Riverine City Flood Vulnerability Index

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RCFVI RIVERINE CITY FLOOD VULNERABILITY INDEX SHIVANI AGARWAL I HUIWON HONG I DEVAKI HANDA


“THE SINGLE RAINDROP NEVER FEELS RESPONSIBLE FOR THE FLOOD” - Douglas Adams

Geographic Information Systems

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PREFACE Worldwide, there is a need to enhance our understanding of vulnerability and to develop methodologies and tools to assess vulnerability. One of the most important goals of assessing coastal flood vulnerability, in particular, is to create a readily understandable link between the theoretical concepts of flood vulnerability and the day-to-day decision-making process and to encapsulate this link in an easily accessible tool. The Coastal City Flood Vulnerability Index is applied to nine cities around the world, each with a different kind of exposure and with regard to the following system’s components, that is, hydro-geological, socio-economic and politicoadministrative. The index gives a number from 0 to 1, indicating comparatively low or high coastal flood vulnerability, which shows which cities are most in need of further, more detailed investigation for decision-makers.

Geographic Information Systems

However, since average global temperatures are already rising and the effects of climate change are becoming palpable around the world, cities also need to focus on adaptation measures in order to strengthen their resiliency and better protect billions of global urbanites due to river flooding. Currently, approximately 21 million people worldwide could be affected by river floods on average each year, and that number could increase to 54 million in 2030 due to climate change and widespread urban development. Given that cities are the primary drivers of economic growth and are home to over half the world’s population, it’s critical that city leaders are informed about the threats that river flooding poses to their citizens’ health, security, and economic well-being. There is therefore a need for a readily calculated and easily understood method to calculate flood vulnerability in such areas.

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BACKGROUND SUMMARY

NATURAL HYDRO-GEOLOGICAL COMPONENTS

COMPONENTS OF COASTAL FLOOD VULNERABILITY: THE SYSTEMS APPROACH The systems approach aims to identify the interactions of different actors or components within certain defined boundaries. The three interdependent subsystems in the coastal vulnerability system are: • •

The natural river subsystem (NS), in which the physical, chemical and biological processes take place. The socio-economic subsystem (SES), which includes the societal (human) activities related to the use of the natural river system; socio-economic systems are made up of rules and institutions that mediate human use of resources as well as systems of knowledge and ethics that interpret natural systems from a human perspective. The administrative and institutional subsystem that includes administration, legislation and regulation, where the decision, planning and management processes take place.

Each of the three subsystems is characterised by its own elements, and it is surrounded within its own environment.

EXPOSURE • Sea-level rise • Storm surge • Number of cyclones in the last 5 years • River discharge • Foreshore slope • Soil subsidence • Km of coastline SUSCEPTIBILITY The hydro-geological component does not consider susceptibility indicators for this method. RESILIENCE The hydro-geological component does not consider susceptibility indicators for this method.

SOCIO-ECONOMIC COMPONENTS EXPOSURE • Population close to coastline • Cultural heritage • Growing coastal population SUSCEPTIBILITY • Percentage of disabled persons (<12 and >65 years) RESILIENCE • Shelters • Awareness and preparedness • Km of drainage • Recovery time

FLOOD EVENT COASTAL CITY VULNERABILITY NATURAL SYSTEM

Hydro-geological Component (Exposure Indicators)

(+)

SOCIO-ECONOMIC SYSTEM

Socio-economic Component (Exposure, Susceptibility, Resilience)

INSTITUTIONAL COMPONENTS (-)

INSTITUTIONAL SYSTEM

Politico-administrative Component (Exposure, Susceptibility, Resilience)

Exposure and Susceptibility Fig.1 Vulnerability System Geographic Information Systems

Resilience, Adaptation & Coping Capacity

EXPOSURE • Uncontrolled planning zone SUSCEPTIBILITY • Flood hazard maps RESILIENCE • Institutional organizations • Flood protection RCFVI


Rotterdam Marseille

Shanghai

Casablanca Calcutta

Dhaka

Osaka Manila

Buenos Aires

NINE CITIES AROUND THE WORLD WHERE CCFVI IS APPLIED Geographic Information Systems

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RESEARCH QUESTION

PUNE, INDIA

How does one measure vulnerability due to riverine floods?

The city of Pune is prone to urban flooding as Mumbai, India. In May 2015, pre-monsoon downpour of 102.6 mm – an 87-year-old all-time record for maximum rainfall in a day in the month threw rail and road traffic out of gear besides causing heavy waterlogging. “Above-normal” rainfall has been flooding the city roads and basements of apartments for the past two years.

We are creating a scale to assess flood vulnerability and risk of flooding for riverine cities of India, starting with Pune in the state of Maharashtra. This scale would take into account the vulnerability of the place based on the various natural and hydro-geological factors. Additionally, the efficiency of the scale would be enhanced because of the various social, economic and institutional factors particular to the city. Specifically, we would use population density, income level, awareness and preparedness data, literacy and illiteracy and many other social factors that affect the vulnerability. Most specifically for Pune, we are making sure to give the highest weightage to areas that include informal settlements.

Chandra Bhushan, the deputy director of New Delhi’s Centre for Science and Environment (CSE), observed that bad urban planning, encroachment of water bodies, increase in extreme weather events and lack of preparedness resulting in urban flooding was relevant to Pune. “Increased rainfall intensity and urban flooding would become a norm rather than exception unless corrective measures are taken immediately. We will have to protect our water bodies and also be prepared for these events,” he stated. The direct impact of urban flooding can be easily understood in the city.

Fig.2 Mutha canal wall breaches: Flood situation: Dandekar, Pune, India

Geographic Information Systems

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Pune District

Mula Mutha River

Maharashtra

Pune City

LOCATION OF PUNE, MAHARASHTRA, INDIA Geographic Information Systems

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WHY PUNE ? •

• •

Pune is one of India’s fastest-growing metropolises, the second largest in the state of Maharashtra and the eighth largest urban agglomeration in India. Over the last three decades it has emerged as a thriving hub for the automotive, information technology and education sectors. The city attracts a large number of migrants from various parts of the country and from all economic classes, many of whom live in poorly constructed informal settlements or bastis.

There are 564 slums in the PMC, with a total population of approximately 11.89 lakh. Approximately 40% of the city’s total population resides in these slums. The city of Pune is the also the 8th most populous city in India among metropolitan areas. It is also the administrative headquarters of both the Pune division and Pune district. Pune has experienced the highest record of growth within a span of 20 years and is known for its traffic density in India.

Fig.3 Average Rainfall, Pune, India

MitKat. “Pune Flood Risk Information.” MitKat, June 2016, www. mitkatadvisory.com/InsightPdf/Pune-Flood-Information-Jun-2016.pdf.

Fig.5 Rivers and Streams, Pune, India Fig.4 Mutha canal wall breaches: Flood situation: Dandekar, Pune, India

Geographic Information Systems

Mishra, SSP. “Ground Water Information, Pune District, Maharashtra.” CENTRAL GROUND WATER BOARD, 2009, cgwb.gov.in/District_Profile/ Maharashtra/Pune.pdf.

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WETLAND CHANGE MAP OF PUNE (1990 - 2018)

WETLAND CHANGE -1 0 1 0 Geographic Information Systems

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4 Miles RCFVI


METHODOLOGY FOR THE PHYSICAL FACTOR VULNERABILITY SCALE

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GATHERING THE RIGHT DATA

DATA USED

The natural factors that have to be included in The different data that we have used for the the vulnerability scale for the hydro-geological or natural factor vulnerability scale are: natural physical factors first have to be gathered from the online portals. These pdfs have to be • MITKAT Flood Map selected based on trusted sources so that the end • Red and Blue Line Flood Map (just for result do not turn out to be incorrect. Hence, a reference) lot of the data chosen by us has been taken from • USGS Landsat 2018 FLOOD MITKAT (Mitigating Knowledge Age Elevation Threats)Model (DEM) official websiteMAP for Pune- Government. • Aster Digital

NATURAL EXTENTS OF THE R

Mitigating Knowledge Age Threats Flood Map (Based on flood history of Pune)

Map showing high-risk flood prone areas in Pune based on last few years of flood history. https://www.mitkatadvisory.com/InsightPdf/Pune-Flood-Information-Jun-2016.pdf

MitKat. “Pune Flood Risk Information.” MitKat, June 2016, www. mitkatadvisory.com/InsightPdf/Pune-Flood-Information-Jun-2016. pdf.

Pune Municipal Corporation, Blue and Red Line Map (Based on man-made structures along the river) PMC. “Pune Riverfront.” Pune Riverfront, 2016, puneriverfront.com/

Map showing the developed and vacant plots within the Red Line http://puneriverfront.com/

USGS LANDSAT 2018

USGS. “Landsat 8 OLI/TIRS C1 Level-1.” Earth Explorer, 2018, earthexplorer.usgs.gov/.

Geographic Information Systems

ASTER Digital Elevation Model (DEM)

USGS. “Aster Global DEM.” Earth Explorer, 2011, earthexplorer.usgs. gov/.

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MITKAT FLOOD MAP(Mitigating Knowledge Age Threats) FLOOD MAP - MITKAT

Digitize using Rhino

Mitigating Knowledge Age Threats This map makes use of the previous flood history in Pune to determine high risk flood zone areas.

The digitized version of the MITKAT map This map would be used by us for determining the vulnerability of floods within the hydrogeological factors.

Map showing high-risk flood prone areas in Pune based on last few years of flood history. https://www.mitkatadvisory.com/InsightPdf/Pune-Flood-Information-Jun-2016.pdf

MitKat. “Pune Flood Risk Information.� MitKat, June 2016, www.mitkatadvisory.com/InsightPdf/Pune-FloodInformation-Jun-2016.pdf.

Make a polygon feature as a rectangle shape to give the extra areas a value of 0.

Erase flooding area polygon feature from the rectangle created with value 0.

Merge dark blue line, light blue line and the subtracted rectangle to give final values.

Polygon to Raster Reclassify the three areas 1 - reclassified as 0 2 - reclassified as 7 3 - reclassified as 10 Geographic Information Systems

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0

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4 Mil

Non-Flooding Areas : Weight 0

0

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General Flood Affected Areas : Weight 7

3 : Weight 10 High-risk 2 Flood Prone Areas River Wards

Geographic Information Systems

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4 Mil


LANDSAT IMAGE TO PERMEABILITY MAP

USGS. “Landsat 8 OLI/TIRS C1 Level-1.” Earth Explorer, 2018, earthexplorer.usgs.gov/.

Natural Composite R:3 G:2 B: 1

USGS. “Landsat 8 OLI/TIRS C1 Level-1.” Earth Explorer, 2018, earthexplorer.usgs.gov/.

False color urban R:7 G:6 B: 4

Reclassify Permeable Area (0) Impermeable Area (3)

Water Wetlands Farmlands Urban Areas USGS. “Landsat 8 OLI/TIRS C1 Level-1.” Earth Explorer, 2018, earthexplorer.usgs.gov/.

Geographic Information Systems

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0

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3

Permeable Area : Weight 0 Impermeable Area : Weight 3

Geographic Information Systems

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DIGITAL ELEVATION MODEL

Elevation (530-853) Lower elevation is more vulnerable.

Raster Calculation Range [530-853] to [5-0] (-(“value�-853))/(853-530/5)

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Geographic Information Systems

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DIGITAL ELEVATION MODEL TO BASIN MAP

Basin map created from DEM.

Revalued based on the proximity to the river. Weights (2 or 1)

0

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Further Away Basin : Weight 1 0.5 1 2 3 Immediate Basin : Weight 2

Geographic Information Systems

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4

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COMBINED PHYSICAL VULNERABILITY MAP

0

7

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MITKAT FLOOD MAP

0 ELEVATION MAP

Geographic Information Systems

0

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PERMEABILITY MAP

5

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RIVER BASINS MAP

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0

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Physical Vulnerability Scale

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0 River Wards Geographic Information Systems

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METHODOLOGY FOR THE SOCIAL FACTOR VULNERABILITY SCALE

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(0-10)

(0-5)

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Geographic Information Systems

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GATHERING THE RIGHT DATA

DATA USED

The natural factors that have to be included in the vulnerability scale for the hydro-geological or natural physical factors first have to be gathered from the online portals. These pdfs have to be selected based on trusted sources so that the end result do not turn out to be incorrect. Hence, a lot of the data chosen by us has been taken from official website for Pune Government.

The different data that we have used for the natural factor vulnerability scale are: • • •

Pune Ward Map Pune Land Use Map Pune Informal Settlements Map

Pune Municipal Corporation Ward Map

Pune Municipal Corporation Ward Map Digitized map of the Pune ward map using Arc Map and this has been used as an important base map for all the functions carried out further.

Pune Municipal Corporation Ward Map

Pune Municipal Corporation Land Use Map Digitized map of the Pune ward map using Arc Map and this has been used as an important base map for all the functions carried out further.

Mundhe, Nitin, et al. “Assessment of Municipal Solid Waste Management of Pune City Using Geospatial Tools.” International Journal of Computer Applications, vol. 100, no. 10, 2014, pp. 24–32., doi:10.5120/17562-8184.

PMC. “Land Use Map of PMC.” Revised City Development Plan for Pune - 2041, 2012, pmc.gov.in/sites/default/files/project-glimpses/Draft_City_Development_ Plan_for_Pune_City_2041_Vol-1.pdf.

Geographic Information Systems

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INFORMAL SETTLEMENTS MAP The informal settlements map is very important to be considered as a factor to calculate the social vulnerability scale since the poor and low income people who live here in squatters are the most vulnerable since they are unprepared and illiterate. Also, they are the unmapped people on the landuse maps of Indian cities. Digitized Landuse map of Pune. But, Informal Settlements which is an effective factor to calculate vulnerability is missing.

Lundberg, Mattias K. A., et al. “Location and Welfare in Cities: Impacts of Policy Interventions on the Urban Poor.� Policy Research Working Papers, 2004, doi:10.1596/1813-9450-3318.

Hence, digitize the informal settlements map from an available PDF. Convert each polygon feature of the Informal Settlements to point features.

Spatially join the points to the Landuse ap that has been digitized.

Therefore, the result is that a lot of the informal settlements are within different land uses that were not marked initially.

Use the Informal Settlements to inform the social factor vulnerability scale. Geographic Information Systems

RECLASSIFIED WEIGHTAGE : 5 RCFVI


POPULATION PER WARD POPULATION PER WARD 10,000 - 15,000 15,000 - 20,000 20,000 - 25,000 25,000 - 30,000 30,000 - 35,000 35,000 - 40,000 40,000 - 45,000 45,000 - 50,000 0

0.5

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Miles 4

Population per Ward

But, population within a certain area is a more effective factor to calculate vulnerability.

Hence, add a new field called Ward Area.

Use field calculator to find density which is: Population per Ward / Ward Area.

Finally, Population Density per Ward. Denser along the river edge.

POPULATION DENSITY POPULATION DENSITY PER PER WARDWARD 0.00 - 0.005 0.005 - 0.01 0.01 - 0.02 0.02 - 0.03 0.03 - 0.04 0.04 - 0.05 0.05 - 0.07 0.07 - 0.10 0 Geographic Information Systems

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POPULATION DENSITY WITHIN RESIDENTIAL AREAS PER WARD RECLASSIFIED WEIGHTAGE : 0 TO 10

POPULATION DENSITY PER WARD (WITHIN RESIDENTIAL LANDUSE) 0.003 - 0.014 0.014 - 0.025 0.025 - 0.04 0.04 - 0.06 0.06 - 0.084 0.084 - 0.120 0.120 - 0.25 0.25 - 0.5 0 Geographic Information Systems

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ILLITERATE AND UNAWARE/ UNPREPARED POPULATION DENSITY WITHIN RESIDENTIAL AREAS PER WARD RECLASSIFIED WEIGHTAGE : 0 TO 5

UNAWARE POPULATION DENSITY PER WARD (WITHIN RESIDENTIAL LANDUSE) 0.001 - 0.01 0.01 - 0.02 0.02 - 0.1 0 Geographic Information Systems

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1

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Miles 4 RCFVI


CANTONMENT AREA LANDUSE MAP

INDUSTRIAL AREA LAND

The cantonment areas shown in the landuse map are the least vulnerable as they these areas are under army control and have high preparedness against any risk, social or physical.

The industrial areas shown in the land vulnerable when compared to residen chances of people evacuating with m of less population density.

Cantonment

RECLASSIFIED WEIGHTAGE : 0

Geographic Information Systems

RECLASSIFIED

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DUSE MAP

PUBLIC AMENITIES LANDUSE MAP

duse map are considered to be less ntial areas because they have higher much ease and which is also because

The public amenity areas in the landuse map are more vulnerable when compared to cantonments but less compared to industrial and residential zones in the landuse map. This is because it might contain facilities like hospitals, schools and commercial shopping centers.

Industrial Areas Public Amenities

WEIGHTAGE : 3

Geographic Information Systems

RECLASSIFIED WEIGHTAGE : 2

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COMBINED SOCIAL VULNERABILITY MAP

POPULATION DENSITY PER WARD (WITHIN RESIDENTIAL LANDUSE)

UNAWARE POPULATION DENSITY PER WARD (WITHIN RESIDENTIAL LANDUSE)

0.003 - 0.014 0.014 - 0.025 0.025 - 0.04 0.04 - 0.06 0.06 - 0.084 0.084 - 0.120 0.120 - 0.25 0.25 - 0.5

0.001 - 0.01 0.01 - 0.02 0.02 - 0.1

POPULATION DENSITY : W (0 - 10) 0

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ILLITERATE POPULATION : W (0 - 5)

Cantonment

Industrial Areas

CANTONMENTS : WEIGHT 0

INDUSTRIAL AREA : WEIGHT 3

ELEVATION MAP Public Amenities

PUBLIC AMENITIES : WEIGHT 2

Geographic Information Systems

INFORMAL SETTLEMENTS : W - 5

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20

0 Geographic Information Systems

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COMBINED RIVERINE CITY FLOOD VULNERABILITY MAP (ADDED) PHYSICAL VULNERABILITY MAP 20

1

+ 20

1 SOCIAL VULNERABILITY MAP

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40

0 Geographic Information Systems

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COMBINED RIVERINE CITY FLOOD VULNERABILITY MAP (MULTIPLIED) PHYSICAL VULNERABILITY MAP 20

1

X 20

1 SOCIAL VULNERABILITY MAP

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400

0 Geographic Information Systems

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3. The maps that were used for digitizing had projections that were unable to be identified. 4. The area of study was constrained because of the extents of the available flood data. 5. The datasets used in the study are not consistent in terms of the particular time periods they represent. 6. The Modifiable Area Problem will be a limitation while determining the population density to census tract. 7. The study also assumes that climate and pollution would have an impact on the flood vulnerability whether or not it is considered as part of the scale. 8. The Illiteracy rate has been used as a proxy data for awareness/income data.

MOST VULNERABLE

2. The analysis did not take into account the man-made structures like dams, bridges and paved areas along the riverfront that exacerbate the problem.

20 18 16 14

10

X

HURRICANE

8 6 4

EARTHQUAKE

2 0

The social vulnerability scale created can be combined to calculate the vulnerability due to any other natural disaster like Hurricanes or Earthquakes. 400

350

300

250

200

LEAST VULNERABLE

150

Geographic Information Systems

FLOOD

12

LEAST VULNERABLE

1. This study is not taking into consideration the effects that other natural disasters have on flood vulnerability of a region. For example, the 1987 flood in Bihar occurred due to a landslide blockage in the region.

CONCLUSION

MOST VULNERABLE

LIMITATIONS

In this particular project we assessed vulnerability by combining the social and physical flood vulnerability scales, to get the Riverine City Flood Vulnerability Index that ranges from 0-400. Furthermore, to test our scale we implemented it on the city of Pune, an area prone to urban flooding due to rivers. Anything above 350 would require immediate attention/ funds from the government.

100

50

0 RCFVI


DATA SOURCES 1. Lundberg, Mattias K. A., et al. “Location and Welfare in Cities: Impacts of Policy Interventions on the Urban Poor.” Policy Research Working Papers, 2004, doi:10.1596/1813-9450-3318. 2. PMC. “Land Use Map of PMC.” Revised City Development Plan for Pune - 2041, 2012, pmc.gov.in/sites/default/ files/project-glimpses/Draft_City_Development_Plan_ for_Pune_City_2041_Vol-1.pdf. 3. Mundhe, Nitin, et al. “Assessment of Municipal Solid Waste Management of Pune City Using Geospatial Tools.” International Journal of Computer Applications, vol. 100, no. 10, 2014, pp. 24–32., doi:10.5120/175628184. 4. USGS. “Aster Global DEM.” Earth Explorer, 2011, earthexplorer.usgs.gov/. 5. USGS. “Landsat 8 OLI/TIRS C1 Level-1.” Earth Explorer, 2018, earthexplorer.usgs.gov/. 6. PMC. “Red and Blue Line Map.” Pune Riverfront, 2016, puneriverfront.com/. 7. Mishra, SSP. “Ground Water Information, Pune District, Maharashtra.” CENTRAL GROUND WATER BOARD, 2009, cgwb.gov.in/District_Profile/Maharashtra/Pune.pdf.

BIBLIOGRAPHY 1. MitKat. “Pune Flood Risk Information.” MitKat, June 2016, www.mitkatadvisory.com/InsightPdf/Pune-FloodInformation-Jun-2016.pdf. 2. Mishra, SSP. “Ground Water Information, Pune District, Maharashtra.” CENTRAL GROUND WATER BOARD, 2009, cgwb.gov.in/District_Profile/Maharashtra/Pune.pdf. 3. Rogala, Alexander, et al. “Why Cities Need to Address River Flooding Now.” World Resources Institute, 12 Mar. 2015, www.wri.org/blog/2015/03/why-cities-needaddress-river-flooding-now. 4. Kudale, Devendra. “Mutha Canal Wall Breaches - Flood Situation : Dandekar Bridge, Pune.” YouTube, YouTube, 27 Sept. 2018, www.youtube.com/watch?v=0XvycLI3pWA. 5. TNN. “Experts Reiterate Pune Prone to Urban Flooding - Times of India.” The Times of India, 31 Aug. 2017, timesofindia.indiatimes.com/city/pune/ experts-reiterate-pune-prone-to-urban-flooding/ articleshow/60299029.cms. 6. Center for Communication and Development Studies. “Where Do We Stand - Urban Poverty and Slums in Pune.” Digital Equality, 2017, digitalequality.in/reports/ profile-of-surveyed-settlements/. 7. Balica, S. F., et al. “A Flood Vulnerability Index for Coastal Cities and Its Use in Assessing Climate Change Impacts.” SpringerLink, Springer, 16 June 2012, link.springer.com/ article/10.1007/s11069-012-0234-1#citeas.

“REMEMBER : WHEN DISASTER STRIKES THE TIME TO PREPARE HAS PASSED” - Steven Cyros


Geographic Information Systems Professor Leah Meisterlin Professor Grga Basic Fall 2018 Columbia University in the City of New York GSAPP, MS. Architecture and Urban Design Shivani Agarwal saa2226@columbia.edu Huiwon Hong hh2749@columbia.edu Devaki Handa dh2915@columbia.edu


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