the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Scenario-based multi-risk assessment from existing single-hazard vulnerability models. An application to consecutive earthquakes and tsunamis in Lima, Peru
Juan Camilo Gómez Zapata
Massimiliano Pittore
Nils Brinckmann
Juan Lizarazo-Marriaga
Sergio Medina
Nicola Tarque
Fabrice Cotton
Abstract. Multi-hazard risk assessments for building portfolios exposed to earthquake shaking followed by a tsunami are usually based on empirical vulnerability models calibrated on post-event surveys of damaged buildings. The applicability of these models cannot easily be extrapolated to other regions of larger/smaller events. Moreover, the quantitative evaluation of the damages related to each of the hazards type (disaggregation) is impossible. To investigate cumulative damage on extended building portfolios, this study proposes an alternative and modular method to probabilistically integrate sets of single-hazard vulnerability models that are being constantly developed and calibrated by experts from various research fields to be used within a multi-risk context. This method is based on the proposal of state-dependent fragility functions for the triggered hazard to account for the pre-existing damage, and the harmonisation of building classes and damage states through their taxonomic characterization, which is transversal to any hazard-dependent vulnerability. This modular assemblage also allows us to separate the economic losses expected for each scenario on building portfolios subjected to cascading hazards. We demonstrate its application by assessing the economic losses expected for the residential building stock of Lima, Peru, a megacity commonly exposed to consecutive earthquake and tsunami scenarios. We show the importance of accounting for damage accumulation on extended building portfolios while observing a dependency between the earthquake magnitude and the losses derived for each hazard scenario. For the commonly exposed residential building stock of Lima exposed to both perils, we find that classical tsunami empirical fragility functions lead to an underestimation of predicted losses for lower magnitudes (Mw) and large overestimations for larger Mw events in comparison to our state-dependent models and cumulative damage method.
Juan Camilo Gómez Zapata et al.
Status: final response (author comments only)
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RC1: 'Comment on nhess-2022-183', Anonymous Referee #1, 18 Aug 2022
The paper properly describes the topic declared by the authors. The different parts of the proposed method are presented in a detailed way, with a rich literature reference. The topic of the paper affords a challenge in the field of multirisk loss assessment, so, the comments presented in the discussion (limits and positive aspects) are agreeable.
In addition:
- A re-reading of the paper is suggested to correct some typing errors and just some language errors;
- In the last paragraphs check the use of the numbered list, to extend it to the final sentences;
- A check of the conclusion and discussion paragraph is suggested to avoid some repetitions.
Citation: https://doi.org/10.5194/nhess-2022-183-RC1 - AC1: 'Reply on RC1', Juan Camilo Gomez, 30 Nov 2022
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RC2: 'Comment on nhess-2022-183', Anonymous Referee #2, 09 Sep 2022
A. General comments
The manuscript investigates a novel method for accounting for damage accumulation on large building portfolios exposed to sequential earthquake and tsunami hazards. This work is of great interest to the readers of NHESS. The paper is well-structured and clear, despite very minor typos. However, some contents of the current manuscript need to be clarified and a few sections to be improved before the paper can be considered for publication.
A.1 Lines 100-103. The purpose of this study is stated in these three sentences. The aim is relatively clear, however it remains unclear how the state-dependent fragility models are obtained. This is one of the critical parts of this methodology and should be briefly explained at this stage, as this would help the readers.
A.2 Lines 125-130. Regarding the integration of a set of modular components, the authors should provide a clearer definition of “inter-scheme compatibilities” and “their related compatibility levels between inter-scheme damage states”. I recognise that these concepts are described in more detail in the following sections, but this paragraph is quite difficult to read. It is not clear what these “conversions” are and how they make it possible for a cumulative assessment of the damage.
A.3 Lines 160-177. The AeDES forms have been consistently used for post-earthquake damage assessment. The authors state that these can also be used for tsunami: why? Also, did the expert elicitation help to adapt these forms to tsunami damage?
A.4 Lines 178-185. What are the details of the expert elicitation? Who took part in this exercise? Did the expert elicitation involve experts in earthquake and tsunami engineering? What are Scheme A and Scheme B? Are A and B earthquake and tsunami, respectively? It is quite confusing.
A.5 Lines 203-227. State-dependent fragility functions are developed for accounting for the cumulative damage. It is not clear the fragility function for a building type damaged by the earthquake and then by the tsunami is obtained. What are the scaling factors? How are these calculated, based on what ad-hoc calibration? The authors should clarify this key element, which remains quite obscure in the application as well.
A.5 Lines 275-300. If the case-study area is by definition constrained by the presence of both perils, why do the authors present the SARA buildings data for the whole city?
A.6 Figure 11. I would present a similar work-flow for the general methodology earlier in the manuscript.
B. Specific comments
B.1 Line 34: Indian Ocean Tsunami
B.2 Line 83: consider also Petrone et al. (2017) as a relevant study on tsunami analytical fragility functions for a single building.
B.3 Line 96: “to” repeated twice.
B.4 Line 111: “scenario” instead of “scenarios”
B.5 Line 114. Please clarify the meaning of “vulnerability modes”
B.6 Line 127. The authors refer to the “purple part” and then “red part” and so on – however the use of colors might be challenging if the paper is printed using greyscale. I would suggest to use a different way to identify the different components in Figure 1b.
B.7 Line 645. Amend typo “an\”
Citation: https://doi.org/10.5194/nhess-2022-183-RC2 - AC2: 'Reply on RC2', Juan Camilo Gomez, 30 Nov 2022
Juan Camilo Gómez Zapata et al.
Juan Camilo Gómez Zapata et al.
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