Here we present an interdisciplinary approach to developing comprehensive, systematic, and evidenced visual syntheses of potential natural-hazard interactions at regional scales (or
The Sendai Framework for Disaster Risk Reduction (UNDRR, 2015) is a global plan to reduce disaster losses from natural hazards, adopted by UN member states in 2015. The Sendai Framework emphasises the need for multi-hazard approaches, defined 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” (UNDRR, 2017). A key, but complex, step in understanding risk (Sendai Framework, Priority for Action 1), and the focus of our paper, is understanding the multi-hazard landscape of a region (i.e. the relevant single natural hazards and the processes by which they may interrelate to generate combinations or cascades of hazards). In this Introduction, we give a brief background of natural-hazard interrelationships, existing regional studies of potential hazard interactions, and the general organisation of our paper.
We divide natural-hazard interrelationships into the following two
categories (see Gill and Malamud, 2014; Duncan et al., 2016; Ciurean et al., 2018; Tilloy et al.,
2019, for a general review of hazard interrelationship
frameworks):
These interrelationships can combine to form complex networks (with both
spatial and temporal dimensions). For example, tropical storms can trigger
floods and/or landslides, volcanic eruptions can trigger wildfires that
subsequently increase the probability of debris flows, and earthquakes can
trigger regional subsidence which increases the likelihood of flooding. Many
more examples, and extensive case studies, of such interactions feature in
the literature (e.g. Tarvainen et al., 2006; Kappes et al., 2010; Gill and Malamud, 2014; Duncan et al., 2016; Tilloy et al., 2019).
Stakeholders involved in implementing the Sendai Framework (e.g. civil-protection agencies, hazard-monitoring scientists, urban planners, and
development practitioners) will therefore all benefit from resources (e.g.
tools and review reports) that help with increasing understanding of the
multi-hazard landscape of a region by systematically identifying and
characterising potential hazards and hazard interactions. Building on global
approaches for identifying and characterising hazard triggering and
increased probability interactions laid out in Gill and Malamud (2014, 2016,
2017) and Tilloy et al. (2019), here we explore the following research
questions:
For a defined spatial region, how does one construct and populate a synthesis of potential natural-hazard interactions using blended sources of evidence for past case histories and theoretical future possibilities from that region's characteristics? (Here we focus particularly on triggering and increased probability interactions but discuss additional hazard interrelationships in the context of future developments of this work.) How do triggering interactions documented in the literature contrast with the knowledge of hazard or civil-protection professionals operating in the region? What are the implications of our multi-hazard methodologies on supporting disaster risk reduction, management, and response?
We address these questions by collating and uniting diverse evidence sources
(e.g. field observations and interviews) from the natural and social sciences
through a visual database (i.e. a matrix) of potential hazard interactions
at regional (e.g. national and sub-national) scales. We demonstrate an approach
that is comprehensive (includes a broad array of potential hazards),
systematic (exploring the potential for interactions between each hazard
pairing), and evidenced (documenting the evidence for the existence of
interactions). We label these frameworks “regional interaction frameworks” defined as visualisations that support the identification and characterisation of relevant hazard interactions in a defined region (from 10
Currently, regional studies of potential hazard interactions are sparse and typically do not explain a replicable and scalable method for systematically doing this. Table 1 outlines and characterises seven examples of frameworks for specific named regions or geographical features that include natural hazards and a deliberate attempt to characterise possible hazard interactions. While there is significant variation in the approaches used to construct and populate these frameworks, they helpfully demonstrate the scalability of regional interaction frameworks and issues to be considered when constructing regional interaction frameworks. These examples also highlight the complexity of understanding potential hazard interactions. For example, while many multi-hazard studies focus only on two or three hazards (Ciurean et al., 2018), the examples in Table 1 all show regions exposed to many more hazard types (6–11 natural hazards). This results in significant complexity when trying to constrain and characterise the potential interactions between natural hazards, using either qualitative or quantitative tools.
Examples of seven regional interaction frameworks, including a summary of the spatial extent, hazards and processes considered, and interaction types.
Guatemala map: key locations and physiography, using CIA (2001) Base 802723AI (C00113) 12-00. A combined political and physiographic map of Guatemala, showing differential relief (greyscale shading), departmental boundaries (green lines and text), key locations (black text), rivers (blue lines and text), and roads (red lines). We group Guatemala into four broad regions (1–4) based on physiography. We refer particularly to the southern Guatemalan Highlands (region 3) throughout this paper.
Building on these examples, we present and apply an interdisciplinary methodology in this paper to develop and enhance comprehensive, systematic, and evidenced regional interaction frameworks. We apply this interdisciplinary approach in the context of Guatemala to produce a suite of comprehensive and robust frameworks of potential hazard interactions for two spatial extents (national and sub-national) and describe their application to multi-hazard disaster risk reduction in Guatemala. We trialled our approach in Guatemala due to (i) the hazardousness of the region and (ii) logistical feasibility (contacts, language, and accessibility). A broad range of natural hazards and anthropogenic processes in Guatemala make it an appropriate country for examining hazard interactions. Guatemala's dynamic geological history and geographical setting give rise to many potential hazards. These include geological (e.g. earthquakes, volcanic activity, landslides, and surface collapses) and hydrometeorological hazards (e.g. tropical cyclones, thunderstorms, hailstorms, tornados, coastal storm surges, floods, drought, heatwaves, and cold spells), as defined by UNDRR (2017). Guatemala ranks high in descriptions of countries exposed to multiple hazards and risks (e.g. Welle et al., 2013; Kreft et al., 2015; Bündnis Entwicklung Hilft/United Nations University, 2017). Figure 1 shows a map of Guatemala, including key locations and four physiographic regions that we have defined and refer to later in the paper.
We believe this paper to be the first national-scale comprehensive characterisation of potential hazard interactions in the peer-reviewed literature, relevant to a wide range of actors involved in disaster risk reduction (DRR). While the regional interaction frameworks developed in this paper specifically support Guatemalan stakeholders, we suggest that our approach is replicable and can support implementation of the Sendai Framework in other settings through improved characterisation of multi-hazard interactions, as we discuss throughout this paper.
Examples of five diverse evidence categories with examples for each
one that might indicate the relevance of a given multi-hazard interaction. We
use an asterisk (
The paper is structured as follows: in Sect. 2 we outline the methods used to collect five diverse evidence types, characterise this evidence, and describe how we integrate this evidence to construct and populate a regional interaction framework. We combine our description of data collection methods with the characterisation of the data, as it is more helpful for the reader to have these together. In Sect. 3 we integrate and use this evidence to characterise hazard interactions and networks of interactions (cascades), constructing two regional interaction frameworks for Guatemala (national and sub-national spatial extents). In Sect. 4 we discuss future developments of this work and our findings in the context of regional interaction frameworks and multi-hazard assessments for disaster risk reduction. Conclusions are presented in Sect. 5.
Developing comprehensive and evidenced regional interaction frameworks requires diverse evidence to improve the systematic identification of relevant hazards and interactions. From our experience, in Table 2, we outline examples of different types of evidence to help construct and populate regional interaction frameworks and group these into five categories: (1) publications and other reports, (2) social and other media, (3) field evidence, (4) stakeholder engagement, and (5) miscellaneous. Some overlap exists between these categories, and not all the examples given are relevant in any given location.
In this paper, we use many of the examples of evidence in Table 2
to help construct and populate a regional interaction framework for
Guatemala. We group our evidence into five broad types (A–E below) and use these five types throughout this paper.
For the latter two evidence types (D and E), principal government organisations tasked with informing disaster risk reduction and
response activities in Guatemala are CONRED (2018a; Coordinadora Nacional para la
Reducción de Desastres – National Coordinator for Disaster Reduction) and
INSIVUMEH (2018; Instituto Nacional de Sismología, Vulcanología, Meteorología e Hidrología – National Institute for Seismology, Volcanology, Meteorology and Hydrology). CONRED focuses on disaster preparedness and response, with a broad range of professional expertise. INSIVUMEH focuses on hazard monitoring and is a scientific agency
of the government of Guatemala. Additional organisations include universities (e.g. Universidad de San Carlos de Guatemala), private-sector consultancies and research institutes (e.g. Private Institute for Climate Change Research), civil-society organisations (e.g. Oxfam), and regional and international intergovernmental organisations (e.g. CEPREDENAC or UN OCHA).
Other evidence types (e.g. historical records or community knowledge) are included in the peer-reviewed and grey-literature publications we examined or may be particularly pertinent in other geographical locations. The use of multiple evidence types (vs. a reliance on one evidence type) facilitates a more comprehensive characterisation of hazards and hazard interactions. For each evidence type considered, we do not use all possible examples, methods, and sources; rather we use examples of key case studies from regions of interest. Collecting and interpreting this evidence requires engagement with a range of organisations engaged in research and practitioner work relating to natural hazards, disaster risk reduction, and disaster response. In Sect. 2.2 to 2.6 we characterise our data (evidence types) and the methods used to collect and unite this to address our research questions. We outline limitations associated with this evidence and the methods used to collect it in Sect. 2.7. In Sect. 2.8, we summarise how we integrate evidence types to develop our regional interaction frameworks in Sect. 3.
Internationally accessible publications and reports includes both peer-reviewed and grey literature, such as journal articles, edited volumes, master's and PhD theses, textbooks, technical reports, databases, and NGO disaster situation reports. This compilation of literature includes reports on hazard events in specific geographic regions, providing evidence of hazard interactions. For example, Rose et al. (2004) presents an edited volume of papers on natural hazards in El Salvador, and ReliefWeb (2018) presents a disaster situation report on the impact of Tropical Storm Nate in Central America. We identified multiple publication and report types with information about Guatemala. We prioritised literature giving a broad overview of natural hazards, synthesising multiple texts, or characterising hazard interactions. It is beyond the scope of this study to examine publications on every aspect of hazards in Guatemala or to review all publications on any one aspect of a hazard.
We primarily accessed literature using large Web databases (Google Scholar and Web of Science) for peer-reviewed articles and general online searches for other grey literature (e.g. media reports). We used Boolean search methods, including both “Guatemala” and keywords associated with a preliminary list of 21 natural hazards (from Gill and Malamud, 2014). For example, “earthquake”, “aftershock”, “seismic”, “tremor”, and “liquefaction” were searched for alongside “Guatemala” and “Central America” to identify relevant material. We evaluated results to determine their relevance and identify other keywords. We also identified specialist books, such as an edited volume on the geology of Central America (Bundschuh and Alvarado, 2007).
We examined literature in a systematic manner, collating references, maps, and figures for 17 (of the 21) natural hazards: earthquake, tsunami, volcanic eruption, landslide, flood, drought, regional subsidence, ground collapse, soil (local) subsidence, ground heave, storm, tornado, hailstorm, lightning, extreme temperature (heat), extreme temperature (cold), and wildfire. Snow avalanche and snowstorm have limited spatial relevance to Guatemala, and geomagnetic storm and impact event have little country-specific (vs. generically relevant) information. For each hazard considered, we cross-referenced diverse literature to characterise it at a level of detail appropriate to this study, including information on spatial and temporal distribution, triggering relationships, and impacts. We identified and used 169 sources as evidence, with 93 (55 %) of these being peer-reviewed and 76 (45 %) of these being grey literature.
Another evidence type to inform the development of regional interaction frameworks is locally accessible reports, such as government or NGO bulletins, newspapers, and emergency call-out records. Civil-protection information bulletins and newspapers can both give a focused overview of natural-hazard occurrences (e.g. Guzzetti et al., 1994; Trimble, 2008; Raška et al., 2014; Taylor et al., 2015), providing information on hazard interactions or noting triggering relationships.
In Guatemala, we use Spanish-language civil-protection information bulletins from the CONRED. Bulletins are issued when there is a threat to lives, livelihoods, and infrastructure and include information on hazards, their spatial and temporal extent, and their impacts, including triggering other hazards. Natural hazards occurring in remote regions or having a very low impact (e.g. very small landslides) are unlikely to be included in bulletins, and therefore bulletins do not provide a complete record of events. CONRED may issue multiple bulletins per day, depending on the evolution of, for example, a weather system or a disaster event. Bulletins are distributed to a mailing list of personnel, with some on their website (CONRED, 2018b) and ReliefWeb (2016). At the time of writing, CONRED bulletins were not systematically archived online. We therefore classify these bulletins as locally accessible.
CONRED made 291 information bulletins available to the authors (electronic format), published over a 127 d period between the 11 June and 15 October 2010, of which 24 were corrupt files and 267 were accessible. Based on their numbering, we believe that CONRED published 413 bulletins during this 127 d period. Additional information that characterises these bulletins is included in the Supplement (Table S1). We searched the 267 accessible bulletins for keywords, placing these into context by looking at the surrounding sentences. Taylor et al. (2015) used this approach to enrich the UK national landslide database by examining newspaper archives.
We selected and used the following six keyword verbs connecting two hazard
types and suggesting an interaction between them (with an abbreviated
Spanish verb base in parentheses): to trigger (
In total, there were 143 results from 95 CONRED bulletins prior to us processing them based on their relevance to the theme of hazard interactions. By examining the context, we determined that 39 of the 143 results (from 36 different bulletins on 28 unique days) described unique events where interactions occurred between natural hazards. These results are presented in Table S2. The results in this section, although based on an incomplete dataset, demonstrate examples of the range of types of interactions that could occur. Further research could use a larger sample of bulletins to better characterise interactions in Guatemala or an event database such as EM-DAT (CRED, 2018). This would be necessary if the frequency of different types of events were a consideration, with a 4-month period being too short to analyse this.
Field observations can also help with understanding the relevance and dynamics of hazards and hazard interactions. For example, Havenith et al. (2003) describe field evidence of earthquake-triggered landslides in the northern Tien Shan of Kyrgyzstan. Approaches include reconnaissance visits to improve contextual understanding of the region; detailed geological, geomorphological or hazard mapping; and the application of technologies such as rain gauges, drones, and thermal-imaging infrared cameras.
In Guatemala, from January to March in 2014 (9 weeks total), the lead author visited regions in the southern Guatemalan Highlands (identified in Fig. 1) affected by multiple natural hazards and anthropogenic activity. This helped with familiarising the non-Guatemalan authors with the features of key locations and hazards in Guatemala, but primary field data (e.g. community interviews) were not gathered. Observing the spatial and temporal scales at which hazards and anthropogenic processes act enhanced understanding of Guatemala's multi-hazard environment. It also enriched interviews with expert participants (described in Sect. 2.5), with the interviewer making better use of examples, local places names, and descriptors used by participants to characterise and evidence natural-hazard interactions in Guatemala.
The lead author conducted multiple field visits alongside INSIVUMEH, with support from the University of Bristol, and one field visit with CONRED. This helped with developing constructive relationships, establishing the mutual trust and respect required for subsequent data-rich interviews (Kitchin and Tate, 2000). Examples of principal field locations and relevant interactions are (i) Lake Atitlán (e.g. tropical storms triggering landslides, landslides triggering flooding, and landslides triggering lake tsunamis), (ii) Fuego volcano (e.g. lahars triggering floods), and (iii) Santiaguito volcano (lahars triggering flooding).
Interviews provide additional evidence to construct and populate regional interaction frameworks. Participants often come from diverse backgrounds, with differing understanding of natural hazards and geographic regions. Participants with relevant evidence can include hazard and disaster professionals and local people who might be impacted by hazards (e.g. farmers, local government, and communities). Selecting participants based on their experience and relevance to a research question (purposeful sampling) can result in data-rich interviews (MacDougall and Fudge, 2001; Longhurst, 2003; Suri, 2011; Palinkas et al., 2015). Semi-structured interviews provide one means by which to have this dialogue, with questions focused on hazards and hazard interactions. This style gives enhanced freedom in exploring areas of interest and pursuing emerging lines of enquiry (Qu and Dumay, 2011).
Prior to stakeholder engagement in Guatemala in 2014, we obtained ethics approval (reference REP(GSSHM)/12/13-18) from King's College London for research with human participants. At the start of each interview (conducted by the authors Joel C. Gill or Joel C. Gill and Bruce D. Malamud) we explained the purpose of our work and sought informed, prior consent to use data generated. All participants gave permission for us to use their data and identify their institution unless this would identify the individual. We interviewed 21 hazard and civil-protection professionals in Guatemala during 19 interviews. Table S3 characterises the interview participants. Participants came from academia, the private sector, INSIVUMEH, and CONRED. We selected interview participants from diverse professional backgrounds in terms of hazard speciality (e.g. earthquakes, landslides, and floods) and engagement in the disaster cycle (e.g. early warning, mitigation, and recovery). We identified contacts before travelling to Guatemala through their online profiles and professional engagement in other projects and through introductions once in Guatemala.
Interviews ranged from 30 to 120 min, following a semi-structured approach (Longhurst, 2003; Qu and Dumay, 2011). Interviews included opportunities for participants to talk about (i) their background and training, (ii) their consideration and use of information on hazard interactions, (iii) examples of existing networks of multi-hazard interactions, and (iv) hazard interaction visualisations. All interviews aimed to cover these key themes; however there were differences in the order in which they were introduced and the specific questions asked. Interviews were conducted in Spanish (with a translator), in Spanish (without a translator), and in English, depending on the context. To reduce possible power relations, we ensured that participants were at ease with the interviewer and participant setting (Kitchin and Tate, 2000; DiCicco-Bloom and Crabtree, 2006; Qu and Dumay, 2011).
Table S4 presents key statements relating to natural hazards, hazard interactions, and anthropogenic processes, extracted from these 19 semi-structured interviews. Multiple participants highlighted specific interaction examples. These include ones already noted in accessible peer-reviewed or grey-literature sources (e.g. lahars from Santiaguito triggering flooding; Harris et al., 2006) and interactions not described in other evidence types (e.g. Pacific coastal flooding due to simultaneous high tides and river sedimentation).
Workshops are another form of stakeholder engagement and are designed to
generate data through activities and focused discussion. We organised a
3 h workshop in Guatemala involving 16 civil-protection professionals at
CONRED. Participants included senior and junior staff working in diverse
departments. Table S3 characterises the 16 workshop participants (of whom 4 also took part in interviews), with all giving permission for us to use their data in an anonymised form. During our workshop, participants independently completed two tasks.
We therefore collected two sets of visual records that document
participants' perceptions of relevant hazard interactions in Guatemala. We
include all completed diagrams in Figs. S1 and S2. Completed network linkage and interaction matrix diagrams vary in the number and range of interactions proposed to be relevant in Guatemala. The number of interactions proposed by any one participant using the hazard linkage diagram, for example, ranged from 8 to 35, with a mean of 18 and a median (50th percentile) of 15.
Using all 16 completed network linkage diagrams (Task 1 above), we can represent the combined knowledge of the workshop participants and use this as evidence when constructing regional interaction frameworks for Guatemala. In Fig. 2, we overlay evidence from 16 completed network linkage diagrams on a blank interaction framework, showing the number of participants (out of 16) proposing each triggering relationship. This interaction framework has 21 primary natural hazards on the vertical axis and the same 21 secondary natural hazards on the horizontal axis, using an approach laid out in Gill and Malamud (2014).
Stakeholder identification of possible hazard interactions in Guatemala, using network linkage diagrams produced by 16 civil-protection
professionals in Guatemala. A
Of a total possible 441 (
Evidence types A–E, characterised in Sect. 2, are each associated with limitations and uncertainties.
using a reflexive and respectful approach reduced language barriers, cultural barriers, and power dynamics on the results of stakeholder engagement; using a critical approach to literature analysis determined where inaccuracies may exist in grey or historical literature; integrating multiple evidence types to reduce the impact of uncertainties on regional interaction frameworks; cross-referencing personal perspectives expressed in interviews, for example, with peer-reviewed literature to explore accuracy; using global interaction frameworks to serve as useful databases of what could occur, helping to evaluate the scope of possible interactions before ascertaining their relevance to Guatemala.
These factors are likely to have resulted in some uncertainties within the
evidence used and therefore within the interaction frameworks produced
using this evidence. Some sources of uncertainty can be mitigated, and
appropriate actions were taken to do so, including the following:
We suggest, therefore, that the regional interaction frameworks presented in
the remainder of this paper are robust assessments of potential triggering
and increased probability interactions in Guatemala. It is possible,
however, that relevant hazard interactions and anthropogenic processes, or
the likelihood or spatial distribution of these, will vary over time.
The construction of comprehensive and systematic regional interaction
frameworks requires three components for a region of interest, each bringing
together diverse strands of evidence and unifying them within a formal
structure, supported by expert knowledge (Neri et al., 2008):
information on relevant single hazards and appropriate ways to classify these, using the evidence in Sect. 2.2 to 2.6 and the classification of 21 natural hazards in Gill and Malamud (2014); information on relevant hazard interactions to populate the interaction framework (i.e. identifying how single hazards interact with each other), using the evidence in Sect. 2.2 to 2.6 and the matrix of globally possible interactions in Gill and Malamud (2014); an appropriate visualisation framework to represent hazard interactions; we adapt existing visualisation frameworks (Gill and Malamud, 2014, 2016, 2017) and ensure that these are appropriate to Guatemala.
We can then use this framework and evidence presented in Sect. 2 to
identify potential networks of multi-hazard interactions and explore how
anthropogenic processes can trigger natural hazards or catalyse hazard
interactions (Gill and Malamud, 2017).
We now proceed to develop our comprehensive, systematic, and evidenced
regional interaction framework for Guatemala. In Sect. 3.1, we discuss the construction and population of regional interaction frameworks. In Sect. 3.2, we present a revised hazard classification scheme for Guatemala. In Sect. 3.3, we use this scheme and additional evidence to populate two regional interaction frameworks, a
In Table 3, we explore, in the context of Guatemala, six themes laid out by Gill (2016) to guide the generation of regional interaction frameworks: spatial scale, temporal scale, likelihood–magnitude relationships, selection and classification of natural hazards, identifying relevant hazard interactions, and visualisation style and user communities. We integrate perspectives from hazard and civil-protection professionals in Guatemala (from semi-structured interviews and the workshop; see Sect. 2.5 and 2.6). Professional organisations have an understanding of local culture, language, and knowledge and have the mandate to adapt interaction frameworks into suitable forms for other stakeholders (e.g. policymakers and communities).
Consideration of six regional hazard interaction themes (identified in Gill, 2016) with respect to Guatemala. A description is given of how each theme is addressed in this regional interaction framework, using stakeholder comments discussed in Sect. 2.5 (interviews) and Sect. 2.6 (workshop results) to inform this process.
Gill and Malamud (2014) propose a broad classification of 21 natural hazards into six hazard groups (geophysical, hydrological, shallow Earth, atmospheric, biophysical, and space). This, or an alternative, comprehensive classification can be adapted to develop a regionally specific classification, using available evidence. We use this approach to propose a detailed, location-specific classification of natural-hazard types in Guatemala, building on evidence in Sect. 2. We begin by identifying which of the 21 natural hazards listed in Gill and Malamud (2014) are relevant in Guatemala and sub-divide selected hazards where evidence supports an expanded classification. We present our evidenced classification scheme in Table 4, including six natural-hazard groups, 19 hazard types, and 37 hazard sub-types. We also include an indication of the evidence types supporting this classification, using identifying letters A–E introduced in Sect. 2.1 and specific referenced publications and reports where appropriate. The 37 detailed natural-hazard sub-types in Table 4 help with improving the detail by which we can characterise interactions in regional interaction frameworks (e.g. see Sect. 3.3).
Detailed classification of six natural-hazard groups, 19 hazard types, and 37 hazard sub-types relevant to Guatemala. An outline of a possible hazard classification scheme relevant to Guatemala. Evidence types A to E (from Sect. 2) are used to justify the inclusion of each hazard sub-type and noted in the table, with references from international literature.
Our classification is one way of grouping relevant natural hazards, with alternative classifications possible. Other natural-hazard types may exist in Guatemala that have been missed from our classification, including those occurring less frequently or having a smaller impact than those we consider. We reduce the likelihood of missing key hazards by reviewing multiple evidence types to ensure a comprehensive and evidenced classification. We include 26 to 32 more hazard sub-types than existing regional interaction frameworks (e.g. Tarvainen et al., 2006; Kappes et al., 2010; Liu et al., 2016). In addition to the 37 natural-hazard sub-types in Table 4, we could also consider how a changing climate influences natural hazards (see McGuire and Maslin, 2012, for a full discussion) or include other hazard groups or processes, such as biological hazards (e.g. epidemics), technological hazards (e.g. structural collapse), or anthropogenic processes (e.g. vegetation removal). The latter are discussed in Sect. 3.5.
Building upon the reflections in Sect. 3.1, and using the hazard classification in Sect. 3.2 and evidence in Sect. 2, we now construct and populate interaction frameworks for two different spatial extents in Guatemala:
Both interaction frameworks use a matrix visualisation approach.
To develop an interaction framework for the national spatial extent of
Guatemala, we start with an existing
The evidence types (A–E) given in Sect. 2 supporting these 50 hazard interactions are outlined in Table S5. We believe that this to be the first
national-scale assessment of possible hazard interactions in the peer-reviewed
literature, with our approach being generalisable for other national
contexts. We use Table S5 to inform the development of an additional national-scale
National interaction framework for Guatemala. A
We now proceed to develop a regional interaction framework for a sub-national spatial extent. Using physiography, we divide Guatemala into four spatial regions as indicated in Fig. 1: (1) low-relief northern plateau, (2) central Guatemalan Highlands, with deep valleys, (3) southern Guatemalan Highlands, and the (4) Pacific Coastal Plain. In Table 5, we show the 37 hazard sub-types described in Sect. 3.2 and use the evidence types (A–E) given in Sect. 2 to characterise their spatial relevance to these four regions. More hazards are spatially relevant to the southern Guatemalan Highlands than other regions in Guatemala; 33 (89 %) of 37 possible hazard sub-types are possible in the southern Guatemalan Highlands, compared with 26 (70 %) to 27 (73 %) of 37 hazard sub-types relevant in the other regions. The southern Guatemalan Highlands are a region of variable topography between the Pacific Coast and the Polochic–Motagua–Chamalecón fault system. It incorporates the volcanic arc, with at least three active volcanic systems (Pacaya, Fuego, and Santiaguito).
Southern Guatemalan Highlands (sub-national) interaction framework, Guatemala. A
Spatial distribution of 37 natural-hazard sub-types in Guatemala. A synthesis table to characterise which regions in Guatemala are susceptible to each of the 37 natural-hazard sub-types. Selected regions (see Fig. 1) are (1) low-relief northern plateaus, (2) central Guatemalan Highlands, with deep valleys, (3) southern Guatemalan Highlands, and (4) Pacific Coastal Plain.
The 33 hazard sub-types relevant in the southern Guatemalan Highlands are used as
primary and secondary hazards in our regional interaction framework. This
results in 1089 (
The 114 interactions in Fig. 4 include interactions that occur over
large and small spatial areas, with both high and low frequencies and both
high- and low-magnitude events. The temporal relevance of interactions in
Fig. 4 may change, for example due to evolving anthropogenic
activity (see Sect. 3.5) or environmental change. Interactions
include some originating outside of the spatial region of interest and
others that may propagate outside. For example, (i) an earthquake north of
the southern Guatemalan Highlands may result in ground shaking, liquefaction,
landslides, and other secondary hazards inside the southern Guatemalan Highlands; (ii) lahars triggered in the southern Guatemalan Highlands may trigger flooding outside of the southern Guatemalan Highlands, in the Pacific Coastal Plain; and (iii) large
volcanic eruptions in the southern Guatemalan Highlands can eject ash and tephra far beyond
this extent. Characteristics of interactions (e.g. likelihood) are not
included in Fig. 4 but could be added as additional information
layers if further research results were available.
In addition to one hazard triggering or increasing the probability of another hazard, longer linear or non-linear networks of multi-hazard interactions (or cascades) can also occur (Han et al., 2007; Choine et al., 2015; Gill and Malamud, 2016; Pescaroli and Alexander, 2018). These network events have both spatial and temporal dimensions, include both high- and low-likelihood events, and have diverse impacts. Ciurean et al. (2018) outline a range of methods for qualitatively and quantitatively characterising such multi-hazard interaction network events. For example, event scenario trees can be used to assess the probabilities of specific hazard cascades (Neri et al., 2008, 2013).
The evidence we present in Sect. 2 includes many examples of
multi-hazard interaction network events. For example, the internationally
published literature characterising the 1976
The civil-protection bulletins characterised in Sect. 2.3 also include several examples of events consisting of multi-hazard interactions in Guatemala. These include events with primary, secondary, and tertiary hazards as well as events reporting primary hazards changing the likelihood of future hazards. Table 6 gives three diverse examples of network events derived from Table S2, demonstrating the complexity of hazard interaction networks in Guatemala. Table 6 also includes a simple visualisation of each example, showing the range of hazards and interaction relationships:
linear events where one primary hazard triggers one secondary hazard which triggers one tertiary hazard ( multi-branch events where a primary hazard may trigger multiple secondary hazards, each triggering one or more tertiary hazards ( a primary hazard triggering and increasing the likelihood of multiple secondary hazards during a high-magnitude, complex event, replicated in multiple areas of Central America ( Assessing, managing, and reducing disaster risk require better modelling of the natural environment by moving from understanding discrete, independent events to matching the observed reality by including interaction networks. Identifying possible multi-hazard interaction network scenarios may allow improvements to disaster preparedness by better assessing how vulnerability will change during successive hazard events. Aspects of social and/or physical vulnerability may change following the occurrence of a specific natural hazard (e.g. volcanic eruption), before the triggered hazard (e.g. rain-triggered lahars) occurs. Understanding how multi-hazard interaction network events are initiated and propagated may help determine how to invest resources to minimise disruption should a specific network of interacting hazards occur.
Further examples of hazard interaction network events emerged from
stakeholder interviews, including volcanic eruptions and heavy rain
triggering lahars, which subsequently trigger floods. These networks can be
visualised using interaction frameworks, as illustrated in Figs. 5 and 6:
The regional interaction frameworks we present in this paper can help with
visualising case studies of cascades identified through various evidence types
and identify
Three examples of networks of multi-hazard interaction (cascades), extracted from the CONRED civil-protection bulletins. Each example (1–3) is characterised by bulletin number, date, location, and event descriptions.
Network of hazard interactions (Example 1), southern Guatemalan Highlands, Guatemala. A
Network of hazard interactions (Example 2), southern Guatemalan Highlands, Guatemala. A
In Sect. 3.2 to 3.4, we primarily consider interactions between natural hazards; however, anthropogenic processes can also trigger natural hazards and influence natural-hazard interactions (Glade, 2003; Knapen et al., 2006; Owen et al., 2008; Gill and Malamud, 2017). Information on relevant anthropogenic processes can support hazard and civil-protection professionals in evaluating how anthropogenic activity may trigger hazards and influence hazard interactions.
Using a classification of 18 anthropogenic processes (Gill and Malamud, 2017), and evidence from Sect. 2, we identify 17 relevant anthropogenic processes in Guatemala, listed in Table S6. Some of these processes are only relevant for small spatial extents (e.g. individual towns), with others being more widespread (e.g. in many populated regions). Table S6 includes the evidence types (A–E) from Sect. 2 used to justify their relevance to Guatemala. Some anthropogenic processes feature multiple times within one evidence type. For example, four interviewees noted road construction (infrastructure construction: unloading) and four noted deforestation (vegetation removal) in the context of triggering landslides. In contrast, only one interview participant mentioned groundwater abstraction as a potential trigger of subsidence.
The spatial and temporal relevance of these 17 anthropogenic processes will vary and could change over time. Anthropogenic processes can start and stop and both grow and shrink in their spatial extent. The anthropogenic processes in Table S6 should be regularly reviewed to assess their relevance, if other processes have started, and if there are any consequences of this variation on natural hazards and hazard interactions. For example, increased road construction may change the likelihood of landslides during heavy rain.
We have integrated diverse evidence types regarding hazards and hazard interactions in Guatemala and unified them in a formal structure, supported by expert knowledge. We have collated information on relevant single hazards and appropriate ways to classify these in Guatemala and information on relevant hazard interactions. Using a comprehensive and systematic approach, we have constructed evidenced national and sub-national interaction frameworks in matrix form, considering hazard interaction networks and relevant anthropogenic processes. We have demonstrated that our approach is scalable (with national and sub-national applications described) and therefore suggest that it is reproducible in diverse geographical contexts and at multi-national to local scales. Regional interaction frameworks provide a comprehensive overview of potential hazard interactions that allow agencies responsible for hazard monitoring and response to assess if current disaster risk reduction and response strategies, and communication and collaboration mechanisms, can be enhanced to recognise the complexity represented.
In this discussion section, we first explain how the approach to constructing regional interaction frameworks we have developed in this paper can be replicated and scaled in diverse settings (Sect. 4.1). We proceed to explore how regional interaction frameworks can be used to enhance understanding of multi-hazard interactions (Sect. 4.2) and opportunities to enhance regional interaction frameworks through new research and practice (Sect. 4.3).
The interdisciplinary, multi-method approach we have laid out in Sects. 1 to 3 is scalable and can be applied in diverse geographical settings to generate a comprehensive, systematic, evidenced review of potential hazard interactions. A synthesis of available evidence in any given context (e.g. multi-national, national, and sub-national) is necessary for underpinning the construction of regional interaction frameworks. Our approach first develops an extensive location-specific hazard classification and then populates a customised matrix with information about relevant hazard interactions. This contrasts with many existing studies of multi-hazards which are often focused on the layering of single hazards but not looking at the potential interactions. When potential hazard interactions are considered, most studies are not systematic and are selective about which hazards they include. The studies often do not describe the evidence for including or excluding certain hazards or interactions between hazards. The regional interaction frameworks we present in Sect. 3 include 21 to 33 natural hazards, compared to 6 to 11 natural hazards in the examples summarised in Table 1.
Other countries in Central America (e.g. Nicaragua, El Salvador, and Costa Rica) have similarities to Guatemala in their multi-hazard landscape. Their national interaction frameworks would likely be similar, although not identical, to Guatemala. Interaction frameworks for other countries may look very different, shaped by the tectonic and meteorological setting. Regional interaction frameworks can also be developed for sub-national scales, including large geographical domains, municipalities, or localised sites important to the development of critical infrastructure.
We propose that comprehensive, systematic, and evidenced regional interaction frameworks can improve awareness of complex multi-hazard landscapes and assessment of potential networks of hazard interactions, thus informing disaster risk reduction and response strategies. Detailed and evidenced reviews of multi-hazard interactions are a fundamental first step in understanding the complexity of the multi-hazard landscape and therefore understanding risk (Sendai Framework, Priority for Action 1). In particular, regional interaction frameworks can be a powerful tool for scenario discussions between hazard managers and those responsible for single hazard preparedness and response. Through sitting down and discussing together the potential multi-hazard scenarios that may occur, decisions can be made about the preparedness steps required and how different actors would work together to respond. It may be possible to indicate which scenarios have a high likelihood vs. a low likelihood and which could have a large impact vs. a small impact. When the regional interaction frameworks were used by us in this way in Guatemala during a visit of the first author in 2018, some participants questioned the inclusion of particular hazards and/or hazard interactions in the interaction frameworks (e.g. landslides triggering tsunamis). Following discussion of the evidence used to populate the matrix for this scenario, participants reported changes in opinion about the relevance of these interactions and their need for inclusion within planning.
Further examples of how the information within regional interaction frameworks, and generated scenarios, can be used by agencies responsible for hazard monitoring, DRR, and disaster response are as follows.
Failing to consider multi-hazard interactions can therefore lead to the
distortion of management priorities, increased vulnerability to other
spatially relevant hazards, overwhelming a community with multiple and
sometimes conflicting hazard management strategies for multiple hazards, or
an overall underestimation of risk (Tobin and Montz, 1997; ARMONIA, 2007;
Kappes et al., 2010; Budimir et al., 2014; Mignan et al., 2014; Gill and
Malamud, 2014). Regional interaction frameworks are a valuable informational
compilation and visualisation tool for (i) raising awareness of the
complexities of the multi-hazard environment and (ii) extracting and
discussing potential scenarios of multi-hazard interaction networks to
explore how exposure and vulnerability may change between successive hazard
events.
Hazard interactions cut across multiple disciplines and so require input
from diverse specialisms (Kappes et al., 2012; Scolobig et al., 2017). Interaction frameworks could therefore help with facilitating enhanced cross-institutional dialogue about hazard interactions and their likelihoods and potential impacts. This could help with strengthening collective knowledge of hazard interactions and the ability of an individual to access this knowledge. By contrasting results from our workshop (Fig. 2) with our Guatemala national interaction framework (Fig. 3), we can examine and quantify congruence between the two matrices and create a new figure. Figure 7 is a
Stakeholder identification of possible natural-hazard interactions
in Guatemala, overlain over the national interaction framework developed in
Fig. 3. A
Figure 7 combines information and knowledge from 16 participants to present something that is “owned” by no individual. It is collective knowledge, combining information and knowledge owned by multiple people (Antonelli, 2000). We do not expect an individual scientist or hazard professional to map out all relevant interactions. Assessing how an organisation rather than an individual understands interactions demonstrates their collective knowledge. For this knowledge to be truly collective, there must be effective communication between participants and a means by which this knowledge can be accessed, shared, and applied (Foray, 2000; Antonelli, 2000; Paton et al., 2008).
Calculation of Matthews' correlation coefficient (MCC) to assess
agreement between the collective knowledge of 16 workshop participants
(Fig. 2) and national interaction framework (Fig. 3). Three different
thresholds, each relating to the number of workshop participants (out of 16)
identifying a particular interaction, are used to determine collective
knowledge of hazard interactions. The number of “agreements” and
“disagreements” between the workshop participants' response and national
interaction framework (see column headers for descriptions) is shown. For
each row, the sum of true positives (TPs) and false negatives (FNs) is 50, and
the sum of true negatives (TNs) and false positives (FPs) is 392. MCC values
are determined using Eq. (1). MCC
Multi-hazard research is complex and requires scientists and professionals
operating in many different disciplines. Figure 7 demonstrates large
variation in perspectives between participants on hazard interactions. There
is a unanimous consensus (i.e. 16 participants) that an interaction exists
in 2 (0.5 %) of 441 possible triggering interactions. To assess
congruence between the participants' perspectives (numbers in Fig. 7) and national interaction framework (grey shading in Fig. 7), we use Matthews' correlation coefficient, or MCC (Matthews, 1975). MCC values are a function of true positives (TPs), true negatives (TNs), false positives (FPs), and
false negatives (FNs) and can be expressed as follows (Matthews, 1975; Powers, 2011):
For these three thresholds (
Matthews' correlation coefficient is a simple indicator of agreement, which we use to examine differences between stakeholder perspectives and our national interaction framework (Fig. 3). When applying a small threshold ( Enhanced communication within and across organisations involved in natural hazards and DRR in Guatemala could help when considering hazard interactions. When co-created by diverse stakeholders, interaction frameworks can help with facilitating communication across specialisms engaged in hazard monitoring and civil-protection. Interaction frameworks could also help elicit additional information for characterising interactions, such as which are most likely to occur and which could cause the greatest damage to interaction likelihoods and impacts. Ensuring that collective understanding of hazard interactions is operationalised to greatest effect will require strong institutions and cross-departmental and cross-disciplinary communication (Scolobig et al., 2017). National and sub-national interaction frameworks could promote dialogue on both high- and low-likelihood events. Interactions in the national interaction framework (Fig. 3) include some low-likelihood hazard interactions, such as impact events triggering tsunamis and storms triggering meteotsunamis. Workshop participants may not consider low-likelihood events due to lack of access to peer-reviewed literature. Only 5 of the 21 interview participants (Sect. 2.5) had access to, or regularly used, peer-reviewed journals. Interview participants predominantly relied on experience and communication with colleagues for further information on natural hazards and interactions. We can use MCC values to monitor changing awareness and perceptions of natural-hazard interactions. MCC values can be determined before interaction frameworks are introduced into an organisation and then recalculated weeks, months, or years after individuals have explored, discussed, and used them in their work.
The results of this exercise demonstrate that there are knowledge gaps that
the development of comprehensive and evidenced frameworks of interactions
could help address and provide a tool that could help with monitoring changes
in awareness of hazard interactions over time.
We lay out an approach in Sects. 1 to 3 that integrates diverse evidence sources from the natural and social sciences through a visual database to give a comprehensive, systematic, and evidenced review of the multi-hazard interactions for a regional spatial extent. We believe that this approach builds on and enhances existing forms of regional interaction framework, such as those described in Table 1. Additional research can further enhance regional interaction frameworks (Sect. 4.3.1), as can better understanding how to embed research outputs into relevant agencies through meaningful stakeholder dialogue (Sect. 4.3.2). Engagement with hazard and civil-protection professionals, academics, the private sector, and intergovernmental organisations in Guatemala informed our development of regional interaction frameworks. Understanding stakeholder requirements (e.g. terminology, spatial scales, and temporal scales) helps to ensure that frameworks are fit for purpose. Draft results were discussed with many of these stakeholders in Guatemala in 2018, prior to publishing. We shared our interaction frameworks through seminars, roundtable discussions, and interviews to document perspectives on (i) the structure and content of the interaction frameworks, (ii) use of the interaction frameworks, and (iii) future research and innovation opportunities. We highlight some of the common themes in the following two sub-sections.
Three broad areas where additional research could help with enhancing regional interaction frameworks include (i) expanding the range of interaction types considered, (ii) increasing the number of layers within regional interaction frameworks to better characterise interactions, and (iii) quantifying more complex scenarios derived from regional interaction frameworks.
In the regional interaction frameworks we have developed, we have particularly focused on triggering and increased probability interaction types and the way in which these can connect to form multi-hazard interaction network events (cascades). Other interaction types are also important and emphasised in the Sendai Framework, notably where hazardous events occur simultaneously or cumulatively over time. Additional literature searches, fieldwork, data interrogation, and/or stakeholder engagement could be used to document particular physical and social impacts of two or more independent hazards occurring simultaneously or consecutively in a region of interest (e.g. the near-simultaneous eruption of Pacaya volcano and Tropical Storm Agatha in Guatemala in 2010). Examining the impacts of simultaneous or consecutive events on physical infrastructure, response systems, and community well-being could identify particular strengths or weaknesses where investment or capacity strengthening could help with reducing vulnerability to the broad multi-hazard landscape (de Ruiter et al., 2018).
A second stream of research that could enhance regional interaction frameworks is the development and inclusion of additional layers of information such as how often each interaction occurs, possible thresholds, and likelihoods and scales of impact. For each interaction, understanding the frequency–magnitude of occurrence and the range of potential impacts would involve the collation of additional and extensive evidence. We previously noted that some of this information could be elicited from diverse stakeholders, including through forensic studies of past and ongoing disasters, to generate new insights into potential impacts. A “multi-hazard observatory” could also enable the collection of diverse data to better characterise these layers of information. Information for characterising multi-hazard interactions would help with informing decision-making about which interactions primarily need to be addressed to reduce disaster risk.
Building on the enhanced characterisation of potential interactions outlined above, a third stream of research is the quantification of more complex scenarios (interaction network events or cascades) derived from regional interaction frameworks. There is a gap for more modelling of real multi-hazard situations, involving multiple natural-hazard types, anthropogenic processes, and a range of interaction types. A review of multi-hazard literature completed by Ciurean et al. (2018) highlighted that much of the current literature described simulated environments for a limited number of hazard and interaction types. This is potentially due to challenges in access to the data needed to characterise these complex multi-hazard environments and the need to integrate data from different disciplines. One approach to collate relevant data and improve the characterisation of hazard interactions is to use an online wiki-style system where relevant papers, datasets, and assessments of frequency–magnitude can be uploaded.
Furthermore, interaction frameworks can also be used as a tool to
Embedding regional interaction frameworks into key agencies responsible for hazard monitoring, disaster risk reduction, and disaster response can contribute to improved decision-making by having a more holistic understanding of the multi-hazard landscape. Interaction frameworks are a visual synthesis of diverse knowledge, traditionally owned by diverse disciplinary groups. They can help with enhancing awareness of the spectrum of hazards and hazard interactions in a given territory and strengthen communication across disciplinary boundaries. Interaction frameworks allow those undertaking research into any particular single hazard to place their work within the context of other natural hazards, thus fostering communication between hazard specialists and encouraging a more interdisciplinary approach. When reviewing the draft regional interaction frameworks for Guatemala, one interview participant noted that (translated from Spanish) “sometimes knowledge is in a head, but now it is in a visual summary [that can be used by a range of people]”.
One future step to help embed regional interaction frameworks into decision-making is to consider the scale of the spatial extent for which they are prepared. Many participants suggested that municipalities are the preferred scale of interest for further multi-hazard tools. Guatemala currently has 340 municipalities across 22 departments. The emphasis on municipalities likely arises from the political context in Guatemala, with municipal authorities being the final users of information. Other stakeholders noted that it may not be most effective (or efficient) to produce municipal-scale hazard assessments as hazards cross municipal, departmental, and national boundaries. Tools can therefore be prepared at scales that both provide useful information to those working at a municipal scale and recognise the artificial nature of these boundaries. Tools that allow the spatial representation of information in Sect. 3 could facilitate this, seeing both municipal perspectives and cross-border challenges. A GIS tool allowing the creation of municipal multi-hazard risk maps was a high priority of stakeholders, allowing the identification of hazard hotspots, improved disaster preparation (e.g. evacuation routes), and enhanced response through improved communication of potential secondary hazards. Spatial representation of information could help with identifying regions where secondary hazards are more likely after a primary hazard and the assessment of disaster impacts, including those generated through secondary hazards, by overlay of exposure and multi-hazard maps.
Participants also noted specific ways in which they could use regional interaction frameworks in their ongoing work. INSIVUMEH, CONRED, and UN-OCHA indicated that they could use interaction frameworks as reference tools to strengthen preparedness and response to hazards. CONRED suggested they could integrate secondary hazards information into their public information bulletins and requested blank matrices to complete for specific high-risk municipalities. Finally, universities indicated that they would use this research and our systematic classification of hazards in Guatemala in their teaching. Fully realising the impact of regional interaction frameworks, and ensuring positive social impact, will require sustained collaborative engagement with user communities. The potential developments and applications outlined through Sect. 4.3 would support the embedding and operationalisation of this research in Guatemala with the lessons learned helping other regions and the wider hazard or disaster risk community.
Understanding and characterising the multi-hazard landscape of a region
directly support the implementation of the Sendai Framework (UNDRR, 2015).
In this paper, we have addressed three research questions, originally
outlined in Sect. 1:
For a defined spatial region, how does one construct and populate a synthesis of all relevant potential natural-hazard interactions using blended sources of evidence for past case histories and theoretical future possibilities from that region's characteristics? How do triggering interactions documented in the literature contrast with the knowledge of hazard or civil-protection professionals operating in the region? What are the implications of our regional interaction frameworks for multi-hazard methodologies to support disaster risk reduction, management, and response?
We develop and describe an approach for understanding the multi-hazard landscape
through comprehensive, systematic, and evidenced regional interaction
frameworks. We apply this approach in Guatemala, generating regional
interaction frameworks for the national spatial extent of Guatemala and
sub-national spatial extent of the southern Guatemalan Highlands. Five
evidence types (internationally accessible publications and reports, locally
accessible civil-protection bulletins, field observations, semi-structured
stakeholder interviews, and a stakeholder workshop) underpin the
construction and population of these frameworks. We use this evidence to do the following:
Interaction frameworks can help with improving understanding of the multi-hazard
landscape of a given region and potential scenarios of multi-hazard
interaction network events (cascades). We present information in accessible
visualisations, primarily with interaction matrices. The use of accessible
visualisation tools, such as matrices, to represent complex hazard
interactions contributes to knowledge exchange across different disciplines. We demonstrate through Matthews' correlation coefficient, a simple indicator of agreement, that there are many differences between stakeholder perspectives and our national interaction framework. The development of comprehensive and evidenced frameworks of interactions could help with increasing awareness of multi-hazard interactions and strengthening communication between different stakeholders to improve collective knowledge. They could also be used as a tool to monitor changes in understanding of hazard interactions over time.
Our approach allows those working on any individual hazard in Guatemala to place their work within the context of other natural hazards. When taking drafts of regional interaction frameworks back to Guatemala government hazard scientists and technicians in 2018, we observed them fostering communication between hazard specialists and encouraging integrated multi-hazard approaches to DRR. We believe that our approach is scalable and can be replicated in diverse geographical settings. While examples of regional interaction frameworks exist in the literature, these often do not include a systematic assessment of possible natural hazards and interactions for a defined spatial extent.
By integrating diverse evidence types, we have developed an approach that constrains relevant interactions between a comprehensive selection of natural hazards, simplifying a broad array of complex information to facilitate an effective analysis by those working on reducing and managing the risk from natural hazards within both policy and practitioner sectors. We believe that our approach can support the scientific community in constructing more evidenced and detailed profiles of relevant interactions for diverse user groups, identifying and exploring multi-hazard interaction scenarios and how they may result in changes to exposure and vulnerability (potentially exacerbating risk), and extracting locally specific research and innovation gaps.
Underlying data used in this research are laid out in Sect. 2, with further information in the Supplement. This includes existing published literature, civil protection bulletins, field observations, stakeholder interviews, and focus groups.
The supplement related to this article is available online at:
JCG and BDM designed and conducted research, including in-depth discussions with EMB and AGN during data collection. All co-authors analysed results and their implications to disaster risk reduction in the region. JCG wrote the paper, with major contributions from BDM and further input from all co-authors.
Joel C. Gill, Edy Manolo Barillas, and Alex Guerra Noriega declare that they have no conflict of interest. Bruce D. Malamud is a member of the editorial board of the journal.
We are grateful to staff at INSIVUMEH, CONRED, and Universidad de San Carlos de Guatemala for their engagement with our work. We are particularly thankful to Gustavo Chigna (INSIVUMEH) for his sustained advice and support in the field while in Guatemala. We thank Roxana Ciurean, Christian Huggel, and Kirsten v. Elverfeldt for their constructive reviews. This article is published with the permission of the Executive Director, British Geological Survey (UKRI).
The lead author initiated this work, while a PhD candidate in the Department of Geography, King's College London, with funding from a NERC/ESRC studentship (grant no. NE/J500306/1). Subsequent engagement in Guatemala was funded by the British Geological Survey Innovation Flexible Fund and supported by BGS NC-ODA (grant no. NE/R000069/1): Geoscience for Sustainable Futures.
This paper was edited by Sven Fuchs and reviewed by Kirsten v. Elverfeldt and Christian Huggel.