This document summarizes a student's research project analyzing coastal flooding risks in the Solent and Humber Estuary regions of England under different sea level rise scenarios. The student used GIS analysis with digital elevation models to map flood inundation extents and impacts on property, population, and land cover. High resolution LIDAR data improved results for Portsmouth over lower resolution ASTER data. The simplified "bathtub" flooding model produced unrealistic results for Hull due to connectivity issues. The analysis found increasing damages with higher flood depths in Portsmouth, highlighting risks of unprotected coastal cities from sea level rise.

1. Introduction Research Design & Methodology Results
Conclusions
References
Aims & Objectives
GIS Analysis of Coastal Flood Events: A Case Study Approach
Programme: BSc Geography
Name: Cory Williams
Student number: 793055
Supervisor: Prof. Adrian Luckman
Discussion
 Low lying coastal regions, such as the
South and East coast of England are being
increasingly exposed to coastal flooding
as a result of climate change (Wahl et al.,
2011).
 It is crucial that low probability future
flooding scenarios are considered due to
the huge potential impacts.
 UKCP09 created the H++ scenario which
is a high end estimate of the effect of
climate change on sea level rise (1.9m)
and storm surges (increased height of
0.7m) by 2100.
 Two case studies chosen: The
Solent and Humber Estuary.
 Portsmouth and Hull were
chosen for more in-depth
analysis as following London,
these two cities are considered
most at risk to coastal flooding
in the UK (RIBA & ICE, 2009).
Despite this, little
literature focuses on them,
presenting a research gap.
Figure 1: Case study
locations. Humber
Estuary (orange) and
the Solent (purple).
Research Aim:
 To determine the potential impacts of
coastal flooding scenarios for the Solent
and Humber Estuary, using Portsmouth
and Hull as focussed case studies.
Research Objectives:
For each study location and flood scenario:
 Calculate the inundated area.
 Analyse the impact on property and
estimate associated insurance claims.
 Calculate number of people affected.
 Calculate the area of different inundated
land cover types.
 Extreme coastal flooding (ECF) is made
up of three main constituents: sea level
(SL), tides (T) and storm surges (SS)
(NTSLF, 2016).
ECF = SL + T + SS
 For each region, the main constituents
were combined to create five scenarios
with increasing severity.
 SL: contribution begins at mean sea level,
increasing with sea level rise up to 1.9m
(H++ scenario of UKCP09).
 T: Region specific high astronomical tide
values were converted to meters above
mean sea level.
 SS: Region specific skew surge values
calculated, providing isolated surge water
heights.
 GIS analysis carried out at regional scale
using ASTER 30m DEM. Using an
‘adapted bathtub’ model, the raster
calculator identified cells less than or
equal to flood water depth as inundated.
The cells not hydrologically connected to
coastline were removed.
 Portsmouth and Hull identified as
hotspots. In-depth analysis using a high
resolution 2m LIDAR DEM was executed.
Figure 2 outlines the layers used in this
analysis.
Figure 2: Summary of layers used to determine impacts for
Portsmouth and Hull.
Figure 3: Five coastal flooding scenarios for Portsmouth.
Figure 4: Land cover classes and postcode centroids for
scenario 5 H++ in Portsmouth.
Figure 5: The difference in extent of flooding between
water depths of 4.09m and 4.59m in Hull, displaying poor
model results.
 Resolution of DEM is a key factor.
ASTER DEM vastly underestimated flood
extent compared with LIDAR DEM.
 Adapted bathtub model was very
simplistic. Ensuring hydrological
connectivity produced unrealistic results
for Hull. Conversely, it contributed greatly
in the Portsmouth analysis.
 Economic analysis of Portsmouth is in
accordance with Brown et al. (2011) in a
study of the EU as similar increases in
flood water depth produce comparable
increases in flood damages (multiplication
factor of ~7).
 Lack of consideration for flood defences
is not necessarily a limitation as their
future economic viability is questionable
due to continued damage.
 The Portsmouth analysis produced
reasonable results, clearly displaying the
potential impacts associated with each
scenario.
 The bathtub method used produced
unrealistic results for the Hull case study
as a result of known disadvantages
associated with the simplistic model.
 High resolution DEM’s are necessary to
increase the accuracy of flood modelling.
 Brown S, Nicholls RJ, Vafeidis A, Hinkel J, and Watkiss P (2011). The Impacts and
Economic Costs of Sea-Level Rise in Europe and the Costs and Benefits of
Adaptation. Summary of Results from the EC RTD ClimateCost Project. In Watkiss,
P (Editor), 2011. The ClimateCost Project. Final Report. Volume 1: Europe.
Published by the Stockholm Environment Institute, Sweden, 2011.
 Lowe, J. A., Howard, T. P., Pardaens, A., Tinker, J., Holt, J., Wakelin, S.,Milne, G.,
Leake, J., Wol , J., Horsburgh, K., Reeder, T., Jenkins, G., Ridley, J.,Dye, S.,
Bradley, S. (2009), UK Climate Projections science report: Marine and coastal
projections. Met Office Hadley Centre, Exeter, UK.
 Ntslf.org, (2016). Chart datum & ordnance datum | National Tidal and Sea Level
Facility. [online] Available at: http://www.ntslf.org/tides/datum [Accessed 2 Feb.
2016].
 Wahl, T., Jensen, J., Frank, T. & Haigh, I. (2011). Improved estimates of mean sea
level changes in the German Bight over the last 166 years. Ocean Dynamics, 61, 701-
715.
 RIBA & ICE. (2009). Facing up to rising sea-levels: retreat? defend? attack? The
future of our coastal and estuarine cities. Royal Institute for British Architects,
London, UK & Institute of Civil Engineers.