Abstract
This study presents a new method, the MYRIAD-Hazard Event Sets Algorithm (MYRIAD-HESA), that compiles historically-based multi-hazard event sets. MYRIAD-HESA is a fully open-access method that can create multi-hazard event sets from any hazard events that occur on varying time, space, and intensity scales. In the past, multi-hazards have predominately been studied on a local or continental scale, or have been limited to specific hazard combinations, such as the combination between droughts and heatwaves. Therefore, we exemplify our approach by compiling a global multi-hazard event set database, spanning from 2004 to 2017, which includes eleven hazards from varying hazard classes (e.g. meteorological, geophysical, hydrological and climatological). This global database provides new scientific insights on the frequency of different multi-hazard events and their hotspots. Additionally, we explicitly incorporate a temporal dimension in MYRIAD-HESA, the time-lag. The time-lag, or time between the occurrence of hazards, is used to determine potentially impactful events that occurred in close succession. Varying time-lags have been tested in MYRIAD-HESA, and are analysed using North America as a case study. Alongside the MYRIAD-HESA, the multi-hazard event sets, MYRIAD-HES, is openly available to further increase the understanding of multi-hazard events in the disaster risk community. The open-source nature of MYRIAD-HESA provides flexibility to conduct multi-risk assessments by, for example, incorporating higher resolution data for an area of interest.
Original language | English |
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Article number | 13808 |
Pages (from-to) | 1-14 |
Number of pages | 14 |
Journal | Scientific Reports |
Volume | 13 |
DOIs | |
Publication status | Published - 23 Aug 2023 |
Bibliographical note
Funding Information:This research is carried out in the MYRIAD-EU project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 101003276). The work reflects only the author’s view and that the agency is not responsible for any use that may be made of the information it contains. E.E.K., P.J.W. and M.C.R. were additionally funded by the e European Union’s Horizon 2020 MIRACA project; Grant Agreement No. 101093854. This work used the Dutch national e-infrastructure with the support of the SURF Cooperative using Grant No. EINF-4493.
Publisher Copyright:
© 2023, Springer Nature Limited.
Funding
This research is carried out in the MYRIAD-EU project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 101003276). The work reflects only the author’s view and that the agency is not responsible for any use that may be made of the information it contains. E.E.K., P.J.W. and M.C.R. were additionally funded by the e European Union’s Horizon 2020 MIRACA project; Grant Agreement No. 101093854. This work used the Dutch national e-infrastructure with the support of the SURF Cooperative using Grant No. EINF-4493.
Funders | Funder number |
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SURF | EINF-4493 |
Horizon 2020 Framework Programme | 101003276, 101093854 |
Horizon 2020 Framework Programme |