Facilitating the Smooth Migration of Inhabitants of Atoll Countries to Artificial Islands: Case of the Maldives

Abstract

The vulnerability of atoll countries to sea level rise underscores the pivotal connection between climate change and migration. This study examines the multifaceted challenges faced by such countries, including land loss, economic disruption, water contamination, and increased vulnerability to extreme weather events, and potential adaptation strategies, such as migration to developed countries and other islands, land reclamation, and floating platform development. The situation of the Maldives, particularly the creation of the artificial island of Hulhumalé, is explored as a case study. Hulhumalé is designed to alleviate congestion while addressing concerns about rising sea levels. This study employed a questionnaire survey and analyzed the data using importance analysis of permutation features and structural equation modeling following the Wilcoxon–Mann–Whitney tests. The results revealed that the key factors influencing resident satisfaction after migration were clean housing, resilience to natural disasters, sports facilities, and environmental quality. Adaptation strategies must be tailored to each country’s unique circumstances, considering the interconnectedness of environmental and socioeconomic factors in addressing climate-induced migration. Considering Hulhumalé as a model for climate change adaptation, concerted global action is necessary to mitigate the impacts of climate change and ensure the security and well-being of vulnerable populations.

1. Introduction

Globally, four countries comprise entirely of atolls: Kiribati, the Republic of Maldives, the Marshall Islands, and Tuvalu. These atoll nations face exceptional vulnerability to climate change impacts, notably sea level rise, with projections suggesting many could become uninhabitable by the end of the 21st century, particularly if global mean sea levels rise by 2 m by 2100 and 5 m by 2150 [1]. The Republic of Maldives, in particular, is at heightened risk due to its low elevation, with 80% of its islands positioned less than 1 m above mean sea level [2]. The geographical vulnerability of atolls, formed from coral reefs, makes them inherently susceptible to even minor sea level increases, accentuating the severity of the threat posed by climate change. This vulnerability becomes a pathway to extensive land loss, resulting in the displacement and homelessness of the population as habitable areas shrink. The limited land area of atoll nations compounds this problem. According to Sasaki [3], the countries faced with disasters caused by climate change have tended to prioritize climate change in their official statements at international ministerial conferences on disaster risk reduction. With their already restricted space, the reduction in habitable land due to sea level rise exacerbates existing social and economic challenges. Land scarcity impacts not only housing but also essential sectors such as agriculture and infrastructure, jeopardizing livelihoods and overall well-being. The contamination of water resources poses a major threat. As sea levels increase, saltwater intrusion into freshwater sources like groundwater aquifers jeopardizes clean drinking water availability and exacerbates food and water security concerns. This crisis is compounded by the economic reliance of atoll nations on the ocean. With their economies heavily dependent on marine resources, sea level rise can disrupt vital components such as coral reefs, marine habitats, and fish populations, thereby endangering their economic foundations. Heightened vulnerability to extreme weather events, such as storm surges from hurricanes and cyclones, compounds the challenges faced by these nations. Elevated sea levels amplify the impact of these events, leading to extensive damage, infrastructure loss, and increased risks to human safety. Current international law does not address the situation in which a state’s territory sinks [4]. There are no provisions specifying to which state the territory, airspace, and territorial waters of the sunken area would belong.

Nakayama et al. [5] suggested that atoll countries have four potential options for addressing sea level rise: (i) migration to developed countries, (ii) migration to other island nations, (iii) land reclamation and elevation, and (iv) development of floating platforms. Outmigration is the most problematic of these. Expatriate migrants often struggle to maintain their “migratory dignity” within the current framework. Additionally, widespread emigration would directly threaten the history, traditions, and cultural integrity of the country involved, resulting in a loss of national identity. Thus, both qualitative and quantitative damage becomes significant. In addition, the decline in productivity and economic damage caused by population decline cannot be overlooked as this could significantly impact not only the country concerned but also neighboring countries, potentially resulting in the collapse of diplomatic balance.

Given this context, the study aims to elucidate the critical nexus of climate change and migration, with a focus on the vulnerability of atoll countries to sea level rise. The efficacy of adaptation strategies, particularly from the perspective of residents in atoll nations, remains unclear. Leveraging its low-lying geography and heightened susceptibility to rising sea levels, the study examines the case of migration to the artificial island of Hulhumalé in the Republic of Maldives as an illustrative example of this challenge. Hulhumalé is strategically designed to alleviate congestion in the capital, Malé, while addressing concerns about rising sea levels. The significance of projects in terms of economic development, urban planning, and environmental resilience are highlighted in this study.

2. Methodology

2.1. Research Area

The Republic of Maldives, officially the smallest country in Asia with a land area of approximately 298 km² [6], is a captivating island nation situated in the Indian Ocean, southwest of Sri Lanka and India. According to the country’s Ministry of Environment and Energy [2], the archipelago is composed of over 1000 coral islands grouped into 26 atolls; approximately 200 of these islands are inhabited, and the rest remain either uninhabited or used primarily for agricultural purposes. As an archipelago in the Indian Ocean, the Maldives have a history dating back more than two millennia, with early settlers believed to have arrived from the Indian subcontinent and Sri Lanka [7]. Globally, it holds the distinction of being the lowest-lying country, with an average elevation of merely 1.5 m, and its highest point reaching a modest 2.3 m above sea level, earning it the unique title of having the world’s lowest naturally occurring “highest point” [8]. Serving as the economic, political, and cultural nucleus of the nation, Malé, the capital and most populous city, stands at the forefront.

Migration in the Maldives is a significant social phenomenon shaped by various factors. Despite its natural beauty, sandy beaches, and thriving marine life, the country faces unique challenges due to its geographic characteristics. Similar to numerous other countries, the Maldives experiences rural-to-urban migration, as individuals relocate from rural areas to urban centers, especially Malé. This migration is propelled by various factors, including the pursuit of enhanced job prospects, access to education, healthcare amenities, and improved living standards [9].

In 1997, the Maldivian government initiated the construction of Hulhumalé, an artificial island situated near Malé, for multiple purposes. Apart from mitigating the impacts of sea level rise, this ambitious project addresses other pressing concerns. Primarily, it provides a solution to alleviate the high population density experienced in the capital city of Malé, where issues related to public security, sanitation, and living conditions arise due to overcrowding. Hulhumalé offers larger, well-managed land to effectively disperse the population. Second, the government intends to transform Hulhumalé into an economic and administrative center. It currently houses an international airport and has a commercial and economic zone, as well as a marine hub for tourist boats.

According to Sakamoto et al. [10], construction of the city’s Phase 1 was completed in 2002, with the true launch being celebrated in 2004, upon the arrival of the first settlers. Hulhumalé was built 1.8 to 2.0 m above mean sea level [11], surpassing the average height of natural islands, to provide protection against flooding caused by sea level rise, estimated to be up to 0.6 m [12]. An additional 216 ha were reclaimed in 2015 to fulfill the broader vision of the city. While Phase 1 was funded by the national state budget, Phase 2 required an investment of 160 million USD from the state-owned Housing Development Corporation (HDC), established in 2001 by presidential decree to oversee Hulhumalé’s development [13]. The corporation’s current focus is making Hulhumalé the first sustainable city in the Maldives by targeting key areas such as housing, commercial development, recreational spaces, and job creation. The HDC’s efforts have now extended beyond residential projects, incorporating large-scale developments in tourism, IT, telecommunications, finance, industry, and education, resulting in an increase in population on the island.

After the completion of Phase 1 in 2004, the first 1000 people officially migrated to Hulhumalé. Meanwhile, the population of Malé was 98,744 in 2020, projected to reach 129,560 by 2023, and expected to grow to 240,000 residents in the mid-2020s [10]. Approximately 80% of the Maldivian population will eventually migrate to the Greater Malé Region. Thus, the population of Hulhumalé is expected to reach at least 240,000 people. The HDC seeks major investments in Hulhumalé, with Phase 2’s development expected to provide employment to approximately 85,000 people [10]. The Hulhumalé Smart City project, launched in 2017 in collaboration with Qatar’s telecom companies Ooredoo and UNDP, is one of the notable features of this initiative.

2.2. Design of the Questionnaire Survey

The HDC and Global Infrastructure Fund Research Foundation Japan (GIF Japan) jointly conducted a survey of Hulhumalé residents in August and September 2022. Using snowball sampling, the survey recruited 252 participants through a web-based platform. Previous studies, such as that by Sasaki et al. [14], have utilized web-based surveys to prevent the overallocation of resources in the sampling process. For this study, residents of Hulhumalé were initially recruited to participate in the survey through social networking platforms. They were subsequently encouraged to refer their neighbors to participate, utilizing their social networks and connections. Employing a snowball sampling technique enabled the researchers to engage a more diverse pool of respondents, including individuals who might have been less accessible through conventional sampling approaches. The questionnaire included 11 questions (equivalent to attributes c1–c11) about respondents’ attributes (

Table 1. List of survey questions (c1 to c11) on respondent attributes.

Question No.	Question
c1	Age
c2	Sex
c3	Education level
c4	Year of migration to Hulhumalé
c5	Pre-migration settlement
c6	Occupation before migration
c7	Occupation after migration
c8	Annual personal income before migration
c9	Annual personal income after migration
c10	Reason for moving to Hulhumalé
c11	Interest in returning to the place where you lived before moving to Hulhumalé

) and 32 questions (x1–x32) about various aspects of their lives after moving to Hulhumalé (

Table 2. List of Survey questions (x1 to x32) about various aspects of respondents’ lives after moving to Hulhumalé.

Question No.	Question
x1	You were satisfied with your life before you moved to Hulhumalé.
x2	You are satisfied with your life at the moment.
x3	There are many opportunities for high-paying jobs.
x4	There are many opportunities for non-physical work.
x5	The cost of living is low.
x6	A wide range of dining, shopping, hotels, and entertainment options are available.
x7	Many hospitals make it easy for people to access medical care.
x8	A high level of medical care is available (e.g., for serious illnesses such as cancer).
x9	Many sports facilities and parks provide environments for people to maintain their health through exercise.
x10	Rent or house acquisition cost is low.
x11	There are many opportunities to live in a clean new home.
x12	The quality of primary education is good.
x13	The quality of higher education is good.
x14	Tutoring and learning opportunities are widely available.
x15	Links are maintained between people from pre-migration settlements.
x16	There are many opportunities to gain new friends and partners.
x17	Many local community activities are available.
x18	There are good neighborly relations.
x19	Great efforts have been made to preserve the local and traditional culture in various parts of the Maldives.
x20	The living environment is healthy without air and water pollution.
x21	The living environment is kept clean, with proper waste collection and cleaning of public areas.
x22	There are beautiful and rich natural surroundings.
x23	Hulhumalé is resilient to natural disasters, such as cyclones, storm surges, flooding, and water shortages.
x24	Hulhumalé is safe against sea level rise due to climate change.
x25	Hulhumalé ensures the territorial integrity of the Maldives in the event of a rise in sea level.
x26	Lives are safeguarded by the police.
x27	The public manners of the people are good.
x28	Infrastructure such as electricity, gas, water, sewage, and telecommunications are in place.
x29	Transport infrastructure, including public transport, is well developed.
x30	Transport links are well-developed throughout the Maldives.
x31	Transport links to international airports (abroad) are well developed.
x32	There are good quality administrative services.

). For the 32 questions, respondents were asked to assess statements on a 5-point Likert scale. Specifically, they were supposed to choose one of the following options: “Strongly agree” (5 points), “Agree” (4 points), “Neither agree nor disagree” (3 points), “Disagree” (2 points), and “Strongly disagree” (1 point).

The study employed the permutation feature importance (PFI) technique to identify the primary explanatory variables [15,16]. PFI involves quantifying the increase in the model’s prediction error by rearranging the feature values, thereby disrupting the relationship between the feature and the true outcome. The significance of each feature is evaluated by measuring the extent to which the prediction error of the model rises when the feature values are shuffled. A feature is considered “important” if shuffling its value results in a higher model error, indicating that the model heavily depends on that specific characteristic for making predictions. In contrast, if the shuffling has little effect on the model’s error, implying that the feature is not considered during predictions, it is considered “unimportant.” Finally, structural equation modeling (SEM) was applied to clarify the causal relationships between variables. SEM offers a comprehensive depiction of relationships between variables and enables the evaluation of “latent variables,” which are not directly observable, including subconscious factors. As proposed by Tarka [17], latent variables can be indirectly gauged by employing a collection of observable variables and exploring the causal effects among these latent variables within the framework of SEM. There exist a certain number of previous studies related to disaster statistics [18], one of which is Sasaki et al. [19] which has adopted SEM to analyze hidden common factors in disaster statistics in Nepal. Another earlier investigation conducted by Sasaki et al. [20] utilized SEM in analyzing a questionnaire survey conducted in the Marshall Islands.

The statistical software used for the analysis included the following R packages [R version 4.3.3]: caret, xgboost, dplyr, psych, GPArotation, lavaan, semTools, and semPlot.

3. Results and Discussion

3.1. Wilcoxon–Mann–Whitney Test

We first conducted an ordinary statistical analysis to determine whether migrants became happier after moving to Hulhumalé. Figure 1 and

Table 3. Statistical assessment of people’s satisfaction before and after migration.

		Mean	Median
x1	Satisfaction before migration	3	3
x2	Satisfaction after migration	3.7	4

show the respondents’ life satisfaction levels before and after their migration to Hulhumalé. Results show that many people are satisfied with their lives after migration. (Unless otherwise noted, the difference between the two groups presented in this paper was found to be significant by the Wilcoxon–Mann–Whitney test with a p-value < 0.05.)

Table 4. Most and least appreciated aspects of life in Hulhumalé.

		Rank	Mean	Median			Rank	Mean	Median
x28	Utility infrastructure	1	3.7	4	x10	Rent or house acquisition cost	30	1.7	1
x22	Beautiful and rich natural surroundings	2	3.5	4	x5	Cost of living	29	1.8	1
x9	Sports facilities and parks	3	3.4	4	x26	Safeguarded by the police	28	2.2	2
x29	Transportation in the island	3	3.4	3	x19	Preserve local and traditional culture	26	2.3	2
x31	Transport links (abroad)	3	3.4	4	x27	Public manners	26	2.3	2
x20	No air and water pollution	6	3.3	4	x3	High-paying jobs	25	2.4	2

shows different aspects of life in Hulhumalé that are the most or least valued by the residents. Residents generally value the environment of Hulhumalé, specifically its natural beauty and air and water quality. Transportation is also highly valued, as are sports facilities and parks. In contrast, the high costs of acquiring a residence and living in Hulhumalé were least appreciated by the residents, along with the lack of cultural activities, well-paying jobs, police protection, and public order.

The statistical significance between the two groups per attribute was then examined using the Wilcoxon–Mann–Whitney test. Respondents were divided into two groups according to age (c1), sex (c2), education (c3), place of origin (c5), income (c8 and c9), and intention to return to their place of origin (c11) (

Table 5. Division of attributes into Category 1 and Category 2 and the number of samples in each category.

Attribute		Category 1	Category 2	Number of Samples of Category 1	Number of Samples of Category 2	Total Number of Samples
c1	Age	20–29 years old	More than 50 years old	69	20	89
c2	Sex	Male	Female	114	138	252
c3	Education level	O’Level	First Degree & Higher	35	137	172
c5	Pre-migration settlement	Malé	Other cities	193	59	252
c8	Annual personal income before migration	Less than Rf. 29,999	More than Rf. 210,000	141	31	172
c9	Annual personal income after migration	Less than Rf. 29,999	More than Rf. 210,000	111	49	160
c11	Interest in returning to the place where you lived before moving to Hulhumalé	Yes or undecided	No	75	177	252

). We then attempted to identify the demographic characteristics associated with higher life satisfaction among residents of Hulhumalé. To achieve this, we analyzed the responses regarding satisfaction after migration (x2). We assessed whether there were significant differences in responses to this question based on respondents’ attributes. As illustrated in

Table 6. Questions with statistically significant differences (p < 0.05) between attributes in Categories 1 and 2.

Question		Attribute	Category 1		Category 2		p Value	p Value <
			Mean	Median	Mean	Median
x1	Satisfaction before migration	c5	2.85	3	3.46	4	0.00079	0.01
		c11	3.35	3	2.84	3	0.00184	0.01
x2	Satisfaction after migration	c5	3.76	4	3.31	4	0.04854	0.05
		c11	3.17	3	3.85	4	0.00011	0.01
x3	High-paying job	c1	2.64	3	1.95	2	0.02402	0.05
		c2	2.65	3	2.2	2	0.00563	0.01
		c5	2.21	2	3.05	3	0.00004	0.01
		c11	2.76	3	2.25	2	0.00856	0.01
x4	Non-physical work	c1	2.9	3	1.95	2	0.00029	0.01
		c2	2.82	3	2.43	2	0.00678	0.01
		c5	2.45	2	3.1	3	0.00017	0.01
x5	Cost of living	c5	1.96	2	1.44	1	0.00007	0.01
x6	Wide choice of entertainment	c5	2.64	3	3.24	3	0.00206	0.01
x8	High level of medical care	c1	2.9	3	1.9	2	0.00213	0.01
		c11	2.24	2	2.66	3	0.03602	0.05
x9	Sports facilities and parks	c9	3.24	4	3.69	4	0.04348	0.05
		c11	2.99	3	3.59	4	0.00069	0.01
x10	Rent or house acquisition cost	c5	1.74	1	1.37	1	0.00358	0.01
x11	Clean new home	c5	3.21	3	2.75	3	0.01222	0.05
		c11	2.68	3	3.28	3	0.00061	0.01
x12	Quality of primary education	c1	3.46	4	2.8	3	0.0127	0.05
		c5	3.06	3	3.44	4	0.0106	0.05
x13	Quality of higher education	c3	3.29	3	2.47	3	0.00056	0.01
		c5	2.41	2	3.24	3	0.00001	0.01
x14	Tutoring and learning opportunities	c1	3.22	3	2.45	3	0.00324	0.01
		c5	2.66	3	3.25	3	0.00025	0.01
x15	Links of people before migration	c1	3.38	3	2.75	3	0.01945	0.05
x19	Preservation of local and traditional culture	c2	2.46	3	2.21	2	0.03411	0.05
x20	No air and water pollution	c11	2.96	3	3.46	4	0.00424	0.01
		c5	3.41	4	2.98	3	0.02173	0.05
		c9	3.08	3	3.49	4	0.03607	0.05
x22	Beautiful and rich natural surroundings	c2	3.4	3	3.66	4	0.02445	0.05
		c11	3.21	3	3.68	4	0.00149	0.01
x23	Resilience to natural disasters	c1	3.22	3	2.7	3	0.04616	0.05
x25	Territorial integrity	c2	3	3	2.71	3	0.03705	0.05
x27	Public manners	c3	2.71	3	2.26	2	0.0436	0.05
x28	Utility infrastructure	c8	3.56	4	3.94	4	0.02219	0.05
		c9	3.5	4	3.96	4	0.00476	0.01
x29	Transportation in the island	c1	3.65	4	2.95	3	0.01893	0.05
x32	Administrative services	c1	2.75	3	2.15	2	0.02823	0.05
		c11	2.24	2	2.65	3	0.00651	0.01

, migrants from Malé (Category 1 of attribute c5) exhibited significantly higher satisfaction with life in Hulhumalé compared to those from outside Malé (Category 2 of attribute c5). Additionally, our analysis revealed that migrants who opted to remain in Hulhumalé (Category 2 of attribute c11) reported greater life satisfaction compared to those intending to return to their place of origin or were undecided about returning (Category 1 of attribute c11).

We further determined the instances in which the answers to a particular question differed significantly by attribute (

Table 7. Questions with statistically significant differences (p < 0.05) between attributes in Categories 1 and 2.

Question		Attribute	Category 1		Category 2		p Value	p Value <
			Mean	Median	Mean	Median
x3	High-paying jobs	c1	2.64	3	1.95	2	0.02402	0.05
x4	Non-physical work		2.9	3	1.95	2	0.00029	0.01
x8	High level of medical care		2.9	3	1.9	2	0.00213	0.01
x12	Quality of primary education		3.46	4	2.8	3	0.0127	0.05
x14	Tutoring and learning opportunities		3.22	3	2.45	3	0.00324	0.01
x15	Links of people before migration		3.38	3	2.75	3	0.01945	0.05
x23	Resilience to natural disasters		3.22	3	2.7	3	0.04616	0.05
x29	Transportation in the island		3.65	4	2.95	3	0.01893	0.05
x32	Administrative services		2.75	3	2.15	2	0.02823	0.05
x3	High-paying jobs	c2	2.65	3	2.2	2	0.00563	0.01
x4	Non-physical work		2.82	3	2.43	2	0.00678	0.01
x19	Preservation of local and traditional culture		2.46	3	2.21	2	0.03411	0.05
x22	Beautiful and rich natural surroundings		3.4	3	3.66	4	0.02445	0.05
x25	Territorial integrity		3	3	2.71	3	0.03705	0.05
x13	Quality of higher education	c3	3.29	3	2.47	3	0.00056	0.01
x27	Public manners		2.71	3	2.26	2	0.0436	0.05
x1	Satisfaction before migration	c5	2.85	3	3.46	4	0.00079	0.01
x2	Satisfaction after migration		3.76	4	3.31	4	0.04854	0.05
x3	High-paying jobs		2.21	2	3.05	3	0.00004	0.01
x4	Non-physical work		2.45	2	3.1	3	0.00017	0.01
x5	Cost of living		1.96	2	1.44	1	0.00007	0.01
x6	Wide choice of entertainment		2.64	3	3.24	3	0.00206	0.01
x10	Rent or house acquisition cost		1.74	1	1.37	1	0.00358	0.01
x11	Clean new home		3.21	3	2.75	3	0.01222	0.05
x12	Quality of primary education		3.06	3	3.44	4	0.0106	0.05
x13	Quality of higher education		2.41	2	3.24	3	0.00001	0.01
x14	Tutoring and learning opportunities		2.66	3	3.25	3	0.00025	0.01
x20	No air and water pollution		3.41	4	2.98	3	0.02173	0.05
x28	Utility infrastructure	c8	3.56	4	3.94	4	0.02219	0.05
x9	Sports facilities and parks	c9	3.24	4	3.69	4	0.04348	0.05
x20	No air and water pollution		3.08	3	3.49	4	0.03607	0.05
x28	Utility infrastructure		3.5	4	3.96	4	0.00476	0.01
x1	Satisfaction before migration	c11	3.35	3	2.84	3	0.00184	0.01
x2	Satisfaction after migration		3.17	3	3.85	4	0.00011	0.01
x3	High-paying jobs		2.76	3	2.25	2	0.00856	0.01
x8	High level of medical care		2.24	2	2.66	3	0.03602	0.05
x9	Sports facilities and parks		2.99	3	3.59	4	0.00069	0.01
x11	Clean new home		2.68	3	3.28	3	0.00061	0.01
x20	No air and water pollution		2.96	3	3.46	4	0.00424	0.01
x22	Beautiful and rich natural surroundings		3.21	3	3.68	4	0.00149	0.01
x32	Administrative services		2.24	2	2.65	3	0.00651	0.01

). The following findings were obtained.

In terms of age (c1), the answers of Category 1 (20–29 years old) and Category 2 (more than 50 years old) respondents to questions x3, x4, x8, x12, x14, x15, x23, x29, and x32 significantly differed. Unsurprisingly, the younger generation is more concerned about convenience, particularly access to educational opportunities, employment possibilities, transportation, and services provided by government offices. In addition, interest in natural disasters varies by age, with younger generations being more concerned about the resilience of Hulhumalé to natural disasters. This was also the case with people’s connections before migration.

In terms of sex (c2), Category 1 (Male) and Category 2 (Female) responses to questions x3, x4, x19, x22, and x25 also differed considerably, suggesting that sex influences employment opportunities in Hulhumalé. Interestingly, concerns such as the preservation of local and traditional culture, beautiful and rich natural environments, and territorial integrity are evaluated differently by sex.

In terms of education level (c3), the responses of individuals from categories 1 (O’Level) and 2 (First degree and higher) to questions x13 and x27 were significantly different. This was a surprise to the authors, as we expected educational level to have an impact on other questions. This suggests that factors other than education have a greater impact on residents’ evaluations of their living environment in Hulhumalé.

In terms of pre-migration settlement (c5), the answers to questions x1, x2, x3, x4, x5, x6, x10, x11, x12, x13, x14, and x20 were significantly different for respondents from Malé (Category 1) and other cities (Category 2). Notably, for those who have migrated to Hulhumalé from areas other than Greater Malé, life in Hulhumalé is quite different (mostly positive) compared with their places of origin. This may be because of the better educational and employment opportunities offered in Hulhumalé, which are major factors in people’s decisions to move. However, for these people, the cost of living in Hulhumalé is a major constraint in their decision to move.

In terms of annual personal income before migration (c8), only responses to question x28 proved significantly different between Category 1 (less than Rf. 29,999) and Category 2 (more than Rf. 210,000) respondents. Wealthier people are more likely to enjoy the services provided by Hulhumalé, such as public facilities.

In terms of annual personal income after migration (c9), the answers to questions x9, x20, and x28 were significantly different between people who earn less than Rf. 29,999 (Category 1) and more than Rf. 210,000 (Category 2). These findings suggest that the higher-income bracket enjoys the facilities and favorable environment in Hulhumalé, whereas people with lower incomes miss the opportunity to enjoy services and public facilities provided in Hulhumalé.

In terms of respondents’ interest in returning to their original homes (c11), the answers to questions x1, x2, x3, x8, x9, x11, x20, x22, and x32 proved significantly different between Category 1 (yes or undecided) and Category 2 (no). The respondents’ intention to live permanently in Hulhumalé was reflected in the differences in their ratings of the living environment in Hulhumalé across a number of questions. Unsurprisingly, those who rated their living environment as high intended to continue living in Hulhumalé. This suggests that the proportion of people who wish to continue living in Hulhumalé can be increased by further improving public facilities and other services.

3.2. Permutation Feature Importance

To identify the factors influencing migration, we implemented two sequential procedures. Firstly, we applied the extreme gradient boosting algorithm to construct a model, with respondents’ satisfaction after the migration (question x2) as the objective variable and all other questions serving as explanatory variables. Subsequently, we utilized PFI within the calibrated model to pinpoint the explanatory variables contributing to the most significant factors.

PFI assesses the importance of independent variables by quantifying the reduction in model accuracy when the values of a specific independent variable are randomly rearranged. Notably, for the dependent variables, which were categorized using the Likert scaling method from 1 to 5, the estimation error was minimized to 0% when the model’s output was rounded to the nearest integer.

The outstanding factors that were identified are as follows:

• x11—Clean new home
• x23—Resilience to natural disasters
• x9—Sports facilities and parks
• x20—No air and water pollution
• x25—Territorial integrity

These factors represent the five most significant independent variables, as evidenced by the magnitude of the model error rate. This finding indicates that current inhabitants highly value the factors related to their living conditions.

“Resilience to natural disasters” was the second-most influential explanatory variable. The respondents perceived the ordinary land of the Maldives, which consists of coral reefs, as vulnerable to natural disasters, and Hulhumalé, a modern city, as more vulnerable to natural disasters than coral reefs.

“Territorial integrity” was also found to be an important explanatory variable, suggesting that this issue, which in part should be affected by the expected sea level rise, is of interest to the residents of Hulhumalé.

3.3. Structural Equation Modeling

The SEM results are presented in Figure 2, depicted as a path diagram. According to the results, the quality of the living environment (L_E in Figure 2) greatly impacts the level of life satisfaction (x2). Notably, the living environment appears to be influenced by two additional factors: disaster risk reduction and climate change adaptation (DRR and CCA), as well as the educational environment (E_E). Furthermore, the analysis reveals that job opportunities (J_O) also impact current life satisfaction (x2), albeit to a lesser extent compared to the living environment. The path coefficient from disaster risk reduction and climate change adaptation to the living environment (0.42) is relatively high, suggesting that disaster risk reduction and climate change adaptation indirectly affect life satisfaction through their influence on the living environment. These results are also consistent with those of the PFI analysis, which identifies x11 (clean new home) and x20 (air and water pollution) under the living environment, and x23 (resilience to natural disasters) and x25 (territorial integrity), belonging to disaster risk reduction and climate change adaptation, as outstanding variables.

The model’s fit indices were as follows: comparative fit index (CFI) = 0.943, root-mean-square error of approximation (RMSEA) = 0.060, and adjusted goodness-of-fit index (AGFI) = 0.880.

3.4. Overall Implications

The vulnerability of atoll countries to the impacts of climate change, particularly sea level rise, presents an existential threat that cannot be ignored. The atoll nations of Kiribati, the Maldives, the Marshall Islands, and Tuvalu are at the forefront of this crisis, facing the prospect of uninhabitability within the coming decades if global sea levels continue to rise at the projected rates. This vulnerability arises from a combination of geographical characteristics, limited land area, economic dependence on the ocean, and heightened susceptibility to extreme weather events. Addressing this critical problem requires multifaceted strategies that consider the socioeconomic, environmental, and cultural dimensions of these affected countries.

Migration stands out as a potential solution for atoll nations grappling with the impact of sea level rise. The Maldives exemplifies this approach with the construction of Hulhumalé, an artificial island, offering a place for residents to seek higher ground. Hulhumalé serves as a model for addressing population congestion in the capital, Malé, while simultaneously responding to the threat of rising sea levels. The Maldivian government’s efforts to create economic opportunities and develop sustainable infrastructure demonstrate a proactive approach to the challenges posed by climate change. However, the survey revealed that many of the current residents of Hulhumalé did not move to the island because of its immunity to the effects of climate change. As Karabchuk et al. [21] observed, there is a negative association between life satisfaction and the desire to emigrate in the existing literature. They also examined the role of human development as a moderator in this relationship. This suggests that higher levels of human development in Hulhumalé could encourage residents to stay in the Maldives.

The findings of the questionnaire survey conducted in Hulhumalé shed light on the factors influencing resident perceptions of life after migration. Residents’ satisfaction with their new lives, as evident from the survey results, underscores the importance of addressing concerns such as housing quality, environmental resilience, sports facilities and parks, and air and water quality. These factors play crucial roles in determining the success of migration-based adaptation strategies. The PFI analysis, as well as SEM analysis, highlights the significance of factors such as clean housing, resilience to natural disasters, sports facilities and parks, and unpolluted environments, indicating that residents’ well-being and comfort are central to their overall satisfaction.

4. Conclusions

The lessons learned from the Maldivian experience can provide insights for other atoll countries facing similar challenges. However, recognizing that migration is not a one-size-fits-all process is important. Each nation’s unique circumstances, cultural identity, and developmental priorities must be considered when devising adaptive strategies. Furthermore, international collaboration and support are crucial for ensuring that vulnerable nations have access to the resources, technology, and expertise required to implement effective solutions. The Maldives’ construction of Hulhumalé was facilitated by the country’s diverse circumstances, but not all atoll nations have similar circumstances.

Constructing an artificial island requires substantial financial investment. The Maldives funded most of the construction costs of Hulhumalé through foreign loans and guarantees. For other atoll nations, securing funds would likely depend on the international community’s loss and damage response fund. Thus, financing such investments poses a significant challenge, hindering the broader implementation of smooth migration of inhabitants of atoll nations to artificial islands. Furthermore, efforts should be made to raise awareness among the international community that some atoll countries may not be able to build artificial islands even if resources are available to them.

As the global community grapples with the complex and urgent problem of climate change-induced displacement, the case of atoll countries such as the Maldives underscores the interconnectedness of environmental, social, and economic factors. The urgency of addressing sea level rise requires proactive measures that encompass not only physical relocation but also sustainable development, infrastructure improvement, and cultural preservation. The fate of these atoll nations should serve as a wake-up call for concerted global action to mitigate the impacts of climate change and ensure the well-being and security of vulnerable populations.

Addressing the challenges of climate-induced migration and minimizing its impacts on future generations requires collaborative efforts, innovative solutions, and a shared commitment to responsibility. The authors firmly believe that Hulhumalé’s construction in the Maldives should serve as a harbinger for other atoll and even non-atoll nations in their development of climate change adaptation strategies.