the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Sep 2024
Impact Webs: A novel conceptual modelling approach for characterising and assessing complex risks
Abstract. Identifying, characterising and assessing the complex nature of risks is vital to realise the expected outcome of the Sendai Framework for Disaster Risk Reduction. Over the past two decades, the conceptualization of risk has evolved from a hazard-centric perspective to one that integrates dynamic interactions between hazards, exposure, systems vulnerabilities and response risks. This calls for a need to develop tools and methodologies that can account for such complexity in risk assessments. However, existing risk assessment approaches are hitting limits to tackle such complexity. To this aim, we developed a novel complex risk assessment methodology named ‘Impact Webs’, inspired by a conceptual risk modelling approach named Climate Impact Chains that integrates aspects of various other conceptual models used in risk assessments such as Causal Loop Diagrams and Fuzzy Cognitive Mapping. Impact Webs are developed in a participatory manner with stakeholders and characterise and map interconnections between risks, their underlying hazards, risk drivers, root causes, responses to risks, as well as direct and cascading impacts across multiple systems and at various scales. In this methodological paper, we show how we developed the Impact Web methodology, including which elements we use to populate the model and steps we followed for construction. As proof of concept, we present the results of a complex risk assessments in Guayaquil, Ecuador, which investigated how COVID-19, concurrent hazards and responses propagate risks and impacts across sectors and systems during the pandemic. Reflecting on the utility of Impact Webs, application in case studies demonstrates the methodologies usefulness for understanding complex cause-effect relationships and informing decision-making across different scales. The participatory process of developing Impact Webs promotes stakeholder engagement, uncovers critical elements at risk and trade-offs in decision making, helping to evaluate both positive and negative outcomes of disaster risk management practices.
- Preprint
(1008 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2024-2844', Franziska Stefanie Hanf, 20 Oct 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2844/egusphere-2024-2844-RC1-supplement.pdf
-
RC2: 'Comment on egusphere-2024-2844', Anonymous Referee #2, 21 Oct 2024
In the manuscript "Impact Webs: A novel conceptual modelling approach for characterising and assessing complex risks", the authors make use of expert judgment and non-systematic literature review to build on lessons from different approaches to come up with a new conceptual modelling approach for systemic risk characterization. It is a relevant topic, however the contextualization and purpose of the paper are not clearly supported. I would thus recommend major revisions as outlined in the following.
The structure of the manuscript is very unclear. It is unclear what is result, what is method, and most often, how certain conclusions were drawn. The authors should revisit their structure and narrative for this paper. It is not clear to me, what this paper offers to its readers. Is it the pure idea of impact webs (as an advancement of impact chains), is it the visualization, is it the guidance to build impact chains? In its current form, the authors seem to do everything a bit, but nothing sufficiently in depth. Re-structuring and clarifying the objective of this paper. Just outlining the process of developing the web (as mentioned in the introduction), seems to fail answering a specific research question.
What is Impact Webs? It would be very valuable if authors could clarify what they mean when they refer to impact webs as a conceptual modelling approach. Part of what the authors present seems to be tools (how to visualize), some analysis guidance (see Figure 2). Overarchingly, it would be beneficial, if the authors could make it more explicit, what the purpose of impact webs is. They refer to Bayesian Belief Networks and other modelling methodlogies, include participatory elements which are then refined/complemented through desk studies. Are impact webs meant to be complete and/or correct? Used by who?
Method section: This paper seems to heavily rely on expert judgment - which makes it very difficult to reproduce and to offer evidence regarding the claims offered here. One key question I had when reading this section was why the authors limited their search for inspiration to the field of single-hazard risk assessment instead of learning from fields that address similar or different complex systems (e.g. integrated water management, agent based modelling, system dynamics research community). If I understand correctly, the authors propose this method based on iterations/refinements in 5 case studies. At least a short introduction of these cases would already offer insight regarding the complex risk context/dynamics Impact Webs has been developed upon I would recommend taking inspiration from studies that have developed methodological approaches or investigated how such approaches have been developed (e.g. McMeekin, 2020) to extend the method section and add an additional section covering the approach development process.
Regarding the Impact web development process: Table 1 looks like something that would be worth for the Appendix or could be used in a shortened version to support a discussion of the different methods in the context of complex risk elements to be addressed with Impact Webs (section 3.1?). It would also be interesting to learn, why authors refer to storyline approaches as one of the steps in the impact web development process but did not consider them in Table 1 for inspiration. Section 3.1 seems a mix of presenting the complex risk elements of interest and mentioning what elements from which approach were used to visualize. I would suggest to separate these two purposes and rather provide more justification regarding the choices regarding the visual elements, e.g. by referring visualization research that justifies the choices. I also want to point out that terminology in Figure 1 is inconsistent (and not referred to in the paper). 'driver of risk', 'hazard', 'vulnerability' are all concepts that overlap (at least partially) and thus do not offer clear guidance what visualization element should be used.
The development steps (section 3.2) is unclear whether they are an outcome of the paper or the method to derive it. It is presented as a method (with limited justification why it is done that way), but lack insights/guidance into how the complexity of systemic risk (and the corresponding visualization) can be managed.
McMeekin, N., Wu, O., Germeni, E., and Briggs, A. (2020). How methodological frameworks are being developed: evidence from a scoping review. BMC Med. Res. Methodol. 20, 173. https://doi.org/10.1186/s12874-020-01061-4
Citation: https://doi.org/10.5194/egusphere-2024-2844-RC2 -
CC1: 'Comment on egusphere-2024-2844', Iuliana Armas, 27 Oct 2024
This paper is part of the ongoing efforts to design new operational and conceptual models that more effectively track risk propagation when multiple co-occurring or cascading hazards are involved. As researchers actively engaged in this field, we are glad to see more models emerging, and we are committed to contributing with insights that may help polish models such as Impact Webs.
Accordingly, we commend the authors on their work and highlight several key points to address during this review:
Use of concepts from the existing literature without definition or attribution to original models
Impact Webs include "risks, their underlying hazards, risk drivers, root causes, responses to risks, as well as direct and cascading impacts" (lines 22-23). Although these components are briefly described in section 3.1., they are not clearly defined (e.g., hazard, shock, impacts, risk drivers, root causes). Moreover, the models that introduced these concepts are overlooked – for instance, the root causes that come from the PAR and Access models (Blaikie et al., 1994; Wisner et al., 2004), which are not explicitly mentioned in the paper. Also, the rationale for choosing these specific components for inclusion in Impact Webs and why they do not adhere to more intuitive component names (such as the ones of Impact Chains) are not discussed.
Overlooking the use of Impact Chains to analyze multi-risk
The manuscript presents only the preliminary applications of Impact Chains, omitting recent advances and uses. In its current form, the paper fails to bring the reader up to date in terms of the ways Impact Chains (as inspiration for Impact Webs) are currently employed in the literature. Prominent research projects in the field of DRR, such as Paratus, use Impact Chains to assess systemic multi-sectoral and multi-hazard risk using a wide range of scenarios (Cocuccioni et al., 2024; Hurliman et al., 2024).
Failure to address the similarities between Impact Webs and recent conceptual models (i.e., Enhanced Impact Chains)
The authors acknowledge that their literature review on conceptual risk models is incomplete (line 123). Nevertheless, this literature review omits the model with the highest similarity to Impact Webs: the Enhanced Impact Chains (hereafter EICs) developed by Albulescu and Armaș (2024) and published in this very same Special Issue of NHESS. This shortcoming is understandable, given that this conceptual model was published only a month before this manuscript's submission.
In light of the following arguments, we believe that the authors should 1) include EICs in the literature review on the models used for inspiration and 2) address the novelty of Impact Webs by comparing them to EICs:
- The models share the purpose of analyzing the interactions between risk elements. The difference is that EICs look at this problem through the lens of vulnerability dynamics, whereas Impact Webs adopt a broader approach. In essence, both serve as co-development tools that account for the complexity of risk assessment, standing out in terms of their capacity to organize a diverse and consistent volume of information, visualize it, and, based on it, evaluate the strengths and weaknesses of disaster risk management across multiple systems, sectors, and at various scales.
- Both models include similar elements under different terminologies. For example, the vulnerabilities in EICs are the risk drivers and root causes in Impact Webs, the adaptation options in EICs are the responses to risk, while impacts and hazards are the same in both models.
- Both models zoom in on cause-and-effect relationships while employing feedback loops to illustrate dynamic interactions among risk elements. In this particular case, EICs introduce named and clearly defined connections between the elements (including positive feedback loops), while Impact Webs do not name or describe the types of connections established among the elements. We recommend addressing this ambiguity on the types of connections included in the model.
- Both models are applied in case studies involving multi-hazards represented by the COVID-19 pandemic and co-occurring natural hazards. The results from the two case studies should be compared in the Discussion section, as these are the only two multi-hazard case studies (including the COVID-19 pandemic) that employ conceptual models focused on the dynamics of risk elements.
- Both models integrate stakeholder perspectives. In our paper on EICs, the level of stakeholder input is limited, but the model can be fully developed based on these perspectives (as the paper explicitly states).
- Both models adopt a cross-sectoral approach, demonstrating high flexibility and allowing for the cross-comparison of results across different geographic and socio-cultural settings.
Ambiguous terminology
"Response to risk" is a term marked by ambiguity. Risks arise as the convergence of hazard, exposure, and vulnerability, and to respond to them would mean addressing all three components. However, disaster risk management typically focuses on mitigating the vulnerability and impacts of the hazard—not the hazard itself. Therefore, we recommend changing the term to one that avoids confusion.
Citation: https://doi.org/10.5194/egusphere-2024-2844-CC1
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 178 | 44 | 162 | 384 | 2 | 5 |
- HTML: 178
- PDF: 44
- XML: 162
- Total: 384
- BibTeX: 2
- EndNote: 5
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1