LUẬN văn THẠC sĩ cost benefit analysis of grey and green infrastructures to adapt to sea level rise in the mekong river delta

INTRODUCTION

The necessary of the research

Climate change is one of the most important global issues in the 21 st century.

It affects not only environmental problems but as well economic and social problems and instability in the future Sea level rise (SLR) is one of the signs of climate change, even though there is a very small change in sea level, it has a great impact on other factors such as hydrological or extreme events such as storms, hurricanes or droughts In addition, SLR causes widespread and irreversible flooding in coastal areas, causing migration to other lands, affecting social security and food security as well as economic growth, environmental issues in coastal areas and also other areas.

Vietnam is one of the countries most affected by climate change, including SLR The Mekong river delta (MRD), the largest delta region in Vietnam and the main food producing region, has been affected by SLR in recent years According the scenario of climate change and SLR in 2100 of MONRE (Ministry of natural resources and environment), with 1m of SLR by the end of the 21 st century, nearly 50% of this area will be completely inundated It is very influential that more than

20 million people living here and their livelihood, living standards and social welfare may be affected It is necessary to identify the physical damage, economic damage and other factors for choosing the appropriate adaptation solution.

Because the SLR impact is uncertain, in conjunction with socio economic development trend in the 21 st century, it is difficult to evaluate the damage due to SLR to the mainland At present, there is little study focusing on the impact of SLR taking the socio economic scenarios, especially in the MRD region – the 3rd largest delta in the world Therefore, this study was conducted to fill the research gap and to contribute information for choosing an appropriate adaptation solution for this

The research questions and hypotheses

This study has the main objective of answering the question “Can mixing grey and green infrastructure be a good solution to adapt to SLR in MRD?”

To answer the central research question, the research address to answer following questions:

Question one: What is the area inundated due to SLR in the Mekong delta especially with large scale land use areas?

Question two: How many people in MRD might be affected by SLR in 21 st century?

Question three: How much the cost of the damage of the land loss due to SLR?

Question four: What is the effect of mixing grey and green infrastructure by CBA?

Question five: Does mixing grey and green infrastructure has more effectiveness than other adaptation option?

The hypothesis is mixing grey and green infrastructure has the greater benefit than the cost to set up this system (the highest effective compare with other adaptation option) and it can be a good way to apply in MRD to adapt to SLR.

Research objectives and tasks

To answer these research question, my research objectives are:

 Objective one: Address the potential inundated area by SLR in MRD in land use type and administrative area based on SLR scenarios.

 Objective two: Evaluated and estimated the potential impact of SLR in MRD by the value of land loss and the population affected based on the different socio economic scenarios in 21 st century?

 Objective three: Estimate the cost of mixing grey and green infrastructure when applying in MRD and calculate the effective of grey and green infrastructure by cost benefit analysis

 Objective four: Compare the effective of grey and green infrastructure to other adaptation solution.

Figure 1.1 Structure of the research This study is conducted based on five main steps as in Figure 1.1:

Literature review: conduct a search and review of national and international studies on the topic of the impact of SLR and analyse adaptive solutions, thereby identifying research gaps and addressing issues that the research will focus on solving.

Set up the theoretical framework and practical framework: after the literature review, the establishment of a theoretical basis and the adaptation solution have been applied to adapt to SLR for conducting the impact assessment of SLR and evaluate the effectiveness of adaptation solutions in MRD.

Carry out evaluation and estimation of damage caused by SLR by identifying the economic and social impacts of SLR to the Mekong Delta region.

Set up the theorical framework analytical and framework for the research

Assess and estimate the socio- economic damage of SLR in MRD

Calculate the cost of the mixing grey and green infrastruct ure when apply in MRD

Apply cost- benefit analysis to get the most effective adaptation option for MRD

Assess the costs of mixing grey and green infrastructure to adapt to SLR in MRD.

Cost benefit analysis: Based on the results from previous step, benefit cost analysis is conducted to evaluate the effectiveness of mixing grey and green infrastructure.

Scope of the research

In general the research tries to assess the impact of SLR in MRD aiming to calculate the effectiveness of the grey and green infrastructures On the other hand, to confirm the effectiveness of mixing grey and green infrastructures, the research will also compare this solution with other solutions including current applications

In terms of content: The study will focus on estimating the damage value of dry land loss due to the impact of mean SLR, and estimate the population affected by this impact does not include other impacts such as SLR to coastal and marine ecosystem service, infrastructure and economic activities The effects of local extreme events are not within the scope of this study.

For adaptation measures, the study will focus on analysing the effective of mixing grey and green infrastructure and after that compare the effective of itself with other adaptation solution including the current adaptation was applying in MRD Currently, the Mekong Delta is applying the solution to build sea dikes in combination with mangrove to protect the mainland from the effects of SLR The study will compare this solution with the solution of lifting and constructing concrete dikes and alternating concrete dikes and mangrove in the coastal areas of the Mekong Delta.

In terms of time: The study will evaluate the impact of SLR in the 21st century under the SLR scenario provided by Tamura et al., (2019) and socio economic development scenarios SSPs (Share Socio economic Pathway) The study does not apply forecasts for longer time periods due to the volatility and uncertainty

Regarding the scope of space: The scope of the research space of the topic is the region of the Mekong Delta of Vietnam, including 13 provinces and cities directly under the region as prescribed by the Vietnam government.

Research Methods

Methods of collecting information: The study was conducted based on secondary data gathered based on articles and reports of the Government of Vietnam and international organizations for SLR impact analysis to the Mekong Delta and estimate the cost of implementing adaptation measures.

Methods of data analysis: The thesis uses the benefit cost analysis method to evaluate the effectiveness of mixing grey and green infrastructure.

Framework of the Master’s thesis

Figure 1.6: Logical framework of the research

Figure 1.6 presents the logical framework of the research To estimate the Socio economic impact of SLR in MRD, the inundation area will be identified by applying GIS The potential dryland loss and the population affected will be evaluated by different Socio economic scenarios Next, adaptation options – mixing grey and green infrastructure will be applied to reduce the inundation damage.

Finally, the effectiveness of the mixing grey and green infrastructure will be assessed by applying CBA in the various socioeconomic scenarios.

Overview of research in Vietnam and international

1.7.1 Climate change and climate change impact

Climate change is the global issue in 21 st century It was defined as “a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties and that persists for an extended period, typically decades or longer.” (Field et al., 2014) The recorded data present a dramatically changing of the global climate since the middle of 20 th century It was shown on these evidence: the rise of the global mean temperature, the warming of the oceans, the reduction of the ice sheets in the Greenland and Antarctic, the retreating of the glacial around the world, the decreased of snow cover in the Northern Hemisphere, the rising of the global mean sea level, the increasing of the extreme events, etc

The global warming is the main reason of climate change caused by the greenhouse effect However, there is high agreement that the human activities are the main reason which maximizes the greenhouse effect causing the rising of global temperature and the rapid climate change This process is immutable and will impact for the continues centuries

The impact of climate change is happening which is significantly affected both on human and environment in global scale It is expected to continue and intensify in the future One of the worst impact of climate change is that the melting of the ice sheet at the poles causes an increase in the average sea level leading to the inundation risk in the coastal areas, especially some areas may disappear completely Climate change also increases the appearance of the extreme event such as drought, flooding, hurricane or storm Moreover, it also has strong effect on the environment, ecological balance, causing biodiversity loss and destroying the food chains These impacts will create the economic damage and social unrest, especially in the developing countries Therefore, it is necessary to reduce the effect of climate change

1.7.2 SLR and SLR impact in the 21 st century

SLR is one of the main results of climate change Although it is changing during the history of Earth, it becomes faster than the previous history under the impact of anthropogenic climate change Since the 1990s the average global sea level has increased 3mm/year and is still rising during the 21 st century (Field et al.,

2014) Until the last 21 st century, the global mean sea level may rise 0.3 1.2m under using the different RCPs scenarios (Kopp et al., 2014) and 0.28 1.31m with the different concentration scenarios (Mengel et al., 2016) According to the IPCC AR5 (Field et al., 2014), the global mean sea level has increased 5m during the last 3 million years and still increasing It is predicted that global mean sea level will rise 26 82cm at the end of this century Jevrejeva et al (2016) also estimate that medium SLRs may continue up to 52 63cm with the global temperature rise 1.5

2°C by 2100 respectively On the other hand, Nauels et al (2017) has estimated that in 2081 2100 the mean sea level will rise 5 19mm per year based on each Share Socioeconomic Pathways scenarios (SSPs) This phenomenon is caused by three main reasons under impacts of climate change: thermal expansion, melting glaciers and loss of Greenland and Antarctica’s ice sheets

It is a challenge to identify the direction socioeconomic impact of SLR on coastal area The impacts depend on the “geologic setting and physical and ecological processes operating in that environment” (FitzGerald et al., 2008) It does not only affect the change of coastal habitat but also inland, causing extreme weather events such as storms or floods to become more frequently and stronger In addition, it may also lead coastal soil erosion, aquifers and saline agricultural land,reducing the habitat of coastal flora and fauna These impacts are the main causes affecting human activities in the coastal area, forcing people to migrate to other areas causing economic and social instability It may lead to the changes in land use when the area of land is narrowed, cause of the economic conflicts and social unrest(Goldemberg et al., 2000; Field et al., 2014).

Asuncion & Lee (2017) pointed out that SLR will be impacted by economic growth, migration, and tourism European Climate Research Alliances has mentioned that SLR will be a threat to human and infrastructure in the coastal area which is in the low lying coastal regions living area of 10% world population (about 0.7 billion people) Moreover, it also has impacts on the biodiversity, ecosystem and creates a more extreme events such as flood, inundation, storm or hurricane Mimura (1999) showed the vulnerabilities of island nations in South Pacific to SLR Inundation and flooding can have a major impact on these countries which is located in the low elevation, leading to changes in population growth and migration of small islands to bigger islands for less risk These areas need to focus on climate change adaptation solutions rather than mitigation Ericson et al (2006) has conducted an analysis on the effects of SLR on 40 river deltas in the world The results suggested that SLR could be a major cause of flooding and erosion in these area that will affected on 8.7 million people and 28,000 square kilo meters of plain by 2050 FitzGerald et al (2008) focused on the inundated impact by SLR to the island and low land area, especially in the large river delta or high population density Neumann et al (2015) estimated the total population in the coastal area in global scale and the number of people likely to be affected by the sea level in the future The results show that the number of population exposed by SLR increases in proportion to population growth in coastal areas, of which Vietnam is one of the countries with the highest total population in this area Besides that, the total population facing with SLR might be one of the highest countries in Asia along with China, India, Bangladesh, Indonesia in 2060.

The cost of damage by SLR in the coastal area is an important element to calculate the total damage of climate change in the future, contributed to the designing and choosing climate policy (Asuncion & Lee, 2017)

The concept of adaptation mentioned by the IPCC in its first reports systems, in response to actual or expected climate stimuli or their effects, that moderate harm or exploit beneficial opportunities” Each impact of climate change on different subjects will have different adaptation measures (Nicholls, 2015) mentioned that adaptation to SLR should include activities that adapt to moderate and extreme increases He also pointed out that the current major adaptation activities focus on responding to events and disasters rather than forecasts for a long term, active adaptation plan.

Adaptation strategies can be divided into three main ways (IPCC, 1990;

Bijlsma et al., 1996; Klein, 1999;Linham & Nicholls, 2010):

 Retreat all the human system is driven deep into the land through changing plan, develop policies and migration activities.

 Accommodation mitigate impacts by adjusting human activities in coastal areas through land use changes, early warning systems, flood and insurance adaptation measures.

 Protect system infrastructure has been built in the coastal area to reduce the impact of SLR These protect strategies can be hard infrastructure or soft armouring.

The adaptation strategies should not only focus on the initial impacts but also carry out the potential impact in the future On the national or local scale, it is necessary to consider the complex interaction between humans and the natural system on the coastline Therefore, it is essential to ensure the long term effectiveness and to consider carefully.

Based on the main solutions to adapt to SLR, many studies have been carried out on a global and regional scale to calculate the feasibility of each solution in practice Hallegatte et al., (2013) suggested that adaptation measures should be applied and upgraded to achieve the goal for minimizing the potential adverse due to topographic conditions, other factors such as erosion and local wave model (Gornitz, 1991) Klein & Nicholls (1999) confirmed the complexity and the necessary for many solutions to adapt to SLR in coastal areas To date, the previous study in national and local scale in European countries revealed the higher adaptation cost in the higher level of risk or very high adaptation standard There is a large number of published studies (e.g.Diaz, 2008; Hinkel et al., 2010 ; Lincke &

Hinkel, 2018) confirmed the effectiveness of protection solution to adapt to SLR.

For some developing countries, adopting adaptation solutions in equivalent to those of the Netherlands or the Gulf of Mexico is not affordable (FitzGerald et al., 2008).

For some areas, the only solution to adapt to SLR is to retreat from low lying coastal areas to higher areas

Indeed, adaptation strategies are often aggregated from more than one approach, and most assessments currently focus on retreat or protection without considering accommodation.

The protection strategies have been used for a long term to minimize the impacts of flooding due to the increase in the water of rivers or storm surge They can be applied in various options such as hard engineering techniques such as seawalls, breakwaters, or revetments In recent years, there is a new trend focusing on biological solutions like using natural protection which can bring more natural benefits than traditional hard infrastructure solutions It also has shown the effects without disturbing the natural coastal environment throughout our development history The subtropical and tropical regions have emphasized the current trend of protecting and restoring coastal mangrove to the impacts of nature and humans

Grey infrastructures are defined as artificial constructions and structures such as embankments, reservoirs, canals, etc which have built in the river basin or coastal areas (Browder et al., 2019) To adapt to SLR, the grey infrastructure can be

In which, the sea dike is a rigid coastal barrier that has been established along the open coast and is widely applied in the Netherlands, East Asia, and part of North America On the open coast, sea dike is always the first choice to protect this area The material of the sea dike can be artificial or natural materials consisting of earth In addition, some countries had made use of it for multifunction Take Netherlands as an example, the sea dike also as a road or highway

METHODOLOGY

The history of CBA and reasons for CBA

In the beginning, the CBA based on the ideas of Benjamin Franklin and Joseph Priestley in 1772 Dupuit (1844) developed a method of cost benefit analysis considered to be the first in the world (Dobes, 2008) Later, CBA was more widely used in the early 19th century (Shabman, 1997) Until the early 20th century, CBA was used in the US to analyse the impact of floods on the Mississippi River Up to

1930, CBA was applied to the US Flood Control Act and then to the US Army Corps of Engineers In the Netherlands, CBA has been applied to benefit cost analysis for the construction of a coastal protection dike system under the influence of the Southern Sea (The Zuiderzee) since 1901 and subsequently widely used in the infrastructure construction, water management After that, it was developed and improved for other areas such as education, labour market, or health care(Cabinet,

2014) (Fritz and Zwaneveled, 2017) In Australia, studies using CBA were carried out in the late 19th century with the main objective is calculating the cost of benefits for the nation's rail construction project even though the results were not considered as an official reference to government decisions (Cabinet, 2014) InFrance, the theory of CBA was recorded in the 19th century regarding infrastructure appraisal And since the 1960s, the CBA has been recognized as an effective tool for appraising public investment and public policy (Pearce et al., 2006).

CBA is now widely used in developed and developing countries The US government mentioned that cost benefit analysis is a “guidance to heads of executive agencies” which “all benefits and costs can be quantified and expressed in monetary units, benefit cost analysis provides decision makers with a clear indication of the most efficient alternative, that is, the alternative that generates the largest net benefits to society (ignoring distributional effects).” Although the economic benefit is not the only goal of some policies, CBA is still considered a useful tool to show its effectiveness with decision makers and the public who received it Therefore, CBA is widely used by the US government on environmental issues and policy In developing countries, under the recommendations of the World Bank, CBA has applied to analyse the impact of different projects, especially in World Bank's environmental investment projects (Atkinson & Mourato, 2008).

The OECD (Pearce et al., 2006) has listed the benefits of CBA when compared to other tools, specifically as follows:

Firstly, CBA provides a re structured model that not only helps to calculate benefits and costs, it also helps address the beneficiary and non beneficiary to consider decision making.

Second, CBA also analyses alternatives to achieve set goals.

Third, CBA has the ability to help determine the maximum benefits of the project Thereby helping to choose the highest benefit option

Fourth, with a full analysis, CBA can show the total cost and benefit for the various social aluminium profiles of both the beneficiaries and the project affected.

Fifth, CBA shows the value of the project at different times when discounted to the present Because the value of future money will differ from the present value depending on market factors, CBA helps to consider the value of project benefits and costs in the future when they are returned.

Sixth, CBA clearly shows the priority of the policy, it shows what the decision maker wants.

From the perspective of environmental economists, the current CBA analysis is still considered to be the most reliable solution and the most professional economic tool to choose the right adaptation solution in the right situation.

Uncertainty is overcome by project sensitivity analysis In the climate economy, there is still a lot of controversy regarding the application of CBA as a decision analysis framework that helps provide advisory information to support decision making However, it is still widely applied in adaptive selection models such as DIVA, CosMos and CIAM due to its benefits when comparing with other methods such as Cost Effective analysis

Therefore, this research decided to choose CBA as the main method to analyse the effectiveness of mixing grey and green infrastructure.

Outline the methodology

Figure 2.1 outlines the overall of methodology First, the SLR scenarios and the socio economic scenarios was collected in the global scale and need to downscale to apply for MRD The SLR damage without adaptation was calculated by three components: the inundated area, the potential population affected and the economic damage The SLR damage with the adaptation of mixing grey and green infrastructure was calculated by the inundated area, the potential population affected, the economic damage and the cost and benefit of mixing grey and green infrastructure Finally, the effectiveness of mixing grey and green infrastructure was assessed by CBA.

Cost­benefit analysis model

The CBA model is described in the figure 2.2 The damage of SLR in no adaptation scenarios by primary impact on dry land loss and potential population affected in the worst case was monetized by the different socio economic scenarios.

The negative impact of adaptation scenarios was monetized with the different dike height scenarios to get the most effectiveness adaptation scenarios Based on this results, the cost and the benefit of mixing grey and green infrastructure was evaluated Finally, the effectiveness of mixing grey and green infrastructure was assessed by CBA The effectiveness of other adaptation solution will do with the same model.

Figure 2.2: Cost benefit analysis model

The research applied the basic model of cost benefit analysis (CBA) Some preparatory steps need to be carried out in CBA The method of CBA has the following seven step procedures.

Step 1: Define the scope of analysis

The first step determines the range of the research The geographic scope and the payback period should be identified These factors may influence the results.

This study measures the costs and benefits affecting the socio economic region of the MRD in Vietnam in the 21 st century The mixing grey and green infrastructure will set up base on the option:

“A concrete dikes system with 4 meter height is built in the areas without mangrove The mangrove forest can grow in the possible area The life span of concrete dikes is 100 years, the lifetime of mangrove forest is 50 years and the growth period of mangrove forests is 10 years before performing its protection function.”

SLR has the strong impact on the costal line and low lying area such as MDR The potential direct impact of mean SLR on this area were mentioned in the fifth assessment report of IPCC (2014), specifically:

 Loss of land and land uses

 Loss of coastal and marine ecosystem services

 Damage to the environment and human activities.

Step 3: Quantify the predicted impacts

There are many factors that can affect both cost and benefit However, due to the limitations of existing data, This study focused on some market and non market factors The benefits assessed in this study only include land use value when land areas are protected, socially, the number of local populations protected from the effects of rising sea levels The project cost is the total cost of construction cost, maintenance cost, and upgrade cost.

Table 2.1 summarizes the indicators to estimate costs and benefits.

Table 2.1: Cost and benefit of adaptation solution to reduce the damages due to inundation by SLR in MRD, Vietnam.

Construct cost Avoiding the economic loss of land loss by inundation due to SLR Maintenance cost Protected population in the inland area

Upgrade cost The forestry production and timber benefit from the mangrove forestInundation damage if the dikes is breached The fishery/ aquaculture of the

The economic damage is estimated directly by the object based approach (Karlsson and Larsson, 2014) In other words, the cost is estimated by multiplying the number of affected objects by the corresponding standard value In particular, the economic damage of inundated area is calculated by multiplying the inundated land by each land use and the corresponding land price set by the Vietnam’s central government The cost of adaptation option can be calculated as the economic damage from dryland loss which applying the object based approach The value of these factors will change over time There is uncertainty regarding calculating these future values Therefore, the application of socio economic development scenarios is an ability to analyse the sensitivity of the project

Step 5: Discount to get the present value

To determine the final outcome of CBA, converting the costs and the benefits in the future is an important and necessary step The present value of cost and benefit could be the sum of all costs and benefits, “present and future with each year’s cost and benefit discounted at the selected rate” (UNDP, 2018) The discount rate is important to get the final results especially in the environmental management and climate change case and also raise the question of which discount rate value is appropriate for the project (Saez and Calatrava, 2006) The costs and benefits in the future may decline in high discount rate In contrast, the results are greater in low discount rates The present value of cost and benefit of the project at time t with the discount rate r is calculated using the following formula:

The present value of benefit: PVB = ∑ t=0 n B t

The present value of cost: PVC = ∑ t=0 n C t

Step 6: Calculate the net present value

The final result of CBA is the difference between the costs and benefits of the project and can be expressed in three ways:

 Net present value (NPV) is the difference between the present value of benefit and cost.

When NPV> 0 that is the benefit is larger than the cost and the project can be accepted In the case of multiple compared projects, the project in which the largest NPV will be selected.

The benefit cost ratio (BCR) is the ratio of benefit to cost of the project A project with a BCR greater than one is acceptable.

 Internal rate of return (IRR)

The internal rate of return (IRR) is the value of the discount rate at which the net present value of the project is zero or the present value of the benefit is equal to the present value of the cost If IRR is higher than the rate of return on alternative investment, the project can be accepted.

Step 7: Perform expected value and/or sensitivity analysis

Some variable factors of CBA can be uncertain than others Applying a sensitivity analysis can identify the level of the impact of factors to the final results.

It might be useful to identify the important factors that can be further assessed to get more precise results This analysis provides more information when considering project options before proceeding The basis of a sensitivity analysis is considering impacts of the change in the discount rate on the output of CBA

The selection of the discount rate has been instrumental in conducting cost benefit analysis Both TBCS (2008) and ADB agree that the discount rate should be determined between 3 to 7 percent based on the project and its length Zhuang et al.

(2007) mentioned that developing countries should use the interest rate of 8% or higher rate due to the risk and uncertainty of the projects in these countries The Australian Government has proposed a discount rate from 3% to 10% of which 8% is used to calculate on the long term project to ensure profitability comparing with the private project.

In private sector, as the opportunities cost assessment, the rate of 3% and 10% are used to calculate the sensitivity of the analysis (Vo Thanh Danh, 2012) use the rate of 3%, 6%, and 10% in their CBA; Coastal Protection for the Mekong delta (CPMD) uses the discount rate of 5%, 8%, and 10% to calculate the cost and benefit corresponding to each adaptation option based on the different length of the project.

As a result, this study will use the discount rates of 3%, 8% and 10% to calculate the cost and benefit of the dikes system and the sensitivity analysis.

Data

This study is based on secondary data including economic data and geospatial data These data are considered as accurate, based on official information of Vietnam government and international organizations such as GIZ for the MRD.

Table 2 presents elements and sources of the data.

Table 2.3: Data sources and description

Input data Entity Attribute Source Note

SLR scenarios in global scale

Txt Raster Global assessment of the effectiveness of

Based on the RCP8.5 of MICROC adaptation in coastal areas based on RCP/SSP scenarios (Tamura et al., 2019)

MRD land use planning to 2020

Ministry of Agriculture and Rural

National institute of agricultural planning and projection MRD

GADM (World Wide Fund for Nature) version 1.0

Detail to province administrativ e level in 2015 Land price bracket

Average land use price based on Decree 44/2014 / ND CP of Vietnam governmentPopulation Number Person/km 2 General Statistic Population

MRD as district administrativ e level

Based on Statistic Yearbook of Vietnam 2010

Sea dikes cost Number Coastal

Protection for the Mekong delta (CPMD)

(2008) and Mai et al (2008) in Vo Thanh Danh (et al., 2012)

Based on current situation and the planning of the central government

Protection for the Mekong delta (CPMD)

Based on 13 mangrove planting projects that have been successfully implemented in the Mekong Delta region MRD historical coastlines map

Based on the data of

(Deutsche Gesellschaft für Internationale Zusammenarbeit:

The inundation data was determined by the difference between sea surface height and the elevation of land (Tamura et al., 2019) Sea surface height data is based on Mean Higher High Water Level from TPXO7.2 (Egbert and Erofeeva, 2002); sea surface height from General Circulation Model (GCM) from MIROC

ESM model (Watanabe et al., 2011) The topography data is provided by NationalCentres for Environmental Information (NOAA) with 1 arc minute global relief model of Earth surface These data focus on ordinal inundation due to SLR and astronomical tide but do not take into account other temporarily factor effects on sea level such as subsidence or extreme events (Tamura et al., 2018)

Figure 2.3: The potential inundated area in MRD by SLR in 2100

In the last few years, the world scientist had tried to model the global socio economic growth in the 21 st century Shared Socio economic Pathway (SSPs) is an important input for the global climate forecasting models, which are the recent reports of IPCC such as IPCC AR5 (2014) and IPCC 6th assessment report will be released in 2021

Five socio economic scenarios have been applied based on the IPCC ShareSocio economic Pathways (SSP) (O’Neill et al., 2014) for global scale and rescaling by Murakami and Yamagata (2016) to estimate the potential damage bySLR in MRD in the future The SSPs are based on the different storylines in various social and economic development scenarios The SSP1 (Sustainability) presents a sustainable development world that focuses on environmental protection, social welfare, and sustainable consumption that minimizes the consumption of natural decrease in the 21 st century The SSP5 scenarios (Fossil fueled Development) has similar storylines to SSP1 in terms of economic development as well as population growth, however in this scenario, the economic growth based on the promotion of fossil energy and natural resources consumption SSP2 (Middle of the Road) assumes that the world has a moderate growth in both population and economy in the future, while SSP3 and SSP4 describe the storylines less optimistically in the global development with less investment in social welfare, the population continues growth through 21 st century in increasing the social inequality

In summary, the SSP1 and SSP5 introduce the scenarios of rapid economic development with the decline of the population SSP3 and SSP4 represent a scenario of slow economic growth accompanied by population growth and SSP2 emerging the medium economic and population growth worldwide

Figure 2.4: World population and GDP in different SSP scenarios (Source: IIASA,

The secondary data of the MRD’s socio economic were collected from available sources of Vietnam government The economic and population information was provided by Vietnam and Mekong’s Provincial statistical yearbooks The land use data was aggregated by MARD for each province in theMRD The value of land use is based on the Vietnam government regulations In fact, this value does not represent the market value of the land, but it is used for compensating or supporting to the landlord when the damage occurs This value is averaged on the land tariff, because the tariff is based on the location of the parcel and there are large ranges between different price points The costs of sea dikes and mangrove construction are calculated by Vo Thanh Danh (2012) and CoastalProtection for the Mekong delta (CPMD, 2017) which related to current situation and previous research.

Estimate costs of adaptation options

The cost of adaptation is calculated by multiplied the length of the protection area by the unit cost of each adaptation options and adjusted by economic growth rate of the different scenarios then summed to get the total cost The cost of adaptation is calculated by:

A C A =UC A × PI t × L A where: AC A ¿ total cost of adaptation option A (US$) under SSP1 5

UC A ¿ unit cost of option A (US$/km)

L A ¿ total length of option A (km)

PI t ¿ price index in year t under SSP1 5

Estimate benefits of adaptation options

The following steps describe how to calculate the benefit of the adaptation option to adapt to SLR in MRD Benefit categories were selected in accordance with the focus of this thesis: inundation in rural area The benefit of the protection option can determined into two types: first is the economic damage can be avoid by applying the mixing grey and green infrastructure including (1) economic loss of the dryland inundated, (2) number of population affected by SLR and second is (3) the add benefit of the mangroves forest

2.6.1 Estimate the economic damage of dryland loss can be avoid

The economic damage of dryland loss is the value of lost dry land As same as Hinkel and Klein (2009), the value of dry land loss can be estimated by multiplying the inundated area and the value of land according to the Vietnam government regulations The values are based on the economic growth rate of SSP scenarios and summed to the total damage The cost of land loss was calculated by the assumption that the type of land use and the policy of Vietnam government may not change until the end of 21 st century The cost of land use is estimated by:

DC = COST landuse i =∑UC i × PI t × Area i where: DC= COST landuse ¿ total damage in dry land of type i (US$) under

UC i ¿ average unit cost of land use i (US$/m 2 )

Area i ¿ total of potential inundated area of land use i (m 2 )

PI t ¿ price index in year t under SSP1 5 The benefit of the adaptation option can calculate as below:

Where: B = Benefit of the adaptation ∑ DC 0 = The economic damage without adaptation

∑ DC A =The economic damage with adaptation option A

2.6.2 Potential affected population by SLR

The total affected population by SLR in MRD was calculated by the population at the province level multiplied with the rate of inundated area and then summed to get the results in different socio economic scenarios (SSP1 5) with the assumption that the population growth rate in MRD is equal with Vietnam population growth rate (Wolff et al., 2016) The affected population was estimated by:

Po affected i ,t =∑ Po i ,t ×r i ,t where: Po affected i ,t =¿ the potential population affected by SLR in district i in year t

Po i ,t ¿ the total population of province i in year t and was given as

Po i ,t = Po i ,2010 × a t which a t was the population growth rate in year t from 2010. r i ,t ¿ Potential inundated area of provincei(km 2 )

Total areaof provincei(km 2 ) , the rate of inundated area in province i in year t

Applying ArcGIS software

To map and address the inundation area in MRD, the research used ArcGIS 10.7 to perform The specific steps taken in this study are described below:

The input data was collected in various sources and raw data It needs to be converted before applying in ArcGIS/QGIS environments The steps to perform data processing are described as below.

In this part, the different layers are added to the GIS environment and corrected geometrically (Georeferencing) after that Some other adjustment related to projection and Transformation are also made

The base map used in this study is the inundation map in global scale are obtained in txt file First, the data on SLR was transformed into shapefile and added the georeferencing by the ArcCatalog It is corrected geometrically (Georeferencing) together with land use data and then is referred to the coordinate system.

Land use planning is presented separately for each province, but to shorten the time and unnecessary steps, they are aggregated through the Merge Vector layer in the Data Management tools function of the Vector box on the QGIS toolbar As a result, the land use plan for the whole Mekong Delta swings in a shapefile.

The administrative boundary map also needs to be corrected geometrically (Georeferencing) together with land use data and then referred to the coordinate system

The 21 st SLR scenarios and the MRD Administrative area map were in a projected coordinate system in EPSG:4326 – WG 84 – Geographic therefore need to transform into a Projected Coordinate System: EPSG:32648 – WGS 84 / UTM zone 48N which is the same with other maps and suitable to analyse the Vietnam geography data Finally, all the map is received UTM zone 48N Projection coordinate system as a spatial reference.

The land use planning data and the shoreline layer had some geometry problem To fix them, these classes were repaired Geometry to delete the Geometry error by Repair Geometry function in Arc Toolbox

ArcGIS buffer tool was used to prepare and analyse the data This function helps to create a specific boundary of the mangrove data based on the designated distance to calculate the length of the coastline where mangrove can be substituted for the sea dikes

After processing the SLR and land use planning data or administration map, to determine the area of the flooded land, Clip (cut) parameter SLR map based on the land use map should be done The inundated area due to SLR was divided by land use and by administrative area

Similarly, to determine the length of the sea dikes and mangrove system, the MRD Coastline in 2017 was overlaid with the Administrative map and Mangrove forest map and after that use Clip function to get the results

To estimate the potential inundated area and the length of sea dikes and mangrove forest, the map of the total inundation area, the sea dikes and mangrove line as the result of previous step were calculated by “Calculate Geometry”,respectively Finally, the total potential inundated area by square meters and the length of sea dikes and mangrove forest by kilometres were obtained.

RESULTS

Socio­economic damage of SLR without adaptation

Figure 3.1 indicates the inundation area in the different time in the 21 st century with the SLR scenarios in RCP 8.5 of MIROC ESM (sea Section 1, Appendix A).

Figure 3.1: The potentially inundated area by land use in MRD in the 2020, 2050,

Figure 3.2: Potentially inundated area due to SLR in MRD in the 21 st century

Figure 3.2 shows the potentially inundated area due to SLR in MRD in the

21 st century without adaptation solution As indicated in Figure 3.2, total potentially inundated area in the Mekong Delta will increase 25,368 km 2 from 2010, counting for 62.6% total area in MRD To 2050, approximately 36,000 km 2 will be inundated, counting for nearly 89% area of MRD To 2100, the inundation area has little significant change comparing with 2030 In 2100, the inundated area of MRD was nearly 36,910 km 2 , which counts for more than 90% of the total area It really has the strong impacts on environment, fauna and flora, socio economy on MRD.

To simplify the calculation for the value of land use loss due to SLR, the land use is grouped into seven main groups which may occupy most of area of MRD, including: land for cultivation of annual crop including paddy field and land for cultivation of other annual crops; land for production forests; land for aquaculture; land for cultivation of perennial trees; rural residential land; urban residential land and land for salt production.

La nd fo r c ult iva tio n o f a nn ua l c ro ps

La nd fo r p ro du cti on fo res ts

La nd fo r a qu ac ult ur e

La nd fo r c ult iva tio n o f p ere nn ial tr ee

Ru ral re sid en tia l la nd

Ur ba n r es ide nti al lan d

La nd fo r s alt pr od uc tio n

Figure 3.3: Land use of potentially inundated areas due to SLR in 2100 in MRDFor more details, Figure 3.3 indicates that agriculture, aquaculture and residential area would be mainly flooded in 2100 As SLR 1 meter, almost land for cultivation of annual crops including paddy fields, land for cultivation of perennial tree will be inundated with 93% land for cultivation of annual crops, 95% land for aquaculture, 89% land for cultivation of perennial tree, 93% land for rural residential, and 85% land for urban residential will be inundated It not only impacts on agricultural activities – the main livelihood of the majority of people in the region but also impact on their living standard and especially the ability to ensure the food security when the MRD is the main source of 50% and 60% of Vietnam rice and fishery production, respectively.

3.1.2 Population at risk from SLR

Figure 3.4: The potentially inundated by districts in MRD in 2020, 2050, 2100 respectively.

Figure 3.4 illustrates the potentially inundated area by provinces in the 21 st century Coastal provinces including Ben Tre, Tien Giang, Tra Vinh, Soc Trang,Bac Lieu, Ca Mau and Kien Giang will be inundated in the early 21 st century, and inundated areas will gradually increase inland To 2100, only a part of An Giang and Dong Thap provinces may not be at risk of SLR (see Section 1, Appendix A)

SSP1 SSP2 SSP3 SSP4 SSP5

M ill io n p eo p le /y ea r

Figure 3.5: Total population at risk from SLR in MRD in 21 st century

Figure 3.5 presents the total population at risk from SLR in MRD in the 21 st century without adaptation under five socio economic scenarios (SSP) The highest value reaches nearly 20 million people under SSP3 in 2100 The remaining scenarios show the declining trend of the number of total population at risk until the end of the 21 st century They are slightly different between SSP1, SS5, SSP4, and SSP2 SSP2 presents slower decline trend than other scenarios

Almost all provinces in MRD may be at high risk of inundation due to SLR which over 90% of these provinces may be inundated by the middle of this century.

In particular, the provinces of Vinh Long, Soc Trang, Bac Lieu and Tra Vinh may be inundated up to 99% by 2030 without adaptation solution Two provinces, Dong Thap and An Giang may have the lowest inundated area in 2100, and less than 80% of provinces may be under the sea It may lead the mass migration of population in the MRD especially in the provinces with high population density such as TienGiang (702 person/km 2 ), Can Tho (891 person/km 2 ), and Vinh Long (689 person/km 2 ) (GSO, 2018), increasing the pressure on the infrastructure, economic and social welfare in other regions (see Section 2, Appendix C).

3.1.3 The economic damage without adaptation

The average unit price of each land use was multiplied by the price index of each year according to SSP, in order to estimate economic damage of land changes over time

Table 3.1: The unit cost of land use by SSP1 5

Land for cultivation of annual crops

Land for cultivation of perennial trees

Urban residential land SSP1 656.88 1,512.79 2,795.20 3,767.61 4,650.13 6,045.37 7,418.01 9,453.07 10,268.39 12,028.76 SSP2 669.23 1,512.79 2,637.58 3,387.66 3,982.26 4,733.80 5,884.42 7,814.51 8,431.99 9,788.66 SSP3 676.87 1,512.79 2,531.46 3,062.75 3,375.79 3,782.60 4,244.92 4,804.74 4,976.59 5,373.59 SSP4 676.25 1,512.79 2,499.90 2,980.40 3,282.03 3,700.58 4,186.48 4,804.97 5,004.46 5,450.42 SSP5 650.86 1,512.79 2,903.83 4,141.84 5,416.00 7,404.92 9,755.83 14,301.77 16,132.86 20,135.63

The total economic loss due to SLR by land use can be calculated by Table

2 Monetary values were converted to 2010 US 1 dollars with the exchange rate in

SSP1 SSP2 Year SSP3 SSP4 SSP5

Figure 3.6: Economic losses due to SLR in MRD in the 21 st century

Figure 3.6 gives the overview of the economic losses due to SLR in MRD without adaptation under five socio economic scenarios (SSP1 5) The damage affected annual growth significantly in both scenarios Under SSP5, damage cost is the highest in all SSP scenarios which reached 22,943 billion US$ in 2100, counting for more than 0.5% national GDP There is the slight difference between SSP3 andSSP4 They also have the lowest economic damage due to the smaller economic growth and their loss ranged 0.2% 0.5% of national GDP (see Section 1, AppendixC).

The economic loss in the different adaptation scenarios

3.2.1 The potential inundation area with adaptation

Due to impacts of SLR in Vietnam, the central and local government had a project to set up a sea dikes system along the coastal line including MRD A sea dikes system will be built and improved based on the current situation to response to impacts of SLR The plan is implemented according to the roadmap from 2010 to

2030 with the main goal is protecting the entire Mekong delta region from the impact of SLR and climate change

Four scenarios of adaptation solution are used to calculate their effectiveness as follows:

- Sea dikes system with 1 meter average height

- Sea dikes system with 2 meter average height

- Sea dikes system with 3 meter average height

- Sea dikes system with 4 meter average height

1m dike height 2m dike height 3m dike height 4m dike height Without adaptation

Figure 3.7: Comparison of land use loss due to SLR in MRD with and without adaptation solution (km 2 /year)

Figure 3.7 showed the impact of SLR in MRD with each option and compared with without adaptation option by the land loss (km 2 /year) by year (see Section 2, 3, 4; Appendix A).

Through Figure 3.7, the inundated area and economic damage of SLR can reduce significantly with the height of sea dikes along the coastal line With 1 m to

3 m dikes system, MRD may begin to be at risk of inundation in 2050, 2070, 2100,respectively With 4 meter dikes height, swinging the MRD will no longer bear at risk of inundation in the 21 st century It shows that the raising sea dikes system can perform well for the protection level of the inland area (See Section 2, 3, 4;

The most interesting thing is it also shows that the current adaptation situation in the MRD cannot fully protect this area along the 21 st century in case the height of the sea dikes is non uniform (2.5 meters to 4 meters)

3.2.2 The economic damage with adaptation

Along with the reduced inundating time corresponding to the height of the dyke, the damage value is also recalculated to the adaptation scenarios mentioned above Figure 3.8 illustrates the damage cost with adaptation measures without discount rate The figure shows that adaptation dramatically reduce the economic damage in all socioeconomic scenarios with 1 meter height of sea dike, the total economic loss reduces from 5,500 billion USD to nearly 6,700 billion USD in different scenarios The economic loss can be reduced in proportion to the dike height When the height of the dyke is 4 meters, the damage will be zero.

SSP1 SSP2 SSP3 SSP4 SSP5

Total economic loss without sea dike Economic loss with sea dike 1 meter height Economic loss with sea dike 2 meter height Economic loss with sea dike 3 meter height Economic loss with sea dike 4 meter height

U ni t: B il li on U SD

Figure 3.8: The damage cost of SLR with different adaptation option (no discount

Cost of adaptation options

This study is calculated by the assumption that the MRD still do not have any concrete dikes In order to carry out its protection function, according to technical design standards, the sea dikes system must have an average life expectancy of at least 50 years and be able to adapt to the effects of other extreme weather events Currently, the coastal region of Mekong delta has chosen to build a dikes based on the project simulation wave level: the earth dikes will be selected with the wave lower than coal 0.5 meter and for the higher wave an earth dikes with a hard revetment will be selected (CPMD, 2017) This study will compare costs of existing dikes construction and upgrade to the concrete dikes system or combination between mangrove and concrete dikes with a stronger structure and a longer life span Due to the lack of practical data on the cost of dikes construction, the cost values are calculated by the government's budget and CPMD (2017) with current dikes construction costs Concrete dikes construction cost is based on the calculation of Vo Thanh Danh (2012) Both CPMD (2017) and Vo Thanh Danh

(2012) estimated the construction cost of the dikes including labour costs, material costs and land use cost These estimates are crude costs (CPMD) that do not include disaster mitigation costs and do not take factors such as inflation and other additional costs into account

In reality, the mangrove cost is calculated by the initial cost as well as protection cost to protect mangrove avoiding the effect of sea water until it can perform the protected function The initial cost of reforestation depends on the type of tree, the location and the preparation before planting Henk (2018) shows that the cost of planting mangrove can vary from 13 million VND/ha to 80 million VND/ha, depending on the planting location Planted mangrove are assumed to be replanted once more to include the cost incurred due to the damage of storm The cost of the planting mangrove is calculated by GIZ based on the cost of 13 successful projects in MRD and it was determined as 172 million VND/ha Maintenance costs were determined at a relatively high level, 160 million VND/ha including mangrove protection costs such as wooden and bamboo fence Most of this expense comes from labour costs and is only counted within the first 10 years after afforestation (Tas, 2016).

The Vietnamese government's strategy for adapting to SLR in the Mekong Delta region stipulates that the mangrove belt width should have at least 500 meter or more to protect the earth dikes behind However, a mangrove belt with 350 meters width can greatly reduce the impact of waves in MRD (CPMD, 2017; Quang Bao, 2011) Therefore, this study assumes that a mangrove belt with the minimum width of 350 meter can have the same function as a 4 meter height of sea dikes.

Cost of afforestation and maintenance cost

- A mangrove belt with 350 meter width means 350 m 2 of mangrove along 1 meter coastal line or 0.035 ha/m This will cost 0.035*172 ¿ 6.02 million VND/m for planting and 0.035*160 ¿ 5.6 million VND/m for maintenance.

- Similarly, if width of mangrove forest is 500 meter, the planting cost is 8.6 million VND/m and the maintenance cost is 8 million VND/m

The unit cost has been recalculated to the common based year 2010 using the GDP deflation and the rate of economic growth by SSPs Table 4 shows the unit cost of adaptation solutions in 2010:

Table 3.2: Unit cost of adaptation options using dikes and mangrove in 2010

Upgrade the earth dikes to 4 meter height

Concrete dikes with 4 meter height

Mangrove belt with 350 meter width

Mangrov e belt with 500 meter width

Rebuilt cost 0.189 Sources: (Vo Thanh Danh, 2012), CPMD (2017)

Benefit of the mangrove forest

Besides protection, mangroves also create the economic benefits such as forestry production, timber or fishery The calculation of CPMD has shown that one hectare of mangrove forest in the Mekong Delta will provide 1495 USD of forestry and timber as well as 455 USD of fishery and aquaculture With the same calculation as previous part, one meter of mangrove forest has 350 meter width will have 68,28 USD total benefit per year; and the benefit value of 1 meter of mangroves forest with 500 meter width is 97,5 USD/ year.

Cost benefit analysis of mixing grey and green infrastructure

The coastline of the Mekong Delta has a length of 1,302 km including an estuary area of which 945 km can be planting mangrove forest It is assumed that the area's existing earth dike will be upgraded to 4 meters and no mangrove and concrete dikes have been built in the area This part presents the results of CBA of mixing grey and green infrastructure in MRD to adapt to SLR The mixing grey and green infrastructure as below:

A concrete dikes system with 4 meter height is built in the areas without mangrove The mangrove forest can grow in the possible area The life span of concrete dikes is 100 years; the lifetime of mangrove is 50 years and the growth period of mangrove forests is 10 years before performing its protection function

SSP1 SSP2 SSP3 SSP4 SSP5 0

Figure 3.9: Net present value and Benefit cost ratio of mixing grey and green infrastructure

Figure 3.9 illustrates the CBA of mixing grey and green infrastructure assume this apply in MRD in 21 st century The benefit of the mixing grey and green infrastructure is greater than the cost Both net present value and benefit cost ratio are higher than 1, that mean mixing grey and green infrastructure can be an effectiveness adaptation option The net present value is expected range from 2098 billion USD to more than 4000 billion USD The benefit is mainly from the economic loss reduce due to SLR impact The benefit contribution of mangroves forest is not significant compare with the protection function (see Section 1, Appendix D).

SSP1 SSP2 SSP3 SSP4 SSP5

Construction cost of sea dike Maintenance cost of sea dike

Figure 3.10: Cost contribution of mixing grey and green infrastructure

Figure 3.10 describes the cost allocation of mixing grey and green infrastructure The afforestation cost of mangrove forest only ranges from 4% to 5% of total cost More than 70% of total cost is for maintenance cost of mangrove forest It is higher more than fifteenth time compare with the afforestation cost and nearly seven time with the sea dike maintenance cost The main reason is mangrove forest occupy the majority of the system and the maintenance costs are approximately as afforestation cost.

Comparison of mixing grey and green infrastructure with other adaptation option

The following cases are used to compare the effectiveness of mixing grey and green infrastructure to other adaptation option including the current adaptation option Two comparation option are the cooperate between earth dike and mangrove, and concrete dikes The description details are as follows:

Option 1: Upgrade the earth dikes system to 4 meter height with new construction technology with the life span is 20 years, the sea dikes has a 500 meter width mangrove system with the lifetime is 50 years The growth period of mangrove is 10 years before performing the protective function.

Option 2: A concrete dikes system with 4 meter height, and the technical lifetime of this dikes is 100 years.

SSP1 SSP2 SSP3 SSP4 SSP5 0

Earth dike combine with mangrove forest Concrete dike Mixing grey and green

Figure 3.11: Cost of adaptation options under SSP1 5 without discount rate

Figure 3.11 presents the total cost to set up an adaptation solution to SLR in the MRD with different options under SSP 1 5 scenarios The chart showed that Concrete dike has the lowest cost and combination of earth dikes and mangrove forest has the highest cost in both scenarios Although the unit cost of earth dike and mangrove is the lowest, the life span of the earth dikes is shorter than concrete dikes and the rebuild cost increases the total cost of this option (see Option 2, Appendix D).

Table 3.3: Present value of the cost and benefit in different option (discount rate 3%)

B/C NPV Earth dike and mangro ve forest

Table 3.3 shows the present value of cost and benefit in each option The benefit of the earth dike combining with mangrove forest, in other words, mixing grey and green infrastructure is higher than the benefit from concrete dike although the BCR of the concrete dike is highest by the benefit contribution of mangrove forest

SSP1 SSP2 SSP3 SSP4 SSP5 0

Earth dike combine with mangrove forest Concrete dike Mixing grey and green

Figure 3.12: BCR in different adaptation options under SSP1 5

Table 3.3 and Figure 3.12 show the NPV and BCR of three adaptation options The NPVs and BCRs are similar according to different scenarios As seen from Table 3.3, all alternatives show positive NPV ranging from 2,090 billion USD (Concrete dike, SSP4) to 4,385 billion USD (Mixing grey and green, SSP5).

Overall, mixing grey and green infrastructure has the highest total NPV in all SSP1

5 scenarios although the BCR is lower than concrete dike option The results also indicate that the benefit of SLR adaptation can be greater than the cost to set up adaptation system The most positive alternative reveals that the cost of adaptation option equals 19.08 billion USD and the total benefit adds up to 4,404 billion USD(see Section 2, Appendix D).

Sensitivity analysis

Discount rate decisively contribution in CBA calculation In order to deal with uncertainty that may occur in the future, a discount rate is often applied to calculate impacts changing individual key factors As mentioned above, this study uses 8% and 10% values to compare its impact on results.

Table 3.4: Change in NPV and BCR in with discount rate = 8%

SSP1 SSP2 SSP3 SSP4 SSP5

Table 3.5: Change in NPV and BCR with discount rate = 10%

SSP1 SSP2 SSP3 SSP4 SSP5

Both Table 3.4 and Table 3.5 suggested that as discount rate has the strong impact on the final results of CBA When it increases, the values of NPV and BCR of the options decrease inversely proportionally The higher discount rate significantly reduce the benefit and cost mixing grey and green infrastructure, then the final outputs also decrease However, it still has the benefit greater than the cost (see Section 3, 4; Appendix D).

3.6.2 Change in width of the mangrove belt

As the previous section, assuming that the 350 meter width mangrove forest can have similar function to the 4 meter height of sea dikes To evaluate the impact of technical standards on the effectiveness of mixing grey and green infrastructure,this study continues to compare the impact of input data to the final result; in this case, the width of the mangrove belt to the outcome of the analysis Other inputs,such as the cost of the construction of dikes and the lifetime of structures, are kept unchanged, only the width of the mangrove belt is changed from 500 meters to 350 meters The below presents the corresponding change:

“A concrete dikes system with 4 meter height is built in the areas without mangrove, the mangrove forest will grow in the possible area, the life span of the concrete dikes is 100 years, the lifetime of mangrove is 50 years and the growth period of the mangrove forest is 10 years before performing its protection function.”

Table 3.6: Present value of the cost and benefit with the change in the mangrove width (discount rate = 3%)

SSP1 SSP2 SSP3 SSP4 SSP5

Table 3.6 demonstrates that the change in technical standards of inputs affected the results Comparing with Table 3.3, the cases where width of the mangrove forest decreased from 500 meters to 350 meters, the BCR of options increased 1.7 times with SSP1 5 scenarios

The sensitivity analysis shows the benefit can be still much greater than the cost even changing the discount rate and width of mangrove It also illustrated that discount rate and the technique standards has strong impact on the effectiveness of the mixing grey and green infrastructure (see Section 5, Appendix D).

DISSCUSSION AND RECOMMENDATION

Summary

The main objective of this thesis was to assess the effective of combine mangrove and sea dikes to adapt to SLR in MRD in 21 st century The primary research question of this research was:

“Can grey and green infrastructure be a good solution to adapt to SLR in MRD?”

The others objective of the research is valued the economic losses due to SLR impact in MRD in 21 st century and the effectiveness of grey and green infrastructure compare with other adaptation option.

To get the final answer, firstly, the potential damage of SLR in MRD were quantified in chapter 3.1 and 3.2 After that, the economic losses was assessed in the chapter 3.3 in US$ with the different socio economic development scenarios and in the various adaptation option in 21 st century The benefit of the adaptive activities can be evaluated by the difference of the damage with or without adaptation.

Complementary, the cost of the different adaptation option also was assessed in the various scenarios in chapter 3.4 Discounting was used to get the present value of the future costs and benefits Finally, with the aggregation of the previous steps, the cost and the benefit were compared to get the net present value and assessed in chapter 3.5 The evaluation was based on the NPV and BCR The sensitivity of the analysis was assessed in chapter 3.6 which consider the impact of changing the input value to the final.

The result of determining damage due to the impact of SLR shows that most of the area of the Mekong Delta will be flooded in the 21 st century without adaptation measures By 2100, the provinces of the Mekong Delta will be inundated most of the area, while Dong Thap and An Giang provinces, although affected the lowest, still have nearly 80% of the area below sea level Coastal provinces such as

2030 This could affect the majority of the population living in the Mekong Delta region In the worst case, by 2100, the population could be affected up to 19 million; in the most positive scenarios, the affected population could be more than

10 million This result is many times higher than previous studies of (Reid, 2008) and MONRE (2016) The reason may be due to the difference when selecting the input data to build the SLR method to identify the flooded area Compared to previous studies, Tamura et al (2018) was improved the SLR scenarios in identifying flooded areas based on the difference of sea level elevation and the topography of the coastline area including the linkage of land topography and ocean bathymetry

Whereas of the MRD area is inundated, the value of the dry land loss is estimated to be between USD 2102 billion (SSP4) and USD 4388 billion (SSP5).

The value of this damage is greater many time compared to This study of Kumano et al (2019) when applying the analysis to Vietnam, the cause may be due to the value of real estate is much higher than the annual GDP and this results is presented the added present value of the land Establishing a sea dike system around the Mekong Delta will help reduce flood damage under the impact of rising sea levels.

Inundating time is inversely proportional to the height of the dike, with a dike height of 1 meter, the Mekong Delta could be flooded from 2050 and when the height of the dike is 4 meters, this area might be no longer a risk of inundating in the 21 st century.

The CBA results show that the benefits can be much higher than the cost of all adaptation option in both socio economic scenarios The combination of sea dikes and mangrove has the highest NPV compare with other adaptation option was mentioned in the research, that mean, it would be the good solution to adapt to SLR for MRD This result shows the similarity with the research results of (Vo ThanhDanh, 2012) when analysing the benefits of constructing concrete dikes in the coastal area of Tra Vinh province to adapt to the rising sea level in 21 st century In addition, it also present the same trend with (Lincke & Hinkel, 2018) Their results also show that MRD has the greater benefit than the cost of the robust protection system against to SLR in the 21 st century, the benefit cost ratio of this one in MRD might reach 75 up to more than 100.

However, the results are higher many times than the study of CPMD (2017) in Kiên Giang This is because they consider the SLR damage only for coastal areas but do not consider impacts on inland area, where also under the impact of SLR, especially in low land areas such as MRD.

Up to this point, the main finding of the thesis is implied for the impacts of mean SLR on socio economic of MRD and the effectives of the mixing grey and green infrastructure Within the scope of this study, the application of mixing grey and green infrastructure has the most effectiveness to adapt to SLR in MRD.

Limitation of the research and future work

A genetic limitation of a cost benefit analysis is hard to define and value all the benefit and costs of the project

This study has only focused on one of the direct impacts of SLR on land.

Other factors such as the impact of SLR on coastal and marine ecosystem, infrastructure and human activities have not been taken into account In addition to the effects of flooding, impacts due to temporary SLR also do not present in this case

On the other hand, this study has not taken into account the effects of SLR or other natural factors such as subsidence, groundwater depletion on the effectiveness of adaptation measures (Minderhoud et al., 2019) has warned that with the current rate of subsidence in the Mekong Delta, by 2050 it is likely that most of the Mekong Delta can be below sea level People and economic activities also affect solutions to increase SLR For example, both sea dikes and mangrove are affected by erosion, in fact, mangrove in the Mekong Delta are declining both in terms of area of forest quality, which may increase planting costs and forest conservation. and broken Another factor not yet taken into account is the impact of the solutions on the inland ecosystems near the dike The construction of a sea dike will change the factors affecting the reproductive system in the Mekong Delta region, which is a sensitive and vulnerable system The interaction of sea dikes and mangrove should also be considered and evaluated in subsequent studies

In terms of benefits, the benefits of mangrove have not yet been realized.

Mangrove have been concluded as a promising solution to protect coastal ecosystems, provide economic value such as medicine, timber or enhance habitat and facilitate aquaculture Another benefit of mangrove for mitigation is that mangrove is able to absorb and store large amounts of carbon

The factors outlined above can have a direct impact on the end result, meaning that the benefits may actually be significantly higher or lower than the estimates of this study.

Therefore, further researches are needed to address the limitations of this study In fact, there are a limited number of studies on the impacts of SLR and adaptation measures on small areas, so finding solutions to SLR in these areas is still a problem.

Recommendation

The results of this thesis are an addition to address the impact of SLR in MRD in the future The MRD is facing with the mass damage due to SLR impact, without adaptation, inundation might appear in the ongoing years All of adaption option are presented the effectiveness to adapt to SLR, however mixing grey and green infrastructure has highest effective than other option In reality, MRD has the mass mangrove forest that mean it will reduce the cost of afforestation and maintenance cost of the mangrove forest

The current adaptation solution needs to be improved to get the higher technical standard and can perform the protection function for a long time and urgency of coastal protection in MRD The red line shows the high urgency is facing with SLR damage, should be set up the concrete dike to protect the inland area The yellow line indicated the reduction trend of mangrove forest In this area, it is highly recommended to investigate beach nourishment, afforestation and protect the mangrove forest The green line which shows the good growth of mangrove forest should continue improve the quantity and quality of the existing mangrove system

The most important key factor for the successful adaptation strategies is rising the local people awareness on the climate change and SLR impact and the benefit of mixing grey and green infrastructure

Figure 4.1 The urgency of coastal protection (Source: ICMP, 2017)

CONCLUSION

Impact of SLR on the Mekong Delta region

The Mekong Delta can be heavily affected by SLR In the context of SLR, measures, more than 50% of this area will be below the sea level By maintaining the current state of the sea dikes, this plain will be protected until 2070 With the height of the dikes being 4m, this area will avoid submerged in the 21 st century It is necessary to take measures for upgrading and renovating the system of sea dikes and coastal mangrove to protect the vast areas of the delta and fulfil other socio economic goals.

Solutions to adapt to SLR

The protection system options all show benefits that are many times higher than the construction costs Specifically, the combined solution of mangrove and concrete dikes brings the highest benefits in this research framework The sensitivity analysis of CBA altered the effectiveness, nevertheless, the significance for adaptation is unchanged It shows the promising ability of the grey and green infrastructure.

Albert, S., Saunders, M I., Roelfsema, C M., Leon, J X., Johnstone, E.,

Mackenzie, J R., Hoegh Guldberg, O., Grinham, A R., Phinn, S R., Duke,

N C., Mumby, P J., Kovacs, E., & Woodroffe, C D (2017) Winners and losers as mangrove, coral and seagrass ecosystems respond to sea level rise in Solomon Islands Environmental Research Letters, 12(9), 094009. https://doi.org/10.1088/1748 9326/aa7e68 Alongi, D (2002) Present state and future of the world’s mangrove forests.

Environmental Conservation, 29((3)), 331–349. https://doi.org/10.1017/S0376892902000231 Alverson, K (2012) Vulnerability, Impacts, and Adaptation to Sea Level Rise:

Taking an Ecosystem Based Approach Oceanography, 25(3), 231–235. https://doi.org/10.5670/oceanog.2012.101 Anthony, E J., Brunier, G., Besset, M., Goichot, M., Dussouillez, P., & Nguyen, V.

L (2015) Linking rapid erosion of the Mekong River delta to human activities Scientific Reports, 5(1), 14745 https://doi.org/10.1038/srep14745 Asuncion, R C., & Lee, M (n.d.) Impacts of Sea Level Rise on Economic Growth in Developing Asia 23.

Atkinson, G., & Mourato, S (2008) Environmental Cost Benefit Analysis Annual

Review of Environment and Resources, 33(1), 317–344. https://doi.org/10.1146/annurev.environ.33.020107.112927 Barnard, P L., Erikson, L H., Foxgrover, A C., Hart, J A F., Limber, P., O’Neill,

A C., Ormondt, M van, Vitousek, S., Wood, N., Hayden, M K., & Jones, J.

M (2019) Dynamic flood modeling essential to assess the coastal impacts of climate change Scientific Reports, 9(1), 1–13. https://doi.org/10.1038/s41598 019 40742 zBeck, M W., Losada, I J., Menéndez, P., Reguero, B G., Díaz Simal, P., & reefs Nature Communications, 9(1), 2186 https://doi.org/10.1038/s41467

018 04568 z Besset, M., Gratiot, N., Anthony, E J., Bouchette, F., Goichot, M., & Marchesiello,

P (2019) Mangroves and shoreline erosion in the Mekong River delta, Viet Nam Estuarine, Coastal and Shelf Science, 226, 106263. https://doi.org/10.1016/j.ecss.2019.106263 Browder, G., Ozment, S., Bescos, I R., Gartner, T., & Lange, G M (2019).

Cabinet, P M and (2014, December 12) A Century of Australian cost benefit analysis working paper [Text] https://www.pmc.gov.au/resource centre/regulation/century australian cost benefit analysis working paper Carew Reid, J (n.d.) Rapid Assessment of the Extent and Impact of Sea Level Rise in Viet Nam 82.

Cheong, S M., Silliman, B., Wong, P P., van Wesenbeeck, B., Kim, C K., &

Guannel, G (2013) Coastal adaptation with ecological engineering Nature

Climate Change, 3(9), 787–791 https://doi.org/10.1038/nclimate1854

Diaz, D B (n.d.) Estimating Global Damages from Sea Level Rise with the

Coastal Impact and Adaptation Model (CIAM) 28.

Dobes, D L (n.d.) A Century of Australian Cost Benefit Analysis 24.

Egbert, G D., & Erofeeva, S Y (2002) Efficient Inverse Modeling of Barotropic

Ocean Tides Journal of Atmospheric and Oceanic Technology, 19(2), 183–

204 https://doi.org/10.1175/1520 0426(2002)0192.0.CO;2 Ellison, J C., & Zouh, I (2012) Vulnerability to Climate Change of Mangroves:

Assessment from Cameroon, Central Africa Biology, 1(3), 617–638. https://doi.org/10.3390/biology1030617 Ericson, J P., Vửrửsmarty, C J., Dingman, S L., Ward, L G., & Meybeck, M.

(2006) Effective sea level rise and deltas: Causes of change and human dimension implications Global and Planetary Change, 50(1), 63–82. https://doi.org/10.1016/j.gloplacha.2005.07.004 Evers, J., & Pathirana, A (2018) Adaptation to climate change in the Mekong

River Basin: Introduction to the special issue Climatic Change, 149(1), 1–

11 https://doi.org/10.1007/s10584 018 2242 y Field, C B., Barros, V R., & Intergovernmental Panel on Climate Change (Eds.).

(2014) Climate change 2014: Impacts, adaptation, and vulnerability:

Working Group II contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change Cambridge University Press.

FitzGerald, D M., Fenster, M S., Argow, B A., & Buynevich, I V (2008) Coastal

Impacts Due to Sea Level Rise Annual Review of Earth and Planetary

Sciences, 36(1), 601–647. https://doi.org/10.1146/annurev.earth.35.031306.140139 Gilman, E L., Ellison, J., Duke, N C., & Field, C (2008) Threats to mangroves from climate change and adaptation options: A review Aquatic Botany,

Godoy, M D P., & Lacerda, L D de (2015) Mangroves Response to Climate

Distribution Anais Da Academia Brasileira de Ciências, 87(2), 651–667. https://doi.org/10.1590/0001 3765201520150055 Goldemberg, J., United Nations Development Programme, United Nations, &

World Energy Council (Eds.) (2000) World energy assessment: Energy and the challenge of sustainability United Nations Development Programme.

Gornitz, V (n.d.) Global coastal hazards from future sea level rise 20.

Hallegatte, S., Green, C., Nicholls, R J., & Corfee Morlot, J (2013) Future flood losses in major coastal cities Nature Climate Change, 3(9), 802–806. https://doi.org/10.1038/nclimate1979 Hinkel, J., & Klein, R J T (2009) Integrating knowledge to assess coastal vulnerability to sea level rise: The development of the DIVA tool Global

Environmental Change, 19(3), 384–395. https://doi.org/10.1016/j.gloenvcha.2009.03.002 Hinkel, J., Nicholls, R J., Vafeidis, A T., Tol, R S J., & Avagianou, T (2010).

Assessing risk of and adaptation to sea level rise in the European Union: An application of DIVA Mitigation and Adaptation Strategies for Global

Jevrejeva, S., Jackson, L P., Riva, R E M., Grinsted, A., & Moore, J C (2016).

Coastal sea level rise with warming above 2 °C Proceedings of the National

Academy of Sciences, 113(47), 13342–13347. https://doi.org/10.1073/pnas.1605312113 Klein, R J T., & Nicholls, R J (1999) Assessment of Coastal Climate Change.

Kopp, R E., Horton, R M., Little, C M., Mitrovica, J X., Oppenheimer, M.,

Rasmussen, D J., Strauss, B H., & Tebaldi, C (2014) Probabilistic 21st and 22nd century sea level projections at a global network of tide gauge sites:

KOPP ET AL Earth’s Future, 2(8), 383–406. https://doi.org/10.1002/2014EF000239 Krauss, K W., McKee, K L., Lovelock, C E., Cahoon, D R., Saintilan, N., Reef,

R., & Chen, L (2014) How mangrove forests adjust to rising sea level New

Phytologist, 202(1), 19–34 https://doi.org/10.1111/nph.12605

Lincke, D., & Hinkel, J (2018) Economically robust protection against 21st century sea level rise Global Environmental Change, 51, 67–73. https://doi.org/10.1016/j.gloenvcha.2018.05.003 Linham, M M., & Nicholls, R J (2010) Technologies for climate change adaptation: Coastal erosion and flooding UNEP Riso Centre on Energy,

McCarthy, J J., & Intergovernmental Panel on Climate Change (Eds.) (2001).

Climate change 2001: Impacts, adaptation, and vulnerability: contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change Cambridge University Press.

McGranahan, G., Balk, D., & Anderson, B (2007) The rising tide: Assessing the risks of climate change and human settlements in low elevation coastal zones Environment and Urbanization, 19(1), 17–37.

Menéndez, P., Losada, I J., Torres Ortega, S., Narayan, S., & Beck, M W (2020).

The Global Flood Protection Benefits of Mangroves Scientific Reports,

Mengel, M., Levermann, A., Frieler, K., Robinson, A., Marzeion, B., &

Winkelmann, R (2016) Future sea level rise constrained by observations and long term commitment Proceedings of the National Academy of

Sciences, 113(10), 2597–2602 https://doi.org/10.1073/pnas.1500515113

Mimura, N (2013) Sea level rise caused by climate change and its implications for society Proceedings of the Japan Academy, Series B, 89(7), 281–301. https://doi.org/10.2183/pjab.89.281 Minderhoud, P S J., Coumou, L., Erkens, G., Middelkoop, H., & Stouthamer, E.

(2019) Mekong delta much lower than previously assumed in sea level rise impact assessments Nature Communications, 10(1), 3847. https://doi.org/10.1038/s41467 019 11602 1 Nauels, A., Rogelj, J., Schleussner, C F., Meinshausen, M., & Mengel, M (2017).

Linking sea level rise and socioeconomic indicators under the Shared Socioeconomic Pathways Environmental Research Letters, 12(11), 114002. https://doi.org/10.1088/1748 9326/aa92b6 Nicholls, R J (2015) Adapting to Sea Level Rise In Coastal and Marine Hazards,

Risks, and Disasters (pp 243–270) Elsevier https://doi.org/10.1016/B978

0 12 396483 0.00009 1 Pearce, D W., Atkinson, G., & Mourato, S (2006) Cost benefit analysis and the environment: Recent developments Organisation for Economic Co operation and Development.

Quang Bao, T (2011) Effect of mangrove forest structures on wave attenuation in coastal Vietnam Oceanologia, 53(3), 807–818. https://doi.org/10.5697/oc.53 3.807 Sara, K (n.d.) Cost benefit analysis 135.

Shabman, L (n.d.) MAKING BENEFIT ESTIMATION USEFUL: LESSONS FROM

Syvitski, J., Kettner, A., & Overeem, I et al (2009) Sinking deltas due to human activities Nature Geosci, 2, 681–686 https://doi.org/10.1038/ngeo629 Tamura, M., Kumano, N., Inoue, T., & Yokoki, H (2018) Impact and cost assessment of coastal protection mixing green infrastructure against sea level rise in Vietnam Towards Sustainable Development, 6.

Tamura, M., Kumano, N., Yotsukuri, M., & Yokoki, H (2019) Global assessment of the effectiveness of adaptation in coastal areas based on RCP/SSP scenarios Climatic Change, 152(3–4), 363–377. https://doi.org/10.1007/s10584 018 2356 2 Tas, S (n.d.) Coastal protection in the Mekong Delta 130.

Vo Thanh Danh (2012) Adaption to sea level rise in the Vietnamese Mekong River delta: Should a sea dike be built? EEPSEA.

Watanabe, S., Hajima, T., Sudo, K., Nagashima, T., Takemura, T., Okajima, H.,

Nozawa, T., Kawase, H., Abe, M., Yokohata, T., Ise, T., Sato, H., Kato, E., description and basic results of CMIP5 20c3m experiments Geoscientific

Model Development, 4(4), 845–872 https://doi.org/10.5194/gmd 4 845 2011

Wolff, C., Vafeidis, A T., Lincke, D., Marasmi, C., & Hinkel, J (2016) Effects of

Scale and Input Data on Assessing the Future Impacts of Coastal Flooding:

An Application of DIVA for the Emilia Romagna Coast Frontiers in

Marine Science, 3 https://doi.org/10.3389/fmars.2016.00041

Zhuang, J., Liang, Z., Lin, T., & Guzman, F D () Theory and Practice in the

Choice of Social Discount Rate for Cost Benefit Analysis: A Survey 51.

APPENDIX A MAP OF INUNDATION AREA IN MRD IN 21st CENTURY

Section 1: Potential inundation map without adaptation solution

Section 2: Potential inundation map with dike system 1 meter height

Section 3: Potential inundation map with dike system 2 meter height

Section 4: Potential inundation map with dike system 3 meter height

APPENDIX B THE POTENTIAL IMPACT OF SLR

Section 1: Potential inundated area due to SLR without adaptation

Table 1: The potential inundated area due to SLR in MRD without adaptation in 21 st century

Land for cultivation of annual crops 12,261.52 18,197.30 18,197.30 18,294.41 18,294.41 18,405.18 18,419.11 18,529.66 18,581.19

Land for cultivation of perennial tree 3,271.08 3,785.58 3,785.58 3,788.83 3,788.83 3,809.48 3,809.52 3,809.84 3,893.75

Table 2: Inundation rate by province in MRD

Section 2: Potential inundated area due to SLR with 1m dike height

Table 1: The potential inundated area due to SLR in MRD without adaptation in 21 st century

Land for cultivation of annual crops 0 0 0 18,294.41 18,294.41 18,405.18 18,419.11 18,529.66 18,581.19

Land for cultivation of perennial tree 0 0 0 3,788.83 3,788.83 3,809.48 3,809.52 3,809.84 3,893.75

Table 2: Inundation rate by province in MRD

Section 3: Potential inundated area due to SLR with 2m dike height

Table 1: The potential inundated area due to SLR in MRD without adaptation in 21 st century

Land for cultivation of annual crops 0 0 0 0 0 18,405.18 18,419.11 18,529.66 18,581.19

Land for cultivation of perennial tree 0 0 0 0 0 3,809.48 3,809.52 3,809.84 3,893.75

Table 1: The potential inundated area due to SLR in MRD without adaptation in 21 st century

Land for cultivation of annual crops 0 0 0 0 0 0 0 18,529.66 18,581.19

Land for cultivation of perennial tree 0 0 0 0 0 0 0 3,809.84 3,893.75

Table 2: Inundation rate by province in MRD

Section 5: Total inundated area due to SLR in MRD with and without adaptation

Without adaptation 1m dike height 2m dike height 3m dike height 4m dike height

APPENDIX C THE SOCIO ECONOMIC DAMAGE OF SLR

Table 1: Economic loss due to dry land loss by SLR without adaptation in different socio economic scenarios

Table 2: Average annual loss in each decade in 21 st century without adaptation in different socio economic scenarios

Table 3: Economic loss compare with the estimated GDP in 21st century in different SLR scenarios

Section 2: Potential population affected by administrative due to SLR in MRD in 21st century in different socio economic scenarios

Table 1: Potential population at risk of SLR in Dong Thap province in 21 st century in different socio economic scenarios without adaptation

Table 2: Potential population at risk of SLR in An Giang province in 21 st century in different socio economic scenarios without adaptation

Table 3: Potential population at risk of SLR in Bac Lieu province in 21 st century in different socio economic scenarios without adaptation

Table 4: Potential population at risk of SLR in Ben Tre province in 21 st century in different socio economic scenarios without adaptation

SSP1 670.69 1,193.55 1,204.79 1,206.64 1,149.24 1,072.38 980.98 882.74 761.78SSP2 677.19 1,225.51 1,257.87 1,282.21 1,244.77 1,185.90 1,112.24 1,044.61 971.84SSP3 684.78 1,263.68 1,322.68 1,383.23 1,384.85 1,370.31 1,352.76 1,357.45 1,362.53SSP4 670.44 1,191.99 1,198.23 1,190.86 1,121.37 1,029.41 922.59 820.75 717.96SSP5 668.88 1,184.51 1,190.33 1,187.06 1,126.02 1,046.93 954.95 857.52 739.03

Table 6: Potential population at risk of SLR in Can Tho city in 21 st century in different socio economic scenarios without adaptation

Table 7: Potential population at risk of SLR in Hau Giang province in 21 st century in different socio economic scenarios without adaptation

SSP1 803.75 857.48 865.56 848.20 807.85 753.82 689.57 613.90 529.78SSP2 811.54 880.44 903.69 901.32 875.01 833.62 781.84 726.47 675.86SSP3 820.63 907.87 950.25 972.33 973.47 963.25 950.92 944.03 947.57SSP4 803.45 856.36 860.85 837.11 788.26 723.62 648.53 570.78 499.30SSP5 801.58 850.98 855.17 834.43 791.53 735.93 671.28 596.36 513.96

SSP1 896.92 1,626.01 1,641.32 1,609.66 1,533.09 1,437.63 1,315.10 1,173.88 1,013.04 SSP2 905.62 1,669.54 1,713.63 1,710.47 1,660.53 1,589.82 1,491.07 1,389.15 1,292.37 SSP3 915.76 1,721.55 1,801.92 1,845.23 1,847.40 1,837.04 1,813.51 1,805.17 1,811.93 SSP4 896.59 1,623.87 1,632.38 1,588.62 1,495.91 1,380.03 1,236.82 1,091.45 954.76 SSP5 894.50 1,613.68 1,621.61 1,583.54 1,502.11 1,403.52 1,280.21 1,140.35 982.78

Table 9: Potential population at risk of SLR in Long An province in 21 st century in different socio economic scenarios without adaptation

SSP1 1,200.59 1,575.41 1,590.25 1,567.88 1,493.30 1,393.43 1,274.66 1,134.77 984.01 SSP2 1,212.23 1,617.58 1,660.30 1,666.07 1,617.43 1,540.94 1,445.22 1,342.87 1,255.33 SSP3 1,225.81 1,667.98 1,745.85 1,797.33 1,799.45 1,780.56 1,757.75 1,745.02 1,760.00 SSP4 1,200.15 1,573.34 1,581.59 1,547.38 1,457.09 1,337.60 1,198.79 1,055.08 927.40 SSP5 1,197.35 1,563.47 1,571.15 1,542.43 1,463.12 1,360.36 1,240.85 1,102.35 954.62

Table 10: Potential population at risk of SLR in Soc Trang province in 21 st century in different socio economic scenarios without adaptation

SSP1 1,209.31 1,452.09 1,465.77 1,436.37 1,368.05 1,276.55 1,167.75 1,039.59 897.15SSP2 1,221.04 1,490.97 1,530.34 1,526.33 1,481.77 1,411.69 1,324.01 1,230.23 1,144.53SSP3 1,234.72 1,537.42 1,609.19 1,646.58 1,648.52 1,631.21 1,610.32 1,598.66 1,604.65SSP4 1,208.87 1,450.19 1,457.79 1,417.60 1,334.87 1,225.41 1,098.25 966.59 845.54SSP5 1,206.05 1,441.09 1,448.17 1,413.06 1,340.40 1,246.26 1,136.77 1,009.89 870.35

SSP1 1,262.63 1,669.88 1,685.61 1,668.28 1,588.92 1,511.18 1,395.78 1,254.72 1,082.80 SSP2 1,274.87 1,714.59 1,759.87 1,772.76 1,721.01 1,671.16 1,582.55 1,484.81 1,381.37 SSP3 1,289.15 1,768.00 1,850.54 1,912.43 1,914.68 1,931.02 1,924.77 1,929.48 1,936.70 SSP4 1,262.16 1,667.69 1,676.43 1,646.47 1,550.39 1,450.63 1,312.70 1,166.61 1,020.51 SSP5 1,259.22 1,657.22 1,665.37 1,641.20 1,556.81 1,475.32 1,358.75 1,218.88 1,050.46

Table 12: Potential population at risk of SLR in Tra Vinh province in 21 st century in different socio economic scenarios without adaptation

SSP1 837.16 1,086.31 1,096.54 1,085.28 1,033.66 974.06 891.04 793.25 684.56 SSP2 845.27 1,224.08 1,458.20 1,749.83 2,018.35 2,239.88 2,308.52 2,210.74 1,969.62 SSP3 854.74 1,150.14 1,203.84 1,244.11 1,245.57 1,244.68 1,228.74 1,219.84 1,224.41 SSP4 836.85 1,084.89 1,090.57 1,071.09 1,008.59 935.03 838.00 737.54 645.18 SSP5 834.89 1,078.08 1,083.38 1,067.67 1,012.77 950.94 867.40 770.59 664.11

Table 13: Potential population at risk of SLR in Vinh Long province in 21 st century in different socio economic scenarios without adaptation

Table 14: Total population at risk of SLR in MRD in 21 st century in different scocio economic scenarios without adaptation

Section 1: The CBA of mixing grey and green infrastructure

Table 1: Construction cost of grey infrastructure (discount rate = 3%)

Table 2: Maintenance cost of grey infrastructure (discount rate = 3%)

Table 3: Afforestation of green infrastructure (discount rate = 3%)

Table 4: Maintenance cost of green infrastructure (discount rate = 3%)

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 5: Benefit of green infrastructure (discount rate = 3%)

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 6: Benefit of loss avoiding due to SLR (discount rate = 3%)

SSP1 SSP2 SSP3 SSP4 SSP5

Benefit PV Benefit PV Benefit PV Benefit PV Benefit PV

Table 7: CBA of mixing grey and green infrastructure (discount rate = 3%)

Section 2: Cost of another adaptation options

Table 1: Construction cost of earth dike (discount rate = 3%)

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 2: Maintenance cost of earth dike (discount rate =3%)

Year Mangrove and earth dike

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 3: Afforestation cost of combination earth dike and mangrove (discount rate = 3%)

Year Mangrove and earth dike

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 4: Maintenance cost of mangrove forest (discount rate = 3%)

SSP1 SSP2 SSP3 SSP4 SSP5

Table 5: Construction cost of concrete dike (discount rate = 3%)

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 6: Maintenance cost of concrete dike (discount rate = 3%)

Year SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Section 3: Sensitivity analysis, discount rate =8%

Table 1: Construction cost of grey infrastructure

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 2: Maintenance cost of grey infrastructure

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 3: Afforestation of green infrastructure

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 4: Maintenance cost of green infrastructure

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Table 5: Benefit of green infrastructure

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 5: Benefit of avoiding damage due to SLR

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Benefit PV Benefit PV Benefit PV Benefit PV Benefit PV

Section 4: Sensitivity analysis, discount rate %

Table 1: Construction cost of grey infrastructure

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 2: Maintenance cost of grey infrastructure

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 3: Afforestation of green infrastructure

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 4: Maintenance cost of green infrastructure

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 5: Benefit of green infrastructure

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 6: Benefit of avoiding SLR damage

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Section 5: Sensitivity analysis, mangrove width = 350 meters, discount rate = 3%

Table 1: Afforestation cost of mangrove forest

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 2: Maintenance cost of mangrove forest

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV

Table 3: Benefit of mangrove forest

Year Mixing grey and green

SSP1 SSP2 SSP3 SSP4 SSP5

Cost PV Cost PV Cost PV Cost PV Cost PV