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Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
Report prepared for the Inter‐Amercian Development Bank
Final
November 2019
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Executive Summary
This report provides the results of the Disaster Risk and Climate Vulnerability Assessment (DRCVA) that has
been undertaken for the capital city of Guyana – Georgetown and its surrounding area. This study is one of a
series of baseline studies for Georgetown, forming part of the Inter‐American Development Bank’s (IDB)
Emerging and Sustainable Cities Initiative. The studies have been developed under the IDB’s technical
cooperation agreement with Guyana’s Central Housing and Planning Authority, titled “Climate Resilience
Support for the Adequate Housing and Urban Accessibility Program in Georgetown, Guyana” (GY‐T1137).
The DRCVA takes account of climate and land use change as well as alternative adaptation approaches. The
key findings from this study and the recommended next steps are summarized below.
Key messages
● Neighbourhood Democratic Councils (NDC) in Regions 3 and 4, the Regional Democratic Council (RDC) for Region 3 and the Municipal Council for Georgetown all identified coastal and inland flooding as the highest priority hazards for DRCVA efforts.
● Today, the expected annual damage from flooding is around GYD 1.3 billion (USD 6 million) across the wider Georgetown area with a further GYD 0.625 billion (USD 3 million) of disruption and repair to critical infrastructure; this equates to approximately 1% of economic activity. The expected annual (average) number of people exposed to flooding exceeding 0.5m is around 10,200. Forty‐six critical infrastructure sites (including hospitals, bus station, health clinics, fire stations, hospital, military barracks, police station, school and both airports) experience flooding during major storms (exceeding a 1in100 year return period).
● Assuming a business as usual adaptation approach, the expected annual damage from flooding is projected to reach between USD 10‐12 million by 2040s in response to climate change and projected urban growth. The expected annual number of people exposed to flooding is also likely to increase significantly. The “Business as Usual” approach therefore is not a viable DRCVA option for Georgetown and a more ambitious adaptation strategy is required.
● Clear and decisive action now could dramatically reduce economic damages from flooding and improve Georgetown’s resilience. This will be most effective if it includes:
spatial planning and building regulation that embrace flood risk management related issues
realign the coast and maintain green space where possible to make space for a natural response to sea level rise and surface water by adopting a ‘living with water’ approach.
selectively implement hard measures to hold the line by constructing and rehabilitation of hard sea and flood defences such as sea walls and embankments where necessary.
promote a ‘naturally resilient coastline’ with soft measures (ecosystem‐based adaptation) to restore and expand mangroves and sediment management.
strategic management of land drainage, through improved channel management and rehabilitation/replacement of control structure and pumps.
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Given a feasible or smart adaptation approach future risks are much lower (Figure A), with a projected 2040s
Expected Annual Damage (EAD) of USD 5.5‐6.5 million and USD 3‐4 million respectively. Figure A
demonstrates the changing flood risks under a business as usual, feasible and smart adaptation scenarios
through the 2030s and 2050s.
Figure A Future flood risks: business as usual, feasible and smart adaptation scenarios
Source: Sayers and Partners (2019)
Next steps beyond this project
Successful adaptation will require significant resources (both financial and human). To take forward the
findings of this study, the high‐level analysis presented here will need to be translated into actionable (and
investable) plans. In particular, the development of a strategic urban and coastal management policy and
action plan is recommended. This project would aim to map and model coastal processes to enable better
protection of the coastal zone and provide the integrated framework of coastal policy planning with
supporting detailed investment plans. There is overlapping legislation which has led to coastal and urban
management being shared among several institutions such as MoPI, EPA, GFC, NAREI and GL&SC. The
integrated plan should strengthen participation among these major stakeholders and sectors, and provide an
agreed strategy plan which, if developed well, should guide decision making, promote awareness of the
issues and facilitate the execution of programs to manage coastal resources and reduce vulnerability climate
change.
The project should address issues relating to policy development, analysis and planning, inter‐agency
coordination, public education and awareness‐building, environmental control and compliance, monitoring
and measurement, and information management alongside a programme of investable infrastructure
improvement actions. Secondly, the development of an improved forecasting and early warning system is
proposed. This has been suggested by stakeholders throughout this study. Although not the focus here it is
recommended that future attention is also directed towards providing timely and reliable information on
forecast and projected flood risks to support early action.
0.0
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Low High Low High Low High Low High Low High Low High
2030s 2050s 2030s 2050s 2030s 2050s
PresentDay
Business as Unsual Feasible Smart
Expected Annual Dam
ages (USD
, m)
Coastal Rainfall
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Authorship and acknowledgements
Team members
IDB: Patricio Zambrano‐Barragan, team leader (CSD/HUD); Edgar Lemus, Derise Williams (CCB/CGY); Merle
Reyes (WSA/CGY); Tanja Lieuw (CCS/CGY).
Consultants
Vivid Economics (consultant lead, and lead CE3): Charlie Dixon, Neeraj Baruah with in‐country support from
Haimwant Persaud
Sayers and Partners (lead for CE2 – this report): Paul Sayers, Jonathan McCue, Harvey Rodda, Jack Dearman,
Giorgia Sacco with in‐country support from Ranata Robertson.
Aether: (lead for CE1) Melanie Hobson, Ryan Glancy
Guyana stakeholders
Government authorities: Central Housing and Planning Authority, Solid Waste Management Dept – Ministry
of Communities; Guyana Lands and Survey Commission; Agricultural Sector Development Unit and Hydro‐
meteorological Service – Ministry of Agriculture; Civil Defence Commission; Ministry of Natural Resources;
Office of Climate Change and Environmental Protection Agency – Ministry of the Presidency; Guyana
Mangrove Restoration Project; Sea and River Defence Unit, Work Services Group and Transport and
Harbours Dept. – Ministry of Public Infrastructure; National Drainage and Irrigation Authority; Guyana
Bureau of Statistics; Guyana Power and Light; Guyana Water Inc.; Guyana Maritime Administration; Faculty
of Environmental and Earth Sciences – University of Guyana; National Agriculture Research and Extension
Institute.
Academic partners
Faculty of Environmental and Earth Sciences – University of Guyana; National Agriculture Research and
Extension Institute.
Citation: Sayers and Partners (2019). Disaster risk and climate change vulnerability assessment . A report for
the Inter‐American Development Bank produced in association with Vivid Economics and Aether.
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Acronyms
CDC ‐ Civil Defence Commission
CH&PA ‐ Central Housing and Planning Authority
DRCVA ‐ Disaster Risk and Climate Change Vulnerability Assessment
DTM – Digital Terrain Model
EAD ‐ Expected Annual Damage
EPA – Environmental Protection Agency
ESCI ‐ Emerging and Sustainable Cities Initiative.
GFC – Guyana Forestry Commission
GL&SC – Guyana Lands and Surveys Commission
GSDS ‐ Guyana State Development Strategy
IDB ‐ Inter‐American Development Bank
JICA ‐ Japan International Cooperation Agency
JRC – Joint Research Centre (European Commission)
MoPI – Ministry of Public Infrastructure
NAREI ‐ The National Agricultural Research & Extension Institute
NDC ‐ Neighbourhood Democratic Council
RDC – Regional Democratic Council
SPL – Sayers and Partners LLP
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Glossary
Adaptation: A continuous process of adjustment in natural, human or infrastructure systems in response to
actual or expected future change with the aim of moderating harm or exploiting beneficial opportunities.
Community resilience‐building: This is a community‐driven process, rich with information, experience, and
dialogue, where participants identify top hazards, current challenges, strengths, and priority actions to
improve community resilience to all hazards today, and in the future.
Climate change: A change in the statistical properties of the climate system when considered over long
periods of time (including mean and variance).
Ecosystem‐based Adaptation (EbA): EbA is the use of biodiversity and ecosystem services as part of an
overall adaptation strategy to reduce the adverse effects of climate change (CBD 2009) and the role of
sustainable management, conservation and restoration of natural systems.
Expected Annual (economic) Damage (EAD): An integration of the relationship between annual probability of
occurrence of a flood (taking account of the storm and system states) and the associated consequence.
Exposure: Any component of a physical location, population or habitat that may suffer harm (loss of well‐
being) when subject to a hazard.
Event risk: The damage associated with a particular (storm) event
Hazard (and threats): Any situation with the potential to cause harm. A hazard maybe a function of the
environment (a storm surge) or arise directly from a human activity (a cyber threat).
Nature ‐based solutions (‘soft’ engineering). Actions to protect, sustainably manage, and restore natural or
modified ecosystems, that address societal challenges effectively and adaptively, simultaneously providing
human well‐being and biodiversity benefits.
Resilience: The capacity of social, economic and environmental systems to cope with a hazardous event or
trend or disturbance, responding or reorganizing in ways that maintain their essential function, identity and
structure, while also maintaining the capacity for adaptation, learning and transformation.
Risk: Typically defined as combination of the chance that a given hazard occurs and the associated
consequences (that in turn reflects the vulnerability of those exposed to the hazard, either directly or
indirectly).
Risk Assessment: The process of determining the qualitative or quantitative value of risk. It determines the
nature and extent of the risk by considering the hazard, vulnerability as well as capacities to cope
(resilience).
Vulnerability: The degree of harm (e.g. economic loss) when a receptor (e.g. a house, person, business etc.)
is exposed to given severity of hazard (e.g. a flood depth of 1m). Vulnerability is the function of several
factors including physical, social/cultural, economic, and ecological which increase or reduce susceptibility or
resilience to the impact of a hazard.
Vulnerability Assessment: This activity seeks to examine the individual factors of vulnerability for a place or
population. It attempts to identify the features which are susceptible to damage as well as those which
provide some protection (resilience) from such negative effects. It may be used to prioritize mitigative
interventions as well as recovery, response and developmental planning.
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Contents
Authorship and acknowledgements .................................................................................................... iii
Acronyms ............................................................................................................................................. iv
Glossary ................................................................................................................................................. v
1 Introduction .......................................................................................................................................... 1 2 Priority climate related hazards and risks ............................................................................................ 4 3 Present day flood risk ........................................................................................................................... 8 4 Future flood risk .................................................................................................................................. 33 5 Adaptation cost ................................................................................................................................... 45 6 Conclusions ......................................................................................................................................... 49
Appendices .......................................................................................................................................... 51
List of tables
Table 1 Storm scenarios: coast and rainfall ..................................................................................................... 14
Table 2 Drainage capacity in relation to land use ............................................................................................... 15
Table 3 Current shares (2017) by land use class ............................................................................................. 20
Table 4 Direct economic damage functions (flood depth) ............................................................................. 23
Table 5 Replacement cost of critical infrastructure ........................................................................................ 24
Table 4 Adaptation measures included in each alternative strategy ............................................................. 34
Table 5 Standards of service – Coastal defences and drainage infrastructure .............................................. 35
Table 6 Conditional failure probabilities ‐ Coastal defences and drainage infrastructure ............................. 35
Table 9 Proposed SLR scenarios ...................................................................................................................... 36
Table 10 Proposed increases in extreme rainfall scenarios .............................................................................. 36
List of figures
Figure 1 Georgetown lies on the Atlantic coast of Guyana .................................................................................. 1
Figure 2 Study focuses on Georgetown (the capital of Guyana) and surrounding area ................................... 4
Figure 3 Structured participatory approach to Identifying priority hazards ...................................................... 5
Figure 4 Past flood events in Guyana recorded since 1972 .................................................................................. 6
Figure 5 Basic framework of assessment ........................................................................................................... 8
Figure 6 Final DTM including highly resolved linear flood infrastructure. ........................................................... 9
Figure 7 Extreme value tidal levels ................................................................................................................... 10
Figure 8 Extreme Rainfall .................................................................................................................................. 11
Figure 9 Coastal protection is typically provided by conventional 'hard' seawalls and 'soft' mangrove
stands .................................................................................................................................................. 12
Figure 10 Coastal defence condition survey (ciria 2011) .................................................................................... 12
Figure 11 A view over the Demerara estuary looking east towards Georgetown ............................................. 13
Figure 12 A network of channels, pumps and sluices act to drain the flat coastal plains .................................. 13
Figure 13 The drainage channel network represented in the hazard analysis ................................................... 17
Figure 14 Present day ‐ Rainfall induced flood hazards ...................................................................................... 18
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Figure 15 Present day ‐ Coastal induced flood hazards ...................................................................................... 19
Figure 16 Present day (2017) land use map of study area ................................................................................. 20
Figure 17 Current population distribution across the study area ...................................................................... 21
Figure 18 Critical infrastructure within the study area: Mapped ....................................................................... 22
Figure 19 Critical infrastructure within the study area: By count ...................................................................... 22
Figure 20 Present day‐ Expected Annual Damage (spatial distribution) ............................................................ 25
Figure 21 Present day flood risk by sector and flood hazard – Economic risk ................................................... 27
Figure 22 Risk profile: Present day relationship between probability and economic damage .......................... 27
Figure 23 Event risk – Present day 1 in 100‐year return period storm .............................................................. 28
Figure 24 Present day ‐ People at risk – Expected annual number of people exposed to flooding .................. 29
Figure 25 Present day ‐ People at risk – Example map 1in100 return period rainfall ....................................... 30
Figure 26 Present day flood risk by land use and flood hazard – Critical infrastructure risk ............................ 31
Figure 27 Present day‐ Critical infrastructure at risk (spatial distribution ‐ 1in100 return period) ................... 31
Figure 28 Portfolio of flood management measures ......................................................................................... 33
Figure 29 Projected development hotspots under BAU, smart and feasible scenarios .................................... 37
Figure 30 Present and future land use maps of Georgetown under BAU, smart and feasible scenarios .......... 37
Figure 31 Relative changes in economic risk by sector: Present day ‐ 2050s (Baseline adaptation) ................ 39
Figure 32 Changes in economiuc risk by flood hazard: Present day – 2050s (A comparsion of altnernative
adpatation strategies) ......................................................................................................................... 39
Figure 33 Expected Annual Damage ‐ Spatial distribution ................................................................................. 40
Figure 34 Expected Annual Damages given alternative adaptations – By flood source .................................... 41
Figure 35 Expected Annual Damages given alternative adaptations – By sector .............................................. 42
Figure 36 Expected annual number of people exposed to flooding by 2050s (High climate, business as
usual future) ........................................................................................................................................ 43
Figure 37 Expected annual number of people exposed to flooding greater than 0.5m by 2050s .................... 43
Figure 38 Expected annual impact of physical damage and disruption to critical infrastructure (mUSD) ....... 44
Figure 38 Projected business as usual spending on core adaptation measures from 2020‐2040 .................... 46
Figure 39 Projected spending from 2020 to 2040 by type of adaptation measure and adaptation scenario .. 47
List of boxes
Box 1 2005 flood event ................................................................................................................................... 6
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1 Introduction
Georgetown lies on the Atlantic coast of Guyana at the mouth of the Demerara River (Figure 1). Georgetown
is the capital and largest city in Guyana and, due to its location, is subject to a range of climate‐related hazards,
including coastal storms and rainfall. Since the major floods of 2005, significant investment has been targeted
towards improving sea and river defences as well as upgrading the extensive network of canals and drainage
infrastructure; but a significant adaptation deficit persists. Without further action, flood events will continue
to undermine economic development and as sea levels rise and rainfall patterns change, risks are likely to
increase. This study therefore focuses on developing an understanding of disaster and climate change risks
across the greater Georgetown area.
In recognition of this, the Government of Guyana (GOG) has sought to incorporate climate change
considerations into its development policies. For example, the Framework of the Green State Development
Strategy (GSDS) and Financing Mechanism in 2017 (Ministry of the Presidency, 2017) sets out ‘Guyana’s Vision
2030’ as:
“A green, inclusive and prosperous Guyana that provides a good quality of life for all its citizens based
on a sound education and social protection, low‐carbon resilient development, green and decent jobs,
economic opportunities, individual equality, justice, and political empowerment. Guyana serves as a
model of sustainable development and environmental security worldwide, demonstrating the
transition to a de‐carbonised and resource efficient economy that values and integrates the multi‐
ethnicity of our country and enhances the quality of life for all Guyanese.”
Appropriately adapting to climate related risks will be prerequisite to achieving this vision. Developing and
investing in natural and built coastal and fluvial infrastructure that responds to climate change will be, in turn,
of the highest priority.
Figure 1 Georgetown lies on the Atlantic coast of Guyana
Source: OCHA, accessed 2019
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About this report
This report is one of a series of baseline studies for Georgetown, forming part of the Inter‐American
Development Bank’s (IDB) Emerging and Sustainable Cities Initiative (ESCI). The studies have been developed
under the IDB’s technical cooperation agreement with the Central Housing and Planning Authority (CH&PA),
“Climate Resilience Support for the Adequate Housing and Urban Accessibility Program in Georgetown,
Guyana” (GY‐T1137). The following three studies were produced for Georgetown:
● Climate Change Mitigation Assessment, to analyse Georgetown’s carbon footprint and help the city identify concrete options to reduce this.
● Disaster Risk and Climate Change Vulnerability Assessment (DRCA), to better understand the risks the city faces from natural hazards, including increasing hazardous risk due to climate change, and facilitate adequate planning to reduce these risks and the city’s vulnerability.
● Urban Growth Study, which assesses the urban footprint of the city and its dynamics under expected future trends, to inform and facilitate successful infrastructure and environmental planning at the city and regional level.
This report focuses on the DRCA. In doing so, two climate projections (a lower and higher projection) are
considered alongside three alternative adaptation scenarios (business as usual, feasible and smart). The
future changes in risk are then assessed for the 2030s and 2050s and the whole life costs of the measures
associated with adaptation estimated.
Objectives
The study objectives are to:
● Identify priority climate related hazards and risks (determined during the study to be coastal storm surge and rainfall induced flooding);
● Provide a strategic, broad‐scale, assessment associated with the priority risks for the present day and 2040s (viewed through the changing risk from 2030s and 2050s) taking account of climate change (Low and high), socio‐economic development (a central projection, Vivid, 2019) and alternative adaptation strategies (baseline, feasible and smart);
● Assess the associated adaptation investment (capital and operating) costs.
Structure of study and report
The report is structured as follows:
● Chapter 2 ‐ Priority climate related hazards: presents the qualitative stakeholder led process of identifying the flood hazards (coastal and rainfall) as the priority hazards to be assessed in more detail.
● Chapter 3 ‐ Present day flood risks: presents the analysis of present‐day hazards (including extreme value analysis of rainfall and tide levels), exposure and vulnerabilities.
● Chapter 4 – Future flood risks: presents the climate change and adaptation assumptions together with an assessment of the potential changes in flood risk by the 2030s and 2050s.
● Chapter 5 – Adaptation costs: presents an assessment of the whole life costs associated with the alternative adaptation scenarios and the supporting evidence.
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● Chapter 6 – Conclusions: presents a brief summary of key findings and recommendations for next steps.
A series of supporting reports have been produced during the study. The detailed analysis provided by these
reports are included in the following appendices:
● Appendix 1 Prioritization of hazards and risk.
● Appendix 2 Creation of a credible understanding of topography (DTM).
● Appendix 3 Extreme value analysis.
● Appendix 4 Defence standards and approach to modelling the inundation scenarios.
● Appendix 5 Long list of adaptation options.
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2 Priority climate related hazards and risks
2.1 Geographical setting
Guyana has a tropical climate and is generally hot and humid, though moderated by northeast trade winds
along its coast. There are two rainy seasons, the first from May to mid‐August, the second from December to
January, that lead to frequent flooding. Although Georgetown does not truly have a dry season with monthly
precipitation throughout the year typically above 60 millimetres. Guyana, however, lies south of the typical
tropical cyclone formation regions that drive hurricanes towards the Caribbean hence coastal flooding is driven
by storm surge.
Guyana’s physical landscape is diverse and vibrant. Inland, Guyana has one of the largest unspoiled rainforests
in South America, some parts of which are almost inaccessible by humans. Guyana’s coastline forms part of a
1,600km‐long coastal system dominated by mangrove forests and a network of mud banks that migrate north
from the mouth of the Amazon River in Brazil to the Orinoco in Venezuela (Anthony et al., 2010). This system
of complex mud banks is highly dynamic and exhibits significant variation on intra and inter year timescales.
This coastal system is increasingly being squeezed by sea level rise and land‐based development, increasing
Guyana’s exposure to coastal flooding and erosion. The coastal risks are not however confined to the
degradation of coastal ecosystems, but also impact social and economic wellbeing. Frequent flooding in the
past has had significant economic consequences.
Georgetown itself is located on Guyana's Atlantic coast on the east bank of Demerara River estuary (Figure 2).
The topography is typical of a coastal delta, flat and low‐lying (in many places lying significantly below high
tide levels). The coastal protection is provided by a combination of built seawalls and natural mangrove forests
complemented by a network of canals and kokers (sluices and pumps first developed by the Dutch) that act to
drain flood waters during heavy rainfall events.
Figure 2 Study focuses on Georgetown (the capital of Guyana) and surrounding area
Note: Urban population density from European Union Global Human Settlement Layer (GHSL). LiDAR data available from the
Ministry of Agriculture for the area spanning in pink.
Source: Vivid Economics and Sayers and Partners
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2.2 Priority hazards
The risks in Regions 3 and 4 (Essequibo Islands West Demerara and Demerara Mahaica) have been
prioritized through a participatory, qualitative, approach based on two workshops and the application of the
Hazard Assessment Matrix tool (a process summarised in Figure 3).
Figure 3 Structured participatory approach to Identifying priority hazards
Source: Sayers and Partners
The assessment identified a total of 22 relevant hazards and threats and enabled information to be
exchanges between attendees involved in two on‐going related studies (funded by European Development
Bank and the Caribbean Development Bank). The workshops were well attended and involved a range of in‐
country experts enabling the available quantitative information on different hazards (both historic and future
given climate change) to be combined with expert insights to develop a robust risk ranking as follows:
1. Pluvial flooding.
2. Coastal/tidal Flooding.
3. River Flooding.
4. Improper Solid Waste Management.
5. Water Pollution.
6. Oil/Chemical Spills.
7. Poor Infrastructure.
8. Tsunamis.
The priorities for further study established through this process (and discussed in detail in the following
chapters) reflect observational evidence that flooding is increasing in both frequency and significance in
Guyana (
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Box 1 2005 flood event
In January 2005, extreme rainfall caused devastating flooding on the coastal lowlands, with many areas
remaining inundated for up to 3 weeks and water levels reaching chest height in many homes. Due to the
inability of the system to drain away the excess water quickly enough, water levels in the EDWC were
significantly above safe operating levels, weakening the dam and leaving it more vulnerable to
overtopping and a potential breach. Fortunately, the dam did not breach but the 2005 flood and other
floods since then have highlighted the vulnerability of the system to catastrophic failure. In summary, in
January 2005 over 1 m of rain fell, nearly 5 times the monthly average, with 65cm in just 5 days. The
extreme rainfall caused widespread flooding which affected almost half of Guyana’s population. Total
damages from the disaster are estimated to have been US$ 465 million or 59% of Guyana’s GDP for 2004.
Source: World Bank, 2013 Managing Flood Risk in Guyana The Conservancy Adaptation Project 2008‐2013
Figure 4).
A full description of the prioritisation process, those involved, and the qualitative scores for each hazard are
presented in Appendix 1.
Box 1 2005 flood event
In January 2005, extreme rainfall caused devastating flooding on the coastal lowlands, with many areas
remaining inundated for up to 3 weeks and water levels reaching chest height in many homes. Due to the
inability of the system to drain away the excess
water quickly enough, water levels in the EDWC
were significantly above safe operating levels,
weakening the dam and leaving it more
vulnerable to overtopping and a potential
breach. Fortunately, the dam did not breach but
the 2005 flood and other floods since then have
highlighted the vulnerability of the system to
catastrophic failure. In summary, in January
2005 over 1 m of rain fell, nearly 5 times the
monthly average, with 65cm in just 5 days. The
extreme rainfall caused widespread flooding
which affected almost half of Guyana’s
population. Total damages from the disaster are
estimated to have been US$ 465 million or 59%
of Guyana’s GDP for 2004.
Source: World Bank, 2013 Managing Flood Risk in Guyana The Conservancy Adaptation Project 2008‐2013
Figure 4 Flood events in Guyana recorded since 1972
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Source: Inventory of the effects of disasters: https://www.desinventar.org/
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3 Present day flood risk
3.1 Introduction
The assessment of flood risk requires the consideration of the three components of risk: hazard – a situation
with the potential to cause harm; exposure – to that hazard; and, vulnerability – the agreed means of valuing
the harm caused (Figure 5). To provide a credible assessment of the hazard a range of storm scenarios and
alternative defence system states (i.e. the conditional state of the Georgetown seawalls – breached or not –
and conveyance channels – flow restricted or not) are used to provide a probabilistic assessment of the flood
risk and an assessment of the Expected Annual Damage (EAD). The following sections elaborate each aspect
of this framework.
Figure 5 Basic framework of assessment
Source: Sayers and Partners, based on Sayers et al, 2014
3.2 Flood hazard
An appropriately reliable assessment of the probability of flooding is a prerequisite to the assessment of risk.
Achieving this relies upon several important inputs as introduced below.
Topography
To produce a suitable Digital Terrain Model (DTM) for this project, several steps were undertaken in ArcGIS
to generate outputs with enhanced accuracy for flood modelling. The approach uses two sources of DTM (i)
a freely available SRTM (Shuttle Radar Topography Mission) – 30m resolution grid and (ii) a high‐resolution
LiDAR (Light Detection and Ranging) covering part of the study area at a 1m horizontal resolution and
resampled here to a 10m grid. To ensure a credible representation of the defence crest levels in the DTM
used for the flood modelling, the location of crests of the EDWC dam and the coastal defences were digitised
from the 1m DTM as a polyline1. The resulting integrated DTM is shown together with example defence
cross‐sections in
Figure 6. A more detailed discussion of the data used, and the associated processing is provided in Appendix
2.
1 Note: The harmonisation of the vertical datums is based on the assumption that Mean Sea Level (today) equates to 15.56mGD (Guyana Datum). The reference GD is taken from the Brass Datum plate on the Lighthouse, set at 17.41mGD. The feature used to set 0mGD is unknown to the authors.
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Figure 6 Final DTM including highly resolved linear flood infrastructure.
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Source: Sayers and Partners
Tidal levels
Astronomical tides in Guyana are diurnal with two high and two low tides each day in Georgetown. The tidal
range averages about 2m with the tidal influence extending a considerable distance inland (as far as 80 km
to 100 km inland along the Demerara River under surge conditions, Daniel 2001). An extreme value analysis
of the annual maxima water level data from Georgetown Tide Gauge (located at the mouth of the Demerara)
using an extreme value Gumbel distribution is presented in Figure 7. A more detailed discussion of the data
and the associated processing is provided in Appendix 3.
Figure 7 Extreme value tidal levels
Note: Top: Annual maxima records from the Georgetown tide gauge. Bottom: Extreme value distribution
Source: Sayers and Partners
Coastal wind‐waves
The Guyana coastline is characterized by relatively mild meteorological and hydrodynamic conditions; winds
are generally from between northeast and east (Trade Winds) and vary between 5 and 10 m/s (Van Ledden
et al., 2009). The wave energy incident to the shoreline is limited by the large continental shelf and network
of mud banks. Wave overtopping alone typically results in more localized flooding (in comparison to a breach
or major surge event) but does act to increase the chance of breach (through scour and structural damage to
the front, crest or rear face of the coastal embankment or seawall).
Rainfall
The annual meridional migration of the Intertropical Convergence Zone (ITCZ) northward generally brings
heavy rainfall between mid‐April and the end of July, with a major peak rainfall in June. During the
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southward migration of the ITCZ, a second wet season is observed between mid‐November and the end of
January with peak rainfall in December. Large interannual variability in rainfall is driven by El Nino (typically
higher rainfall) /La Nina (typically lower rainfall) cycles; although this cycle is not a ‘perfect’ indicator of the
likely seasonal rainfall, for example, during the mild El Nino year 2004–2005, rainfall was 49% above normal
(Rama Rao et al., 2012).
In the absence of well‐conditioned observed rainfall data, the daily rainfall depth estimates from the CHIRPS
(Climate Hazards Group InfraRed Precipitation with Station data) dataset (covering the period 1981‐2018) is
used to support the extreme value analysis. The annual maxima values from the CHIRPS dataset for
Georgetown together with the Gumbel extreme value analysis are presented in Figure 8. A more detailed
discussion of the data and the associated processing is provided in Appendix 3.
Figure 8 Extreme Rainfall
Note: Top: Annual maxima for Georgetown based on CHIRPS. Bottom: Extreme value distribution
Source: Sayers and Partners
Existing defence and drainage standards and condition
Flood protection is provided by a combination of a seawalls, mangrove forests, wharf walls and a network of
drainage channels, pumps and sluices. The standard of protection typically provided varies from around
1in100 year return on the open coast, to 1in50 year return on the tidal Demerara and around 1in25 year
drainage standard in urban centre of Georgetown (less elsewhere). These protection systems are
introduced in turn below with a more detailed discussion provided in Appendix 4.
Open coast: Protection from coastal flooding is provided by a combination of conventional sea defences
(with a mix of concrete and rip‐rap revetments) fronted by a muddy foreshore and mangrove forest (
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Figure 9). Sediment control structures (groynes) and the mangrove forests help to stabilise the morphology
and attenuate wave energy. The systems of mud banks are also crucial elements of the coastal defence
system. The latest Sea Defence Condition Survey (Work Services Group 2016) highlights some sections of
defence in ‘critical’ or ‘poor’ condition reflecting the difficulties in securing investment to appropriately
maintain the existing defences (Figure 10).
Figure 9 Coastal protection is typically provided by conventional 'hard' seawalls and 'soft' mangrove stands
Left: The new sea defence being constructed at Cornelia Ida (Region 3). Right: The fronting mangrove stands backed by
old sea walls (Region 4).
Source: Jonathan McCue, 2019
Figure 10 Coastal defence condition survey (ciria 2011)
Source: Work Services Group Sea Defence Structures Survey Map (2011)
Tidal reaches of the Demerara River: On the east bank the commercial wharves provide a de facto defence
line (
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Figure 11). On the west bank mangrove forests and natural banks continue to provide the dominate
boundary together with some localised protection structures.
Figure 11 A view over the Demerara River mouth looking east towards Georgetown
Source: Jonathan McCue
Land drainage: The drainage around the coastal plain of Guyana forms a series of larger primary channels
fed by secondary channels (often the relics of agricultural drainage) on a regular rectangular grid system
(Pelling, 1999). This network of channels, pumps and sluices acts to drain flood waters to the sea. In many
cases the drainage capacity of this network is unable to accommodate daily rainfall events that exceed a 25‐
year return period (i.e. a daily rainfall depth of 275 mm). The drainage capacity is not however standard
across the study area. This variation reflects several factors, including both the past investment in drainage
infrastructure and the effort devoted to the on‐going maintenance of that infrastructure (including debris
clearance and conveyance management).
Figure 12 A network of channels, pumps and sluices act to drain the flat coastal plains
Far left: Sluice (Cornelia Ida, Region 3), Left: Ogle sluice Right: coast parallel channel (Stewartville, Region 3), Georgetown, Far right:
Heavy vegetation channel near Stabroek Market
Source: Jonathan McCue and Paul Sayers
The Conservancy Dam: The EDWC dam (located to the east of the Demerara) is designed to intercept and
retain flows from the area to the south of the coastal plain. The performance of the dam is outside the
scope of this study but is included within the DTM (with a crest level of between 18 and 18.5m GD).
Combined storm scenarios and system states
Based on the extreme value analysis a set of 13 rainfall and coastal flood scenarios are used to represent the
storm scenarios (Table 1). To reflect the possibility of a significant rainfall event coinciding with a high tide
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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event, several joint events are included. In the absence of well‐conditioned observed data, a formal joint
probability analysis has not been possible but is recommended for further study.
Table 1 Storm scenarios: coast and rainfall
Coastal extremes Rainfall extremes
Joint return
period (years)
Return period
(years)
Tidal level
Demerara
(m GD)
Tidal Level
Open
Coast
(m GD)
Return
period
(years)
Rainfall
(mm/day)
2 17.08 17.28 2
10 17.34 17.54 10
50 17.6 17.8 50
100 17.72 17.92 100
200* 17.98 18.18 200
Low tide 14.79 14.79 2 130.8 2
Low tide 14.79 14.79 10 222.5 10
Low tide 14.79 14.79 25 274.8 25
Low tide 14.79 14.79 100 353.8 100
Low tide 14.79 14.79 200 393.3 200
2 17.08 17.28 2 130.8 2
100 17.72 17.92 2 353.8 150
2 17.08 17.28 100 130.8 150
Source: Sayers and Partners and Vivid Economics
To provide a whole system probabilistic framing of the hazard analysis, each storm scenario is associated
with the following conditional system states:
Coastal defence system states: In representing the coastal defences, two defence states are considered:
● No breach – in this case it is assumed that the backshore defences remain intact and provide protection up to their notional design standard. For events exceeding this, the defences are overtopped but remain structurally intact.
● Breach – in this case it is assumed that the backshore defences are breached at the weakest locations (defined where the present day condition of the defence is assessed to be ‘critical’ – Figure 10). Based on this reasoning, three locations along the coast east of the Demerara and one location to the west of the Demerara are assumed to breach. The breach width is assumed to be 20% of the length of the defence section (with a minimum breach length of 100m) and an invert level determined by the natural ground level (although considered reasonable, see Sayers et al, 2001, Hall et al, 2004, specific breach initiation and growth studies have not been possible here).
Tidal defence system state: Given the absence of significant lengths of raised defences, no consideration is
given to the potential for a breach, although the tidal walls may be overtopped.
Drainage system states: Two possible system states are considered:
● Unrestricted function – in this case, the system is operating to capacity and linked to the land use categories (with greater standards provided in more established urban and industrial settings) as set out in Table 1.
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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● Restricted function – Failure of the drainage system is considered in terms of a reduced capacity that may arise due to blockage (of the channel itself or sluice due to vegetation or anthropogenic debris) or operational failure (e.g. failure of a pump or failure of a sluice to open or close). For example, during the 2005 floods, it is estimated that the canal system functioned at 60% capacity (Muntz, 2005). ‘Failure’ is therefore represented through a reduction in the drainage capacity (Table 2).
Table 2 Drainage capacity in relation to land use
Land use category
From CE3
Drainage capacity
(present day – expressed in return period, years)
Unrestricted Restricted
Residential areas 25 10
Predominantly Industrial 10 2
Predominantly commercial 10 2
All other areas 10 2 Note: Unrestricted refers to the standard provided assuming the channels and associated pumps and sluice perform as designed
(where they exist). Restricted refers to the cause of a partial loss in conveyance due to poor channel management, or a pump or
sluice failure.
Source: Sayers and Partners and Vivid Economics
Flood hazard mapping
The flood hazard analysis considers both the storm conditions (rainfall and coastal surge) as well as
representation of the system states (breach or not, blocked or not). Given the strategic nature of the
analysis, representation of each individual sluice and pump is not appropriate but where possible insights
from the recent localized model studies by JICA (2017) and TUD (Remmers et al., 2016) – studies that have
focused on Georgetown only – have been used to inform the inundation analysis.
A cell‐based routine is used to map the flood extent and depth across the floodplain in a way that builds
upon approaches typically used as part of larger scale analysis (e.g. Rodda, 2005). These are capable of using
the high resolution of the mosaic DTM (see earlier) and characterising the complexity of the channel network
and coastal defences. Within this approach, it is assumed that rainfall directly on the land surface is first
conveyed to the drainage network before spilling on to the floodplain; a reasonable assumption given the
extensive nature of the network (
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Figure 13). Flood waters overtopping the crest level of the coastal or tidal defences (or in the case of a
breach, the invert level of the breach) provide the coastal boundary to the model. Propagation inland of
coastal flooding is then limited by the roughness of the floodplain (through a Manning’s function that
accounts for the various inland cover and use).
A more detailed description of the approach to the flood hazard mapping is provided in Appendix 4.
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Figure 13 The drainage channel network represented in the hazard analysis
Note: Blue: Previously mapped channels. Green: Channels derived here from the DTM
Source: Sayers and Partners, Vivid Economics
Selected present day hazard maps are presented in the following figures. Figure 14 Present day ‐ Rainfall
induced flood hazardsFigure 14 shows the flood extent and depth associated with a 1in100 year return
period rainfall event2. Two sets of hazards maps are provided in response to this storm event. The first
considers the drainage network performs as designed (i.e. an unrestricted system state) and the second
considers the impact of a partial loss of conveyance (i.e. the restricted system state).
2 A 1in100 return period expresses the expected number of events that will exceed this value in any given 100 years, but it is easily possible that within any given 100 year period an event that exceeds this value may not occur at all, or else it may occur more than once – See Sayers et al, 2015.
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Figure 14 Present day ‐ Rainfall induced flood hazards
Note: Example output hazard mapping: Left: 1in100 return period present‐day rainfall assuming the drainage network, pumps and
sluices perform as designed. Right: the same storm event, but assuming conveyance is partially restricted (due, for example, to poor
channel management, pump or sluice failure).
Source: Sayers and Partners and Vivid Economics
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Figure 15 Present day ‐ Coastal induced flood hazards
Note: Example output hazard mapping: Left: 1in50 return period storm event given the present‐day climate and three defence
breaches (of the critical condition defences). All other defences remain structural intact with limited (no) overtopping. Right: 1in100
return period storm event given the present‐day climate and three defence breaches, but with the added inflows from overtopping
of other defences.
Source: Sayers and Partners and Vivid Economics
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3.3 Flood exposure
Flood exposure is used here to refer to three aspects of the study area that may be subject to flooding.:
Economic (Land use) exposure
Error! Reference source not found.Error! Reference source not found. shows the spatial pattern of
commercial, industrial and residential land use and highlights the clusters of development around central
Georgetown and along the East Bank and south along the bank of the Demerara River. Agricultural land
buffers these developments and accounts for 20% of land use within the study area and predominantly
urban areas 6% (with exposure highest along the coast, where urban development is most dense) ‐ Table 3.
Figure 16 Present day (2017) land use map of study area
Table 3 Current shares (2017) by land use class
Land use class Area (Ha) Proportion
Dense vegetation and forests 85,535 32.6%
Agriculture 52,589 20.0%
Wetlands and swamps 52,103 19.8%
Sparse vegetation 34,411 13.1%
Predominantly residential 15,562 5.9%
Water bodies 9,277 3.5%
Shrublands and sandy areas 8,585 3.3%
Urban greenspaces 3,127 1.2%
Mangroves 731 0.3%
Predominantly industrial 477 0.2%
CBD and predominantly commercial 166 0.1%
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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People exposure
Around 140,000 people live in the study area with the majority living in Central Georgetown and its suburbs
(~85,000 people or 66% of the total population) ‐ Error! Reference source not found.. This mirrors the
distribution of critical infrastructure and highlights the high exposure here. The East Coast is the next most
populous region with 28,000 people or 22% of the total population. There are considerably less people west
of the Demerara and in the Timehri region, and very few living in the forests and wetlands (as expected). As
expected, the population density is also greatest in Central Georgetown (~14 people per hectare) and less
dense elsewhere.
Figure 17 Current population distribution across the study area
Source: Vivid Economics
Critical infrastructure exposure
Infrastructure that provides critical socioeconomic services such as health care, education and emergency
response are largely located within Georgetown itself and the immediate surroundings (Error! Reference
source not found.). This includes hospitals, health clinics, schools, police stations, fire stations, bus stations,
ferry terminals, airports with the majority of critical infrastructure within Central Georgetown and its
suburbs 3.
Figure 19 provides a summary count of the critical infrastructures within the study area. Within central
Georgetown and its suburbs, infrastructure is most densely located in the administrative boundary of
Georgetown, especially in the North‐western corner and along the southern border. This includes 41
schools, 20 hospitals, 18 bus stations, 8 police stations, 7 health clinics and 4 fire stations.4 It also includes
the ferry terminal (Stelling) between Georgetown and Vreed‐en‐Hoop, the Eugene F. Correira International
Airport (formerly Ogle) Airport, the National Park Stadium and Providence Stadium and the Camp Ayanganna
military base. Outside of the administrative boundary of Georgetown, critical infrastructure is mostly located
3 In the context of Georgetown, water, electricity and waste infrastructure are also critical to the provision of basic services and susceptible to flood damage. However, we were unable to include these assets within our analysis as no consolidated data sources exist mapping their location across Georgetown (or our wider study area). We also include Providence Stadium as well as the Camp Ayanganna Army Barracks. 4 While Guyana has only one National Referral Hospital, we use a wider definition of hospital as per Open Street Maps (2019) criteria. Hospitals mark ‘institutions for health care providing treatment by specialised staff and equipment, and typically providing nursing care for longer‐term patient stays.’ Health clinics mark ‘medical centres with doctors for outpatient care’.
0
2
4
6
8
10
12
14
16
0
10
20
30
40
50
60
70
80
90
Forests andwetlands
West ofDemerara
CentralGeorgetown and
suburbs
East Coast Timehri region
Bui
lt ar
ea d
ensi
ty (
peop
le p
er h
a)
Pop
ulat
ion
(tho
usan
ds)
Currentpopulation
Built area density
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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along the Demerara river, following the East Bank Highway. This includes a series of schools as well as a few
police stations and hospitals. It also includes Providence Stadium, located 10 minutes by car from central
Georgetown. Along the East coast the infrastructure become more dispersed (including 20 schools, 4
hospitals, 4 bus stations, 4 police stations and 1 health clinic). West of the Demerara infrastructure services
are less developed (with 17 schools, 3 police stations, 1 hospital and 1 fire station). The Leonora Stadium is in
the North Western corner of the region.
Figure 18 Critical infrastructure within the study area: Mapped
Note: Critical infrastructure in the Timehri region is excluded due to the lack of high‐resolution satellite imagery
Figure 19 Critical infrastructure within the study area: By count
2
25
9 6
25
2
15
80
2
1
Airport Bus stations Health clinics
Fire stations Hospitals* Military barracks
Police stations Schools Stadiums
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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3.4 Flood vulnerability
Vulnerability reflects the potential for a given receptor (such as a residential property) to experience harm
when exposed to a flood. To provide a quantified estimate of vulnerability three perspectives are used here:
Economic vulnerability
A damage function is used to relate the characteristics of the hazard (defined in terms of flood depth) to an
economic damage by land use class. The economic damage function used is based on the Guyana country
functions provided in the Global flood depth‐damage functions database (JRC, 2017) as summarised in Table
4.
Table 4 Direct economic damage functions (flood depth)
Hazard indicator USD / m2
Flood Depth (m) Residential Commercial Industrial Agriculture
0 ‐ ‐ ‐ ‐
0.5 18 135 65 0.01
1 26 186 87 0.01
1.5 31 204 93 0.02
2 35 219 98 0.02
3 36 221 98 0.02
Note: Uplifted from the base date of the JRC database (2010) to 2018 prices using IMF consumer price index (CPI) growth
statistics. The values shown are per m2 of land and are adjusted to account for the density of buildings on residential,
commercial and industrial land in Georgetown (based on the land use inventory produced under the Urban Growth
Study component of this project). The JRC vulnerability functions have been used in preference to construction type
damage functions (such as those provided in HAZUS or CAPRA). This reflects the lack of data on building construction
type across the study area. Although available in some areas (within the high‐resolution land use explored in CE3) it is
not possible to provide a credible generalization of this data. Therefore, the more aggregated damage functions
provided by JRC have been used.
Source: Sayers and Partners and Vivid Economics, based on JRC, 2017
People vulnerability
People vulnerability is explored through two counts. The first considered the number of people exposed to
flooding of any depth and the second those exposed to flood depths greater than 0.5m. No distinction is
may by social vulnerability (income, health, or social networks etc). This reflects the lack of information on
the detailed demographics and social vulnerabilities (e.g. as used in the neighbourhood flood vulnerability
index, Sayers et al, 2017) but also the well‐recognised difficulties in monetising the impact of a flood on the
physical and mental well‐being of an individual or group of individuals.
Critical infrastructure vulnerability
The economic damage incurred when critical infrastructure is flooded reflects the impact of the lost service
and the cost of replacing / reinstating those services. These impacts are valued here through two proxy
methods. The first provides an evaluation of the replacement value of each critical infrastructure asset
drawn from a variety of local and regional sources (Table 7). This assessment highlights the significant asset
based within the study area with a total value of around ~450m USD. The second is through a multiplier
applied to the direct economic damages to account for the physical infrastructure damage and disruption
that may be caused when an asset is flooded. This is difficult to assess directly (due to the highly contextual
nature of the damage and disruption). The assessment here assumes such damages add a further 50% to
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
24
the associated of the direct economic damage (above) 5. In the case of a hospital or clinic, for example, this
includes the reduction in the provision of medical services in the local area and repairing the building. This is
only a proxy of course so the basic counts of the number and type of critical infrastructure are also
presented.
Table 5 Replacement cost of critical infrastructure
Type of asset Replacement cost (2018 USD) Source
Hospital 1,747,522 IDB (2015)
Clinic 188,777 IDB (2015)
Ogle airport 28,885,501 Starbroek News (2018)
Cheddi Jagan airport 150,000,000 MOPI (2018)
Bus station 2,048,852 MOPI (2017)
Ferry terminal 1,240,225 MOPI, Transport and Harbours Dept (2017)
Fire station 91,378 Guyana Chronicle (2011)
Police station 73,321 Guyana Chronicle (2011)
School 1,594,255 GoG (2017)
Stadium 37,368,633 ESPN (2019)
Note: All figures are converted to 2018 USD using World Bank official exchange rate and US CPI data.
5 Physical infrastructure damage and associated disruption is typically estimated using a 1.1‐1.8 uplift applied to the direct economic damages. 1.5 is applied here to yield the total damages after Sayers et al, 2018. A study for Paramaribo, the consultant ERM Total Damage/Asset Damage ratio ranges between 1.05 and 1.71 that provides some supporting evidence (although no supporting reference for this can be found). It is noted however noted the assessment of the damage to and from critical infrastructure is highly contextual.
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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3.5 Flood risks
Present day ‐ Economic risk
Expected annual damage
Today the EAD6 from flooding across Georgetown and the surrounding area is around 5mUSD and
dominated by residential and commercial sectors exposed to surface water flooding (Figure 20).
Figure 20 Present day‐ Expected Annual Damage (spatial distribution)
Note: EAD by 30m gird
Source: Sayers and Partners
Coastal and tidal flood risk is much less (~1.2m USD compared to 3.8m USD from surface water) and
predominantly impacts the commercial and industrial sectors with the economic damage to the agricultural
sector small in comparison to other sectors (a function of the low value of the agricultural damage rather
than a lower exposure) ‐ see
6 EAD represents an integration of the relationship between annual probability of occurrence of a flood (taking account of probability of storm and conditional probability of the defence system states – see Table 6) and the associated consequences
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Figure 21.
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Figure 21 Present day flood risk by sector and flood hazard – Economic risk
Source: Sayers and Partners
Risk profile: Economic
To provide insight into the risk profile, Figure 22 sets out the relationship between probability and the conditional economic damage. This highlights the rapid increase in damage as the severity of the storm event exceeds around a return period of around 1in25 years. The increase in damage is much less with higher return periods. This is because floods that exceed a 1in200 year return period impact a significant area. The probable maximum damage, reflecting combined severe coastal and rainfall storm (with a joint return of 1in1000 years7 ). The damage associated with a 1in100 year return period coastal storm (taking account of conditional probability of a breach in the coastal defences) is estimated around 70mUSD with an equivalent rainfall event (taking account of conditional probability of loss of conveyance due to blockage or pump failure) is significantly higher (around 90m USD).
Figure 22 Risk profile: Present day relationship between probability and economic damage
7 As highlighted in Appendix 3 the coincidence record length is limited. This makes it difficult to determine extreme joint probability events from the data directly, so care is needed when considered such extreme events.
0.0
1.0
2.0
3.0
4.0
5.0
6.0
All sectors Residential Agricultural Industrial Commercial
Expected Annual Dam
age (USD
m)
Coastal Rainfall All sources
y = 67.97ln(x) ‐ 208.39R² = 0.99
0
50
100
150
200
250
300
0 200 400 600 800 1000 1200
Conditional economic dam
age (m
USD
)
Return Period (years)
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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The spatial distribution of damage for the 1in100 event is provided Figure 23 and hot spots of damage in the city of Georgetown and along the commercial areas near the mouth of Demerara. The areas immediately in the lee of those sea defences assessed to be in a ‘critical’ condition (assumed here to be the location of a breach, if it occurs) experience significant damage.
Figure 23 Event risk – Present day 1 in 100‐year return period storm
Source: Sayers and Partners
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Present day ‐ People risk
The expected annual number of people exposed to flooding is given in Figure 24. The expected annual number of people flooded is ~28,400 people. This is primarily in response to rainfall events (~26,000) with significantly fewer experiencing coastal flooding (~2,400). The severity of the flooding at the coast is however typically greater, with most people exposed to flooding experiencing flood depths that exceed 0.5m. Although the absolute number of people experiencing flood depths greater than 0.5m in response to a rainfall storms is much higher, the relative proportion is much less than during coastal storms.
Figure 24 Present day ‐ People at risk – Expected annual number of people exposed to flooding
Source: Sayers and Partners and Vivid Economics
The spatial distribution of the people exposed to an annual probability of flooding greater than 0.01 (i.e. a
return period of 1in100 years) is shown in
Figure 26 Present day flood risk by land use and flood hazard – Critical infrastructure risk
Figure 27 Present day‐ Critical infrastructure at risk (spatial distribution ‐ 1in100 return period)
0.0
5.0
10.0
15.0
20.0
25.0
30.0
Any flood depth Flood depths >0.5m
Expected annual number of
peo
ple flooded
(000s)
Coastal Rainfall All sources
32
46
5868
0
20
40
60
80
25 100 150 200
Number of sites affected
Return Period (years)
Total number affectedairportbus_stationclinicfire_stationhospitalmilitarypolice
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Top: Critical infrastructure impacted by 1in100 year rainfall event: Bottom: Critical infrastructure impacted by 1in100 year coastal
event. Source: Sayers and Partners
. The figure highlights a concentration of people at risk at the mouth of the Demerara and along its east bank (as expected). Under such extreme conditions ~375,000 people may be flooded during rainfall events and ~125,000 during coastal storms (if associated with a breach).
Figure 25 Present day ‐ People at risk – Example map 1in100 return period rainfall
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Source: Sayers and Partners
Present day ‐ Critical infrastructure risk
Significant critical infrastructure is exposed to flooding with the number of police stations, bus stations and
schools increasingly significantly with the severity of the storm (Figure 26). As expected, most critical
infrastructure risks are within Georgetown and its immediate surrounding (Figure 27).
Figure 26 Present day flood risk by land use and flood hazard – Critical infrastructure risk
Figure 27 Present day‐ Critical infrastructure at risk (spatial distribution ‐ 1in100 return period)
32
46
5868
0
20
40
60
80
25 100 150 200
Number of sites affected
Return Period (years)
Total number affectedairportbus_stationclinicfire_stationhospitalmilitarypolice
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Top: Critical infrastructure impacted by 1in100 year rainfall event: Bottom: Critical infrastructure impacted by 1in100 year coastal
event. Source: Sayers and Partners
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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4 Future flood risk
4.1 Alternative adaptation measures and strategies
A long list of adaptation measures was first developed through a thorough consultation process with key
stakeholders. From this, a shortlist of the most promising options was identified, based on the economic,
environmental and technical constraints and opportunities in Regions 3 and 4. This process is elaborated in
more detail in Appendix 5. The resulting shortlist is shown in Figure 28.
Figure 28 Portfolio of flood management measures
Note: Short list of measures identified from the stakeholder lead long listing process (Appendix 4) reflects a portfolio
approach widely recognised as a perquisite for good flood risk management, Sayers et al, 2014.
Source: Sayers and Partners
These individual measures form the basis for the three alternative approaches to flood risk management as
follows:
● Business‐as‐usual: Considers the adaptation measures that would be implemented assuming a continuation of current approaches and similar levels of investment as today.
● Feasible adaptation: Assumes the adaptation effort is increased with more investment directed towards maintaining existing natural (‘soft’) and conventional (‘hard’) infrastructure and appropriately plan new infrastructure (taking account of climate change). It is also assumed flood hazards have a greater influence for spatial planning and building regulation than they do today.
● Smart adaptation: Assumes climate change and long‐term resilience are central consideration managing flood risks. This means significant resources are devoted to soft and hard flood protection infrastructure and, importantly, spatial planning choices provide space for the natural dynamics of the coast where possible and avoid development in areas exposed to the highest chance of flooding in the future.
A summary narrative of the individual adaptation actions contributing to each alternative strategy is given in
Table 6. Details of the assumed standards and conditional breach and blockage failure probabilities are given
in Table 76 to 8
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Table 6 Adaptation measures included in each alternative strategy
Adaptation measure Business‐as‐Usual (BAU) Feasible Smart
Soft infrastructure
Mangroves and
sediment control
structures
Conservation areas are maintained but not
extended and groynes remain in poor condition
with limited influence on morphology. Little
protection provided to backshore defences.
Active management and targeted extension of
conservation areas. This acts to reduce the
chance of breach (where opportunities are
greatest).
Further extension of mangrove forest areas and
control structures act to improve the standard of
protection.
Hard infrastructure
Coastal and tidal
defence
Present day standards reduce with climate
change. No significant improvement in defence
condition, ‘Critical’ condition defences have an
increased chance of breaching.
Present day standards reduce with climate
change, but enhanced maintenance leads to
some improvement in defence condition
(reducing the chance of a breach).
Defence standards are raised (through a
combination of conventional and nature‐based
defences) to 1in100 years and their condition
improved (reducing the chance of a breach).
Hard infrastructure
Drainage infrastructure
Drainage capacity continues to be constrained by
channel and pump capacity as well as
anthropogenic debris and vegetation. The chance
of blockage or pump failure is high.
Improved channel management and
pump/sluice maintenance (and targeted
replacement) improve the conveyance
capacity in urban areas. The chance of a
blockage and/or pump is reduced.
Further improvements to conveyance and
maintenance improve standards in urban and
commercial areas (reducing the chance of blockage
and pump failure).
Catchment
management*
All strategies assume the upstream catchment remains unaltered and the flows in the Demerara remain unchanged with climate change (an assumption
that relies on the maintaining the existing forest cover)
Spatial planning*/** Urban growth takes place with no consideration
of flood risk ‐
Urban growth takes place with some
consideration of flood risks, seeks to avoid
those areas where present day flood hazard
during the 1in100 year event > 0.6m. A no
new development buffer is maintained of
100m in tidal areas and 500m at the coast.
Urban growth takes place with some consideration
of flood risks, seeks to avoid all areas exposed
during a 1in100 year coastal event and a pluvial
flood hazard of >0.3m. A no new development
buffer is maintained of 200m in tidal areas and
1000m at the coast.
Forecasting and
warning*
Improved forecasting and warning to support Disaster Risk Management is required across all the strategies and the need to invest in improved systems is
a clear recommendation from the stakeholder workshops. The associated costs and risk reduction however are not quantified here.
Building resilience * Appropriately rising threshold levels to reflect the 1in100 year flood level (mGD) plus a freeboard allowance and the updating building regulations to
encourage resilient designs.
Supporting disaster risk
management, climate
adaptation and social
resilience*
Institutional change and regulatory responsibility, asset management, mangrove management and monitoring and insurance are all important issues that
will need to be addressed going forward are not the focus here. It is however assumed that improvements in asset monitoring enable better targeting of
investment in the feasible and smart strategies yielding some efficiency saving. Also developing social resilience requires actions beyond those listed
above, including specific actions that address the needs of vulnerable individuals and groups. This will rely upon developing long term community
connections and cohesion (Particip 2018). Achieving this is a difficult and complex, requiring community engagement and integrated planning. These
actions are not directly focused on in this report but will be improved aspects of further integrated planning processes as identified by Particip (2018).
Note: * indicates not included in adaptation cost estimates. ** See further discussion in Section 4.2. Source: Sayers and Partners
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Table 7 Standards of service – Coastal defences and drainage infrastructure
Individual measure Alternative adaptation strategies
Baseline strategy Feasible Smart
Mangroves and sediment control structures
Open coast: As now Limited extension and
improvement
Further
extension and improvement
Tidal river: As now Limited extension and
improvement
Further
extension and improvement
Open coast defences standard of protection (years)
East frontage: 1in50 1in50 1in100
West frontage: 1in50 1in50 1in100
Tidal defence standard of protection (years)
East bank: Direct from DTM Min 1in50 Min 1in100
West bank: Direct from DTM Min 1in50 Min 1in100
Drainage system (capacity by land use)
Residential 1in25 1in25 1in25
Agricultural 1in10 1in10 1in25
Commercial 1in10 1in25 1in25
Note: See Appendix 4 for further detail
Source: Sayers and Partners
Table 8 Conditional failure probabilities ‐ Coastal defences and drainage infrastructure
Return period of storm (years
System state
Conditional probability of system state by adaptation assumption given storm event
Present day Future
Baseline Feasible Smart
Coastal 2 No breach 1 1 1 1
10 No breach 1 1 1 1
50 No breach 0.75 0.5 0.75 0.9
Breached 0.25 0.5 0.25 0.1
100 No breach 0.6 0.25 0.4 0.75
Breached 0.4 0.75 0.6 0.25
200 No breach 0.5 0.1 0.25 0.5
Breached 0.5 0.9 0.75 0.5
Rainfall 2 Unrestricted 1 1 1 1
10 Unrestricted 1 1 1 1
25 Unrestricted 0.75 0.5 0.75 0.9
Restricted 0.25 0.5 0.25 0.1
100 Unrestricted 0.6 0.25 0.4 0.75
Restricted 0.4 0.75 0.6 0.25
200 Unrestricted 0.5 0.1 0.25 0.5
Restricted 0.5 0.9 0.75 0.5 Note: See Appendix 4 for further detail
Source: Sayers and Partners
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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4.2 External drivers of future change
Climate change
Sea level rise: Mean sea level (MSL) has risen by 23cm from 15.52mGD (Guyana Datum: GD) to 15.75mGD in
the 37 years from 1979 to 2016 (Mc Sweeney et al., 2010), an average of 6.2mm/year. This rate of rise is
higher than the global average of about 2‐4mm/year (JICA, 2017). Projections of sea level rise from climate
models show an increase in mean sea level from 0.26 (lower RCP2.6) to 0.82 m (upper RCP8.5) by 2081‐
2100 (Church et al, 2014). This is broadly consistent with SLR projections developed by McSweeney for
Guyana. Within this study a lower and higher sea level rise projection are therefore proposed based on this
work (Table 9).
Table 9 Proposed SLR scenarios
Epoch Lower (m) Higher
(m)
2030 +0.14 +0.26
2040 +0.18 +0.35
2050 +0.21 +0.43 Source: McSweeney et al (2010) interpreted for this study (2040 interpolated values)
Increased rainfall intensity: McSweeney et al. (2010) provides projections of mean annual rainfall from
different climate models that show a wide range of changes in precipitation for Guyana. Ensemble median
values of change by the 2060s are consistently negative for all seasons and emissions scenarios. Projections
vary between ‐34% to +20%, by the 2090s with ensemble median values of ‐18 to ‐4%. A considerable
variation is projected for the wet seasons with‐68 to +21mm per month (May to July and ‐82 to +68%
(August to January). The proportion of total rainfall that falls in heavy rain events (extreme precipitation)
however does not show a consistent direction of change and extremes are more likely to increase based on
the rise in intensity of El Niño and La Nina episodes. El Niño episodes bring dry conditions throughout the
year, and bring warmer temperatures between June and August, whilst La Niña episodes bring wetter
conditions throughout the year and cooler temperatures between June and August. Observations since 1960
within Guyana indicate a distinct rise in extreme rainfall events over recent years with floods experienced in
2005, 2006, 2008, 2010, 2011, 2013, 2014 and 2015. This observation of increasing extremes in recent years
is supported by analysis of the CHIRPS data undertaken for this study, where 7 out of the top 10 extremes
have been in the latter half of the 1981‐2018 period. Lower and higher rainfall projections have been
developed based on this evidence, as given in Table 10.
Table 10 Proposed increases in extreme rainfall scenarios
Epoch Lower
(% increase –
applied to all return
periods)
Higher
(% increase – applied
to all return periods)
2030 0 +10%
2040 0 +12%
2050 0 +14% Source: McSweeney et al (2010) interpreted for this study (2040 interpolated values)
Further discussion of the climate change assumptions is provided in Appendix 3.
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Urban development
A spatially explicit stochastic land use change modelling framework is used to produce regional projections
of urban growth (as discussed in detail in Vivid, 2019). To reflect the role of spatial planning in decisions
contributing to the management of flood risk the urban growth model has in part conditioned by the
understanding of present‐day flood hazards. The 1in100 year flood hazard mapping undertaken here has
been used as an input to the urban growth model together with different spatial planning rules applied
under each alternative adaptation strategy (as summarised in Table 6). These alternative rules act to
influence the location of future spatial distribution (Figure 29) and hence the future change in land use
(Figure 30). Including the influence of spatial planning choices is an important part of the alternative
adaptation strategies and avoids the assumption often may than the future urban development is flood
hazard agnostic.
Figure 29 Projected development hotspots under BAU, smart and feasible scenarios
Note: Kernel density of urban built‐up development projections at a scale of 1km. High values in red indicate significant
clustering of projected urban development.
Source: Vivid Economics and Sayers and Partners
Figure 30 Present and future land use maps of Georgetown under BAU, smart and feasible scenarios
Source: Vivid Economics and Sayers and Partners
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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4.3 Future flood risk
Future ‐ Economic risk
Assuming a continuation of business‐as‐usual, future flood risks increase significantly from present day; with
the Expected Annual Damage (EAD) rising from ~5m USD today to 11.7m USD in a lower and 13.0m USD in a
higher climate change scenario by 2050s. Figure 31 illustrates this increase in risk and the growth in the
contribution of commercial and industrial sector risks (rising from 1.8m USD to 3.4m USD, and 1.0m USD to
2.7m USD respectively by 2050s under a higher climate change scenario). Under the business‐as‐usual
assumption the increase in EAD is most stark in response to sea level rise, with the present day coastal risk
increasing almost three‐fold by the 2050s under a higher climate scenario (from 1.2m USD to 3.5m USD –
Figure 32).
There is an opportunity avoid these dramatic increases. Although it is not possible to eliminate future flood
risk (a practical impossibility), future flood risk can be managed if effort is appropriately devoted to
adaptation and well‐managed urban development. Figure 33 illustrates how the spatial distribution of flood
risk in the alterative futures vary and the potential for significantly reduced flood risk in both the Smart and
Feasible adaptation futures (to 3.7m USD and 6.7mUSD EAD by 2050s under a higher climate future
compared to ~13mUSD in a business‐as‐usual approach).
Delivering either the Feasible or Smart strategies will require a concerted and integrated effort. If delivered
successfully the reduction in risk compared to the business as usual approach will benefit the whole
Georgetown and the surrounding areas (Figure 34). A disaggregation of risks by flood source (Figure 34)
highlights the projected growth of risk from both coastal and rainfall sources under the business‐as‐usual
scenarios. Under a feasible strategy risk is maintained close to present day levels, but under the smart
strategy both coastal and rainfall related flood risks can be reduced in real terms. From a sectoral
perspective, all sectors of the economy are projected to experience increases in risk by the 2030s and 2050s
assuming a business‐as‐usual approach to adaptation. The most significant increases are in the residential,
commercial and industrial sectors (Figure 35).
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
39
Figure 31 Relative changes in economic risk by sector: Present day ‐ 2050s (Baseline adaptation)
Note: The sectors represent the relative magnitude of the risk in the Present Day as well as low and higher climate
change futures.
Source: Sayers and Partners and Vivid Economics
Figure 32 Changes in economiuc risk by flood hazard: Present day – 2050s (A comparsion of altnernative adpatation strategies)
Source: Sayers and Partners and Vivid Economics
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
Low High Low High Low High Low High Low High Low High
2030s 2050s 2030s 2050s 2030s 2050s
PresentDay
Business as Unsual Feasible Smart
Expected Annual Dam
ages (USD
, m)
Coastal Rainfall
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Figure 33 Expected Annual Damage ‐ Spatial distribution
Note: High climate change (all sectors) Source: Sayers and Partners and Vivid Economics
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
41
Figure 34 Expected Annual Damages given alternative adaptations – By flood source
All Sources
Coastal and tidal flooding only
Rainfall (surface water) flooding only
Note: High climate change (all sectors)
Source: Sayers and Partners and Vivid Economics
0.0
5.0
10.0
15.0
Present day 2030s 2050sExpcted
Annual Dam
age
(EAD) ‐USD
m
Baseline Feasible Smart
0.0
5.0
10.0
15.0
Present day 2030s 2050s
Expcted
Annual Dam
age
(EAD) ‐USD
m
Baseline Feasible Smart
0.0
5.0
10.0
15.0
Present day 2030s 2050sExpcted
Annual Dam
age
(EAD) ‐USD
m
Baseline Feasible Smart
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Figure 35 Expected Annual Damages given alternative adaptations – By sector
Note: High climate change (all flood sources)
Source: Sayers and Partners and Vivid Economics
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
All sectors Residential Agricultural industrial CommercialExpected Annual Dam
ages (USD
, m) 2050s ‐ High climate change: Baseline adaptation
Coastal EAD Rainfall EAD Total EAD
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
All sectors Residential Agricultural industrial CommercialExpected Annual Dam
ages (USD
, m) 2050s ‐ High climate change: Feasible adaptation
Coastal EAD Rainfall EAD Total EAD
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
All sectors Residential Agricultural industrial Commercial
Expected Annual Dam
ages (USD
, m) 2050s ‐ High climate change: Smart adaptation
Coastal EAD Rainfall EAD Total EAD
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Future ‐ People risk
Assuming a continuation of business‐as‐usual, the expected annual number of people exposed to flooding
increases significantly from 28,400 today to 54,900 by 2050 (under a high climate change future) ‐ Figure 36.
Those flooded to depths greater than 0.5m also increases significantly from 10,000 today to 19,000 in a
lower and 23,000 in a higher climate change scenario by 2050s (Figure 31). Under the feasible and smart
adaptation scenarios the number of people risk also increases. .
Figure 36 Expected annual number of people exposed to flooding by 2050s (High climate, business as usual future)
Source Sayers and Partners
Figure 37 Expected annual number of people exposed to flooding greater than 0.5m by 2050s
Source Sayers and Partners
0.0
10.0
20.0
30.0
40.0
50.0
60.0
Any flood depth Flood depths >0.5mExpected annual number
of peo
ple flooded
(000s)
Coastal Rainfall All sources
0
5
10
15
20
25
Present day Business as Unsual Feasible Smart
Expected annual no. of
peo
ple exposed to flooding
(Number 000s)
2050s ‐ Low climate change
Coastal Rainfall All sources
0
5
10
15
20
25
Present day Business as Unsual Feasible Smart
Expected annual no. of
peo
ple exposed to flooding
(Number 000s)
2050s ‐ High climate change
Coastal Rainfall All sources
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Future – Critical infrastructure risk
Future developments are not assumed to influence the number or spatial distribution of the critical
infrastructure. Given therefore proximity to Georgetown and the coast the number of sites affected changes
little, however the associated economic damage due to physical impacts and disruption increase (assumed
here as a function of the increase in direct economic damages –Figure 38).
Figure 38 Expected annual impact of physical damage and disruption to critical infrastructure (mUSD)
0.00.20.40.60.81.01.21.41.61.82.0
Current Low High Low High Low High Low High Low High Low High
2018 2030s 2050s 2030s 2050s 2030s 2050s
PresentDay
Business as Unsual Feasible Smart
Expected economic im
pact (mUSD
) Coastal sources
0.00.51.01.52.02.53.03.54.04.55.0
Current Low High Low High Low High Low High Low High Low High
2018 2030s 2050s 2030s 2050s 2030s 2050s
PresentDay
Business as Unsual Feasible Smart
Expected economic im
pact (mUSD
) Rainfall sources
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
Current Low High Low High Low High Low High Low High Low High
2018 2030s 2050s 2030s 2050s 2030s 2050s
PresentDay
Business as Unsual Feasible Smart
Expected economic im
pact (mUSD
) All sources
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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5 Adaptation cost
In the business as usual scenario, Georgetown and the surrounding area is expected to spend at least USD
121 million on adaptation measures from 2020 to 2040 in present value terms. This is equivalent to an
annual spend of approximately USD 10 million. This figure covers the following types of measures (discussed
in greater detail in Section Error! Reference source not found.):
● Surface water (pluvial) management – measures to improve the effectiveness and capacity of Georgetown’s drainage system such as the improvement of channels, sluices and pumps;
● Hard defences ‐ built infrastructure to protect the coast or tidal banks such as conventional walls, groynes and backshore protection; and
● Soft defences – natural infrastructure to protect the coast or tidal banks such as mangroves, permeable groynes and other sedimentation structures.
This is split roughly 45%, 54% and 1% between surface water management, hard defences and soft defences
respectively. This reflects an extension of current spending patterns in each of these aspects from 2020 to
2040. The 2019 budget allocates roughly USD 24.6 million (GYD 5.1 billion) to surface water management
(Cooperative Republic of Guyana, 2019). It is estimated that approximately 16% or USD 4 million of this is
spent in the Greater Georgetown area. In 2017, the Ministry of Public Infrastructure (2017) spent
approximately USD 5.2 million on hard defences including conventional walls, rip raps and revetments. USD
3.3 million of this focussed on coastal measures and USD 1.9 million on rivers. The split between capital and
maintenance costs is roughly 80/20, though capital costs tend to be a slightly higher share of total spend for
coastal defences relative to river defences. Between 2010 and 2018, the National Agricultural Research and
Extension Institute (2019) spent an average of USD 97,000 per year (GYD 19.4 million) on mangrove
restoration interventions (see Figure 39).
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
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Figure 39 Projected business as usual spending on core adaptation measures from 2020‐2040
Note: Figures presented are in present value terms based on an annual 5% discount rate.
Source: Vivid Economics and Sayers and Partners
Hard defences are the most expensive category of adaptation spending, largely due to the high capital costs
associated with both rehabilitation and initial construction of sea walls. Improving surface water
management also involves substantial capital costs, particularly associated with additional channels, sluices
and pumps. Mangroves by contrast, are a relatively low‐cost adaptation option. They are not however cost‐
free and do require some capital expenditure (covering seeds and planting, supplementary set back,
backshore defences) as well as moderate expenditure on routine monitoring and maintenance. For this
purpose, mangroves and other soft defences are generally seen as a priority over hard defences where
sufficient space exists (or can be created) to ensure they are able to sufficiently dissipate wave energy and
the response to, and recovery from, storm events. This is not possible in all areas, and conventional sea walls
and embankments will continue to be required.
Total spending from 2020 to 2040 is expected to increase to USD 252 million under the feasible scenario and
USD 394 million in the smart scenario (in present value terms). This represents an increase of approximately
110% and 225% relative to business‐as‐usual respectively, and reflects an average annual spend of around
USD 20 million and USD 32 million. Figure 40 demonstrates that the largest proportional rise is seen in
spending on soft defences, which increases from 1% of total spending in the business as usual scenario to
11% in the feasible and smart scenarios.
45%
35%
19%
1%
Surface water management Coastal hard defences
Tidal hard defences Coastal soft defences
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
47
Figure 40 Projected spending from 2020 to 2040 by type of adaptation measure and adaptation scenario
Note: Figures presented are in present value terms based on a 5% discount rate.
Source: Sayers and Partners; Vivid Economics
Both scenarios represent a marked increase in ambition relative to business‐as‐usual. For surface water
management, this reflects implementation of the recommendations made under the ‘Data collection survey
on drainage capacity in Georgetown in the Co‐operative Republic of Guyana’ by JICA (2017). The feasible
scenario focusses on a subset of improvements for drainage channels, pumping stations and sluices while
the smart scenario includes all recommendations as well as additional rainwater storage facilities. For soft
and hard defences, the feasible and smart scenarios represent an increased level of aggregate spending
relative to the business as usual scenario, in line with ambitions of the relevant authorities, as well as a shift
in priority away from hard defences towards soft defences.
Given the long‐term nature of the alternative adaptation strategies, these measures are expected to
generate a net positive return after 2040. In both the feasible and smart scenarios, average annual
expenditure exceeds the associated reduction in Expected Annual Damage (EAD) in 2040. However, this
result should be treated with caution for several reasons. First, the reduction in EAD only accounts for direct
damages to infrastructure and property and does not include indirect damages such as loss of economic
activity and health impacts. In addition, damage estimates for agricultural land are expected to be
underestimated due to the lack of local data to condition the JRC vulnerability functions. Second, as climate
change continues to drive higher sea levels and potential variation in rainfall beyond the 2040s and 2050s ,
the reduction in EAD attributable to the feasible and smart strategies will increase. Third, costs presented
here are approximate and based on aggregate spending scenarios. While this is a reasonable assumption in
the absence of local asset‐specific cost data, it doesn’t allow a detailed financial assessment of each asset
over its lifetime.
With additional data, the comparison of costs and benefits could be strengthened in the following ways:
● The adaptation measures considered for costing could be more closely linked with the measures considered for estimation of expected annual damage. Due to a lack of specific and local data on
0
50
100
150
200
250
Surface watermanagement
Coastal hard defences Tidal hard defences Coastal soft defences
USD
mns (present value)
Baseline
Feasible
Smart
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
48
potential projects, cost projections are largely based on expected trends in aggregate spending. Feasibility studies or additional cost estimates could allow the modelling of site‐specific improvements which provide a better direct comparison to the risk modelling exercise.
● The costs and benefits of an adaptation measure could be modelled over the lifetime of the asset. This analysis presents costs and benefits to 2040, as there is insufficient information on asset‐specific capital and maintenance costs. With this data, costs would be expected to decline over time while benefits increase, improving the cost effectiveness of the investment.
● Aggregate benefit and cost results could be adjusted to account for complementary interventions such as early warning systems for flood events or streamlined evacuation procedures. These measures, while often difficult to quantify, generally have low costs and high benefits.
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
49
6 Conclusions
Based on a participatory process of qualitative assessment this study has explored the wide range of
potential threats and climate‐related hazards that may impact Georgetown and the wider area. Based on
this analysis, coastal, tidal and rainfall driven flooding, have been confirmed as priorities for action.
Three alternative adaptation strategies have been considered; business‐as‐usual; feasible; and, smart. The
future change in flood risk under each alternative has been assessed given a lower and higher climate
change future. Under a business‐as‐usual adaptation approach the expected annual damage (EAD) from
flooding is projected to increase from around USD 5 million today to between USD 10‐12 million by the
2040s. Given a feasible or smart adaptation approach future risks are much lower, with a projected 2040s
EAD of USD 5.5‐6.5 million and USD 3‐4 million respectively.
Business‐as‐usual is not a viable disaster risk management option for Georgetown and a more ambitious
adaptation strategy is required. Delivering either of the feasible or smart strategies however will require a
concerted and integrated effort. Doing so will require a focus on resilience across all adaptation choices –
from community to city decisions. The concept of ‘living with water’ will need to be central to the adaptation
process alongside making space for nature to provide a dynamic natural resilience where possible. Spatial
planning will have an important role in this to ensure future development takes account of flood hazards and
makes space for the flood waters by creating ‘buffer zones’ around the coastal and drainage network.
To take the findings of this study forward will require resources devoted to an increased understanding of:
● Extension of the high‐resolution topographic data across the study area and updated information of the design standards, geometries and condition of coastal defences and drainage infrastructure.
● The joint probability analysis of surge and rainfall (this has not been possible but is recommended for further study).
● The coastal processes, including the longer term morpho‐dynamic processes.
● Further development of vulnerability functions across the land use sectors, but particularly agriculture.
● Further downscaling of Global and Regional Circulation Models to provide updated changes in sea level rise and storm duration intense rainfall beyond 2040 to 2100.
It is recommended that these improvements in understanding should be taken forward together with the
findings of this study into two detailed planning and investment strategies. First, the development of a
strategic urban and coastal management Policy and Action Plan is recommended. This project would aim to
map and model coastal processes to enable better protection of the coastal zone and provide the integrated
framework of coastal policy planning with supporting detailed investment plans. There is overlapping
legislation which has led to coastal and urban management being shared among several institutions such as
MoPI, EPA, GFC, NAREI and GL&SC. The integrated plan should strengthen participation among these major
stakeholders and sectors, and provide an agreed strategy plan, if developed well, should guide decision
making, promote awareness of the issues and facilitate the execution of programs to manage coastal
resources and reduce vulnerability climate change. The project should address issues relating to policy
development, analysis and planning, inter‐agency coordination, public education and awareness‐building,
environmental control and compliance, monitoring and measurement, and information management
alongside a programme of investable infrastructure improvement actions. Secondly, the development of an
improved forecasting and early warning system is proposed. This has been suggested by stakeholders
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
50
throughout this study. Although not the focus here it is recommended that future attention is also directed
towards providing timely and reliable information on forecast and projected flood risks to support early
action.
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
51
Appendices
Provided as separate files
Appendix 1 Prioritization of hazards and risk
Appendix 2 Creation of a credible understanding of topography (DTM)
Appendix 3 Extreme value analysis
Appendix 4 Defence standards and approach to modelling the inundation scenarios
Appendix 5 Long list and short listing of adaptation options
GIS Datasets
Georgetown, Guyana: Disaster Risk and Climate Change Vulnerability Assessment
52
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Contact us
Vivid Economics Limited Sayers and Partners LLP 163 Eversholt Street High Street London NW1 1BU Watlington United Kingdom United Kingdom
T: +44 (0)844 8000 254 +44 1865 600039 [email protected] [email protected]
Company profile
Sayers and Partners is a leading applied research consultancy focusing on the strategic management water
related risks. We focus on the developing world‐leading decision meaningful analysis, asset management
and investment planning. SPL work internationally for a range of private, public and NGO sector clients. We
have several associations with leading academic institutes and research programmes to ensure to maintain
the leading edge of our work.
Vivid Economics is a leading strategic economics consultancy with global reach. We strive to create lasting
value for our clients, both in government and the private sector, and for society at large.
We are a premier consultant in the policy‐commerce interface and resource‐ and environment‐intensive
sectors, where we advise on the most critical and complex policy and commercial questions facing clients
around the world. The success we bring to our clients reflects a strong partnership culture, solid foundation
of skills and analytical assets, and close cooperation with a large network of contacts across key
organisations.