thames inundation report

THE CREATION OF A 6M INUNDATION ZONE AROUND THE RIVER THAMES, LONDON, UK AND

ITS EFFECTS ON VULNERABLE POPULATIONS AND BUILDING INFRASTRUCTURE

IAN J. MORRIS

ABSTRACT

The intent of this work is to display the benefits provided by two dimensional inundation modelling along the River

Thames in London, UK and how it can be used to identify populations and infrastructure at risk. A total of 107,937

people within a pre-defined set of “vulnerable” age groups, 0-7 and 65+ year olds, fall within the Boroughs of

Greenwich, Lewisham, Newham, Southwark and Tower Hamlets. In total, segments of 14 Boroughs fall within a 6m

inundation level of the river and its tributaries, with differences in the spread of population and infrastructure creating

zones of higher and lower risk across this defined 91.43km2 hazard zone. In this respect the Boroughs of Newham,

containing the highest proportions of total “vulnerable” population and 0-7 year olds, and Southwark, containing the

highest proportion of 65+ year olds, are classified as being the most at risk areas. Building density data confirms this

categorization and shows a higher proportion of buildings, per kilometer radius, in and around these areas.

INTRODUCTION

The aim of this study is to create a model, and subsequent series of thematic maps, in order to visualise both the hazard

zone and the associated risks and effects on building infrastructure, within this zone, brought on by a 6m inundation of

the River Thames, and its tributaries, within Ordnance Survey (OS) tiles TQ37, TQ38, TQ47 and TQ48 of London, UK.

In order to achieve this, the areal extent of the inundation, within the aforementioned OS tiles must first of all be

identified, using LiDAR DTM or DSM data, to establish a hazard zone that will form a basis to the rest of the study. From

the establishment of this hazard zone, 2011 census population data will be used in conjunction with the boundaries of

local Boroughs to identify the population at risk, defined in this study to be those within age groups 0-7 years and those

in advance of 65 years of age. The extent of the hazard zone and its effects on current building infrastructure is to then

be assessed with the end product of this study being the creation of suitable thematic maps including any relevant items

(legend, north arrow, etc) to effectively visualise both the hazard and risk zones of the inundation.

Previous work with inundation modelling has shown it to be useful in the “development of spatially accurate hazard

maps” in “the assessment of risk to life and property in the floodplain” (Mason, Schuman & Bates, year unknown).

It is hoped this study will give further insight to the benefits of inundation modelling so that it may play a bigger role

and/or further assist governmental policy making and operations to further protect populations in and around areas at

risk of inundation and flooding. In particular it is hoped that this study will provide these insights and assistance to the

Boroughs of London affected by the River Thames and its tributaries.

Why is inundation modelling important?

A two dimensional inundation model, as used in this study, effectively displays the areas affected by a given amount of

inundation (the rise in elevation of a terrain) brought on by a known threat or hazard, i.e. water, during a flood event.

Inundation modelling is crucial and used so that the hazards posed by extreme rises in water, such as flooding, can be

visualised in order to identify those at risk and accurately mitigate this risk so that its effects on demographics such

population, infrastructure, various commercial, industrial and residential zones as well as agricultural areas and other

items or areas of interest are lessened as much possible.

Hazards can be defined as a phenomena, physical event or human activity that has the potential to cause loss of life,

injury, damage to property and social or economic disruption as well as environmental degradation (jbpub.com, last

accessed 21st February 2016.). In conjunction with this, risk is defined as a society or element vulnerable to a hazard

(jbpub.com, last accessed 21st February 2016).

According to the London Assembly this mitigation should include the waterproofing of external walls, the use of flood

resistant plaster and using solid concrete for ground floor areas amongst other items (London Assembly, 2002). They

also highlight work done by the Environment Agency and the importance of “living with the Thames” in how crucial

further mitigation, through the implementation of further flood defence infrastructure, is in the face of rising sea levels

(London Assembly, 2002).

METHODS

Note: This study uses ArcMap 10.3 for the processing of data and creation of maps.

The data used in this study comprised of both a DTM and a DSM raster elevation dataset captured by LiDAR technology

at 2m spatial resolutions as provided by the Environmental Agency. Only one of which could be used for the final

thematic maps. A shapefile containing a series of polyline vectors representing the River Thames and its tributaries was

also used and taken from the Ordnance Survey Open Rivers dataset. The fourth dataset, provided by the Office of

National Statistics, was a shapefile containing the boundaries of local boroughs (i.e. Tower Hamlets) and their smaller

local regions (i.e. Bethnal Green South) in polygon shape and the fifth, provided by InFuse portal, the UK’s 2011 census

data gateway, was an excel .csv spreadsheet containing their population and density statistics. The sixth file contained

building footprints represented as polygons and the sixth file as provided by the Ordnance Survey Mastermap

Topography Layer. All files used covered Ordnance Survey (OS) tiles TQ37, TQ38, TQ47 and TQ48 of London, England.

Hazard Zone Creation

In trying to satisfy objective number one of the study, model builder was used and the first stage of building a successful

and transferrable model would be the need to select all areas of terrain either “equal to or less than” 6m in elevation

which, in effect, displays the inundation. Using the DTM raster elevation data set the most efficient way of doing this is

to create an SQL query within the “Raster Calculator” of ArcToolbox in ArcMap to return a new layer displaying both the

true (the inundated areas) and false (the non-inundated areas) values of the input criteria in different colours. It was

decided that more accurate results would be obtained from the DTM raster due to the completeness and continuity of

the data. The DSM raster displayed gaps in the data in crucial areas of the dataset, i.e. near the river and its tributaries

(figure 1), making it difficult to obtain accurate results from this data and therefore make accurate analyses and

decisions through use of it. Tobler’s first law could have been applied and spatial interpolation used to “fill in the gaps”

but this works on the assumption that there are no anomalous heights or topographies that occur in these areas in the

real world. Again this makes it difficult to justify the use of the DSM raster as crucial and potentially life or death

affecting situations (i.e. whether or not to evacuate the area) could be based on these maps. Doing this with potentially

inaccurate data is too great a risk despite the fact that the interpolation has the potential to create near accurate,

compared to the real world, elevation data, it cannot be assumed that it definitely will.

Figure 1 – DSM (left) and DTM (right) raster elevation showing high (red) to low (green) elevations with areas of no data

(white) visible in critical areas near the river and its tributaries.

The second stage would involve reclassifying this new output layer to remove all of the areas of no interest (those

“more than” 6m in elevation) or “non-inundated” areas, as they’re not part of the objectives of this study. This is

achieved by selecting the output raster from stage one as the input raster in the “Reclassify” tool and reclassifying the

false, “1” values, as “NoData”, to remove them from the output raster of this stage and also changing the true, “2”

values to “1”. This has the desirable effect of “de-cluttering” the layer by removing values of irrelevance to the study.

The areas of land between 0-6m in elevation would need to be hydrologically connected to the River Thames and its

tributaries in order for them to flood and become inundated. This third stage of model building initially involves

converting the output raster from stage two in to polygons by using the “Raster to Polygon” tool – it was decided not to

simplify the polygons in order to preserve area size and shapes. This then allows use of the “Select by Location” tool,

during the fourth stage of model building, to select all polygons from the newly created output layer that “are crossed

by the outline of the source layer feature” with the source layer feature being a shapefile containing the “River”

geometries. This output layer was then clipped to ensure that only the relevant data, i.e. the administrative boundaries

that fell within the flood zone, were used in the final map.

This selected data is then exported, using the same co-ordinates as the source layers data and added to the map in a

layer that displays vector polygons, hydrologically connected to the “River” line polygons that are between 0-6m in

elevation and therefore capable of becoming inundated aka the “flood zone”.

Figure 2 – The Model Builder design used to process and complete objective 1 - ascertain a flood inundation hazard zone

caused by a 6m rise in flood waters.

Population at Risk

In order to achieve the second objective of the study and identify the vulnerable (0-7 and 65+ year olds) population at

risk from the created flood zone a population layer needed to be created for each of these demographics. This was done

by first of all joining the shapefile, containing the local area boroughs and regions, with the population statistics data (via

a primary key) excel .csv, file for the two age groups to create two, thematic, population maps. Next the areas within the

inundation zone had to be selected and this was achieved by running another “Select by Location” query and setting the

target layer as the shapefile containing the local boroughs and regions, the source layer as the flood zone and selection

method as “intersect the source layer feature” thereby selecting all local boroughs and areas that are within the flood

zone. This output layer was then clipped to ensure that only the relevant data, i.e. the administrative boundaries that

fell within the flood zone, was used in the final maps. Finally, the two datasets were classified in order to show their

respective population densities, this is discussed in further detail under the heading “Data Classification methods”.

Building Density

To achieve objective three and assess the extent of hazardous regions and their effect on current building infrastructure,

building density was first of all calculated. The first step in this was to initially identify all buildings within the flood zone

and this was done with another “Select by Location” using the building footprints data set as the target layer and the

flood zone as the source layer and selecting anything that “intersects the source layer” feature. Next in order to

calculate the actual density itself the polygons needed to be converted to the location of their centroid points. This was

done by first of all adding two new columns labelled “Latitude” and “Longitude” to the building footprints attribute table

and using the “Calculate Geometry” feature to calculate the X and Y “Co-ordinates of the Centroid”. The results were

then exported to a new table which was then turned into an “XY Event Layer” through ArcToolbox “Data Management

Tools > Layers and Table Views”. The final stage of this process was to set the appropriate fields “X” to longitude and “Y”

to latitude before adding this new layer to the map.

Next, in order to analyse how many points occurred within an arbitrary, circular, radius (1km was used) of one another

the newly created layer from the previous step was used as the input layer of the “Point Density” tool within “Spatial

Analyst Tools > Density”. This layer was then classified using Natural Breaks, separating the data into five classes and

added to the map.

Result Analysis

Note: Results in this study are obtained through descriptive and inferential statistics where applicable

Data Classification Methods for Risk Mapping

It was decided that five classes were to be used on the basis that “viewers can only comprehend about 5-7 categories

and colour ranges” (Parmenter, 2011). Thus five classes were used to display the outputs of the risk maps when

satisfying objective two of this study.

In addition to it was determined that the Natural Breaks classification method displayed the best results as, when

compared with the other classification methods, it simply displayed the variation between the populations of each

administrative area better, making for clearer visualisation and interpretation of the data and, thus, inferences are

easier to make from it. Natural Breaks classification is also designed to fit unevenly distributed datasets and the natural

differences that occur between the data within in them, such as this dataset (figures 3 & 4). This is opposed to other

methods such as Quantiles and Equal Intervals which are based on having an equal number of classes and equal ranges

of values, respectively. On these bases Quantiles and Equal Intervals were discarded as valid classification methods due

to them being based on almost arbitrary class numbers and data ranges when considered in conjunction with the

distribution of the data available. Standard Deviation classification was also discarded because identifying values that fall

above or below a mean doesn’t lend itself to this scenario and determining how much of a population is at risk.

Figure 3 – Histogram displaying natural breaks classification for 0-7 year olds within the flood zone

Figure 4 – Histogram displaying natural breaks classification for 65+ year olds within the flood zone

RESULTS

Objective 1 - Flood Zone Coverage

Note: The following results are calculated using the extents of the data provided in each dataset

Figure 5 – Map displaying the Boroughs within a 0-6m Inundation or “Hazard” Zone of the River Thames in London, UK

(2011 census data)

Figure 6 shows that an area of 91.43km2 (91,425,216m / 1,000,000) is covered by the 6m inundation/hazard zone across

the 14 boroughs displayed in figure 5. As shown in figure 7 the area covered by the study area (OS tiles TQ37, TQ38,

TQ47 and TQ48 of London, England) is 420.73km2 (420,733,702 / 1,000,000) and therefore the percentage of the study

area covered by the flood zone is 21.73% (91.43 / 420.73 * 100).

Differences in the areas covered by the flood zone (91.43 km2) and the administration boroughs (78.92 km2) can be

accounted for by the fact that the flood zone covers an area in which no data, immediately north and south (displayed in

white) of the River Thames, for the administrative boroughs has been provided (figures 6, 8, 9, 10 & 11).

The fact that, through use of the DTM, only integer numbers, as opposed to floating point in the DSM, have been used

gives an error margin of 0.50m either side of each elevation value. This means that in reality the actual terrain used in

the flood zone can be expected to vary between -0.5 to 6.5m due to rounding depending on the actual value of the

decimal places in the floating point data when it was collected.

Figure 6 – Area statistics of Administrative Boundaries

within the Flood Zone

Figure 7 – Area statistics of the Administrative Boundaries

over entire study area

Barking and Dagenham

Area Inundated – 11.23 km2

% of total flood zone inundated – 12.28%

Bexley



City of London



Greenwich



Figure 8 – Flood Zone statistics for the Boroughs of Barking & Dagenham, Bexley, City of London and Greenwich

Hackney



Haringey



Lambeth



Lewisham



Figure 9 – Flood Zone statistics for the Boroughs of Hackney, Haringey, Lambeth and Lewisham

Newham



Redbridge



Southwark



Tower Hamlets



Figure 10 – Flood Zone statistics for the Boroughs of Newham, Redbridge, Southwark and Tower Hamlets

Waltham Forest



Westminster



Figure 11 – Flood Zone statistics for the Boroughs of Waltham Forest and Westminster

The hazard map (figure 5) and figures 8, 9, 10 and 11 show the flood zone to have the largest areal impact on Newham

with 21.58km2 flooded by the 0-6m inundation, representing almost one quarter (23.50%) of the flood zone itself.

Comparatively, the borough in receipt of the least amount of flooding is Haringey with only 0.024 km2 becoming

inundated, representing only 0.02% of the entire flood zone.

The second largest area covered is Southwark at 14.75 km2 (or 16.13% of the flood zone) with Barking & Dagenham third

at 11.23 km2 (or 12.28% of the flood zone) and Greenwich fourth at 10.09 km2 and 11.03% of the flood zone. In total

these four Boroughs represent 57.65km2, or 63.04% of the flood zone.

The Boroughs of City of London, Hackney, Haringey, Redbridge, Waltham Forest and Westminster all represent areas

covered by the flood zone of less than 1% and 1km2 each, totaling 2.28% together, and 2.114km2.

The remaining Boroughs of Bexley, Lambeth, Lewisham, and Tower Hamlets all represent the remaining 19.16km2, or

20.93% of the flood zone – less than the amount and percentage covered by Newham by itself.

In this respect it can be calculated that the area of “no data” covers 12.51km2 or 13.68% of the flood zone.

Objective 2 – Vulnerable population at risk

Figure 12 – Map displaying the number of 0-7 year olds, per administrative area, within a 0-6m Inundation or “Hazard”

Zone of the River Thames in London, UK (2011 census data)

Figure 13 – Map displaying the number of 65+ year olds, per administrative area, within a 0-6m Inundation or “Hazard”


The results in figures 12, 13 and 15 show Newham as having the largest total population of vulnerable age groups within

the flood zone at 35,113 (or 32.53% of the flood zones vulnerable population) whilst Lewisham has the least at 6,848 (or

6.34% of the flood zone population).

Similarly, Newham also has the largest amount of 0-7 year olds within the flood zone at 23,285 (or 33.59% of the 0-7

year old flood zone population) whilst Lewisham has the least amount of 0-7 year olds with 4,451 (or 6.42% of the 0-7

year old flood zone population).

Southwark has the largest amount of 65+ year olds within the flood zone at 14,214 (or 36.80% of the 65+ year old flood

zone population) whilst Lewisham has the least amount of 65+ year olds with 2,397 (or 6.20% of all 65+ year old flood

zone population).

No results for 0-7 or 65+ year olds for the Boroughs of Barking & Dagenham, Bexley, City of London, Hackney, Haringey,

Lambeth, Redbridge, Waltham Forest or Westminster were available due to being provided with administrative

boundary data but no population statistics data.

Area was lost by clipping administrative boundaries so that the number of people within administrative areas on the

perimeter of the flood zone was distorted and therefore shows a larger number of people within a smaller area.

However before the administrative boundaries were clipped an area that was larger than the flood zone was shown as

“in the flood zone”. Unfortunately both ways cannot be used unless there was some way of working out exactly how

many people were in the clip

Figure 14 – Statistics for the vulnerable 0-7 (left) & 65+ (right) year old age groups within the flood zone

Greenwich Total of 16,406 people classified as vulnerable. Of these there are;

10,940 0-7 year olds at risk

5,466 65+ year olds at risk

Contains 15.20% of the study areas vulnerable population and;

15.78% of the 0-7 year olds at risk

14.15% of the 65+ year olds at risk -

Lewisham Total of 6,848 people classified as vulnerable. Of these there are;


2,397 65+ year olds at risk Contains 6.34% of the study areas vulnerable population and;


6.20% of the 65+ year olds at risk –

Newham Total of 35,113 people classified as vulnerable. Of these there are;


11,828 65+ year olds at risk Contains 32.53% of the study areas vulnerable population and;


30.62% of the 65+ year olds at risk

Southwark Total of 34,257 people classified as vulnerable. Of these there are;






Tower Hamlets Total of 15,313 people classified as vulnerable. Of these there are;






Figure 15 – Statistics tables displaying vulnerable population numbers and percentages data for Greenwich, Lewisham,

Newham, Southwark and Tower Hamlets

As can be seen in figure 15 the total number of 0-7 and 65+ year olds within the flood zone stands at 107,937 people of

which 69,311 (or 64.21%) are 0-7 years old and a further 38,626 (or 35.79%) being 65+ years old.

Objective 3 – Effects on building infrastructure

Figure 16 – Map displaying building density, per square km, within the 0-6m Inundation or “Hazard” Zone of the River

Thames in London, UK (2011 census data)

Figure 17 – Statistics map of building centroid map

Figure 16 shows areas of particularly high building density in the boroughs of Newham and Southwark which gradually

fade into the less dense boroughs of Lewisham, Tower Hamlets and Greenwich. Fading also occurs towards the areas of

“no data” immediately north and south of the main river, running through the flood zones entirety from east to west.

This has the potential to skew the accuracy of the final map (figure 16).

Figures 16 and 17 show a total of 179,902 buildings at risk within the 91.43km2 flood zone, an average of 1,968 buildings

per kilometer radius across the entire flood zone. Buildings of note within this flood zone include the O2 Arena in

Greenwich, Stratford Centre in Newham, the Royal London Hospital in Tower Hamlets and Southwark Cathedral not to

mention vital infrastructure as well.

DISCUSSION & CONCLUSIONS

Objective 1 - Flood Zone Coverage

From the results and figures 5 and 15 it can be inferred that, of the 14 Boroughs identified as being within a 0-6m

“hazard” or inundation zone, the Borough of Newham is at the highest risk of becoming inundated as this is where the

largest amount of terrain, within the inundation zone of 0-6m, occurs. Comparatively, Haringey is at the lowest risk of

inundation as this is where the least amount of terrain, within 0-6m, occurs.

By splitting the Boroughs in to arbitrary groupings, based on percentages of total flood zone inundated, of;

Those above 10%

Those between 1-9%

Those below 1%

It can be attained that Newham, Southwark, Barking & Dagenham and Greenwich are at the highest risk of inundation.

Bexley, Lambeth, Lewisham, and Tower Hamlets are at moderate risk of inundation and City of London, Hackney,

Haringey, Redbridge, Waltham Forest and Westminster are at low risk of inundation.

Use of the DTM over the DSM isn’t perfect. The DTM uses “lie of the land” and this affects where the water will flow and

pool (low lying topography, valleys, etc). However use of the DSM will include buildings and other objects that may

divert the flow of water. This is more realistic than use of the DTM if it is assumed that these objects will definitely

impede the flow of water to such a point where it will not flow into and through them and they prevent other areas

from flooding. However the effects of water on the buildings structures and the stability of other objects as identified in

the DSM raster can potentially damage them to a point where they no longer prevent the flow of water and they flood

and allow other areas to flood. Therefore it is “safer” to assume that all areas within the 0-6m elevation will flood and

thus is more prevalent to use the DTM.

Objective 2 – Vulnerable population at risk

From figures 12 and 15 it appears that more 0-7 year olds are at risk to the north east and east of the flood zone in

Newham and Greenwich than the south and south west towards Tower Hamlets, Southwark and Lewisham. This is

where larger areas of “high” population occur however there are small patches of “higher” population amongst the

Tower Hamlets, Southwark and Lewisham regions as well. In addition to this, the occurrence of these “higher”

population regions appears to be clustered where they occur.

For the 65+ year olds (figure 13) the population at risk seems to be a lot more evenly spread, even though clustering of

higher populations still occurs, just not as densely. Having said this it would appear that Tower Hamlets, Southwark and

Lewisham rather than Greenwich and Newham contains a higher proportion of the higher populations, the opposite to

what occurs for the 0-7 year olds.

From this it can be inferred that Newham and Greenwich, with small pockets of Tower Hamlets, Southwark and

Lewisham are higher risk areas for 0-7 year olds with Tower Hamlets, Southwark and Lewisham a higher risk area for 65+

year olds.

However these interpretations can be skewed by the size of each respective administrative boundary. For example a

large administrative boundary may contain similar numbers of 0-7 or 65+ year olds at risk as a smaller one, and it may be

easy to interpret this as the larger administrative boundary being more at risk than the smaller one due the respective

areas covered by each one. Bearing this in mind the smaller administration boundaries seem to appear in the

Southwark, Lewisham and Tower Hamlets regions when compared to Newham and Greenwich.

It is also noted that vulnerable populations did not include those with physical, medical or any other kind of impairment

which leaves them unable to care for themselves in the way that those with no impairment would do.

Objective 3 - Effects on building infrastructure

From a building infrastructure perspective, Newham and Southwark could be described as being at higher risk to the

inundation than Lewisham, Tower Hamlets and Greenwich as this is where highest building densities occur (figure 16).

From this it could inferred that there is a higher chance of important infrastructure such as emergency services,

transport and communication networks, sewage, water and electricity networks, etc occurring within these regions.

Therefore there is more potential for disruption, not only by destruction of infrastructure in these regions, but also

through ongoing dangers and costs caused by the destabilisation of these buildings and infrastructure. They may need to

be structurally surveyed and either repaired or replaced, as well as the loss of income through not being open or in use.

Other work

The flood zone of the hazard map produced for objective one appears to compare favorably in terms of the areal extent

of the Boroughs covered. This is without site of the data used to create the map in figure 18 by the Environment Agency

and just a visual comparison of the areas north and south of the river.

Figure 18 – Environment Agency flood map of the River Thames in London, UK showing comparable study area

(maps.environment-agency.gov.uk, last accessed 21st February 2016)

Fortunately, given even the extreme amount of a 6m inundation, the elevation of terrain around the river Thames is

such that it restricts the flood zone to relatively narrow, 3-4km, zone, either side of the main river and its tributaries.

Importantly this restricts the population at risk from such an event and also lessens the potential impact on

infrastructure which helps not only London operate as efficiently as it does but the rest of the country as well. This is due

to being capital of the UK, with knock on effects possibly even reaching Europe as well with London being a large

economic player as part of the European Union.

Flood inundation modelling has the power to predict what might happen and where it might happen, given the proper

data is at hand. It enables people to plan for extreme events and form policies such as those outlined by the London

Assembly (London Assembly, 2002) designed to protect vulnerable populations and infrastructure at risk.

The next step would be to model the inundation in four dimensions, over a time period, to visualise “where the flooding

comes from?”, “where does the water go?” and utilise water flow rates, etc. Modelling could also be done in three

dimensions so that depth could be considered and the effects on subterranean infrastructure, soil, bedrock, etc be

measured.

REFERENCING

1. Environment Agency. (2016). Flood Map for Planning (Rivers and Sea). Available: http://maps.environment-

agency.gov.uk/wiyby/wiybyController?x=531500.0&y=181500.0&topic=floodmap&ep=map&scale=5&location=L

ondon,%20City%20of%20London&lang=_e&layerGroups=2,&distance=&textonly=off#x=54. Last accessed 21

February 2016.

2. London Assembly. (2002). Flooding in London - A London Assembly Scrutiny Report November 2002.

3. Mason, D. C., Schumann, G., Bates P. D. (year unknown). Data utilisation in flood inundation modelling

4. Parmenter, B. (2011). Cartography Tips

5. Unknown Author (??). Hazards, Vulnerability and Disaster Risk. Jones & Bartlett Learning LLC Available: http://samples.jbpub.com/9780763781552/81552_CH02_FINAL.pdf. Last accessed 21st February 2016.

LIST OF FIGURES

1. DSM (left) and DTM (right) raster elevation showing high (red) to low (green) elevations with areas of no data

(white) visible in critical areas near the river and its tributaries.

2. The Model Builder design used to process and complete objective 1 - ascertain a flood inundation hazard zone

caused by a 6m rise in flood waters.

3. Histogram displaying natural breaks classification for 0-7 year olds within the flood zone

4. Histogram displaying natural breaks classification for 65+ year olds within the flood zone

5. Map displaying the Boroughs within a 0-6m Inundation or “Hazard” Zone of the River Thames in London, UK

(2011 census data)

6. Area statistics of Administrative Boundaries within the Flood Zone

7. Area statistics of the Administrative Boundaries over entire study area

8. Flood Zone statistics for the Boroughs of Barking & Dagenham, Bexley, City of London and Greenwich

9. Flood Zone statistics for the Boroughs of Hackney, Haringey, Lambeth and Lewisham

10. Flood Zone statistics for the Boroughs of Newham, Redbridge, Southwark and Tower Hamlets

11. Flood Zone statistics for the Boroughs of Waltham Forest and Westminster

12. Map displaying the number of 0-7 year olds, per administrative area, within a 0-6m Inundation or “Hazard” Zone

of the River Thames in London, UK (2011 census data)

13. Map displaying the number of 65+ year olds, per administrative area, within a 0-6m Inundation or “Hazard”


14. Statistics for the vulnerable 0-7 (left) & 65+ (right) year old age groups within the flood zone

15. Statistics tables displaying vulnerable population numbers and percentages data for Greenwich, Lewisham,

Newham, Southwark and Tower Hamlets

16. Map displaying building density, per square km, within the 0-6m Inundation or “Hazard” Zone of the River

Thames in London, UK (2011 census data)

17. Statistics map of building centroid map

18. Environment Agency flood map of the River Thames in London, UK showing comparable study area

(maps.environment-agency.gov.uk, last accessed 21st February 2016)

thames inundation report

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