Vulnerability in Coastal Touristic Cities Impacted by Tropical Cyclones and Landslides in a Changing Climate: A Case Study from Los Cabos, Mexico

Abstract

Coastal areas are rich in diverse resources and are ideal locations for developing the tourism industry. Thus, in coastal tourist centers, the growth rate is high, although often disorganized and unsustainable. In Mexico, tourist centers have fostered poverty belts where inhabitants live in conditions of high vulnerability due to hydrometeorological and geological phenomena in regular and irregular settlements. Thus, various coastal tourist areas in Mexico have been impacted by these types of phenomena, causing deaths, a high number of victims, and significant economic losses. Previous studies have confirmed that tropical cyclones can trigger landslides resulting from intense rainfall; however, risk estimation models and their components are presented separately. This paper presents a model based on the Intergovernmental Panel on Climate Change (IPCC) framework to estimate vulnerability to tropical cyclones and landslides in the context of climate change. The integration of both disruptive phenomena and climate change was carried out in the exposure sub-index. The socioeconomic situation of the inhabitants was included in the sensitivity sub-index. Vulnerability was modeled for the near, medium, and distant future, with population growth projections for the towns of Cabo San Lucas and San José del Cabo, Mexico. Climate change associated with urban expansion will increase exposure from 121.27 to 956.74 km², while the vulnerable population is expected to increase from 133,266 to 250,386 by 2100. The model proved to be an effective tool for determining the combined vulnerability of both phenomena, allowing for the generation of strategies for decision-makers to implement actions focused on reducing vulnerability and building resilience.

1. Introduction

Coastal populations contribute to national development by utilizing marine resources for food, tourism, and other key industries. Consequently, these areas often experience rapid, unplanned, and unsustainable population growth, resulting in various socioeconomic and environmental challenges [1,2]. In 2023, 72,699,784 domestic tourists and 24,478,689 foreign tourists arrived in Mexico, of whom 3,839,212 visited Baja California Sur according to data from DataTur in 2023 [3]. San José del Cabo and Cabo San Lucas, located in the south of the state, are the towns that concentrate the largest concentration of tourists in the state, increasing from 2.8 million in 2017 to 3.7 million in 2023 and generating an economic impact of approximately 1.2 billion dollars annually [4]. The rapid expansion of the tourism sector has not been orderly or sustainable, which has led to the creation of the so-called “slum belts”; regular or irregular areas with absent or limited basic services such as water, electricity, and security, among others.

Additionally, the state and Los Cabos in particular are the areas most affected by tropical cyclones in the country, with a frequency of approximately one per year. This situation complicates the situation for thousands of families in the region.

Hydrometeorological events significantly affect these populations. Data from the Center of Research on the Epidemiology of Disasters (CRED) indicate that globally, disasters related to floods and storms increased by 234% and 143%, respectively, between 1980–1999 and 2000–2019 [5]. Additionally, 72% of disasters are associated with both phenomena [5]. Other weather-related disasters, such as extreme temperatures and droughts, accounted for 6% and 5% of all disasters during the same period [5]. Understanding weather conditions is therefore essential for effective planning and productive activities. Deviations from typical patterns can negatively impact both the environment and society, and in severe cases result in material losses and human casualties.

Mass movements are geological phenomena triggered by factors such as earthquakes, faulting, fracturing, rock alterations, changes in density, and precipitation [6,7]. According to Sánchez-Núñez et al. [6], mass movements constitute less than 1% of all disasters, a figure significantly lower than that for floods and storms. These events are classified as geological phenomena, distinct from hydrometeorological phenomena. Although multiple factors influence mass movements, precipitation, particularly intense rainfall, is a critical driver. As a result, mass movements frequently occur in regions vulnerable to tropical cyclones.

Mexico exemplifies this pattern, as its principal tourist destinations, including Acapulco in Guerrero, Cancún in Quintana Roo, and Los Cabos in Baja California Sur, are situated along the coast. Despite their economic success, these locations face significant social and environmental challenges. A common issue among them is their vulnerability to hydrometeorological phenomena. For instance, Hurricane Wilma in 2005 caused $1.7 billion in losses in Quintana Roo, while Hurricane Otis in Acapulco resulted in $15 billion in economic losses and affected 560,000 residents [8,9,10].

In Baja California Sur (BCS), Mexico, hydrometeorological disasters have historically included tropical cyclones, hurricanes, flash floods, and droughts. Due to its geographical location in a semiarid region, surrounded by the Pacific Ocean and the Gulf of California, BCS is highly vulnerable to extreme weather events. Notable examples include Hurricane Odile (2014), one of the strongest hurricanes to hit BCS, with sustained winds of 200 km/h. The storm caused widespread destruction in Los Cabos, La Paz, and other areas, damaging over 15,000 homes and leading to extensive power outages and infrastructure losses, totaling approximately USD 1 billion [11]. Hurricane Liza (1976) triggered catastrophic flooding in La Paz when a retention wall failed under heavy rainfall, resulting in over 600 deaths, thousands of displaced residents, and severe urban flooding, making it one of the deadliest hurricanes in the region’s history. The Hurricanes Isis (1998) and Juliette (2001) left many towns in the Los Cabos region wholly cut off after roads and highways were damaged [12,13]. Other significant storms include Hurricanes Ignacio and Marty in 2003, both Category 2, which caused severe damage and occurred less than four weeks apart [12,14]. Hurricane Jimena (2009) made landfall near Mulegé as a Category 2 storm, causing severe flooding, damaging roads, homes, and water infrastructure, and leaving several communities isolated for weeks [15]. The impact of tropical cyclones has led to the generation of storm surges, with a relatively low impact on the entity, highlighting Hurricane Juliette (2001), which caused two deaths and severely impacted the tourist resort of Cabo San Lucas, leaving it isolated from the outside world for several days, and Hurricane Odile (2014) [11,16].

In addition to storm surges, the impact of tropical cyclones has generated hazards due to landslides. One of the few studies documenting the generation of landslides resulting from the impact of tropical cyclones in the state is Antinao and Farfán 2013, who quantified 419 landslides in the mountainous area south of the state because of the impact of Hurricane Juliette in 2013 [7].

Tropical cyclones and mass removal processes are distinct from each other, they are linked by the rainfall factor that contributes to the softening of geological strata (especially unconsolidated layers) and particularly those located in areas of moderate to high slopes [17,18]; however, on the hazard maps designed for decision-makers and society, these phenomena are represented separately, giving a lack of perception that both cannot coexist at a given time. This leads to an underestimation of the risk, vulnerability, and exposure calculations of urban and rural areas, as has occurred in municipalities of the state of Baja California Sur.

In this context, the objectives pursued in this research are (a) to generate a tool that allows determining the vulnerability to the combination of both phenomena considering climate change and (b) to have vulnerability scenarios in the study areas so that decision-makers can implement mitigation and adaptation actions.

Based on data developed and presented in the Baja California Sur State Risk Atlas, a novel methodology is proposed to calculate vulnerability resulting from the simultaneous occurrence of tropical cyclones and landslides in the context of climate change. The selected study areas are the towns of San José del Cabo and Cabo San Lucas, the main tourist and population centers of the Municipality of Los Cabos, which present significant problems related to the impact of tropical cyclones, urbanization in high-risk areas due to landslides, and irregular settlements, among others.

2. Materials and Methods

2.1. Study Area

The study area comprises the towns of Cabo San Lucas and San José del Cabo, situated in Baja California Sur, northwest of Mexico, within the municipality of Los Cabos. These cities are the primary urban centers in the municipality, largely due to significant tourism activity and rapid economic expansion. According to data from Gobierno Municipal de Los Cabos 2024, the municipal population increased from 238,387 inhabitants in 2010 to 351,111 in 2020, a 47% rise [19] (Figure 1). This population growth is closely linked to the expansion of the tourism sector. As reported in [19], tourist arrivals grew from 2,290,000 in 2017 to 3,028,300 in 2023. Both population and tourism increases have occurred in a disorganized and inadequately planned manner, resulting in substantial social, environmental, and socio-political challenges [20,21,22,23]. A prominent example is the emergence of irregular human settlements, established through illegal land occupation and characterized by poor living conditions, including insufficient water supply, inadequate drainage, and lack of garbage collection housing constructed from waste material. These settlements also experience elevated crime rates and drug use, with most located in high-risk areas.

2.2. Climate Change Projections

Since 1988, the IPCC has accumulated evidence that climate change is unequivocal. The impact of humans on nature has been such that the UN Secretary-General warned that the era of global warming was over, beginning the era of “global boiling.” If current emissions rates continue, largely due to the differential increase in consumption patterns between rich and poor and the persistence of polluting practices, the impacts of climate change will become more acute, resulting in droughts, frost, loss of glaciers and melting of the polar ice caps, ocean warming and acidification, rising sea levels and certainly more intense and recurrent hydrometeorological events.

According to the IPCC Sixth Assessment Report [24], humanity still has a window of opportunity to have a habitable planet in the future, reversing the serious threats that climate change represents to human and planetary well-being and health. These threats, however, continue to worsen. Hurricane Otis, which hit the coasts of Acapulco and five other municipalities in Guerrero on 25 October 2023, illustrates that this is indeed happening, so this unfortunate disaster is undoubtedly a “late lesson” that, beyond adding to others that preceded it, seems to reveal the arrival of the impacts of a new phase of the climate crisis. The favorable conditions for the formation of this type of phenomenon are largely due to the intensification of the El Niño-Southern Oscillation—ENSO (we are in conditions of strengthening of the El Niño phase, which translates into an increase in cyclonic activity in the Pacific and its decrease in the Atlantic). It is also due to the increase in ocean temperatures, with records since March 2023, which have expanded the areas or “pools” of warm water. Likewise, it has been indicated that the presence of fresh water on the surface of the ocean, a product of rainfall, could change the salinity and surface temperature, causing Otis to feed on warm water at greater depth, thus increasing the volume of water extracted and therefore its strength.

2.2.1. Air Temperature

The base values (average of the years 1970–2000, WorldClim 2) [25] or values at “current conditions” indicate that for the State of Baja California Sur, the minimum, maximum, and average values of the variable Minimum Temperature of the coldest month (Bio6) are 3.59 °C, 14.1 °C and 8.37 °C, respectively. For the variable Maximum Temperature of the warmest month (Bio5), the minimum, maximum, and average values are 22.2 °C, 39.79 °C, and 35.22 °C, respectively. On the other hand, the projected future values for the Bio6 variable indicate that it could reach a minimum value of up to 7.5 °C with the Australian Community Climate and Earth System Simulator (ACCESS–CM2) general circulation model (GCM) with an Ssp5 8.5 scenario by 2070, while the highest value projected for the Bio5 variable could be up to 44 °C with the ACCESS–CM2 GCM with the Ssp5 8.5 scenario by 2070 [26].

Regarding the temperature on the sea surface surrounding Baja California Sur, the base values (average of the years 2000–2020) obtained from the Bio-ORACLE ERDDAP database [27,28] show an average value of 22.59 °C. While for the Ssp2-4.5 and Ssp5-8.5 scenarios projected to the year 2100, the average values could be 24.23 °C and 26.06 °C, respectively.

2.2.2. Precipitation

The base values (average of the years 1970–2000, WorldClim 2) [25] or values at “current conditions” show that for the State of Baja California Sur, the minimum, maximum, and average values of the variable Precipitation of the Driest Month (Bio14) are 0 mm, 3 mm and 0.15 mm, respectively. While for the variable Precipitation of the Wettest Month (Bio13) the minimum, maximum, and average values are 11 mm, 224 mm, and 51.42 mm, respectively. However, the highest value projected for the future for the Bio13 variable is 394 mm with the ACCESS–CM2 GCM for the Ssp2 4.5 scenario by 2050 [26]. On the other hand, the future projections of the European Research Consortium EC-Earth GCM, the Max Planck Institute Earth System Model, and ACCESS–CM2 for the Bio14 variable in its minimum, maximum, and average values could be zero [26,29].

2.2.3. Sea Level Rise

The possible total sea level increase projected in the future with the Sea Level Projection Tool of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) (https://sealevel.nasa.gov/) for the City of La Paz indicates that the sea level could increase on average 0.23 m and 0.26 m in the Ssp2-4.5 and Ssp5-8.5 scenarios by 2050, respectively. By 2100, the average sea level rise could be 0.62 m and 0.82 m for the Ssp2-4.5 and Ssp5-8.5 scenarios, respectively.

These scenarios reflect more extreme and contrasting climate conditions for the near future, and the object of study, both in meteorology and climate science, is rapidly changing, which leads to the difficulty of predicting this type of phenomenon with current models [30].

2.3. Present and Future Vulnerability Modeling

To determine vulnerability to hydrometeorological and landslide events in the context of climate change, the reference framework proposed by the IPCC [31] was used, in which vulnerability is the result of the interaction between exposure, sensitivity, and adaptation capacity.

Vulnerability = Exposure + Sensitivity − Adaptation Capacity

(1)

In this context, exposure represents “The nature and degree to which a system is exposed to significant climatic variations”, while sensitivity is defined as “the degree to which a system is affected, either from adversely or beneficially from a climate-related stimulus”, and finally adaptation is defined as “The ability of a system to adjust to climate change, to moderate potential damage, take advantage of opportunities or minimize consequences” [31,32]. This approach has been recently used to estimate vulnerability in various contexts, including ecology [33], coastal areas [34], and aquifers and seawater intrusion [22].

For human settlements in urban areas, exposure refers to the extent to which urbanized regions are impacted by tropical cyclones and landslides of varying frequencies and intensities. Higher frequency and intensity of these events correspond to increased exposure. Cyclonic events may involve three particularly hazardous sub-events: cyclonic winds, intense rainfall, and sea level rise resulting from storm surges. Intense rainfall can lead to localized flooding or increase river and stream flow which may overflow into adjacent floodplains.

For mass remotion processes, multiple factors can induce instability leading to falls, landslides, or flows. There is broad agreement that slope, water from rain or runoff, lithology, and land use are among the primary influences on their occurrence [35,36,37]. In the study area, rainfall-induced landslides have been documented during tropical cyclone events [7], highlighting the connection between hydrometeorological and geological hazards.

In this context, exposure was calculated by integrating a flood hazard map (FHM), a storm surge hazard map (SRHM), and a slope susceptibility map (SSM) obtained from the Risk Atlas for the state of Baja California Sur. This atlas serves as a geospatial tool for assessing hydrometeorological, geological, and anthropogenic risks and hazards throughout the state. Each dataset was assigned quantitative values ranging from 1 to 5, corresponding to hazard levels from very low to very high. To define the weight for each parameter, a group of 12 experts on the subject were consulted and asked to indicate, on a scale of 1 to 10, the importance of each parameter in exposure. The average of the results obtained, scaled from 0 to 1, resulted in a value of 1 for FHM and 0.7 for SRHM and SSM, respectively. Using a map algebra algorithm implemented in QGIS 3.22.16, the three maps were summed, and the results were scaled to produce the Exposure Hazard Index (EHE), which also ranges from 1 to 5.

The sensitivity index (SEN) was calculated using seven indicators sourced from the National Housing Inventory published by INEGI. The database offers block-level resolution for each central city within the state. Based on input from local experts, the availability of state government data, and various bibliographic sources, the following indicators and their corresponding weights were established. The indicators include distance to hospitals (20 km), distance to the nearest airport or runway (20 km), freshwater coverage, sewage coverage, telecommunications access, and housing construction (see

Table 1. Description and value for each indicator of the sensitivity index.

Indicator	Definition	Value	Sources
Distance to hospital	Access to health services is vital in the face of the impact of a disturbing phenomenon. The greater the distance, the greater the sensitivity	Distance < 20 km = 0 Distance > 20 km = 1	[38,39]
Distance to closest airport or runway	Air bridges are vital for receiving supplies in the event of a disturbing phenomenon or to speed up preventive evacuation. The greater the distance, the less capacity for attention and, therefore, the greater the sensitivity.	Distance < 20 km = 0 Distance > 20 km = 1	[38,39]
Freshwater coverage	Due to the aridity and development of cities, the population does not have constant access to water. Access to water is a human right and a necessity that, when absent, increases sensitivity.	Total coverage = 0 Partial coverage = 0.5 No coverage = 1	[40,41,42,43]
Sewage coverage	Connection to the drainage system is a clear indicator of the development of a population. A population without drainage is more sensitive	Total coverage = 0 No coverage = 1	[43,44]
Telecommunication	Developed and less sensitive areas have access to mobile phones, landlines, the Internet, and other types of communication. The lack of connectivity increases the population’s sensitivity	3 or more telecom items = 0 Less than 3 telecom items = 1	[45]
Housing construction	Houses built with concrete (brick, blocks, steel) indicate a less sensitive population than artisanal houses constructed with wood or waste material (cardboard, sheet metal, among others).	Concrete (with blocks, bricks, steel) = 0 Mix or other material = 1	[43]

).

After defining the value of each indicator for every block, these values were summed to determine the sensitivity value. This sensitivity value ranges from 0 to 6, where 6 indicates high sensitivity and 0 represents the lowest sensitivity. For this investigation, we have decided to assign a constant value of zero to the adaptive capacity. The reason for this is the lack of detailed information at the block level. Applying a single value to the entire study area would be inappropriate because resilience and the distribution of adaptation measures vary significantly across different sectors and social strata. Considering the above, a sensitivity analysis for this parameter is included and presented in Section 3.3.

The vulnerability index for each block was calculated using QGIS 3.22.16 and a map algebra algorithm based on Equation (2).

Vulnerability = EHE + SEN − ADCA

(2)

In this context, the P95 values (indicating extreme events) for the “Maximum 5-day precipitation” (RX5day) parameter were obtained from the IPCC WGI Interactive Atlas for RCP 8.5 for the near term (2040), medium term (2060), and long term (2100). The increments of 10.1, 14.3, and 24.2%, respectively, were applied to the FHM indicator of the EHE index, and vulnerability was calculated using Equation (2).

After calculating vulnerability for the different scenarios, we performed geospatial analyses in QGIS to identify the number of blocks classified as having high to very high vulnerability. To estimate the impacted population, we calculated the average number of inhabitants per block using cartographic data and the 2020 population census information from INEGI, which indicated an average of 56 inhabitants per block. This number was then multiplied by the number of vulnerable blocks to determine the affected population under the specified scenarios, alongside its percentage relative to the total population obtained from the INEGI census.

However, this initial calculation assumed zero population growth. Therefore, we needed to project the population for the defined periods, using a growth rate of 4% every five years as provided by the INEGI census data. Subsequently, we recalculated the estimates for the simulated periods, incorporating the percentages of vulnerable populations.

3. Results

3.1. Current Vulnerability to Tropical Cyclones and Landslides

As previously mentioned, Los Cabos is susceptible to extreme hydrometeorological events, particularly tropical storms and their related landslides. Current assessments show that 121.27 km² of urban and rural areas in Los Cabos have high to very high exposure (see Figure 2). While most of this area consists of unimpacted creeks, streams, and undeveloped land, a significant portion includes urban areas such as Caribe-Caribe Bajo (1), Lagunitas (2), Gastelum (3), Las Palmas-Mesa Colorada (4), Downtown Cabo San Lucas (5), Cangrejos (6), and 4 de Marzo (7). In San José del Cabo, the exposed areas include Lomas de Guaymitas (A), Vado Santa Rosa (B), Downtown (C), Vado Puerto Nuevo (D), and Vado La Ballena (E) (see Figure 2).

It is important to note that Caribe-Caribe Bajo, Lagunitas, La Palma Mesa Colorada, Vado Santa Rosa, and Vado La Ballena are considered irregular settlements. These areas lack well-constructed housing, garbage collection services, adequate drainage, and often experience high crime rates. Overall, 26.4% of the blocks in both cities are classified as having high to very high exposure.

The Sensitivity Index indicates that approximately 165,200 people living in 2950 blocks are classified as low sensitivity, while 145,152 people in 2592 blocks are considered moderately sensitive. Additionally, 52,976 individuals living in 946 blocks fall into the highly sensitive category. Notably, 17% of the population in both localities, including areas such as Las Palmas-Mesa Colorada, Lagunitas, Caribe-Caribe Bajo, Vado Santa Rosa, and Vado La Ballena, is categorized as highly sensitive.

Regarding vulnerability, it has been determined that 5.51% of the blocks in both populations exhibit high or very high vulnerability, while the remaining 94.5% range from moderate to very low vulnerability. In Cabo San Lucas, the neighborhoods with the highest vulnerability include Caribe-Caribe Bajo (1), Lagunitas (2), Gastelum (3), and Las Palmas-Mesa Colorada (4). Areas of high vulnerability are observed throughout the urban region.

In San José del Cabo, the most vulnerable areas are located along the margins of Vado Santa Rosa (B), in specific blocks of San José Viejo (C), Vado Puerto Nuevo (D), Vado y Predio La Ballena (E), and their main branches. An estimated 74,786 inhabitants are highly vulnerable to tropical cyclones and landslides.

3.2. Future Scenarios of Vulnerability to Tropical Cyclones and Landslides

In future climate change scenarios, the exposed area is projected to increase to 185.02 km², 663.11 km², and 956.74 km² by 2040, 2060, and 2100, respectively. Figure 2 illustrates that the comparison of exposure between 2025 and 2100 shows that most of the increase occurs in unpopulated and mountainous areas. In terms of blocks, the exposed areas will evolve from 26.4% currently to 39.51% by 2100, representing an increase of 12.75%. The increases for the periods 2040–2060 and 2060–2100 are 6.69% and 9.72%, respectively. Among the three periods, the smallest increase within urban areas occurred between 2040 and 2060, while the largest increase was observed from 2025 to 2040. When considering both urban and rural areas, the greatest increase is expected during the period from 2060 to 2100.

Regarding vulnerability, it is projected that by 2040, the percentage of blocks classified as highly to very highly vulnerable will reach 5.9% of the total number of blocks, reflecting an increase of 0.39% compared to the current situation. By 2060, this percentage is expected to rise to 6.3%, showing an increase of 0.79%. Ultimately, by 2100, the number of vulnerable blocks will grow to 6.85%, which is 1.35% higher than the current scenario.

In Cabo San Lucas, the areas with the greatest vulnerability compared to 2025 are: Caribbean-Lower Caribbean (1), Lagunitas (2), Gastelum (3), Las Palmas-Mesa Colorada (4), Downtown (5), Cangrejos (6), March 4 (7), the Tourist Zone (9), and Cabo San Lucas Airport. In San José del Cabo, the areas of concern include: Vado Santa Rosa (A-B), the Downtown and tourist area (C), Vado Puerto Nuevo (D), Vado, Predio La Ballena (E), San José Viejo (F), Puerto Los Cabos (G), and El Zacatal (H) (Figure 3).

In terms of population, using an average of 57 people per block based on 2020 data from INEGI, approximately 133,266 people currently reside in areas of high to very high vulnerability. This number is expected to increase to 142,956 by 2040, to 143,070 by 2060, and to 165,642 by 2100. After applying a correction factor for population growth, the estimated number of vulnerable individuals rises to 250,386 by 2100 (

Table 2. Quantification of the current population in conditions of high vulnerability and estimation of the near and distant future.

Scenario	Exposure (km2)	Vulnerability (% of Blocks)	Vulnerable Population	% 1	Vulnerable Population (Growth Rate Correction) 2
Recent	121.27	33.5	133,266	37.9	133,266
2040	185.02	35.9	142,956	40.7	149,039
2060	663.11	38.1	151,533	46.6	178,847
2100	956.74	41.6	165,642	53.4	250,386

¹ Percentage considering null population growth. ² Estimation based on population growth factor.

).

3.3. Sensitive Analysis Considering Variations in Adaptation Capacity

In the absence of block-level data to represent adaptive capacity, a constant value of “0” was used. To assess the potential impact of this indicator on the models and results, a sensitivity analysis was conducted with increases of 1.5 and 3.0 points, corresponding to 10% and 20% increments.

The findings indicate that by 2100, the number of blocks experiencing high and very high vulnerability, without any adaptation measures, would reach approximately 41.6%. However, this figure would decline to 32% if a nominal and constant value of 1.5 adaptive capacity points is considered and to 17% for an increase of 3.0 points. As a result, the percentage of blocks categorized as having low to very low vulnerability would rise from 37.1% to 65% in the scenario reflecting maximum adaptive capacity (Figure 4).

While these numbers seem promising, it is essential to note that achieving the adaptive capacity assumed in this analysis would require significant adaptations across social, economic, and political dimensions. Unfortunately, such measures have not been implemented in recent decades, leading to an increase in areas of high vulnerability, particularly in relation to hydrometeorological events.

4. Discussion

4.1. Model Limitations and Validation

The model presented is based on official data from the INEGI Population Census. INEGI, the organization responsible for statistics in Mexico, conducts partial population censuses every five years and complete censuses every ten years. As a result, population growth projections and indicators for 2020 and beyond will need to be adjusted once the official census results are published.

The estimation of the affected population relies on an average number of inhabitants per block. This approach stems from the lack of updated data and significant uncertainty regarding areas where new human settlements may be established. Therefore, the corrected values for the vulnerable population should be viewed as approximations with a high degree of uncertainty since population dynamics in tourist areas—both in terms of quantity and geographic distribution—are complex. These dynamics are influenced by local, national, and international factors, as well as by economic, sociocultural, and political dimensions. Consequently, while total estimates of potentially vulnerable populations are provided, the model does not account for the geographic expansion of regular and irregular settlements, which could impact the reported values.

Additionally, the geospatial database used does not consider regulatory, legal, or strategy implementation aspects that allow quantifying adaptive capacity, so the latter was determined as 0 in the equation for calculating vulnerability. Future updates of the model may include adaptive capacity-linked indicators.

The model was validated by field verification of areas deemed highly vulnerable due to their location, construction style, and irregularities. It also considered the flooding and landslide events that occurred at both sites from 3 to 5 September 2025, caused by torrential rains totaling approximately 170 mm. For this analysis, information was gathered from news media, social networks, and official sources to confirm the locations of these areas. The highly vulnerable zones are primarily characterized by low socioeconomic status and irregular settlements (Figure 5 and Figure 6).

In the case of torrential rains, 14 sites were documented between both towns where flooding occurred, along with one site where a landslide occurred. Comparing these sites with the vulnerability map showed that the correlation was correct in 10 sites, underestimated in 3 sites, and overestimated in 2 sites. In the case of two underestimated cases, the reason was the lack of updated cartography, not the model itself. Considering the above, the model’s effectiveness was 76.9% (

Table 3. Comparison between flooded areas (3 September 2025) and the vulnerability map.

Case	Type	Area/Town	Vulnerability (Figure 3)	Validation
1	Flood	Vado Santa Rosa (SJC)	Very High (A)	Accurate
2	Flood	El Zacatal (SJC)	Very High (H)	Accurate
3	Flood	International Airport (SJC)	n/a	Underestimated
4	Flood	Downtown (SJC)	Very High (C)	Accurate
5	Flood	Tamaral Ave. (CSL)	n/a	Underestimated
6	Flood	Caribe Bajo (CSL)	Very High (1)	Accurate
7	Flood	Mesa Colorada-Chulavista (CSL)	Very High (4)	Accurate
8	Flood	Tezal (CSL)	Very High 2100 (9)	Overestimated
9	Flood	Downtown (CSL)	Very High (5)	Accurate
10	Flood	Downtown (CSL)	Very High (5)	Accurate
11	Flood	Acuario- 4 de Marzo (CSL)	Very High (7)	Accurate
12	Landslide	Libertad (CSL)	n/a	Underestimated
13	Flood	Del Sol—Lagunitas (CSL)	Very High (2)	Accurate
14	Flood	Matamoros-Downtown (CSL)	Very High 2100 (5)	Overestimated
15	Flood	Del Sol—Lagunitas (CSL)	Very High (2)	Accurate

).

4.2. The Construction of Vulnerability in the Municipality of Los Cabos

San José del Cabo and Cabo San Lucas began developing as tourist destinations in the 1970s when the National Tourism Fund (FONATUR) designated them as Integrated Planned Centers (IPCs) [21]. By 1990, their populations were approximately 16,059 and 16,571, respectively, and both towns saw their populations double by 1995 and triple by 2000 [21]. While FONATUR’s strategy promoted tourism, it also caused negative impacts, including a decline in residents’ quality of life and increased environmental pressure [19,21,46]. The local workforce primarily comes from other states facing poverty, leading many immigrants to create informal settlements due to high land prices and living costs. These areas often suffer significant damage from hydrometeorological events, and residents usually rebuild in the same risky locations.

In regular settlements, laws require risk assessments, but flooding risks are sometimes underestimated, resulting in yearly damage and, in some cases, building collapses, such as those seen in Chulavista and Puerto Nuevo in 2017. Despite the establishment of the Los Cabos Municipal Planning Institute (IMPLAN) to promote sustainable growth, there are still 13 irregular settlements with about 42,004 inhabitants; approximately 39,000 people are exposed to flooding risks [19]. Recent visits have identified growing irregular settlements in riverbeds and streams that are not included in official records, indicating that the problem is worsening.

4.3. Comparison with Other Touristic Related Cities in Mexico

The tourism corridor of Los Cabos exhibits unique vulnerability characteristics compared to other destinations in Mexico, particularly concerning water resource constraints, extreme heat, and the risk of flash floods due to its arid coastal environment. However, it also faces common challenges found in other regions, such as exposure of coastal infrastructure, uneven capacity for adaptation, and gaps in the distribution and implementation of risk assessments and practical measures for resilience.

Climate change projections exacerbate existing vulnerability patterns across all major tourist destinations in Mexico, with severe implications for coastal exposure, extreme precipitation events, and thermal comfort thresholds. The ability to respond to these increasing challenges varies significantly between destinations, influenced by different institutional frameworks, economic resources, and governance structures that ultimately affect vulnerability outcomes.

The tourism corridor from Puerto Vallarta (Jalisco) to Nuevo Vallarta and Punta Mita (Nayarit) exhibit specific vulnerability characteristics shaped by its mountainous coastal terrain and seasonal precipitation patterns. One defining vulnerability factor is landslide susceptibility, as 38% of the tourism infrastructure in Puerto Vallarta is built on slopes exceeding 15 degrees [47,48].

The complex watershed dynamics of the Ameca and Banderas Bay region lead to compounded flood hazards during extreme precipitation events, as observed during Hurricane Kenna in 2002 and Hurricane Patricia in 2015. Even though Hurricane Patricia made landfall as a weakened system, it still produced over 300 mm of rainfall within 24 h in the Puerto Vallarta metropolitan area. This resulted in extensive flash flooding, which had disproportionate impacts on informal settlements and workers in the housing tourism sector [49,50].

Compared to Los Cabos, flooding continues to be the main vulnerability factor, as urban and tourist areas are mostly located far from steep slopes. However, urban growth is shifting toward the hillsides, so the percentage of landslides affected will likely increase in the future.

Tourism seasonality leads to specific vulnerabilities that are particularly significant for emergency management. In destinations where the peak tourism season coincides with hurricane season—especially along the Pacific coast—visitors who have limited local knowledge and awareness of hazards can create unique challenges for emergency response efforts [51]. The Los Cabos corridor experiences peak hurricane activity and significant international visitation from August to October.

Infrastructure interdependence is another significant vulnerability factor, particularly in systems at the intersection of water and energy. Muría-Vila documented how power outages during Hurricane Odile in 2014 led to failures in the water supply throughout Los Cabos [11]. This created compounded impacts that extended recovery times from days to weeks in the affected areas [11]. Similar patterns have been observed in various Mexican tourism destinations, where critical system redundancy remains underdeveloped despite the recognition of these vulnerabilities.

Otis is the first Category 5 hurricane to make landfall in a densely populated area of the Mexican Pacific. This event ranks among the instances where the most people have experienced the eye of a hurricane of such intensity. The expansion of urban areas in Acapulco, particularly due to tourism and the beach real estate business, has resulted in greater exposure to such storms. This exposure encompasses both the physical and built environment, as well as the socioeconomic and environmental aspects of the region. According to Ramirez-Herrera et al., Otis potentially flooded approximately 11,000 hectares and caused landslides that affected 11.4 hectares, damaging 273,844 homes, over 5800 commercial buildings, and more than 100 health centers. The impacts extend to areas that support the tourism economy, including 80% of the hotel infrastructure, leading to job losses for many workers in that sector. Other residential areas were also impacted by Otis.

The Diamante zone, an urban development project, was one of the areas most severely impacted by the hurricane. This development drastically altered the landscape and disrupted the ecological balance. In a relatively short period, the lowlands and wetlands were filled, and rivers and streams were redirected to accommodate construction. This included areas that should have been preserved for their ecological functions.

Los Cabos has not experienced destruction on the same scale as Hurricane Otis; however, it has faced significant damage from winds during Hurricane Odile in 2014 and severe flooding from Tropical Storm Lidia in 2017. The socioeconomic impacts of these events were substantial, especially considering that none of them reached intensity categories higher than three. Unfortunately, the area’s vulnerability has not improved. Recently, there have been torrential rains (not related to tropical cyclones) that caused severe flooding, temporary road collapses, damage to homes, and landslides. A phenomenon similar to Liza, Odile, or Otis is likely to strike in the near future, and the impact may be equal to or even greater than what was experienced in Acapulco, Guerrero.

5. Conclusions

The methodology developed in this paper was applied in San José del Cabo and Cabo San Lucas, assessing the impacts of tourism-related phenomena on both regular and informal settlements. Informal urbanization around tourism areas creates vulnerability patterns that significantly affect the worker population essential to tourism operations. In Los Cabos, like other tourist destinations in Mexico, rapid tourism development outstrips formal housing, leading to extensive informal settlements in hazard-prone areas with inadequate infrastructure. This situation fosters systemic vulnerabilities that jeopardize resident well-being and tourism continuity during extreme events. Effective management during disasters, as well as post-disaster care, is crucial for ensuring constructive territorial reconstruction aimed at reducing future vulnerabilities. This process should avoid repeating past mistakes that have led to unequal urban spaces, especially in beach destinations where stark contrasts exist between tourist areas and other urban regions. Reconstruction should also be an opportunity for better territorial planning, implementing measures proposed by international reports. Key measures include enhancing early warning systems, disaster risk management, promoting sustainable construction practices, and advancing renewable energy use. Repairing damages linked to climate change is a moral imperative that must prioritize the most vulnerable populations and uphold human rights, considering gender, age, and cultural identity.

Future research should focus on estimating different scenarios of adaptation capacity at the block level and quantifying the potential effects of tropical cyclones, such as Otis, to propose strategies for protecting homes, infrastructure, businesses, and the tourism sector, which is vital for the region’s economy.