1. Introduction

Climate change is exacerbating the frequency and intensity of climate-driven natural hazards [1]. These events can occur at the same time, or in a short period of time, compounding their impacts [2–4]. Individual hazards can trigger another or amplify each other’s severity. Recent studies show that multi-hazards are becoming more frequent across Europe [5] and globally [6–8]. The term multi-hazards is defined by the United Nations Office for Disaster Risk Reduction [9] as “the selection of multiple major hazards that the country faces, and the specific contexts where hazardous events may occur simultaneously, cascadingly or cumulatively over time, and taking into account the potential interrelated effects”. As a result, recent years have seen a shift from single to multi-hazard risk thinking, both in risk assessments and risk management. Many of those studies have conducted large scale assessments [10,11]. However, this shift from single to multi-hazard risk comes with several challenges. Due to its inherent complexity, the assessment of multi-risk requires data, an in-depth understanding of dynamics and feedback of risk both spatially and temporally, and awareness of the local context in which disasters take place [12–14].

Multi-hazard adaptation strategies are still challenging for decision makers [15,16]. Several challenges in capturing complex, interrelated risks at a local scale and translating these assessments into Disaster Risk Reduction (DRR) strategies. Managing multiple hazards simultaneously may involve competing adaptation priorities or conflicting effects between hazard types ([3,17,18]. DRR effectiveness also depends on how communities perceive and respond to risk. The design of multi-hazard DRR policies therefore requires understanding both the physical and social dimensions of local risk. Mixed-methods research, combining quantitative and qualitative data within the same study [19], addresses this by integrating hazard data with stakeholder insights to co-create a richer understanding of local risk dynamics [20–22]. Such approaches are particularly suited to local case studies where data gaps are costly to overcome and standardised methods fall short.

NBS are defined as “solutions that are inspired and supported by nature, which are cost-effective, simultaneously provide environmental, social, and economic benefits and help build resilience” (European Commission, 2015). Their feasibility in multi-hazard contexts depends also on community acceptance and perceived co-benefits. Which are dimensions that are difficult to quantify yet critical for uptake. The lack of standardised methodologies and indicators further limits the development of a common NBS evidence base [23], which ultimately limits NbS policy uptake and private investment Mixed-methods can help to bridge scientific hazard modelling with qualitative insights on social feasibility, stakeholder priorities, and local governance.

These challenges support the need for an integrated mixed-methods framework (Fig 1). In this essay, we explore the benefits and limitations of adopting a mixed-methods approach at a local scale, integrating fieldwork observations, questionnaire analysis, and stakeholder engagement to provide evidence for policymakers and deepen understanding of the local dynamics that shape multi-hazard risk perception and NBS acceptance. The essay links the following elements as it tackles three recurring challenges in current multi-hazard risk assessments: i) the interaction between hazards; risk perception and adaptation; and iii) translating assessment into feasible adaptation strategies (such as NBS). Mixed-methods can address these challenges by combining quantitative hazard and exposure analysis with qualitative insights from questionnaire and stakeholder interviews. The integration is particularly relevant for NBS, since their effectiveness depends not only on biophysical risk-reduction potential, but also on local land-use conditions, social acceptance, co-benefits quantification, and governance feasibility. For instance, the whole array of co-benefits usually requires different methods to quantify and monetize.

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Fig 1. Conceptual framework showing key multi-hazard challenges (1) and how they feed into the role of mixed-methods approaches (2), and the application of that to the design and assessment of nature-based solutions.

Figure 1 was created with the contribution of AI tools (ChatGPT). The tool was used to generate a preliminary version of the chart, following the components indicated by the researcher, that was then edited by the authors.

https://doi.org/10.1371/journal.pclm.0001070.g001

In the following sections, we present a case study conducted on Tenerife, reflect on the challenges of applying mixed-methods for multi-risk assessment and management, and conclude with a research agenda to improve both the local assessment and governance of multi-hazard risk.

2. Background

Recent years have seen a shift from single to multi-hazard risk thinking, both in risk assessments and risk management [2,24,25]. In a systematic literature review, Mahato et al. [26], also found that the majority of multi-risk assessment studies are dominated by quantitative methods, such as ML developments, while also noting that due to data gaps most studies still take a narrow approach (e.g., only focusing on two vulnerability dimensions) and tend to exclude a focus on LMICs. The selection of models that best capture the dynamics of multi-hazards and testing has also been a key topic in recent literature. What makes an assessment method ideal varies depending on the criteria selected to evaluate models, however, a purely quantitively analysis should be complemented with interaction with key stakeholders and other techniques that could help improve our understanding of a particular case study [13].

Risk-perception assessments are also key for enhancing the understanding of multi-hazards in local contexts. = Recent evidence has shown that risk-perception influences local DRR initiatives and individual adaptation [27,28], as well as the behaviour of investors, owners and real estate market since a study showed that, despite growing risk, coastal properties still increase in value in the U.S. [29]. Risk perception does not always align with the actual risk estimated with climate-risk modelling. This can be due to a wide variety of reasons, including the discourse in the media and the clarity of scientific communication. Despite its relevance for adaptation and policy support, a study conducted in Bangladesh, combining media and local narratives, in-depth interviews and field observations, showed that risk-perception is often ignored in local adaptation planning [28]. The results highlighted a relationship between risk perception, self-efficacy and protective action [30]. There is a wide range of factors that could influence risk perception. Firstly, stronger environmental attitudes are determinant in how stakeholders perceive climate risk and, ultimately, the intention to adapt (van Valkengoed et al, 2025). Xie et al [31] found that mitigation response efficacy and socio-cultural influences (ideology, norms, etc.) were the most important predictors of risk perception. However, for predicting intention to adapt, these were response inefficacy and climate change views [32]. Additionally, recent exposure to risk impacts risk perception considerably. A study found that, immediately after exposure to a flood event, the price of property in the inundated area would drop by an average of 24.9% compared to non-flooded property [33]. Nevertheless, this discount would no longer be statistically significant after 5 years for the same inundated properties. In the case of multi-hazard risk, a complicating factor discussed by several studies is how a focus on the risk of one hazard can decrease people’s attention (and perception of) the risk of another hazard [17]. These dynamics highlight the importance of incorporating risk perception into multi-hazard assessments. In this essay,we employ Protection Motivation Theory (MT) as the theoretical backbone [6,34]: PMT has two key components: threat and coping appraisals. Threat appraisal, explicitly links to risk perception, and answers the questions such as “how likely do I think is this will happen?” “How much do I think I will be hit if it happens?” On the othe hand, coping appraisal is key for NBS research, as it investigates to what extent people believe they can influence risk reduction: “is there anything they can do?”, “Is it too expensive?” “If the government implements adaptation measures, will they be effective?”

This shift to multi-hazard assessments comes with several challenges. Multi-hazard risk assessment was identified as a prominent gap in the understanding of risk, including cascading, compound and triggering interrelationships [5]. Due to its inherent complexity, the assessment of multi-risk requires data, an in-depth understanding of dynamics and feedback of risk. For example, visualization of multiple natural hazards is not straightforward, and it requires developing a way to depict them in a way that allows a clear interpretation of a high quantity of information [35]. The authors suggest a framework, including quantitative and qualitative techniques, that allows to determine which parameters to compare for decision-making.

More recent studies have focused on identifying several challenges that arise from multi-hazard assessment [5]. identified, through stakeholder engagement, five key challenges in practices, communication and data that limit multi-hazard risk management. Firstly, based on the result from 5 pilot studies (Canary Islands, Danube, North Sea, Veneto Region, Scandinavia and one expert workshop), the authors identify a general lack of understanding of stakeholders’ views, which are key for policymaking. Stakeholders identified the complexity of governance of multi-hazard risks and knowledge gaps in multi-hazard relations as the main challenges in designing risk management strategies. Added to the lack of data, there is a lack of translation process from science to policy and practice.

Additionally, mixed-methods can be used to account for dynamics of and feedback between other risk components, and to identify local challenges of managing multi-risk and the role risk perception. As in traditional risk assessments, the availability and quality of data is a key component for understanding natural hazards [2]. Additionally, to compensate for the lack of data the authors employed other mixed-methods such as academic literature review, desk studies and social media analysis [36]. The complex interrelationships between different hazards and how they impact different social groups require a more comprehensive perspective, which requires the combination of assessment methods.

In this esssay, we employ mixed-methods to overcome some of the challenges identified in previous studies and fill the existing research gap. The methodological gap lies in the limited guidance on how modelling, field observations, surveys, interviews, and stakeholder engagement can be integrated step by step to support the design and assessment of NbS. Fieldwork can improve the initial analysis through field observations, and a more in-depth knowledge of how the local communities prepare for natural hazards (e.g., individual adaptation) and their perception of multi-hazards can be obtained through questionnaires and interviews. We combine a preliminary desktop analysis with fieldwork (field observations, questionnaires and stakeholder interviews) to gather a better understanding of multi-hazard risks in the island of Tenerife and identify potential adaptation solutions. These methods, and the inherent challenges faced during the process, are explained in detail in the following section.

3. Mixed-methods: Opportunities and challenges

Mixed-methods can be defined as research projects that bring together results from both qualitative (e.g., interviews) and quantitative (risk-modelling, survey data analysis, etc.) studies [37]. Greene et al (1989) was the foundational study using the “mixed-methods” terminology, although it consisted of a review of studies that combined different methodologies, showing that this practice was already prevalent by then. In the last decade, the interest on mixed-methods for multiple disciplines has increased notably, mostly in social sciences (Tilmans et al., 2019). Mixed-methods main designs are convergent parallel design (where the data is collected simultaneously and analysed separately), explanatory sequential design and exploratory sequential design [38]. Whereas mixed methodologies sometimes occur in different phases of research design [39], we propose that both quantitative and qualitative exploratory simultaneous approaches, through an iterative process, can inform each other and maximize the understanding of local risk assessment. We believe the potential of mixed-methods design for MHR local assessments lie in their potential to promote feasible adaptation solutions.

This can be used to develop more comprehensive tools that can be useful for policymakers such as a hazard interaction matrix, risk heat maps or multicriteria decision analysis. A qualitative interview can help to improve the interpretation of the data received from a structured survey or even influence its design for later stages of research, as new problems could be identified by stakeholders in the interviews, and it may be the only way to capture social dynamics. Recent papers in the multi-hazard risk field have started employing more mixed-methods approaches in their research [37,40],. Mixed-methods can be a powerful approach when well-justified and designed, as it can otherwise lead to inefficiencies and superficial integration of quantitative and qualitative data [41].

One of the key aspects where mixed-methods can be useful for decision-making is when it comes to involving local stakeholders. As an example, Gill et al. [42] proposed the development of a framework to identify multi-hazard interactions in collaboration with local stakeholders. This framework provides a very valuable tool to create a fundamental understanding of different relevant local hazards and their interactions. Additionally, co-creation is important to also account for dynamics of and feedback between other risk components, and to identify local challenges of managing multi-risk and the role risk perception. For example, a quantitative analysis of risk perception and intention to adapt, can help to design a strategy to communicate the results of a catastrophe model and choose the most effective policy. Additionally, a semi-structured interview can help to delve into why this is the case, which ultimately could lead to the root of the problem as the interviewees have more room to express their concerns than in a questionnaire survey, even with open questions. Rowe and Wright [43] argue that mixed-methods, if applied properly, can become a useful, more holistic approach for decision-making to address complex issues under risk and uncertainty.

Mixed-methods also pose several challenges that should also be taken into account, as each method comes with its own limitations. Some combinations of mixed-methods have been mainly applied in local contexts to better assess multi-hazard risk [13,44]. This offers the possibility to couple global models and datasets with information from local stakeholders through questionnaires and interviews, but also to increase the accuracy of the analysis through fieldwork. Whereas these results will only be applicable for a defined spatial context, it can ultimately be more useful for policymaking and investment decisions in adaptation for those regions and minorities that are particularly vulnerable [45]. This is one of the reasons why we applied the mixed-methods in the region of Tenerife, which is exposed to a wide variety of hazards.

4. Benefits of using mixed-methods for multi-hazard risk assessment

Mixed-methods allowed us to combine different data sources to enhance the depth of the findings. This is particularly relevant in a multi-hazard context where no single data or model type can capture the full picture. For instance, in many instances the GIS maps must be updated from what’s available in the desktop review before the fieldwork since the available data does not always reflect the current state of the region. This iterative process has a considerable positive impact on the subsequent hazard maps and adaptation recommendations.

The use of questionnaires and stakeholder interviews improve our understanding of local context, multi-risk dynamics, and perception of risk and risk reduction measures. A good example of how these different sources of data complement each other is what occurred in our last fieldwork, during March 2025: the questionnaire results showed that respondents were not aware of any emergency plan in case of most climate hazards despite recent experience with devastating wildfires (2023) and coastal storms. However, residents were aware of volcanic eruption procedures, as drills have been conducted by a limited number of municipalities after the 2021 La Palma eruption. This insight could help shape future communication plans to improve emergency responses.

Additionally, improving your quantitative methods through co-creation with local stakeholders provides a valuable opportunity for integrating equity considerations into research and the policy recommendations [46]. In a recent study, conversation with local stakeholders helped to improve the design of a Choice Experiment [47]. The aim of the study was to understand the preferences of Dutch stakeholders. Members of the waterboard discussed land use constraints as a main point of conflict, since the whole area was used for agriculture. The hectares of agricultural land that would be converted to NBS was added as an attribute to test for landscape attachment. Indeed, we found that respondents’ utility decreases with more hectares of land converted from agriculture to NBS, which is a key insight that we would have neglected otherwise. Through participatory methods such as focus groups or interviews with local stakeholders, the challenges of local communities can be taken into account, not only for policy design, but also to improve the quantitative methods simultaneously. This is particularly relevant for multi-hazards as the interaction between hazards can lead to new challenges for the local community that could have not been identified beforehand. As a result, multi-hazard adaptation solutions that consider the communities while planning are also more likely to distribute the benefits in a fair manner and have greater public acceptance.

5. Challenges associated with mixed-methods in Tenerife

Conducting fieldwork as part of a mixed-methods approach for multi-hazard risk assessment requires good planning. Based on our 10-day fieldwork trip to Tenerife, we highlighted several challenges for researchers to take into account when planning to employ mixed-methods. Combining GIS-based exposure mapping, field observations, questionnaires and interviews required a multidisciplinary team, clear task division, training and thorough preparation before arriving on the island. For instance, checking out the key locations (such as bottlenecks) was not always possible since they may not be reachable or be inside private property. Researchers should keep in mind that accesses to key areas may be closed and create alternative plans or entry points in order to still make the most of the time in the field.

In practice, time and resources constraints limited the number of questionnaires that could be collected and interviews that could be conducted. This also limited the representativeness of the survey and increased the risk of sampling bias, especially because respondents who were more interested in environmental or climate-related issues may have been more willing to participate. Other sampling strategies such as stratified sampling or quotas were not possible while keeping sample size sufficiently high. Another related challenge was that, due to the lack of pre-testing, if the students wanted to update the survey, they’d lose a full day of data. In order to minimize this, we recommend doing tasks such as explanations about how to use any of the tools or designing surveys and interviews before the fieldwork starts. Although most of the data analysis can be done after the fieldwork, it is important to conduct some preliminary analysis since it can spot some issues with data collection that can still be solved while on the field, but that would be impossible to solve once the fieldwork is over.

Whereas stakeholder interviews provided valuable information about topics such as land use or emergency plans, the lack of response or interest of some stakeholders also highlight how important it is to have a contingency plan and detailed planning. We encountered the language barrier to be additionally challenging as it would require extra coordination between Spanish-speaking students since not all stakeholders were comfortable in conducting an interview in English. Technical terms such as “multi-hazards” or “nature-based solutions” also required clarification to ensure shared understanding.

NBS assessment for multi-hazard risks using mixed-methods also poses several challenges for the researchers. his can allow to overcome the individual limitations of specific methodologies and do a better job at capturing the wide array of risk-reduction benefits and (non-market) co-benefits. Many NBS benefits are qualitative or long-term, requiring input from different disciplines and diverse data sources to assess. This not only requires several experts from different disciplines, but integrating diverse data types (ecological measurements, soil stability, impact on tourism, etc.) into a coherent framework to assess co-benefits of NBS can be difficult due to their different measurements, and levels of subjectivity, potentially leading to inconsistencies or misinterpretations in the analysis of multi-hazard risk. Moreover, NBS benefits, and co-benefits are highly context-dependent, varying significantly by geography, hazard types, etc. Mixed-methods for local case studies can be extremely useful if carefully tailored to each unique settings, but it may be challenging to scale up or make generalizable conclusions from them. In Tenerife, we found that respondents were not always aware of the co-benefits of NBS and potentially underestimated their positive impact (coping appraisal). The multifunctionality of NBS can also increase confusion, as the natural processes involved in the co-benefits are usually technical. t can also exacerbate land-use conflicts, as NBS may require converting productive areas, generating local resistance unless benefits are clearly demonstrated and equitable. In case the land use data is not fully available online, the researcher should update it with observations in the field, surveys or interviews, since the current economic use of the land is a necessary variable to estimate the opportunity costs of NBS. In Tenerife, conversations with locals and field observations revealed large areas of abandoned land, creating opportunities for NBS policies.

5.1. ICase study: Assessing multi-hazards in tenerife through mixed-methods

In this section, we will illustrate the advantages, challenges and lessons learnt of mixed-methods approach during a fieldwork trip in the island of Tenerife.

Context. Tenerife presents a complex multi-hazard environment: volcanic eruptions, coastal exposure, wildfires, landslides, etc. Recent events, such as the 2023 wildfires and the 2021 eruption in the neighbour island of La Palma, have highlighted the lack of preparedness against natural hazards, which can cause severe economic and social losses.

Methods. We applied an iterative mixed-methods approach that combined desktop work, field observations, household questionnaires and semi-structured interviews with stakeholders from several sectors. The key idea is that the information derived from one method helped to improve the others: field observations allowed to update maps, stakeholder interviews allowed to provide realistic adaptation suggestions, etc. This improves both data accuracy and policy relevance. The results are not used for generalization in other contexts. Here, it is used as an illustrative case to show how different methods can inform one another in a local multi-hazard risk assessment. Integration took place in several stages. The used mixed-method design was a sequential design where both quantitative methods influenced the design of qualitative methods (e.g., GIS-based observations or survey results influencing interview questions) and vice versa (with exploratory interviews defining which key questions to address in the survey quantitatively and which adaptation solutions to model). Hence, the methods were combined in a way that insights from one method to inform the design or refinement of another but also, they were presented at the end separately to inform policymaking, for instance comparing real climate risk estimations from physical modelling with risk perception estimates from surveys and interviews.

Due to the constraints about the time available in Tenerife, and while being aware of the limitations, a convenience sampling strategy was chosen. In this way, the sample size could be maximized in order to conduct proper statistical analysis. The questionnaire data, coded in KoboToolbox, was collected in person and online through a web link. In total, 174 respondents filled the survey. There were two versions of the questionnaire, one in Spanish and one in English, mostly for tourists. The questionnaire had 25 questions, including sociodemographic, and the regression analysis was conducted in Python in order to test PMT hypotheses. The 5 interviews were conducted in person whenever it was possible, but students also had several online interviews. The interviews were selected in order to address three key relevant economic sectors in the island of Tenerife, which that are also highly exposed to climate risk: agriculture, tourism and critical infrastructure. Prior to the fieldwork, students conducted a comprehensive screening of potential stakeholders for each of the sectors. The analysis followed a thematic content approach. Students identified main themes: present and future risk perception, current adaptation levels and plans, trust in authorities, etc.

Desktop analysis and GIS-based exposure mapping were used to provide an initial understanding of each region, and to identify which locations to check during fieldwork. Field observations were then used to verify and update this initial assessment, for example by identifying missing infrastructure, land-use conditions, and local bottlenecks. Then, the questionnaires, designed based on PMT, and interviews allowed to understand risk perception, current emergency plans and support for adaptation measures. The interviews also allowed to identify practical opportunities for NBS. These NBS were then implemented in the maps to show how they reduce the original risk in the selected region, as well as which co-benefits they provide.

Insights and lessons learnt: Several regions of the island had buildings that were missing from Google Maps and would have been neglected in modelling otherwise. Questionnaires confirmed a post-2023 shift toward stronger concern for wildfires but also showed low awareness of existing emergency plans. For instance, stakeholder interviews allowed the researchers to find out that most of the terraces near Taganana were abandoned, offering low-conflict opportunities for reforestation since productive farmland requires compensation to farmers (Fig 2).

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Fig 2. Example of mixed-methods assessment in Tenerife (Shelton, F., Koeleman, R., Albertsboer, J., de Wagt, F., 2025).

Permission to use this poster and the included photos was obtained and the copyright permission form was signed. The maps in this figure were made using ArcGIS. Map image is the intellectual property of Esri and is used herein under license. Copyright © 2025 Esri and its licensors. All rights reserved.

https://doi.org/10.1371/journal.pclm.0001070.g002

To illustrate the outcomes of the fieldwork project in Tenerife, and how mixed-methods helped shape the NBS recommendations, we show the results of one of the groups that focused on the area of Tegueste, in the north of the island (Fig 1). The research began with desktop research and exposure mapping before heading to the island of Tenerife. This step is crucial, as it also allows the researchers to establish a plan for the fieldwork and understand what they need to check in the field (e.g., bottlenecks in barrancos, missing infrastructure, etc.). This town lies in a valley between forested mountains, making the region highly exposed to wildfires and flooding from the barrancos. Field observations confirmed that several residential areas and infrastructures were located within these high-risk zones, including some additional buildings that were not registered in the desktop research. Another key observation was the amount of vegetation and debris accumulated in the barrancos, which may exacerbate potential water flow blockages.

These observations helped to inform the questionnaires and semi-structured interviews scripts. The aim was to understand the risk-perception and level of preparedness of the neighbours, given recent small floods from the barrancos and the recent experience of the 2023 wildfire, which did not specifically affect Tegueste, but a neighbouring region. The expectation was that this event would shape their worries about climate risk. This was confirmed by the questionnaire results, since the local population ranked wildfires as the top perceived hazard to Tegueste. The econometric analysis also revealed that the neighbours who had previous experience with climate hazards are likely to have taken adaptive measures, which is aligns with the literature. Nevertheless, the overall worry level for Tegueste was low, as exemplified by the quote in the poster, taken from one of the stakeholder interviews with the chief of the voluntary firefighters’ department. This contrast between perceived and modelled risk highlights how mixed-methods can overcome traditional modelling shortcomings, revealing communication and awareness gaps that pure modelling would overlook.

Upon completion of the fieldwork, adaptation recommendations were (re-)formulated based on the combined insights. The suggested adaptation measures included clearing vegetation at the barranco bottlenecks, installing five small retention basins to slow runoff, and introducing grazing herbivores to manage vegetation regrowth. This example exemplifies the advantages of mixed-methods, and how the iterative integration of desktop analysis, field observations, surveys, and stakeholder interviews produces a better understanding of local MHR and yields more actionable recommendations. In the future, a more structured approach to mixed-methods could improve the efficiency and maximize the synergies between methods, as we discuss in the next section.

6. Research agenda

In this perspective paper, we have discussed the advantages and limitations of mixed-methods for multi-risk assessment. Local multi-hazard risk assessments are also crucial to provide specific recommendations for a specific region to account for region-specific challenges or barriers to adaptation that may not be captured in large scale models or other quantitative analyses. Despite the challenges, a mixed-methods approach can offer a powerful way to bridge the gap between scientific modelling and community realities. The use of mixed-methods enables a more comprehensive understanding, accounting for local contexts, while decreasing the dependency on (often low quality) quantitative data. In Fig 3, we illustrate how the different components in a mixed-method approach synergize with each other. We first present the advantages, then the limitations and then their interaction with the other steps. As we can observe, this is an iterative process, since new data collected at a certain stage could improve our original analysis. The policy recommendations are the result of the integration of qualitative (interviews) and quantitative (surveys, fieldwork) outcomes. For example, the selection of adaptation measures is not only supported by the quantitive analysis of the hazards but also by informed by insights obtained through formal and informal interviews with local authorities and businesses.

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Fig 3. Suggested mixed-methods iterative process.

Microsoft PowerPoint icons used in this figure are trademarks or brand assts of Microsoft. They are used for illustrative purposes.

https://doi.org/10.1371/journal.pclm.0001070.g003

The Tenerife case study provided the basis for this research agenda, Despite the aforementioned challenges, it showed that mixed-methods are most useful when they are planned as an iterative process in which desktop analysis, GIS mapping, field verification, questionnaires and stakeholder interviews directly inform one another. In this way MHR local assessments can provide valuable policy recommendations and support viable adaptation with scientific evidence and a comprehensive understanding of the context.

6.3. Iterative process

Lack of empirical evidence and exclusion of key co-benefits have usually been cited as reasons that limit investment in NBS as key measures to reduce climate risk. Our iterative and participatory design of methods aims to improve the data quality and help design realistic local NBS that can additionally provide several co-benefits to improve societal welfare.

Our framework can also support the [59], as shown in Table 1) since we offer a practical roadmap for designing and evaluating NBS in multi-risk contexts. Criterion 1focuses established that NBS should address societal challenges. Without proper engagement with the community, it is unlikely that the researcher will be able identify all the key challenges the NBS should prioritize. This also applies for Criterion 2, which refers to NBS being developed based on the specific characteristics of the local scale, both from a land use and geographical sense but also from an economic perspective and considering the local values and priorities. Criterion 3 focuses on biodiversity net gain and well-functioning ecosystems. We do not address this in the specific examples from Tenerife, but including a biodiversity assessment before and during the fieldwork could greatly enhance the value of the analysis for decision-makers.

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Table 1. Alignment of mixed-methods framework to IUCN NBS criteria.

https://doi.org/10.1371/journal.pclm.0001070.t001

Criteria 4 and 5 emphasize the importance of the economic viability and inclusive governance, which are supported by our integration of preference-based survey data and interviews with several members of the community, ensuring that the interventions are not only cost-effective, but also locally affected. Nowadays, the lack of inclusion of co-benefits valuation is one of the key challenges for mainstreaming investments in NBS. Criterion 6 is one of the most challenging obstacles for NBS, since they could require changing the land use of productive agricultural land or urban areas. The criterion establishes that the trade-offs should at least be acknowledged, beyond only land use change. This includes identifying the beneficiaries and who would be negatively impacted by the implementation of the NBS.

Criteria 7 and 8 refer to management, monitoring and mainstreaming NBS into policy and DRR planning. These two aspects can be incorporated into our framework through (i) defining a monitoring plan for each of the methods and key indicators, (ii) scheduling periodic reviewers to update maps and assessments of public preferences through surveys and interviews. Specifically, this is relevant after extreme events that may shift priorities or increase the urgency of adaptive policies. The key to mainstreaming NBS into policy is to make the output of the mixed-methods useful for policymaking. They can be incorporated into traditional decision-making tools such as societal CBA or Multi-Criteria Decision Analysis. Overall, our proposed approach increases the accuracy, reliability and contextuality of the evidence-based recommendations to reduce climate risk.

7. Conclusions

This essay aims to show that mixed-methods approaches offer a powerful framework to enhance the understanding of local MHR. They are also pivotal to planning and informing policymaking regarding adaptation solutions that are in line with the needs of the community. By integrating quantitative modelling, qualitative insights from stakeholder interviews and questionnaires, the researcher can aim to bridge the gap between data-driven analysis and viable recommendations for policymakers. The iterative process can increase the accuracy and overcome individual limitations of each of the individual methods.

Mixed-methods are crucial in the case of NBS assessments. A combination of quantitative and qualitative methods allows to capture the full array of benefits of NBS, which is currently a gap in the literature. For instance, mixed-methods are a practical way of incorporating non-market co-benefits such as recreation, heat relief and aesthetic quality improvement. These benefits increase welfare but do not have a market value, leading to underinvestment in NBS. By identifying who benefits and by how much is key to develop financing schemes for NBS policies, while always keeping justice and equity considerations in mind.

At the same time, mixed-methods also come with several challenges and limitations. Fieldwork is resource-intensive and time-bounded. It also requires researchers from different fields of expertise to be conducted efficiently. Language and cultural barriers may increase the difficulty of conducting interviews and the cost of a survey with a sufficient and representative sample size can constrain research budgets. A correct assessment of the needs, cost and potential challenges prior to the fieldwork is required to ensure researchers are prepared for the difficulties that may arise in the field.

The Tenerife case study illustrated this contribution in practice. The combination of desktop work, field verification, GIS analysis, questionnaires and interviews allowed for a comprehensive assessment and feasible climate risk adaptation recommendations. Each of these methods alone would have not allowed us to have the full picture. Each step revealed a new dimension of the problem: field observations corrected spatial data, surveys captured risk perception and awareness of emergency planning, and interviews helped identify feasible NbS opportunities and local constraints. Ultimately, through the lessons learnt from a fieldwork experience, we aim to contribute to the developing of standardized mixed-methods protocols and to foster interdisciplinary cooperation that can enhance the evidence base for equitable and effective climate risk reduction strategies.

Supporting information

Acknowledgments

Fig 1 was created with the contribution of AI tools (ChatGPT). The tool was used to generate a preliminary version of the chart, following the components indicated by the researcher, that was then edited by the authors.

We obtained permission to use the photo’s shown in Fig 2. The maps in this figure were made using ArcGIS. Map image is the intellectual property of Esri and is used herein under license. Copyright © 2025 Esri and its licensors. All rights reserved. https://doc.arcgis.com/en/arcgis-online/reference/static-maps.htm

Microsoft PowerPoint icons used in Fig 3 are trademarks or brand assts of Microsoft. They are used for illustrative purposes. For more information: https://cdn-dynmedia-1.microsoft.com/is/content/microsoftcorp/microsoft/mscle/documents/presentations/Trademark_List_FY26Q1.pdf