## 1. Cost of Sea-Level Rise, Annual Average 2020-2099, Percentage of GDP

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---

### Overview
- Fiji is an archipelagic country of over 332 islands, with 90 percent of the population and most economic activity concentrated along the coastline.
- Sea-level rise (SLR) and associated impacts present long-term macrocritical challenges requiring effective and efficient adaptation policies.
- IMF staff use the CIAM model (Diaz, 2016) with median sea-level change from the RCP4.5 scenario (+0.7m above sea-level in 2000) as a central case and a 90 percent range of +0.4m to +1.11m to illustrate uncertainty.

### Climate trends and projections
- Observed trends:
  - Mean annual temperature increased by 0.3 °C between 1960-1990 and 1984-2014, and by an estimated additional 0.3 °C after 1984-2014.
  - No discernible trend in total annual precipitations; annual rainfall can range between 2,000 and 4,000 mm/year.
  - Sea level is increasing at approximately 4.7 mm per year.
- Model projections:
  - Temperature projected to rise between 0.8 and 1.1 °C in 2050 and between 0.8 and 2.0 °C in 2085 (relative to the 1985-2014 reference period), depending on emission scenario.
  - In 2100, in a fast-warming and accelerated-melting scenario, sea level could be up to 1.0 m higher than in 2000.
  - Precipitation and other weather extremes, including tropical cyclones, show minor projected changes or high uncertainty; tropical cyclone frequency is predicted to decline but uncertainty is large.

### Estimated economic costs of SLR (CIAM results)
- Central estimate (moderate emissions, median SLR):
  - Annual cost of SLR without adaptation: approximately equal to 1.8 percent of GDP, on average, from 2020 to 2099.
- Full scenario range:
  - Annual costs range between 0.9 and 2.6 percent of GDP using the available SLR scenarios (lowest emission/SLR to highest emission/SLR).
- Cost composition and interpretation:
  - Most cost attributed to deaths and loss of capital during storms.
  - Remaining costs due to land loss from permanent inundation and monetized disutility losses from forced relocation; loss of wetlands contributes modestly.
  - These costs measure welfare losses; they are not directly GDP or fiscal losses without further modeling or assumptions.
  - If government assumes full responsibility for all losses, the CIAM estimates can be interpreted as an upper bound to government financing needs.

### Adaptation strategies: protection vs retreat (CIAM comparisons)
- Coastal protection:
  - Cost-effective protection of all coastline requires an investment of approximately 1.5 percent of GDP annually throughout the century.
  - Protection often implies guarding against 1/1,000-year storms in many segments.
  - Protection can disrupt natural exchange between wetlands and open seas; biodiversity losses estimated at 0.2 percent of GDP annually (higher than in the no-adaptation case).
  - CIAM does not model some nature-based protection options (e.g., mangroves, vetiver grass) due to insufficient granular data.
  - Protection can be more costly than no adaptation because the cost of protection may exceed the value of assets and land protected.
- Planned retreat (relocation):
  - CIAM estimates the cost of planned retreat as 0.3 percent of GDP, on average between 2020 and 2100.
  - Planned retreat avoids protection investment; capital losses are minimal in the gradual process (bare land lost to sea).
  - Opportunity cost of land for relocated populations is included and proxied by the value of interior agricultural or marginal land.
  - Planned retreat still entails fiscal costs to finance relocation and requires long-term participatory approaches for equity and effectiveness.

### Fiscal, institutional, and implementation details
- Fiji policy and institutions:
  - Planned Relocation Guidelines (PRG) launched in 2018.
  - Relocation Taskforce (FTRD) established to coordinate planned relocation.
  - Climate Relocation of Communities (CROC) Trust Fund established in 2020 to finance planned relocation.
  - CROC is funded by 3 percent of revenue from the Climate and Environmental Levy (ECAL) plus bilateral and multilateral donor funds.
- Historical relocation costs:
  - Relocation of six communities since 2011 is estimated to have costed FJD 3.6 million, or about 0.03 percent of GDP.
  - Relocation affected 78 households, for an average cost of FJD 46,300 per household.
- Policy implications:
  - Explicit cost-benefit analysis (CBA) of alternative adaptation options can help maximize impact of public funds and international aid while maximizing social welfare.
  - More granular data (hyper-resolution maps of elevation, currents, tides, infrastructure, population) is necessary to refine costs, protection needs, and retreat potential.
  - A long-term participatory approach involving local communities is essential to make planned retreat viable and equitable.

### Key model limitations and data needs
- CIAM limitations noted:
  - Uses averaged coastal slope and does not capture fine coastal characteristics that determine inundation at parcel level.
  - Does not capture interaction of SLR with ongoing coastal erosion processes or cost of saline intrusion into coastal aquifers.
  - Does include non-market costs such as loss of life from storm floods, wetland loss, and disutility from relocation.
- Data inventory:
  - CIAM divides Fiji coastline into 137 segments, with segment lengths ranging from 0.4 km to 619.2 km and a median length of 1.9 km.
  - High-resolution tools and portals (e.g., Sea Level Rise and Critical Infrastructure portal) and digital elevation models (e.g., FABDEM) are available and being used to inform planning.

### Practical takeaways and recommendations
- Cost comparisons and strategy choice:
  - Planned retreat emerges as the least-cost adaptation strategy in CIAM central estimates (0.3 percent of GDP annually vs 1.5 percent for full-protection strategies).
  - Protection can be highly effective locally but may be cost-ineffective at national scale and can generate higher biodiversity losses (0.2 percent of GDP annually).
- Policy recommendations:
  - Use CBA and cost-effectiveness analysis, recognizing challenges but valuing transparency and systematic evaluation.
  - Prioritize the expansion of hyper-resolution mapping and data collection to refine vulnerability and adaptation cost estimates.
  - Finance and plan relocations through instruments like CROC while ensuring participatory approaches to limit social and cultural costs.
  - Consider mixing protection and planned retreat consistent with national guidelines and empirical assessments to contain fiscal costs and maximize welfare.

---

### Box 1. Fiji: Coastal Relocation (concluded)

### Relocation challenges and case evidence
- Relocation entails loss of attachment to "land, history, and livelihoods," and the lack of land with productivity and amenities like the land of origin poses significant challenges.
- Existing land ownership arrangements may constrain local resettlement; example: a long-term lease on a former sugarcane plantation was cut short to accommodate households leaving the Etatoko village.
- Construction of new houses was entirely supported by external aid.
- Intergenerational differences: elders are more reluctant to move, while the younger generation — moving to non-agricultural wage labor and high-skilled jobs in larger towns — is more open to relocation.
- Participatory approaches that involved experts and local communities built trust and persuaded elders to move in Vunidogoloa village (low-lying Serua Island).
  - The new village is now located 1.5 km inland, on Vanua Levu Island, on dry grounds.
- Observations are characterized as partial and anecdotal and are stated as insufficient to draw firm conclusions about the viability of a nation-wide planned retreat from long-term sea-level rise, but they provide important insights.

### Data, mapping, and planning tools
- The government distributes state-of-the-art high-resolution flood maps with sea-level rise up to 2m.
- The Fiji Climate Change Information Hub/GIS platform:
  - Uses a state-of-the-art digital elevation model (DEM) (Hawker et al., 2022).
  - Interactively shows assets and population that can be flooded with sea-level rise from 0 to 2 m.
  - Combines information on exposure with local estimates of protection costs, land values, value of assets at risks, population density, and value of ecosystem services.
- Caveat on elevation data: the global DEM used for the portal has a mean vertical error equal to +/- 1.12 m, which is larger than expected sea level rise at the end of the century; hyper resolution local elevation maps are needed for planning purposes.

### National policy context and adaptation agenda
- Fiji milestones and documents:
  - First country to ratify the Paris Agreement in 2015.
  - First small island state to assume presidency of the United Nations Framework Convention on Climate Change in 2017.
  - One of the first countries that submitted a National Adaptation Plan (NAP) in 2018; a new NAP is in preparation.
- The 2018 NAP identifies 160 adaptation Actions but the effectiveness, efficiency, and fiscal sustainability of policies and concrete measures needs additional criteria.
  - Examples of NAP Actions:
    - Action 12.A.12: “enhance support for irrigation schemes which support agricultural diversification and mitigate increased drought and flooding”
    - Action 12.A.13: “maintain, adapt and construct sea wall and drainage infrastructure to reduce saltwater intrusion on agricultural land due to sea level rise and increased tidal surges”
    - Action 16.5: “strengthen the management an monitoring of ecosystems.”
- Policy design questions highlighted:
  - Variations in design (e.g., sea wall extension, height, material, retreat perimeters).
  - Trade-offs (e.g., preventing coastal tourism development to protect ecosystems).
  - Sizing of irrigation schemes for future water demand.
  - Determining the most efficient mix of public and private investment in adaptation.

### Principles for effective and efficient adaptation
- IMF Staff guidance and referenced literature frame adaptation in economic and sustainable development terms to guide public investment and enable efficient private adaptation.
- Key high-level principles:
  - Integrate adaptation into broader development planning; adaptation is aligned with the Paris Agreement (Article 7) objective and the 2018 NAP principle that “adaptation is seen as synonymous with climate-resilient development.”
  - Allocate resources carefully across competing needs while considering distributional effects:
    - (i) concentrate government efforts and resources in key areas; and
    - (ii) collect information on spending effectiveness across programs and impacts on distinct groups.
  - Prioritize adaptation policies with positive externalities, remove market imperfections that hinder efficient private adaptation, and ensure a just transition.

### Role of government vs. private adaptation; market failures
- Many adaptations have local and private benefits and are often undertaken autonomously at community level (examples from villages along the Ba River):
  - Planting trees around riverbanks, shifting plantations away from coastal areas, planning drought-resistant crop varieties, multi-cropping, changing harvesting times for mussels and prawns, and building houses on raised platforms.
- Government role is warranted when adaptation has large externalities or public-good characteristics (e.g., coastal protection in cities, public infrastructure, climate information services).
  - Fiji Meteorological Service plays an instrumental role in distributing weather and long-term climate information.
- Government should promote reforms that ease efficient use of resources and ensure competitive access to markets (examples: access to credit, efficient water pricing).
- Box 2 summary of market failures and policy responses (selected points reproduced verbatim from source):
  - Adaptations with large positive externalities and public goods are typically underprovided by markets (information, emergency preparedness, seawalls, research, technologies).
  - Network-dependent resilience (dikes, water networks, transportation) may require government coordination.
  - The extent of cooperation required depends on the externality scope; central government provision can amount to wealth transfers across regions when financed nationally.
  - Broader market imperfections (poor business environment, inefficient credit markets) hamper private adaptation.
  - Moral hazard can reduce private adaptation if actors expect central government relief; regulatory measures (zoning, building codes, mandatory evacuations, mandatory insurance) can mitigate moral hazard.
  - Policy failures (e.g., subsidies to inputs or water) can worsen resource use; removing distortions should be considered while accounting for distributional implications.
  - Source for Box 2: Massetti and Bellon (2022a).

### Use of cost-benefit analysis (CBA)
- CBA can help decision makers consistently collect, aggregate, and compare information on public adaptation projects, maximizing overall social welfare and avoiding waste of scarce resources.
- Ethical choices on “what to do, when, how, and at what cost” should reflect preferences of Fiji’s government and population; CBA complemented by distributional analysis is recommended.
- Action 8.10 of the 2018 NAP aims to mainstream "cost-benefit analysis, multi-criteria analysis, and other relevant tools (such as gender analysis) into decision-making processes regarding climate change adaptation."
- Practical implementation of NAP Actions would benefit from quantitative methods grounded in welfare economics; the NAP Costing Methodology developed by the Government can serve as a starting point.

---

### Climate models project continued warming but no significant change in total annual precipitations and other weather extremes

### Temperature projections and weather extremes
- Median projections of warming across all climate model simulations:
  - increase between 0.8 and 1.1 °C in 2050 with respect to the 1985-2014 reference period.
  - increase between 0.8 and 2.0 °C in 2085 with respect to the 1985-2014 reference period.
- Individual models predict more warming and cannot be excluded:
  - In a high-emission, fast-warming scenario (90th percentile across models using the SSP3-7.0 emission scenario) temperature is projected to increase by 2.9 °C in 2085.
- Precipitations:
  - Median projections indicate minor changes relative to average total annual precipitations.
  - Models do not agree on the direction of change; no clear relationship between predicted changes in precipitations and emissions scenarios.
  - Natural variability dominates and is expected to continue to dominate any climate change–induced changes in precipitations.
- Extreme events and drought indicators:
  - No clear signals of changes in the number of maximum consecutive dry days and intense precipitation events.
  - The increased intensity of 5-day heavy precipitation events from their secular minimum around the year 2000 is likely part of medium-term natural climatic cycles and is considered a temporary deviation from long-term expected conditions.

### Sea-level rise projections and vulnerability
- Current trend:
  - Sea-level is increasing at approximately 4.7 mm per year, faster than the global average.
- Median and scenario-based projections relative to year 2000:
  - SSP2-4.5 (moderate emission scenario): sea-level will increase by 0.60 m by the end of the century with respect to its level in 2000.
  - SSP1-2.6 (Paris-aligned scenario): sea-level is projected to increase by 0.49 m by 2100.
  - Worst-case (extremely high emissions and fast ice melting, low-confidence, high-impact ice sheet processes): sea-level projected to increase by 0.98 m in 2100.
- Drivers and local factors:
  - Global oceanographic factors, thermal expansion, tectonic activity, erosion, and land subsidence explain why sea-level rise is faster in Fiji than the global average.
- Exposure:
  - 90 percent of Fiji’s total population of 900,000 live along the coastline, increasing vulnerability to sea-level rise.
- Management outlook:
  - Sea-level rise will likely continue for centuries; the risk can be managed but not avoided.

### Tropical cyclones (TCs)
- Observed frequency and future projections:
  - Approximately 30 TCs cross the Fiji Exclusive Economic Zone per decade.
  - Models predict an overall decline in TC genesis in the future because conditions favorable for TC formation are projected to become less frequent in the region.
  - Uncertainty is large; available data is not suitable for a long-term assessment of TC trends.
- Intensity and impacts:
  - The proportion of more severe TCs may increase, potentially limiting the decline in absolute numbers.
  - Little consensus on whether El Niño and La Niña events will change in intensity or frequency in the region.

### Consistency with national and regional studies
- Alignment and differences:
  - This assessment aligns with the Republic of Fiji National Adaptation Plan (NAP) and the CSIRO major study (Australian Bureau of Meteorology and CSIRO, 2014).
  - Some minor differences likely arise because CSIRO (2014) uses CMIP5 data while this analysis uses CMIP6 simulations.
  - CSIRO (2014) finds a significant change in extreme rainfall; this analysis does not find significant changes.
- Historical warming reported:
  - The NAP estimates mean air temperature has warmed by 0.9 °C over the last half century.
  - CRU-based analysis shows a warming rate of 0.1 °C per decade from 1961, similar to the warming rate measured at Nadi Airport as reported by CSIRO (2014).

### Estimating the cost of sea-level rise and adaptation (CIAM framework and insights)
- Modeling approach:
  - IMF staff use the Coastal Impact and Adaptation Model (CIAM) to estimate costs of sea-level rise (SLR) under alternative adaptation strategies.
  - CIAM divides the global coastline into more than 12,000 segments; Fiji’s coastline is modeled using 137 separate segments varying in length from 0.4 Km to 619 Km.
  - Each segment is divided into areas of different elevation with data on capital, population, and wetland coverage.
  - Projections of local sea-level rise (Kopp et al., 2014) are used to estimate inundated areas and capital/population at risk.
  - Storms cause periodic inundations on top of SLR; CIAM does not consider increased risks from river floods.
- Adaptation scenarios modeled:
  - No-adaptation: population remains until inundation forces relocation; costs include abandoned capital residual value, demolition costs, and value of inundated land; disutility cost of reactive migration is monetized.
  - Protection: investment in cost-effective seawalls and barriers along the entire coastline; capital and land preserved but storms can still cause periodic losses; costs equal cost of protection plus expected storm costs.
  - Planned retreat: gradual relocation and avoidance of new coastal capital; costs equal residual capital losses, value of inundated land, and disutility cost of relocation.
  - Variants consider protection heights to contain SLR and storm surges for 1/10-, 1/100-, 1/1,000- and 1/10,000-year events; Retreat 1 base scenario addresses permanent inundation only, with variants extending retreat perimeter to avoid storm surges.
- Economic valuation and decision rule:
  - For each coastal segment, CIAM calculates the net present value of SLR costs for each adaptation strategy, monetizing loss of life using the Value of Statistical Life and monetizing wetland loss via willingness to pay for biodiversity preservation.
  - The least-cost adaptation strategy is identified per segment by comparing SLR costs across scenarios.
  - Typical outcomes: coastal protection is usually least-cost in areas with large existing capital and high population density; planned retreat is usually least-cost in areas with low capital and population density.
- Model inputs and limitations:
  - Costs of building and maintaining seawalls and other parameters are drawn from the literature; storm surge costs are incremental relative to a baseline without SLR.
  - CIAM relies on necessary simplifications; more granular coastal modeling and accurate asset mapping could refine estimates.
- Key insight on adaptation effectiveness:
  - Literature consensus that long-term planning of adaptation can be highly effective at containing physical impacts and costs of SLR.
  - Example from related literature: the PESETA IV project finds coastal protection can reduce SLR damages in the EU by approximately 90 percent.
  - Transformations needed to adapt to SLR are technologically feasible and economically sound but complex and require strong governance.

### Quantitative highlights
- Temperature increases:
  - 0.8 and 1.1 °C in 2050 (median across models, relative to 1985-2014).
  - 0.8 and 2.0 °C in 2085 (median across models, relative to 1985-2014).
  - 2.9 °C in 2085 (SSP3-7.0, 90th percentile ensemble).
- Sea-level rise:
  - Current rate: approximately 4.7 mm per year.
  - SSP2-4.5: 0.60 m increase by end of century relative to 2000.
  - SSP1-2.6: 0.49 m increase by 2100 relative to 2000.
  - Worst Case: 0.98 m increase by 2100 relative to 2000.
- Exposure:
  - Fiji total population: 900,000; 90 percent live along the coastline.
- Tropical cyclones:
  - Approximately 30 TCs cross the Fiji Exclusive Economic Zone per decade.
- CIAM and coastal modeling:
  - Global coastline segments in CIAM: more than 12,000.
  - Fiji coastline segments in CIAM: 137 segments ranging from 0.4 Km to 619 Km.
- Historical warming and trends:
  - NAP estimate: mean air temperature warmed by 0.9 °C over the last half century.
  - CRU-derived warming rate: 0.1 °C per decade from 1961.

*Source: sipea2025085 - 1. Cost of Sea-Level Rise, Annual Average 2020-2099, Percentage of GDP; https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025085.pdf*

### 1. Cost of Sea-Level Rise, Annual Average 2020-2099, Percentage of GDP ___________ 4

### 1. Cost of Sea-Level Rise, Annual Average 2020-2099, Percentage of GDP

### Overview
- Fiji is an archipelagic country of over 332 islands, with 90 percent of the population and most economic activity concentrated along the coastline.
- Sea-level rise (SLR) and associated impacts present long-term macrocritical challenges requiring effective and efficient adaptation policies.
- IMF staff use the CIAM model (Diaz, 2016) with median sea-level change from the RCP4.5 scenario (+0.7m above sea-level in 2000) as a central case and a 90 percent range of +0.4m to +1.11m to illustrate uncertainty.

### Climate trends and projections
- Observed trends:
  - Mean annual temperature increased by 0.3 °C between 1960-1990 and 1984-2014, and by an estimated additional 0.3 °C after 1984-2014.
  - No discernible trend in total annual precipitations; annual rainfall can range between 2,000 and 4,000 mm/year.
  - Sea level is increasing at approximately 4.7 mm per year.
- Model projections:
  - Temperature projected to rise between 0.8 and 1.1 °C in 2050 and between 0.8 and 2.0 °C in 2085 (relative to the 1985-2014 reference period), depending on emission scenario.
  - In 2100, in a fast-warming and accelerated-melting scenario, sea level could be up to 1.0 m higher than in 2000.
  - Precipitation and other weather extremes, including tropical cyclones, show minor projected changes or high uncertainty; tropical cyclone frequency is predicted to decline but uncertainty is large.

### Estimated economic costs of SLR (CIAM results)
- Central estimate (moderate emissions, median SLR):
  - Annual cost of SLR without adaptation: approximately equal to 1.8 percent of GDP, on average, from 2020 to 2099.
- Full scenario range:
  - Annual costs range between 0.9 and 2.6 percent of GDP using the available SLR scenarios (lowest emission/SLR to highest emission/SLR).
- Cost composition and interpretation:
  - Most cost attributed to deaths and loss of capital during storms.
  - Remaining costs due to land loss from permanent inundation and monetized disutility losses from forced relocation; loss of wetlands contributes modestly.
  - These costs measure welfare losses; they are not directly GDP or fiscal losses without further modeling or assumptions.
  - If government assumes full responsibility for all losses, the CIAM estimates can be interpreted as an upper bound to government financing needs.

### Adaptation strategies: protection vs retreat (CIAM comparisons)
- Coastal protection:
  - Cost-effective protection of all coastline requires an investment of approximately 1.5 percent of GDP annually throughout the century.
  - Protection often implies guarding against 1/1,000-year storms in many segments.
  - Protection can disrupt natural exchange between wetlands and open seas; biodiversity losses estimated at 0.2 percent of GDP annually (higher than in the no-adaptation case).
  - CIAM does not model some nature-based protection options (e.g., mangroves, vetiver grass) due to insufficient granular data.
  - Protection can be more costly than no adaptation because the cost of protection may exceed the value of assets and land protected.
- Planned retreat (relocation):
  - CIAM estimates the cost of planned retreat as 0.3 percent of GDP, on average between 2020 and 2100.
  - Planned retreat avoids protection investment; capital losses are minimal in the gradual process (bare land lost to sea).
  - Opportunity cost of land for relocated populations is included and proxied by the value of interior agricultural or marginal land.
  - Planned retreat still entails fiscal costs to finance relocation and requires long-term participatory approaches for equity and effectiveness.

### Fiscal, institutional, and implementation details
- Fiji policy and institutions:
  - Planned Relocation Guidelines (PRG) launched in 2018.
  - Relocation Taskforce (FTRD) established to coordinate planned relocation.
  - Climate Relocation of Communities (CROC) Trust Fund established in 2020 to finance planned relocation.
  - CROC is funded by 3 percent of revenue from the Climate and Environmental Levy (ECAL) plus bilateral and multilateral donor funds.
- Historical relocation costs:
  - Relocation of six communities since 2011 is estimated to have costed FJD 3.6 million, or about 0.03 percent of GDP.
  - Relocation affected 78 households, for an average cost of FJD 46,300 per household.
- Policy implications:
  - Explicit cost-benefit analysis (CBA) of alternative adaptation options can help maximize impact of public funds and international aid while maximizing social welfare.
  - More granular data (hyper-resolution maps of elevation, currents, tides, infrastructure, population) is necessary to refine costs, protection needs, and retreat potential.
  - A long-term participatory approach involving local communities is essential to make planned retreat viable and equitable.

### Key model limitations and data needs
- CIAM limitations noted:
  - Uses averaged coastal slope and does not capture fine coastal characteristics that determine inundation at parcel level.
  - Does not capture interaction of SLR with ongoing coastal erosion processes or cost of saline intrusion into coastal aquifers.
  - Does include non-market costs such as loss of life from storm floods, wetland loss, and disutility from relocation.
- Data inventory:
  - CIAM divides Fiji coastline into 137 segments, with segment lengths ranging from 0.4 km to 619.2 km and a median length of 1.9 km.
  - High-resolution tools and portals (e.g., Sea Level Rise and Critical Infrastructure portal) and digital elevation models (e.g., FABDEM) are available and being used to inform planning.

### Practical takeaways and recommendations
- Planned retreat emerges as the least-cost adaptation strategy in CIAM central estimates (0.3 percent of GDP annually vs 1.5 percent for full-protection strategies).
- Protection can be highly effective locally but may be cost-ineffective at national scale and can generate higher biodiversity losses (0.2 percent of GDP annually).
- Policymakers should:
  - Use CBA and cost-effectiveness analysis, recognizing challenges but valuing transparency and systematic evaluation.
  - Prioritize the expansion of hyper-resolution mapping and data collection to refine vulnerability and adaptation cost estimates.
  - Finance and plan relocations through instruments like CROC while ensuring participatory approaches to limit social and cultural costs.
  - Consider mixing protection and planned retreat consistent with national guidelines and empirical assessments to contain fiscal costs and maximize welfare.

*Source: sipea2025085 - 1. Cost of Sea-Level Rise, Annual Average 2020-2099, Percentage of GDP; https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025085.pdf*

### Box 1.  Fiji: Coastal Relocation (concluded)

### Box 1.  Fiji: Coastal Relocation (concluded)

### Relocation challenges and case evidence
- Relocation entails loss of attachment to "land, history, and livelihoods," and the lack of land with productivity and amenities like the land of origin poses significant challenges.
- Existing land ownership arrangements may constrain local resettlement; example: a long-term lease on a former sugarcane plantation was cut short to accommodate households leaving the Etatoko village.
- Construction of new houses was entirely supported by external aid.
- Intergenerational differences: elders are more reluctant to move, while the younger generation — moving to non-agricultural wage labor and high-skilled jobs in larger towns — is more open to relocation.
- Participatory approaches that involved experts and local communities built trust and persuaded elders to move in Vunidogoloa village (low-lying Serua Island).
  - The new village is now located 1.5 km inland, on Vanua Levu Island, on dry grounds.
- Observations are characterized as partial and anecdotal and are stated as insufficient to draw firm conclusions about the viability of a nation-wide planned retreat from long-term sea-level rise, but they provide important insights.

### Data, mapping, and planning tools
- The government distributes state-of-the-art high-resolution flood maps with sea-level rise up to 2m.
- The Fiji Climate Change Information Hub/GIS platform:
  - Uses a state-of-the-art digital elevation model (DEM) (Hawker et al., 2022).
  - Interactively shows assets and population that can be flooded with sea-level rise from 0 to 2 m.
  - Combines information on exposure with local estimates of protection costs, land values, value of assets at risks, population density, and value of ecosystem services.
- Caveat on elevation data: the global DEM used for the portal has a mean vertical error equal to +/- 1.12 m, which is larger than expected sea level rise at the end of the century; hyper resolution local elevation maps are needed for planning purposes.

### National policy context and adaptation agenda
- Fiji milestones and documents:
  - First country to ratify the Paris Agreement in 2015.
  - First small island state to assume presidency of the United Nations Framework Convention on Climate Change in 2017.
  - One of the first countries that submitted a National Adaptation Plan (NAP) in 2018; a new NAP is in preparation.
- The 2018 NAP identifies 160 adaptation Actions but the effectiveness, efficiency, and fiscal sustainability of policies and concrete measures needs additional criteria.
  - Examples of NAP Actions:
    - Action 12.A.12: “enhance support for irrigation schemes which support agricultural diversification and mitigate increased drought and flooding”
    - Action 12.A.13: “maintain, adapt and construct sea wall and drainage infrastructure to reduce saltwater intrusion on agricultural land due to sea level rise and increased tidal surges”
    - Action 16.5: “strengthen the management an monitoring of ecosystems.”
- Policy design questions highlighted:
  - Variations in design (e.g., sea wall extension, height, material, retreat perimeters).
  - Trade-offs (e.g., preventing coastal tourism development to protect ecosystems).
  - Sizing of irrigation schemes for future water demand.
  - Determining the most efficient mix of public and private investment in adaptation.

### Principles for effective and efficient adaptation
- IMF Staff guidance and referenced literature (Gonguet et al. 2021; Bellon and Massetti, 2022a,b; Aligishiev, Bellon, and Massetti, 2022; Sakrak et al. 2022) frame adaptation in economic and sustainable development terms to guide public investment and enable efficient private adaptation.
- Key high-level principles:
  - Integrate adaptation into broader development planning; adaptation is aligned with the Paris Agreement (Article 7) objective and the 2018 NAP principle that “adaptation is seen as synonymous with climate-resilient development.”
  - Allocate resources carefully across competing needs while considering distributional effects:
    - (i) concentrate government efforts and resources in key areas; and
    - (ii) collect information on spending effectiveness across programs and impacts on distinct groups.
  - Prioritize adaptation policies with positive externalities, remove market imperfections that hinder efficient private adaptation, and ensure a just transition.

### Role of government vs. private adaptation; market failures
- Many adaptations have local and private benefits and are often undertaken autonomously at community level (examples from villages along the Ba River):
  - Planting trees around riverbanks, shifting plantations away from coastal areas, planning drought-resistant crop varieties, multi-cropping, changing harvesting times for mussels and prawns, and building houses on raised platforms.
- Government role is warranted when adaptation has large externalities or public-good characteristics (e.g., coastal protection in cities, public infrastructure, climate information services).
  - Fiji Meteorological Service plays an instrumental role in distributing weather and long-term climate information.
- Government should promote reforms that ease efficient use of resources and ensure competitive access to markets (examples: access to credit, efficient water pricing).
- Box 2 summary of market failures and policy responses (selected points reproduced verbatim from source):
  - Adaptations with large positive externalities and public goods are typically underprovided by markets (information, emergency preparedness, seawalls, research, technologies).
  - Network-dependent resilience (dikes, water networks, transportation) may require government coordination.
  - The extent of cooperation required depends on the externality scope; central government provision can amount to wealth transfers across regions when financed nationally.
  - Broader market imperfections (poor business environment, inefficient credit markets) hamper private adaptation.
  - Moral hazard can reduce private adaptation if actors expect central government relief; regulatory measures (zoning, building codes, mandatory evacuations, mandatory insurance) can mitigate moral hazard.
  - Policy failures (e.g., subsidies to inputs or water) can worsen resource use; removing distortions should be considered while accounting for distributional implications.
  - Source for Box 2: Massetti and Bellon (2022a).

### Use of cost-benefit analysis (CBA)
- CBA can help decision makers consistently collect, aggregate, and compare information on public adaptation projects, maximizing overall social welfare and avoiding waste of scarce resources.
- Ethical choices on “what to do, when, how, and at what cost” should reflect preferences of Fiji’s government and population; CBA complemented by distributional analysis is recommended.
- Action 8.10 of the 2018 NAP aims to mainstream "cost-benefit analysis, multi-criteria analysis, and other relevant tools (such as gender analysis) into decision-making processes regarding climate change adaptation."
- Practical implementation of NAP Actions would benefit from quantitative methods grounded in welfare economics; the NAP Costing Methodology developed by the Government can serve as a starting point.

### Appendix I: Climate trends and projections — key factual points
- Geography and climate overview:
  - Fiji is an archipelagic country consisting of over 332 islands in the South Pacific Ocean with a tropical marine climate.
  - Average annual mean temperature between 1984 and 2014 was equal to 24.9 °C.
  - Comparable medians: Asia-Pacific countries median 25.1 °C; Small Developing States median 26 °C.
  - Total annual precipitations are equal to 2,500 mm/year on average; world average 1,060 mm/year.
  - Approximately two thirds of total annual rainfall occur during the wet season from December to April.
  - Dry season receives more precipitations (116 mm / month) than most countries on average during a year.
- Historical trends:
  - Positive warming trend since at least the 1960s; precipitations relatively unchanged.
  - Mean annual temperature has increased by 0.3 °C between 1960-1990 and 1984-2014, and by an estimated additional 0.3 °C after 1984-2014.
  - Fiji’s warming trend is in the 13th percentile among countries (one of the slowest warming trends observed across all countries) and roughly half the size of the trend observed by the median country.
  - Warming has been more intense from July to November than in the rest of the year; the seasonal cycle has barely changed.
  - No discernible trend in total annual precipitations; interannual variability driven by ENSO is large with total annual rainfall ranging between 2,000 and 4,000 mm/year.
  - Slight tendency to observe more rainfall during the wet season in recent decades, but changes are small compared to interannual variability.
- Extremes and disasters:
  - No significant long-term trend in maximum number of consecutive dry days in a year (CDD), or in max 1-day (RX1Day) and max 5-day (RX5Day) precipitation indicators.
  - High-resolution analysis does not reveal a significant increase in intensity of heavy precipitations anywhere in the country (Appendix I. Figure 5).
  - Analysis of disaster data from the EM-DAT dataset does not show trends in large flood events and other climate-related disasters (Appendix I. Figure 6).
  - Days with maximum daily temperature above 35 °C are never observed in the data used for this analysis.

*Source: Box 1. Fiji: Coastal Relocation (concluded), sipea2025085*

### 4.       Climate models project continued warming but no significant change in total annual

### 4.       Climate models project continued warming but no significant change in total annual precipitations and other weather extremes (Appendix I. Figure 7)

### Temperature projections and weather extremes
- Median projections of warming across all climate model simulations:
  - increase between 0.8 and 1.1 °C in 2050 with respect to the 1985-2014 reference period.
  - increase between 0.8 and 2.0 °C in 2085 with respect to the 1985-2014 reference period.
- Individual models predict more warming and cannot be excluded:
  - In a high-emission, fast-warming scenario (90th percentile across models using the SSP3-7.0 emission scenario) temperature is projected to increase by 2.9 °C in 2085.
- Precipitations:
  - Median projections indicate minor changes relative to average total annual precipitations.
  - Models do not agree on the direction of change; no clear relationship between predicted changes in precipitations and emissions scenarios.
  - Natural variability dominates and is expected to continue to dominate any climate change–induced changes in precipitations.
- Extreme events and drought indicators:
  - No clear signals of changes in the number of maximum consecutive dry days and intense precipitation events.
  - The increased intensity of 5-day heavy precipitation events from their secular minimum around the year 2000 is likely part of medium-term natural climatic cycles and is considered a temporary deviation from long-term expected conditions.

### Sea-level rise projections and vulnerability
- Current trend:
  - Sea-level is increasing at approximately 4.7 mm per year, faster than the global average.
- Median and scenario-based projections relative to year 2000:
  - SSP2-4.5 (moderate emission scenario): sea-level will increase by 0.60 m by the end of the century with respect to its level in 2000.
  - SSP1-2.6 (Paris-aligned scenario): sea-level is projected to increase by 0.49 m by 2100.
  - Worst-case (extremely high emissions and fast ice melting, low-confidence, high-impact ice sheet processes): sea-level projected to increase by 0.98 m in 2100.
- Drivers and local factors:
  - Global oceanographic factors, thermal expansion, tectonic activity, erosion, and land subsidence explain why sea-level rise is faster in Fiji than the global average.
- Exposure:
  - 90 percent of Fiji’s total population of 900,000 live along the coastline, increasing vulnerability to sea-level rise.
- Management outlook:
  - Sea-level rise will likely continue for centuries; the risk can be managed but not avoided.

### Tropical cyclones (TCs)
- Observed frequency and future projections:
  - Approximately 30 TCs cross the Fiji Exclusive Economic Zone per decade.
  - Models predict an overall decline in TC genesis in the future because conditions favorable for TC formation are projected to become less frequent in the region.
  - Uncertainty is large; available data is not suitable for a long-term assessment of TC trends.
- Intensity and impacts:
  - The proportion of more severe TCs may increase, potentially limiting the decline in absolute numbers.
  - Little consensus on whether El Niño and La Niña events will change in intensity or frequency in the region.

### Consistency with national and regional studies
- Alignment and differences:
  - This assessment aligns with the Republic of Fiji National Adaptation Plan (NAP) and the CSIRO major study (Australian Bureau of Meteorology and CSIRO, 2014).
  - Some minor differences likely arise because CSIRO (2014) uses CMIP5 data while this analysis uses CMIP6 simulations.
  - CSIRO (2014) finds a significant change in extreme rainfall; this analysis does not find significant changes.
- Historical warming reported:
  - The NAP estimates mean air temperature has warmed by 0.9 °C over the last half century.
  - CRU-based analysis shows a warming rate of 0.1 °C per decade from 1961, similar to the warming rate measured at Nadi Airport as reported by CSIRO (2014).

### Estimating the cost of sea-level rise and adaptation (CIAM framework and insights)
- Modeling approach:
  - IMF staff use the Coastal Impact and Adaptation Model (CIAM) to estimate costs of sea-level rise (SLR) under alternative adaptation strategies.
  - CIAM divides the global coastline into more than 12,000 segments; Fiji’s coastline is modeled using 137 separate segments varying in length from 0.4 Km to 619 Km.
  - Each segment is divided into areas of different elevation with data on capital, population, and wetland coverage.
  - Projections of local sea-level rise (Kopp et al., 2014) are used to estimate inundated areas and capital/population at risk.
  - Storms cause periodic inundations on top of SLR; CIAM does not consider increased risks from river floods.
- Adaptation scenarios modeled:
  - No-adaptation: population remains until inundation forces relocation; costs include abandoned capital residual value, demolition costs, and value of inundated land; disutility cost of reactive migration is monetized.
  - Protection: investment in cost-effective seawalls and barriers along the entire coastline; capital and land preserved but storms can still cause periodic losses; costs equal cost of protection plus expected storm costs.
  - Planned retreat: gradual relocation and avoidance of new coastal capital; costs equal residual capital losses, value of inundated land, and disutility cost of relocation.
  - Variants consider protection heights to contain SLR and storm surges for 1/10-, 1/100-, 1/1,000- and 1/10,000-year events; Retreat 1 base scenario addresses permanent inundation only, with variants extending retreat perimeter to avoid storm surges.
- Economic valuation and decision rule:
  - For each coastal segment, CIAM calculates the net present value of SLR costs for each adaptation strategy, monetizing loss of life using the Value of Statistical Life and monetizing wetland loss via willingness to pay for biodiversity preservation.
  - The least-cost adaptation strategy is identified per segment by comparing SLR costs across scenarios.
  - Typical outcomes: coastal protection is usually least-cost in areas with large existing capital and high population density; planned retreat is usually least-cost in areas with low capital and population density.
- Model inputs and limitations:
  - Costs of building and maintaining seawalls and other parameters are drawn from the literature; storm surge costs are incremental relative to a baseline without SLR.
  - CIAM relies on necessary simplifications; more granular coastal modeling and accurate asset mapping could refine estimates.
- Key insight on adaptation effectiveness:
  - Literature consensus that long-term planning of adaptation can be highly effective at containing physical impacts and costs of SLR.
  - Example from related literature: the PESETA IV project finds coastal protection can reduce SLR damages in the EU by approximately 90 percent.
  - Transformations needed to adapt to SLR are technologically feasible and economically sound but complex and require strong governance.

### Quantitative highlights
- Temperature increases:
  - 0.8 and 1.1 °C in 2050 (median across models, relative to 1985-2014).
  - 0.8 and 2.0 °C in 2085 (median across models, relative to 1985-2014).
  - 2.9 °C in 2085 (SSP3-7.0, 90th percentile ensemble).
- Sea-level rise:
  - Current rate: approximately 4.7 mm per year.
  - SSP2-4.5: 0.60 m increase by end of century relative to 2000.
  - SSP1-2.6: 0.49 m increase by 2100 relative to 2000.
  - Worst Case: 0.98 m increase by 2100 relative to 2000.
- Exposure:
  - Fiji total population: 900,000; 90 percent live along the coastline.
- Tropical cyclones:
  - Approximately 30 TCs cross the Fiji Exclusive Economic Zone per decade.
- CIAM and coastal modeling:
  - Global coastline segments in CIAM: more than 12,000.
  - Fiji coastline segments in CIAM: 137 segments ranging from 0.4 Km to 619 Km.
- Historical warming and trends:
  - NAP estimate: mean air temperature warmed by 0.9 °C over the last half century.
  - CRU-derived warming rate: 0.1 °C per decade from 1961.

*Source: IMF staff analysis presented in the chapter “Climate models project continued warming but no significant change in total annual precipitations and other weather extremes” (Appendix I and II) from the provided document.*

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_Source: https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025085.pdf_