1. Introduction
Maps are human creations that reflect the innate need to represent and communicate ideas and reality using graphic language. A sketch comparable to a map found in a cave in northern Spain dated around 12,000 BC is evidence of this [1]. Maps have come a long way and have evolved alongside humanity, supported by advancements in knowledge across various disciplines and technology, and are now widely available on the web and mobile devices [2,3]. The relevance of maps is denoted by their multiple uses, as they serve to store, display, analyze, communicate, and understand information [1,4]. Additionally, according to Liu et al. [5] and Monmonier [6], they are one of the most reliable ways to present and convey information, being used in numerous fields and processes, ranging from navigation, orientation, and education to various calculations, analyses, decision-making, and numerous management activities. One of their functions is influencing social behavior, particularly by driving behavioral changes and improving task performance [7]. According to Tyner [8], map makers must consider four critical aspects when creating these products: (1) the message or information conveyed by the map, (2) their transmission channels, (3) the target audience, and 4) their purpose, as these factors influence certain decisions and selections, shaping their efficacy, a feature also examined by Cao [9].
Considering the previous aspects, hazard maps are designed to inform the public about the threats they face [10]. As for their transmission channels, maps today can be presented using one or multiple media, ranging from printed paper maps to virtual maps hosted on websites, geovisualization tools, and mobile apps. The effectiveness and relevance of some of these media have been analyzed in a study by Song et al. [11], with other authors examining the issues related to some of these innovations [3,12,13]. Once the populations or target audiences are identified, map makers shall consider their needs and abilities to interpret the maps to improve their effectiveness. This is a crucial aspect recommended by the U.S. Geological Survey [14] to ensure the understanding of maps and probabilistic information, which has been little considered, according to Marti et al. [15] in their study on the case of seismic hazard maps. Finally, hazard maps are employed in almost all Risk Management and Disaster Risk Reduction phases, from identifying and characterizing hazards to land-use planning, risk management, and public education.
Crisis and emergency mapping studies have explored the benefits and challenges of standardizing symbols on these maps [2,16], as it constitutes a communication tool for all parties involved [17]. Additionally, in the broader field of cartography, Bocher and Ertz [18] highlight the importance of ensuring interoperability in map design, given the wide range of technological tools available for developing and sharing maps today. They recommend creating specific cartographic standards as a key approach to promoting best practices and facilitating the dissemination of information across the field.
Tsunamis are a natural threat consisting of individual or multiple long, shallow water waves typically seen in large open waters. They result from a sudden displacement of the water column, which can be triggered by several geological or atmospheric mechanisms [19]. While relatively infrequent, they can have a very high impact on the coastlines they reach, and they are characterized by large waves that inundate the coasts both vertically (run-up) and horizontally, depending on factors such as coastal geomorphology, bathymetry, coastal physiography, the energy that generates them, and tidal states [20].
One of the primary expected outcomes of a tsunami hazard assessment for a given coastal region is a map of the areas likely to flood. These maps are essential for coastal risk management, providing critical information about potentially affected zones. Among the various types of tsunami maps, the literature review conducted shows the frequent use of terms such as “Tsunami Hazard maps”, “Tsunami Inundation (or flooding) maps”, “Tsunami Evacuation maps”, and, less commonly, “Tsunami Vulnerability (or Risk) maps”, with each name closely corresponding to its specific focus. A definition of tsunami inundation maps can be found in the guidelines provided by UNESCO and the Intergovernmental Oceanographic Commission (IOC) [21], which describes them as maps that identify the maximum extent of flooded areas from all credible scenarios based on historical evidence or modeling, with a similar definition provided by Koshimura [22]. Wabiński et al. [23] highlight that creating effective maps requires a rigorous and standardized cartographic process conducted efficiently and transparently to make it as repeatable and objective as possible, which in turn results in informed decision-making. An example of initiatives to standardize tsunami maps is the “Tsunami Modeling and Mapping: Guidelines and Best Practices” series by the U.S. National Tsunami Hazard Mitigation Program (NTHMP) [24]. These guidelines are frequently updated, and content, documentation, and recommendations for developing and validating tsunami inundation maps are proposed to make them more understandable. Following them is mandatory for map makers from the USA who receive funding from the program.
Studies referencing or focusing on tsunami maps (flood, hazard, evacuation) are commonly found in indexed literature databases, and it is a current research topic in the context of climate change and sustainable development goals (SDGs). However, these studies typically center around evaluating the phenomenon and its threat to specific coastal areas [25,26]. Research often involves applying a particular approach to threat assessment, whether deterministic or probabilistic [27,28], improving evacuation-related processes [29,30], testing various models, methods, and scenarios [31,32], or incorporating alternative data sources and techniques for analysis [33,34], among other tsunami-related subjects. Despite the critical role of these maps, publications often provide only brief details about them, as they are typically the final phase of the research process.
On the other hand, studies specifically addressing the creation of tsunami maps are less common in recent publications. Still, some examples include Kurowski et al. [35] and Lindell et al. [36], who evaluated flood and tsunami evacuation maps in brochures, and González and Herrera (2016) [37], who analyzed patterns in a sample of tsunami evacuation maps to establish a baseline and suggest improvements. Girres et al. [38] reviewed a set of tsunami evacuation maps, referencing the relevant ISO standard to propose better symbolization. They also validated their proposals with decision-makers and specialists, achieving a certain level of consensus. In the gray literature, the previously mentioned efforts by the IOC/UNESCO [21] and the NTHMP [24] are mirrored by similar initiatives from equivalent organizations in other countries.
Despite the growing body of research on tsunami maps, no studies explicitly addressing user interpretation and perception of such maps were found, unlike other natural hazards like volcanic or seismic events [10,15,39,40]. Understanding user perspectives has been established as a critical factor in designing and validating hazard maps, reinforcing or complementing prior initiatives to improve their effectiveness. This study aims to determine whether there are statistically significant differences in the perception and interpretation of tsunami maps among different types of users. Specifically, the main research questions (RQs) are as follows:
RQ1: Are there statistically significant differences between user types regarding their perception of the function of tsunami inundation and evacuation maps?
RQ2: Are there statistically significant differences between user types regarding their perception of the basic elements and symbology that should make up tsunami inundation and evacuation maps?
RQ3: Are there statistically significant differences between user types regarding their ability to interpret various elements and styles of tsunami inundation and evacuation maps?
2. Materials and Methods
2.1. Data Collection
Following a similar approach to other studies on how users interact with maps [41,42,43], the authors prepared and applied a questionnaire to evaluate how different types of users interpret and perceive tsunami maps. The survey was hosted on the free QuestionPro platform (
The sampling universe consisted of adult individuals (>18 years old) with at least a primary education who either live in or frequently visit coastal regions prone to tsunamis, and the participants were grouped into general users (GUs) and experts (EXs—risk experts or decision-makers) based on their self-classification. While a few items of the questionnaire were specific for each group, and besides the characterization questions, they shared a core of 15 questions that can be categorized as related to the perception of the tsunami maps function (3 questions), the perception of the required elements and symbols (8 questions), and the ability of the users to interpret information on uncertainty (4 questions). Table 1 presents this list of questions, and evaluating the participants’ answers to this set is the base of this article. The answer options consisted of closed-ended, single-, or multiple-choice formats (i.e., the user may select several answers from a list of choices), with many also offering open-ended options to capture complementary information (this “other, please explain” option was not included in the contingency tables analysis).
Three experts reviewed and refined the questionnaires before issuing them: one risk management specialist and two tsunami experts from Tohoku University. A pilot test with ten volunteers helped refine question sequencing and map visualization. Participants were informed about the survey’s objectives, confidentiality, consent options, and contact details, following the ethics committee guidelines of Universidad de la Costa.
The sampling followed a snowball method, similar to that used in the study by Thompson et al. [44], where participants and recipients were encouraged to share the questionnaire with their contacts. The questionnaires were disseminated through various channels such as LinkedIn, Facebook, ResearchGate, WhatsApp groups, email lists like REDESCLIM, and personal emails targeting representatives of the intended population, aiming to reach a broad audience. Additionally, the survey was shared with contacts and attendees at scientific conferences on risk management, where the authors participated. Two key platforms for disseminating the questionnaire were the Ibero-American Network for Beach Management and Certification (PROPLAYAS [45]) and the Network of Social Studies on the Prevention of Disasters in Latin America (LA RED [46]), both crucial in reaching stakeholders and professionals in coastal management and disaster prevention sectors. A total of 181 individuals (24 EXs, 157 GUs) completed the survey, and their profiles are summarized in Figure 1, where it is clear that most participants were from Ecuador.
The aspects addressed in these questions were deemed relevant based on prior research from the authors and the literature review. A detailed version of the questionnaire is provided in the supplementary files. Figure 2 shows maps A to F used in most of the questions in Table 1. The authors created Figure 2a–d with fictitious data (the background image corresponds to the Ecuadorian coast near Manta Bay), while Figure 2e,f were created and extracted from the NEAM Tsunami Hazard Model 2018 website [47] for the area covering the Balearic Islands. The maps chosen reflect current trends in tsunami maps based on observations made by the first author during her doctoral research.
2.2. Statistical Analysis
With an unknown quantity of individuals meeting the population criteria and considering a proportion of 30% (based on the number of people who answered that they had used a tsunami map in the pilot survey) and assuming an acceptable error in the estimate of 5%, the 181 individuals imply a confidence level of approximately 93% [48]. It is important to interpret the confidence level of 93% with caution. The survey was not conducted using a random sampling method, and the high representation of participants from Ecuador (77.9%) may have introduced regional biases into the results. Therefore, these figures may not fully account for representativeness and sampling methodology limitations. On the other hand, it is worth noting that the number of participants was in line with the results of a recent study by Bergmann Martins et al. [49] for research involving the use and users of maps that apply tools such as questionnaires, dissemination through social media, and statistical data processing.
This study’s methodology is based on statistically analyzing responses from professionals concerning their perceptions and interpretations of tsunami maps between two groups of users (GUs and EXs). Because of the non-parametric nature of the possible responses to the questionnaire items, this study employs contingency tables (chi-square test—χ2). The χ2 test examines the null hypothesis that no relationship exists between two categorical variables. It compares the observed frequencies in the data to the expected frequencies, assuming no association between the variables [50,51]. This study employed JASP Version 0.18.1 [52] to conduct the statistical analysis, and the adopted significance level was equal to α = 0.05. We accept the null hypothesis (the contingency table shows no significant differences across categories) when the p-value > α.
3. Results
3.1. Perception of the Function of Tsunami Inundation and Evacuation Maps
Table 2 presents the p-values for the χ2 results of the questionnaire items associated with RQ1. Regarding the perception of the function of a tsunami inundation map, the only statistically significant difference was for the option “serve as a basis for other management activities related to tsunami hazard risks (P9D)”, where EXs gave responses at twice the percentage of GUs. One of the experts mentioned that tsunami inundation maps must be used alongside other site-specific maps such as topographic, soil, subsurface geological, road, urban/rural settlement (to assess structure types and elevation), and tidal and coastal geology maps. Tsunami inundation maps alone are insufficient for estimating flood depth, as they are usually derived from computer models.
Two options related to the perception of why tsunami maps are considered reliable showed significant differences. The first was “It is based on technical-scientific data and analysis (P11B)”, which was nearly unanimously selected by experts. The second was “It includes the information on the persons responsible for the map and its date of creation (P11E)”. As expected, the participants’ perceptions regarding their specific user roles showed a notable difference between the groups only concerning the role of Risk Manager (P12G). Five participants identified themselves as scientific researchers or risk analysts on the subject.
3.2. Perception of the Basic Elements and Symbology to Include in Tsunami Inundation and Evacuation Maps
Table 3 shows the p-values for the χ2 results of the questionnaire items associated with RQ2. Based on the results for P10, significant differences were found between the groups regarding specific map elements they consider necessary for a quick and safe tsunami evacuation. Among the most noteworthy results, options “The probable flooded area (P10A)”, “Estimated times for evacuation according to routes (P10F)”, “The relief of the coastal zone (P10H)”, “ Information on map limitations and uncertainties (P10I)”, and “Information in local language and English for tourists (P10K)” all showed statistically significant differences, indicating varying perceptions of their importance between groups, with the EXs, in general, considering that more elements the better, with some examples including P10A (EX: 75.0%, GU: 46.5%) and P10F (EX: 79.2%, GU: 52.2%). On the other hand, the GUs seem to prefer simplicity, as suggested by elements like P10I (EX: 33.3%, GU: 11.5%) and P10H (EX: 41.7.3%, GU: 16.6%).
The findings suggest that while consensus exists on several evacuation map components, there are discrepancies in prioritizing additional details like evacuation times and map limitations, which could impact the effectiveness of tsunami evacuation strategies.
The responses to the question on considering groups with disabilities in the development and design of tsunami maps showed that most participants from both groups supported option P23A: “Flood or evacuation mapping should be done in formats that allow access to information”. This perception indicates a consensus on the need for inclusive formats that ensure accessibility. Notably, one participant highlighted the importance of participatory approaches and involving disabled communities in the map-making process, suggesting that people with disabilities should participate in the construction of the maps themselves, for example, through the creation of risk perception maps that take into account social representations, myths, misconceptions, and their own disabilities, an approach supported and previously addressed in the literature [53].
For questions P13, P15, and P22, more than two-thirds of participants preferred a map differentiating various inundation levels (Figure 2b) instead of one without this discretization (Figure 2a). Regarding the number of ranges to represent on tsunami inundation maps for clarity (P14), 75% of participants preferred having between three and four ranges. One risk expert suggested a more detailed approach, advocating for at least eight ranges, arguing that inundation should be measured in centimeters rather than in meters, an observation supported by Gibbons et al. [54]. However, having too many categories might cause users to feel visually overwhelmed by the map’s complexity [55]. This participant also emphasized that the map scale should be significantly bigger, allowing better visualization of satellite imagery and enabling users—whether tourists or locals—to quickly identify familiar landmarks such as schools or churches.
Question P18 asked participants to identify which type of map (see Figure 3) would be most helpful for guiding them to the fictitious “Mirador” landmark (the background image corresponds to the Ecuadorian coast near Santa Marianita) if they were in an area affected by flooding. Besides the probable inundation depth, roads, and blocks shown in the three map choices, Figure 3b featured a base aerial/satellite image as the background, while Figure 3c does not present a base image in order to accentuate the contour lines. Both groups preferred options in Figure 3b (EX 37.5%, GU 43.9%) and Figure 3c (EX 50.0%, GU 35.0%), with some participants indicating that more details could improve their comprehension of the presented information. It is worth noting that these maps are not actual evacuation maps and were created for the sake of this research. Real-world examples can be found on webpages from administrative entities of coastal cities [56,57].
As for P16, Table 4 presents the association of hazard levels with colors, and it evidences that most of the participants agree with the standard set of colors used by globally recognized institutions such as OSHA [55,58] to denote high, medium, and low hazards (or risks). However, there was a notable variation between the groups regarding areas perceived as having no hazard. Most EXs and GUs associated this level with the color green, reflecting the traditional use of green to symbolize safety. However, a considerable portion of both groups did not assign any specific color to these areas, suggesting that some might prefer a lack of color or transparency for such zones.
3.3. Ability to Interpret Various Elements and Styles of Tsunami Inundation and Evacuation Maps
Table 5 presents the results of the questionnaire items associated with RQ3, showing statistically significant differences between EXs and GUs for P17 and P21.
For P17, participants were asked to evaluate which of the two maps (Figure 2c,d) incorporating information about uncertainty appeared more reliable. The most adequate answer was Map C (Figure 2c), which uses the widely accepted concept of confidence intervals, typically between 90 and 95%, to express uncertainty. In contrast, Map D (Figure 2d) contains a vague statement, highlighting the general challenge of communicating uncertainty, as noted by Joslyn and Savelli [59] and Rafliana et al. [60] in their discussions on probabilistic tsunami assessments. Among respondents, 58.33% of the EX group identified Map C as more reliable. In comparison, 57.96% of the GU group chose Map D, probably because of the preference for information on inundation levels and demonstrating different interpretations of the maps’ reliability. This question also sought to explore the participants’ perception of the best ways to present uncertainty on maps, following the suggestion by de Sherbinin et al. [61], who emphasized the need to consult map users for effective communication. The scientific literature has extensively debated how to represent uncertainty, and some authors support that presenting uncertainty in textual form may be more effective in minimizing interpretation errors [59].
P19 asked participants which of two maps (Figure 2e,f) they would use to decide the safest place to vacation, considering the threat of tsunamis. The expected answer corresponded to Map F (Figure 2f), which reflects the 1000-year return period and the 84th percentile, a parametrization found in the tsunami-related literature [62]. It is considered a conservative choice since it includes higher flood height values. This map was the most selected option for both groups.
For P20, participants were questioned about which island(s) they could visit without worrying about a tsunami threat. The expected answer was D: “At least certain sites in each of them”, as Figure 2f (84th percentile) shows that some coastal areas on the islands of San Antonio, Mallorca, and Menorca are likely to experience flood heights of no more than 0.1 m with a 1000-year return period. Responses showed a varied understanding: 25% of the EX group and 18% of the GU group chose this option. Interestingly, one-quarter of the EX group also selected Menorca (option C), and a similar portion of the GU group selected Mallorca (option B), indicating differing interpretations of risk across the two groups.
P21 asked the participants to decide if they would buy a house in Menorca based on a tsunami map showing the probability of exceeding a 2 m inundation height for a 50-year return period using the 84th percentile. The expected answer was A: “Decides to buy anywhere from the center to the north of the island”, where the exceedance probability is only 0.5%. Responses revealed a preference for this safe option among both groups: 25% of the EX group and 31.85% of the PG group selected option A. However, a considerable portion of respondents showed interest in different information, with 54.17% of EXs and 24.84% of PGs requesting another map showing flood zones (option D). Additionally, 28.03% of PGs expressed uncertainty, indicating they were unfamiliar with the statistical parameters on the map (option E). In P19 and P20, 10.83% and 12.74% of the general public admitted being unfamiliar with the probabilistic information presented. However, in question 21, this percentage more than doubled, likely due to the change in how probabilistic information was represented on the map.
Additionally, P21 received a considerable amount of feedback from the participants. Based on the map in Figure 2f, they provided various reasons for purchasing a house in Menorca. Many referenced the color-coded risk indicators on the map, such as the light yellow color representing lower risk or areas with no orange, indicating safer zones. Some participants focused on the statistical representation of risk, such as the 84th percentile or lower exceedance probabilities in specific areas, while others highlighted the size of the safe areas and the availability of refuge opportunities. There were also comments about wanting more detailed information about whether the safe areas were habitable or tourist-friendly, as well as general impressions, such as the appeal of the island or the broad safe zone. Overall, participants relied on the visual cues from the map, particularly colors and risk levels, to make their decisions.
4. Discussion
While over half of respondents reported having seen a tsunami map in any medium, only one-fifth of them stated having interacted with these products, which is not far from the proportion employed based on the pilot survey. The declared purposes of use by those familiar with the maps include threat, vulnerability, and risk analysis, evacuation planning, prevention and response strategies, education and training, simulations, coastal engineering, research, tide knowledge, and personal curiosity. Notably, 94% of those who have used tsunami maps have a higher education level or above, primarily working in the public sector, and most fall within the 35 to 64 age range. The primary intended users and beneficiaries of tsunami maps are coastal residents, for whom the maps are essential for preparation and evacuation planning in the event of a tsunami [63]. Based on the research by Marti et al. [15] and Schneider et al. [64] on seismic maps, tsunami maps are likely to be consulted by various users, including experts, risk managers, decision-makers, and the general public.
Besides the sampling limitations acknowledged in the Section 2, the survey conducted for this study primarily involved participants with higher education levels, leaving a notable gap in representation from those without formal education. This is a relevant issue, as individuals without formal education are often more vulnerable to disasters related to natural phenomena, including tsunamis. Among other factors, their increased vulnerability stems from limited access to information, lower levels of awareness and preparedness, and economic constraints [21,65]. Without access to formal education, these individuals may struggle to comprehend disaster warnings and read graphic information (like maps) or evacuation plans, leaving them less equipped to take protective measures. Additionally, those with lower education levels are often economically disadvantaged, potentially residing in more hazardous areas and having fewer resources to recover from disaster impacts. However, it is also worth acknowledging perspectives that challenge the conventional view of vulnerability. Some research highlights that non-formal and informal education, local knowledge, and strong community networks also effectively strengthen disaster preparedness and resilience [65,66].
Even though visual impairments were not reported among the participants of this study, the relevance of this factor in map design cannot be overlooked, as estimates indicate that 8% of men and 0.4% of women globally experience some form of color vision deficiency [55], suggesting that future research should account for this limitation. Incorporating considerations for color vision deficiencies in the development of tsunami maps would improve accessibility and ensure that these maps are helpful to a broader range of users, particularly those who might otherwise struggle to interpret color-coded information.
Regarding the perception of differences between tsunami map types, the responses corresponding to P9, specifically P9C, show that a considerable portion of the participants do not clearly differentiate between them (33% of EXs and 47% of GUs). This observation suggests that users may not fully understand the distinct functions of these maps, which could hinder their effectiveness in communicating risk and guiding evacuation strategies. While hazard and inundation maps are closely related products, and evacuation maps are explicitly defined in the IOC’s Tsunami Glossary [67], a lack of consistent terminology exists, even among specialists [29,68]. This issue is common in risk-related fields, where terms like hazard and risk, despite being differentiated by experts, are sometimes used interchangeably by researchers and the general public [14]. The data from this study reflect this challenge, with only one-fifth of the total sample associating a flood map with its intended function of presenting flood information as a foundation for risk management activities.
A clear differentiation between types of tsunami maps is essential from both a practical and a theoretical perspective. The scientific community often emphasizes the importance of precise definitions and classifications, as this contributes to a structured and organized body of knowledge. As Fairbairn et al. [7] suggest, disciplines in science require clear theoretical frameworks and well-defined paradigms. This approach ensures that researchers and practitioners contribute meaningful knowledge to the research field and science. Although interdisciplinary approaches can bring flexibility, precise definitions remain vital for clarity and effective communication, mainly when dealing with real-world applications, as confusion could lead to inappropriate responses in actual tsunami scenarios, undermining the effectiveness of risk communication and emergency preparedness.
Based on the literature review, tsunami hazard maps show areas at risk of being affected by a tsunami based on historical data, geological studies, and simulations, generally using color coding to indicate different hazard levels. They are primarily used by planners, policymakers, and emergency management officials to develop risk mitigation strategies [10,67]. Tsunami inundation/flooding maps depict the extent of flooding that could occur in the event of a tsunami, often including depth contours to indicate the likely water depth, and they are used by emergency responders, urban planners, and the general public to understand potential flood zones and prepare accordingly [21]. The inundation maps are used as a base to produce the tsunami evacuation maps, which provide information for safe evacuation routes [21,38,67]. These maps are created to be easily interpreted by the general public, often featuring landmarks and clear instructions, and they are meant for residents, tourists, and anyone in the impacted region to enable quick and safe evacuation during a tsunami alert.
The general public’s expectations regarding the content of tsunami-related maps vary significantly, as reflected in this study. P10 presented 12 different content options to the participants, derived from a review of existing evacuation maps in both scientific and gray literature. Notably, 90% of respondents selected two or more content options, with 10% choosing only one option, either “The safe zone” or “Evacuation routes”. This finding indicates that users would like comprehensive information on such maps. Prior studies, such as Lindell [10], highlight the inclusion of additional details on tsunami hazard maps, such as environmental signals of a tsunami, wave arrival times, and potential impacts. These findings align with Cao et al. [9], who suggest that maps must effectively communicate warnings and provide details about threat information and associated risks. Based on European flood mapping experiences, Van Alphen et al. [69] identified minimum content requirements for flood maps, including flood extent, water depth, and flow velocity, which could be similarly valuable in tsunami mapping. Additionally, tsunami evacuation maps typically incorporate key features such as safe zones, evacuation routes, assembly points, local infrastructure, and threat zones [36,38]. These elements are essential for helping users make informed decisions during a tsunami event, as also outlined in UNESCO/IOC guidelines [21].
Probabilistic tsunami hazard assessments, whose results are presented as hazard curves or maps, provide crucial information for tsunami risk management by incorporating uncertainty [70]. However, as shown by the results of items corresponding to RQ3, effectively communicating probabilistic and uncertainty concepts to users has been challenging, as these ideas can be difficult to understand for both the general public and experts [44]. Part of this challenge originates from lacking a universally accepted definition of uncertainty [71,72]. Map design is crucial for conveying risk information, and individual characteristics—such as risk perception, numeracy, living conditions, age, and education—strongly influence users’ ability to interpret them [15]. Additionally, reading maps for the general public may not be easy but rather overwhelming, especially when there is too much information on them [9].
A key finding from previous research [9,14,39,44] is that threat map design cannot follow a one-size-fits-all approach. Instead, it should rely on a foundational framework adapted to the specific nature of the threat, the map’s purpose, and its target audience. Nevertheless, and despite the significant differences observed in some aspects of the map interpretations, many of the items tested were perceived similarly by both user groups in this study, indicating that there are common features in tsunami map design that can be interpreted universally, providing a basis for proposing some level of standardization in certain phases of map creation. This approach aligns with Bocher and Ertz [18], who advocated for sharing both the cartographic products and the underlying design principles, ensuring that critical aspects of map-making are accessible and consistently applied across different contexts. While standardization can be beneficial in ensuring consistency, efficiency, and accuracy in tsunami-related products [2,23,73], these standards often face challenges in adaptability to various contexts and encounter barriers in achieving consensus, acceptance, and widespread implementation [2,15].
5. Conclusions
Risk management for natural and human-induced threats is essential for achieving SDGs in any nation, as this relates to SDG 11: Sustainable Cities and Communities. Among these threats, tsunamis can be particularly lethal and catastrophic to coastal communities. The rarity of these disasters presents a challenge: how to sustain prevention and preparedness efforts among current generations who have not experienced their devastating effects. Tools like tsunami maps effectively convey and reinforce this message and must be accessible to the coastal populations and visitors. Based on the responses from 181 participants from 16 different countries, this study provides insights into how two user groups (GU and EX) perceive and interpret tsunami map information on inundation and evacuation. The results of the chi-square test—χ2 help draw some conclusions on the three main research questions (RQs):
RQ1: Are there statistically significant differences between user types regarding their perception of the function of tsunami inundation and evacuation maps? As only 4 out of 22 items in this category exhibited a p-value < α, the results indicate no significant differences between user types in their understanding of the overall function of these maps. Both experts and the general public view them as essential tools for communicating tsunami risk and guiding safe evacuation, though experts tended to prioritize technical details, while general users focused more on practical elements like evacuation routes and safe zones;
RQ2: Are there statistically significant differences between user types regarding their perception of the basic elements and symbology that should make up tsunami inundation and evacuation maps? Statistically significant differences were observed in the perception of five of the eleven usual map elements listed, particularly in symbology and additional information that should be included. Experts preferred more detailed and technical content, such as precise risk levels and evacuation times, while general users favored simplified symbology and clearer instructions. This insight suggests that while maps should be designed with a degree of standardization, they must also be adaptable to different audience needs to ensure effective communication;
RQ3. Are there statistically significant differences between user types regarding their ability to interpret various elements and styles of tsunami inundation and evacuation maps? Regarding map interpretation, no significant differences were found between experts and general users in two of the four items under this category, with both groups demonstrating an ability to understand basic map elements. However, communicating probabilistic data and uncertainty remains challenging, especially for non-experts. As recommended by previous research, textual explanations of uncertainty appear to minimize interpretation errors, but further research is needed to optimize the presentation of such information on tsunami maps.
In conclusion, this exploratory study provides an initial, valuable perspective on how different user groups (GU and EX) perceive and interpret tsunami hazard and evacuation maps, contributing to the literature that governments and mapmakers could consider when developing tsunami maps. It underscores the importance of creating tsunami maps that are both scientifically rigorous and user-friendly. Standardization is essential, but flexibility in design is crucial to addressing the diverse needs of experts, the general public, and vulnerable groups. While a significant amount of analysis and processes go into generating the information presented on these maps, the final step of developing the cartographic product plays a pivotal role in determining the overall effectiveness of the entire investigative effort. Adopting and observing basic rules or standards could ensure the communicative success of tsunami threat maps, maximizing their impact on risk management and public safety.
Besides addressing the shortcomings of the sampling process, future studies should explore whether differences exist in style and design preferences between printed and digital maps, a question this research could not address. Additionally, continuing the research on refining map communication strategies, particularly regarding uncertainty and risk perception, remains essential to enhancing the utility of these tools in tsunami preparedness and response.
Conceptualization, T.V.S.M., C.M.-R., C.B.M. and F.A.C.; methodology, C.M.-R., C.B.M., F.A.C. and T.V.S.M.; software, T.V.S.M.; validation, F.A.C. and G.I.L.; formal analysis, T.V.S.M. and F.A.C.; investigation, C.M.-R., C.B.M. and T.V.S.M.; data curation, F.A.C.; writing—original draft preparation, T.V.S.M. and F.A.C.; writing—review and editing, F.A.C.; visualization, T.V.S.M. and F.A.C.; supervision, G.I.L. and F.A.C. All authors have read and agreed to the published version of the manuscript.
The original contributions presented in the study are included in the article/
The authors express their gratitude to Erick Mas and Bruno Adriano from Tohoku University, Japan, and Ofelia Pérez Montero from Universidad de Oriente, Cuba, for their invaluable assistance in reviewing and refining the questionnaires prior to distribution. The first author also acknowledges Mario Palacios from Universidad Del Pacífico, Ecuador, for his significant help in sharing the questionnaires and encouraging participation.
The authors declare no conflicts of interest.
Footnotes
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![View Image - Figure 2. Maps employed in most questions: (a) single-zone inundation map; (b) inundation map with depth intervals; (c) single-zone inundation area map with probabilistic information; (d) inundation area map with depth intervals and probabilistic information; (e) probabilistic tsunami hazard map (MIH—Maximum Inundation Height) using a 1000-year return period and 16th percentile model [47]; (f) probabilistic tsunami hazard map (MIH—Maximum Inundation Height) using a 1000-year return period and 84th percentile model [47].](https://media.proquest.com/media/hms/THUM/4/XTlta?_a=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%2BgIBWYIDA1dlYooDHENJRDoyMDI1MDgwOTEwMDkxNDY3MjoxNzg5NTE%3D&_s=z8MTKYJpDsp0ZlXe8CO6nJ15Q0k%3D "View Image - Figure 2. Maps employed in most questions: (a) single-zone inundation map; (b) inundation map with depth intervals; (c) single-zone inundation area map with probabilistic information; (d) inundation area map with depth intervals and probabilistic information; (e) probabilistic tsunami hazard map (MIH—Maximum Inundation Height) using a 1000-year return period and 16th percentile model [47]; (f) probabilistic tsunami hazard map (MIH—Maximum Inundation Height) using a 1000-year return period and 84th percentile model [47].")
Enlarge this image.Figure 2. Maps employed in most questions: (a) single-zone inundation map; (b) inundation map with depth intervals; (c) single-zone inundation area map with probabilistic information; (d) inundation area map with depth intervals and probabilistic information; (e) probabilistic tsunami hazard map (MIH—Maximum Inundation Height) using a 1000-year return period and 16th percentile model [47]; (f) probabilistic tsunami hazard map (MIH—Maximum Inundation Height) using a 1000-year return period and 84th percentile model [47].
Enlarge this image.Figure 3. Maps that incorporate information related to inundation levels and evacuation paths: (a) no background; (b) base aerial/satellite image as background; (c) contour lines included.
Items from the questionnaire considered in this research article.
| Code | Question | Type * | Offered Choices | Assessed |
|---|---|---|---|---|
| P9 | What do you think is the function of a tsunami inundation map? | MC | 6 | Function |
| P10 | If the map’s purpose was to allow a quick and safe evacuation in case of tsunamis, which elements should be included according to you? | MC | 13 | Elements |
| P11 | What is the reason(s) you consider the information contained in a tsunami inundation/evacuation map to be reliable? | MC | 8 | Function |
| P12 | What type of map user are you or would you be? | MC | 10 | Function |
| P13 | As a user of flood maps (inhabitant or tourist of the area), which one do you think represents the flood information more clearly? | SC | 4 | Elements |
| P14 | If you were to decide the number of inundation ranges that should be represented on tsunami inundation maps (Map A shows one and Map B shows 4 ranges), and for the purpose of improving the clarity of the message of this type of map, how many ranges would you include? | SC | 8 | Elements |
| P15 | To answer whether a person is safe in Site 4 (regarding tsunami inundation threat) which map would you consult? | SC | 4 | Elements |
| P16 | Map B uses a discrete palette of colors to represent flooding; how do you (without considering the flood values shown in the legend) associate the hazard levels and colors on the map? | SC | 5 | Elements |
| P17 | Observe maps C and D, in which information about uncertainty has been added. Please answer: In which of the two maps (C, D) is the information more reliable? | SC | 5 | Interpretation |
| P18 | Which of the following maps do you think would be most helpful in guiding you in evacuating to the “Mirador” site if you were anywhere affected by the flooding on the map? | SC | 5 | Elements |
| P19 | If you were planning your vacation and looking for the safest place to go, considering the threat of tsunamis, which of the two maps (E or F) would you use to make your decision? | SC | 5 | Interpretation |
| P20 | Which island or islands (see map E or F) could you visit without worrying about the threat of a tsunami? | SC | 7 | Interpretation |
| P21 | The map shows the island of Menorca. The probability of exceedance (PoE) for the maximum tsunami inundation height of 2 m at various locations around the island is represented by colored circles for a period of interest of 50 years. The statistical model represented in this case is the 84th percentile. What would be your decision if you plan to buy a house in Menorca and have this map? | SC | 6 | Interpretation |
| P22 | Which map would you choose to disseminate the maps to the student population (colleges, schools) and focus on the tsunami hazard information to convey? | SC | 7 | Elements |
| P23 | To consider groups with disabilities (reduced mobility, visual, hearing, intellectual, other) in developing and designing tsunami maps, which of the following statements do you agree with? | MC | 5 | Elements |
Note: * Type: SC—participant is limited to a single choice; MC—multiple choice selection is allowed.
p-values for the chi-squared tests (χ2) of items associated with RQ1.
| Items with Multiple Choices Allowed | ||||||||||||
| Code | A | B | C | D | E | F | G | H | I | J | K | L |
| P9 | 0.593 | 0.823 | 0.206 | 0.041 | 0.106 | N.R. | ||||||
| P11 | 0.329 | 0.015 | 0.785 | 0.180 | 0.036 | 0.721 | 0.719 | 0.695 | ||||
| P12 | 0.980 | 0.391 | 0.769 | 0.203 | 0.375 | 0.422 | < 0.001 | 0.291 | 0.539 | N.R. | ||
Notes: N.R.—no responses corresponding to this option in either group; values in bold and italics denote significant differences between groups; blanks indicate that this option was not available for selection in the corresponding item.
p-values for the chi-squared tests (χ2) of items associated with RQ2.
| Items with multiple choices allowed | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Code | A | B | C | D | E | F | G | H | I | J | K | L |
| P10 | 0.009 | 0.659 | 0.277 | 0.055 | 0.145 | 0.013 | 0.077 | 0.004 | 0.004 | 0.332 | <0.001 | 0.151 |
| P23 | 0.327 | 0.054 | 0.860 | 0.775 | 0.695 | |||||||
| Items with a single choice allowed | ||||||||||||
| P13 | 0.638 | |||||||||||
| P14 | 0.079 | |||||||||||
| P15 | 0.809 | |||||||||||
| P18 | 0.620 | |||||||||||
| P22 | 0.296 | |||||||||||
Notes: N.R.—no responses corresponding to this option in either group; values in bold and italics denote significant differences between groups; blanks indicate that this option was not available for selection in the corresponding item.
Association of hazard levels with colors, based on the responses to item P16.
| Hazard Level | User | Rank 1st | Rank 1st | Rank 2nd | Rank 2nd |
|---|---|---|---|---|---|
| High | EX | 95.83% | Red | 4.17% | Green |
| GU | 93.63% | Red | 3.82% | Yellow | |
| Medium | EX | 87.50% | Orange | 12.50% | Yellow |
| GU | 84.08% | Orange | 14.01% | Yellow | |
| Low | EX | 75.00% | Yellow | 16.67% | Green |
| GU | 73.89% | Yellow | 15.29% | Green | |
| No hazard | EX | 54.17% | Green | 45.83% | No color |
| GU | 66.24% | Green | 33.21% | No color |
p-values for the chi-squared tests (χ2) of items associated with RQ3.
| Items with a Single Choice Allowed | |
|---|---|
| P17 | 0.003 |
| P19 | 0.561 |
| P20 | 0.805 |
| P21 | < 0.001 |
Note: Values in bold and italics denote significant differences between groups.
Supplementary Materials
The relevant supporting information (questionnaires, JASP models, responses from participants) is freely available in the Zenodo repository and can be downloaded at
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; López, Gloria I 2
; Mestanza-Ramón, Carlos 3
; Milanés, Celene B 4
; Canales, Fausto A 1
1 Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, Barranquilla 080002, Colombia
2 Colombian Geological Society, Carrera 32A # 25B-83, Torre 5, Local 105, Bogota 111321, Colombia;
3 Research Group YASUNI-SDC, Escuela Superior Politécnica de Chimborazo, Sede Orellana, El Coca 220001, Ecuador;
4 Faculty of Engineering, Universidad del Magdalena, Carrera 32 No. 22-08, Santa Marta 470004, Colombia;