Future property damage from flooding: sensitivities to economy and climate change View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-08-09

AUTHORS

Jing Liu, Thomas W. Hertel, Noah S. Diffenbaugh, Michael S. Delgado, Moetasim Ashfaq

ABSTRACT

Recent trends in the frequency and intensity of extreme weather events have raised the concern that climate change could increase flooding risks and property damage. However, a major challenge in attributing and projecting changes in disaster risk is that damage is influenced not only by the physical climate hazard, but also by non-climatic factors that shape exposure and vulnerability. Recent assessments of integrated disaster risk have been hampered by the paucity of literature analyzing local-scale interactions between hazard, exposure and vulnerability in the historical record. Here we develop an integrated empirical analysis of historical flood damage that emphasizes spatial and temporal heterogeneity in flood hazard, economic exposure and social vulnerability. Using the Midwestern United States as a testbed, we show that annual property damage from flooding is projected to increase by 13 to 17.4 % over the next two decades. At the state level, over half of the increase is driven by projected growth in housing units. However, at the county level, the dominant factor causing future damage varies, emphasizing the value of a fully integrated, spatially and temporally resolved approach to assessing flooding risk and control strategies. More... »

PAGES

741-749

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10584-015-1478-z

DOI

http://dx.doi.org/10.1007/s10584-015-1478-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1047353086


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Earth Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0406", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Geography and Environmental Geoscience", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Agricultural Economics, Purdue University, 403 W State St., 47907-2056, West Lafayette, IN, USA", 
          "id": "http://www.grid.ac/institutes/grid.169077.e", 
          "name": [
            "Department of Agricultural Economics, Purdue University, 403 W State St., 47907-2056, West Lafayette, IN, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Jing", 
        "id": "sg:person.016032426012.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016032426012.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Agricultural Economics, Purdue University, 403 W State St., 47907-2056, West Lafayette, IN, USA", 
          "id": "http://www.grid.ac/institutes/grid.169077.e", 
          "name": [
            "Department of Agricultural Economics, Purdue University, 403 W State St., 47907-2056, West Lafayette, IN, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hertel", 
        "givenName": "Thomas W.", 
        "id": "sg:person.0707345000.21", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0707345000.21"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Earth System Science and Woods Institute for the Environment, Stanford University, Stanford, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.168010.e", 
          "name": [
            "Department of Earth System Science and Woods Institute for the Environment, Stanford University, Stanford, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Diffenbaugh", 
        "givenName": "Noah S.", 
        "id": "sg:person.07755742371.03", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07755742371.03"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Agricultural Economics, Purdue University, 403 W State St., 47907-2056, West Lafayette, IN, USA", 
          "id": "http://www.grid.ac/institutes/grid.169077.e", 
          "name": [
            "Department of Agricultural Economics, Purdue University, 403 W State St., 47907-2056, West Lafayette, IN, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Delgado", 
        "givenName": "Michael S.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Oak Ridge National Laboratory, Oak Ridge, TN, USA", 
          "id": "http://www.grid.ac/institutes/grid.135519.a", 
          "name": [
            "Oak Ridge National Laboratory, Oak Ridge, TN, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ashfaq", 
        "givenName": "Moetasim", 
        "id": "sg:person.07601543175.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07601543175.18"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/nclimate2516", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014640119", 
          "https://doi.org/10.1038/nclimate2516"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nclimate1961", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031236037", 
          "https://doi.org/10.1038/nclimate1961"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ngeo779", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007726005", 
          "https://doi.org/10.1038/ngeo779"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nclimate1357", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038725935", 
          "https://doi.org/10.1038/nclimate1357"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10584-014-1141-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030747668", 
          "https://doi.org/10.1007/s10584-014-1141-0"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2015-08-09", 
    "datePublishedReg": "2015-08-09", 
    "description": "Recent trends in the frequency and intensity of extreme weather events have raised the concern that climate change could increase flooding risks and property damage. However, a major challenge in attributing and projecting changes in disaster risk is that damage is influenced not only by the physical climate hazard, but also by non-climatic factors that shape exposure and vulnerability. Recent assessments of integrated disaster risk have been hampered by the paucity of literature analyzing local-scale interactions between hazard, exposure and vulnerability in the historical record. Here we develop an integrated empirical analysis of historical flood damage that emphasizes spatial and temporal heterogeneity in flood hazard, economic exposure and social vulnerability. Using the Midwestern United States as a testbed, we show that annual property damage from flooding is projected to increase by 13 to 17.4\u00a0% over the next two decades. At the state level, over half of the increase is driven by projected growth in housing units. However, at the county level, the dominant factor causing future damage varies, emphasizing the value of a fully integrated, spatially and temporally resolved approach to assessing flooding risk and control strategies.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s10584-015-1478-z", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1028211", 
        "issn": [
          "0165-0009", 
          "1573-1480"
        ], 
        "name": "Climatic Change", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "132"
      }
    ], 
    "keywords": [
      "property damage", 
      "historical flood damage", 
      "control strategy", 
      "flood hazard", 
      "flood damage", 
      "flooding risk", 
      "dominant factor", 
      "major challenge", 
      "flooding", 
      "damage", 
      "testbed", 
      "hazards", 
      "extreme weather events", 
      "local-scale interactions", 
      "weather events", 
      "recent trends", 
      "frequency", 
      "climate change", 
      "damage varies", 
      "housing units", 
      "non-climatic factors", 
      "values", 
      "increase", 
      "units", 
      "intensity", 
      "approach", 
      "disaster risk", 
      "physical climate", 
      "changes", 
      "sensitivity", 
      "temporal heterogeneity", 
      "historical records", 
      "analysis", 
      "challenges", 
      "varies", 
      "Midwestern United States", 
      "factors", 
      "growth", 
      "strategies", 
      "interaction", 
      "state", 
      "trends", 
      "recent assessment", 
      "assessment", 
      "climate", 
      "levels", 
      "concern", 
      "vulnerability", 
      "decades", 
      "exposure", 
      "literature", 
      "records", 
      "social vulnerability", 
      "economy", 
      "events", 
      "heterogeneity", 
      "United States", 
      "economic exposure", 
      "half", 
      "risk", 
      "paucity", 
      "county level", 
      "state level", 
      "empirical analysis", 
      "paucity of literature", 
      "shape exposure"
    ], 
    "name": "Future property damage from flooding: sensitivities to economy and climate change", 
    "pagination": "741-749", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1047353086"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10584-015-1478-z"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10584-015-1478-z", 
      "https://app.dimensions.ai/details/publication/pub.1047353086"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-12-01T06:32", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221201/entities/gbq_results/article/article_649.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s10584-015-1478-z"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10584-015-1478-z'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10584-015-1478-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10584-015-1478-z'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10584-015-1478-z'


 

This table displays all metadata directly associated to this object as RDF triples.

176 TRIPLES      21 PREDICATES      95 URIs      82 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10584-015-1478-z schema:about anzsrc-for:04
2 anzsrc-for:0406
3 schema:author N59487a192453445fbc25ef0037dea58d
4 schema:citation sg:pub.10.1007/s10584-014-1141-0
5 sg:pub.10.1038/nclimate1357
6 sg:pub.10.1038/nclimate1961
7 sg:pub.10.1038/nclimate2516
8 sg:pub.10.1038/ngeo779
9 schema:datePublished 2015-08-09
10 schema:datePublishedReg 2015-08-09
11 schema:description Recent trends in the frequency and intensity of extreme weather events have raised the concern that climate change could increase flooding risks and property damage. However, a major challenge in attributing and projecting changes in disaster risk is that damage is influenced not only by the physical climate hazard, but also by non-climatic factors that shape exposure and vulnerability. Recent assessments of integrated disaster risk have been hampered by the paucity of literature analyzing local-scale interactions between hazard, exposure and vulnerability in the historical record. Here we develop an integrated empirical analysis of historical flood damage that emphasizes spatial and temporal heterogeneity in flood hazard, economic exposure and social vulnerability. Using the Midwestern United States as a testbed, we show that annual property damage from flooding is projected to increase by 13 to 17.4 % over the next two decades. At the state level, over half of the increase is driven by projected growth in housing units. However, at the county level, the dominant factor causing future damage varies, emphasizing the value of a fully integrated, spatially and temporally resolved approach to assessing flooding risk and control strategies.
12 schema:genre article
13 schema:isAccessibleForFree true
14 schema:isPartOf N7e2f6f51e58c4739a00519fbf4aa779a
15 Nc4392234fada431181d6136cc840a425
16 sg:journal.1028211
17 schema:keywords Midwestern United States
18 United States
19 analysis
20 approach
21 assessment
22 challenges
23 changes
24 climate
25 climate change
26 concern
27 control strategy
28 county level
29 damage
30 damage varies
31 decades
32 disaster risk
33 dominant factor
34 economic exposure
35 economy
36 empirical analysis
37 events
38 exposure
39 extreme weather events
40 factors
41 flood damage
42 flood hazard
43 flooding
44 flooding risk
45 frequency
46 growth
47 half
48 hazards
49 heterogeneity
50 historical flood damage
51 historical records
52 housing units
53 increase
54 intensity
55 interaction
56 levels
57 literature
58 local-scale interactions
59 major challenge
60 non-climatic factors
61 paucity
62 paucity of literature
63 physical climate
64 property damage
65 recent assessment
66 recent trends
67 records
68 risk
69 sensitivity
70 shape exposure
71 social vulnerability
72 state
73 state level
74 strategies
75 temporal heterogeneity
76 testbed
77 trends
78 units
79 values
80 varies
81 vulnerability
82 weather events
83 schema:name Future property damage from flooding: sensitivities to economy and climate change
84 schema:pagination 741-749
85 schema:productId N3209f22fc0d249b8a5617ea11fe88e4e
86 N72993fd7d3734db897cf1322882708ac
87 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047353086
88 https://doi.org/10.1007/s10584-015-1478-z
89 schema:sdDatePublished 2022-12-01T06:32
90 schema:sdLicense https://scigraph.springernature.com/explorer/license/
91 schema:sdPublisher N3b8f342623654f3ca7ff6cc7af7b6ac1
92 schema:url https://doi.org/10.1007/s10584-015-1478-z
93 sgo:license sg:explorer/license/
94 sgo:sdDataset articles
95 rdf:type schema:ScholarlyArticle
96 N2d77fa9dab934c43a73289049f279b1f rdf:first sg:person.07755742371.03
97 rdf:rest N989772539d0b4f8fb760728068158144
98 N3209f22fc0d249b8a5617ea11fe88e4e schema:name doi
99 schema:value 10.1007/s10584-015-1478-z
100 rdf:type schema:PropertyValue
101 N3b8f342623654f3ca7ff6cc7af7b6ac1 schema:name Springer Nature - SN SciGraph project
102 rdf:type schema:Organization
103 N53a8a0ea41e2405cac6baf9b997f978e rdf:first sg:person.07601543175.18
104 rdf:rest rdf:nil
105 N59487a192453445fbc25ef0037dea58d rdf:first sg:person.016032426012.45
106 rdf:rest N6b3e83d6d58c4fb68aa417344e36adbd
107 N6b3e83d6d58c4fb68aa417344e36adbd rdf:first sg:person.0707345000.21
108 rdf:rest N2d77fa9dab934c43a73289049f279b1f
109 N72993fd7d3734db897cf1322882708ac schema:name dimensions_id
110 schema:value pub.1047353086
111 rdf:type schema:PropertyValue
112 N7e2f6f51e58c4739a00519fbf4aa779a schema:volumeNumber 132
113 rdf:type schema:PublicationVolume
114 N989772539d0b4f8fb760728068158144 rdf:first N9a9dbac217d446f2bff16bd3ea8ba188
115 rdf:rest N53a8a0ea41e2405cac6baf9b997f978e
116 N9a9dbac217d446f2bff16bd3ea8ba188 schema:affiliation grid-institutes:grid.169077.e
117 schema:familyName Delgado
118 schema:givenName Michael S.
119 rdf:type schema:Person
120 Nc4392234fada431181d6136cc840a425 schema:issueNumber 4
121 rdf:type schema:PublicationIssue
122 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
123 schema:name Earth Sciences
124 rdf:type schema:DefinedTerm
125 anzsrc-for:0406 schema:inDefinedTermSet anzsrc-for:
126 schema:name Physical Geography and Environmental Geoscience
127 rdf:type schema:DefinedTerm
128 sg:journal.1028211 schema:issn 0165-0009
129 1573-1480
130 schema:name Climatic Change
131 schema:publisher Springer Nature
132 rdf:type schema:Periodical
133 sg:person.016032426012.45 schema:affiliation grid-institutes:grid.169077.e
134 schema:familyName Liu
135 schema:givenName Jing
136 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016032426012.45
137 rdf:type schema:Person
138 sg:person.0707345000.21 schema:affiliation grid-institutes:grid.169077.e
139 schema:familyName Hertel
140 schema:givenName Thomas W.
141 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0707345000.21
142 rdf:type schema:Person
143 sg:person.07601543175.18 schema:affiliation grid-institutes:grid.135519.a
144 schema:familyName Ashfaq
145 schema:givenName Moetasim
146 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07601543175.18
147 rdf:type schema:Person
148 sg:person.07755742371.03 schema:affiliation grid-institutes:grid.168010.e
149 schema:familyName Diffenbaugh
150 schema:givenName Noah S.
151 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07755742371.03
152 rdf:type schema:Person
153 sg:pub.10.1007/s10584-014-1141-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030747668
154 https://doi.org/10.1007/s10584-014-1141-0
155 rdf:type schema:CreativeWork
156 sg:pub.10.1038/nclimate1357 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038725935
157 https://doi.org/10.1038/nclimate1357
158 rdf:type schema:CreativeWork
159 sg:pub.10.1038/nclimate1961 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031236037
160 https://doi.org/10.1038/nclimate1961
161 rdf:type schema:CreativeWork
162 sg:pub.10.1038/nclimate2516 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014640119
163 https://doi.org/10.1038/nclimate2516
164 rdf:type schema:CreativeWork
165 sg:pub.10.1038/ngeo779 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007726005
166 https://doi.org/10.1038/ngeo779
167 rdf:type schema:CreativeWork
168 grid-institutes:grid.135519.a schema:alternateName Oak Ridge National Laboratory, Oak Ridge, TN, USA
169 schema:name Oak Ridge National Laboratory, Oak Ridge, TN, USA
170 rdf:type schema:Organization
171 grid-institutes:grid.168010.e schema:alternateName Department of Earth System Science and Woods Institute for the Environment, Stanford University, Stanford, CA, USA
172 schema:name Department of Earth System Science and Woods Institute for the Environment, Stanford University, Stanford, CA, USA
173 rdf:type schema:Organization
174 grid-institutes:grid.169077.e schema:alternateName Department of Agricultural Economics, Purdue University, 403 W State St., 47907-2056, West Lafayette, IN, USA
175 schema:name Department of Agricultural Economics, Purdue University, 403 W State St., 47907-2056, West Lafayette, IN, USA
176 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...