very High

Moderate

High

Low

Building Risk

Very High

Moderate

High

Low

Building Risk

Very High

Moderate

High

Low

Building Risk

Thank you

25