{"title":"Comparison of national and local building inventories for damage and loss modeling of seismic and tsunami hazards: From parcel-to city-scale","authors":"Dylan Sanderson, Daniel Cox","doi":"10.1016/j.ijdrr.2023.103755","DOIUrl":null,"url":null,"abstract":"<div><p><span><span>In this paper, we compare the National Structure Inventory, a recently released building inventory for the United States, with a local tax assessor building inventory for use in damage and loss modeling of seismic-tsunami hazards. The city of Seaside, Oregon located in the North American Pacific Northwest and subject to seismic-tsunami hazards from the Cascadia </span>Subduction Zone is used as a testbed. Input attributes – such as spatial footprint, year built, structure type, and number of stories – are compared at the parcel, block, block group, and tract levels. The input attributes show large differences at the parcel level and compare favorably when aggregated at increased spatial scales. The National Structure Inventory consistently underestimates structure value and number of stories compared to the tax assessor data. Expected damages across 7 mean </span>recurrence intervals<span>, from 100-yr to 10,000-yr, are computed using IN-CORE, an open-source community resilience model. Expected damage to the National Structure Inventory tends to be slightly larger than that of the tax assessor data and errors are reduced when aggregated at increased spatial scales. The National Structure Inventory underpredicts total economic losses and risks compared to the tax assessor data, particularly for recurrence intervals associated with high economic risks. A variance-based sensitivity analysis is performed to identify how uncertainties in the input attributes propagate to uncertainties in expected damage. Structure type, design-level, and building location all influence expected damages for seismic-tsunami hazards, highlighting the importance of accurate building inventories in multi-hazard damage and loss modeling.</span></p></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"93 ","pages":"Article 103755"},"PeriodicalIF":4.2000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of disaster risk reduction","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212420923002352","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, we compare the National Structure Inventory, a recently released building inventory for the United States, with a local tax assessor building inventory for use in damage and loss modeling of seismic-tsunami hazards. The city of Seaside, Oregon located in the North American Pacific Northwest and subject to seismic-tsunami hazards from the Cascadia Subduction Zone is used as a testbed. Input attributes – such as spatial footprint, year built, structure type, and number of stories – are compared at the parcel, block, block group, and tract levels. The input attributes show large differences at the parcel level and compare favorably when aggregated at increased spatial scales. The National Structure Inventory consistently underestimates structure value and number of stories compared to the tax assessor data. Expected damages across 7 mean recurrence intervals, from 100-yr to 10,000-yr, are computed using IN-CORE, an open-source community resilience model. Expected damage to the National Structure Inventory tends to be slightly larger than that of the tax assessor data and errors are reduced when aggregated at increased spatial scales. The National Structure Inventory underpredicts total economic losses and risks compared to the tax assessor data, particularly for recurrence intervals associated with high economic risks. A variance-based sensitivity analysis is performed to identify how uncertainties in the input attributes propagate to uncertainties in expected damage. Structure type, design-level, and building location all influence expected damages for seismic-tsunami hazards, highlighting the importance of accurate building inventories in multi-hazard damage and loss modeling.
期刊介绍:
The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international.
Key topics:-
-multifaceted disaster and cascading disasters
-the development of disaster risk reduction strategies and techniques
-discussion and development of effective warning and educational systems for risk management at all levels
-disasters associated with climate change
-vulnerability analysis and vulnerability trends
-emerging risks
-resilience against disasters.
The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.