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#disaster-response — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #disaster-response, aggregated by home.social.

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  1. Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from #GHSL … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #demographics #change #spatiotemporal #1975 #2024 #population #change #grid #global #LandScan #POPGRID #LSMTS #ambientpopulation #GHSL #OakRidge #ORNL #usecase #opendata #disasterresponse #humanitarianaid #environmentalanalysis #urbanplanning #humanexposure #settlementchange #city #rural #infrastructure #demand #accesstoservices #GIS #spatial #mapping #building #outline #model #modeling
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

  2. Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from #GHSL … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #demographics #change #spatiotemporal #1975 #2024 #population #change #grid #global #LandScan #POPGRID #LSMTS #ambientpopulation #GHSL #OakRidge #ORNL #usecase #opendata #disasterresponse #humanitarianaid #environmentalanalysis #urbanplanning #humanexposure #settlementchange #city #rural #infrastructure #demand #accesstoservices #GIS #spatial #mapping #building #outline #model #modeling
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

  3. Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from #GHSL … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #demographics #change #spatiotemporal #1975 #2024 #population #change #grid #global #LandScan #POPGRID #LSMTS #ambientpopulation #GHSL #OakRidge #ORNL #usecase #opendata #disasterresponse #humanitarianaid #environmentalanalysis #urbanplanning #humanexposure #settlementchange #city #rural #infrastructure #demand #accesstoservices #GIS #spatial #mapping #building #outline #model #modeling
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

  4. Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from #GHSL … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #demographics #change #spatiotemporal #1975 #2024 #population #change #grid #global #LandScan #POPGRID #LSMTS #ambientpopulation #GHSL #OakRidge #ORNL #usecase #opendata #disasterresponse #humanitarianaid #environmentalanalysis #urbanplanning #humanexposure #settlementchange #city #rural #infrastructure #demand #accesstoservices #GIS #spatial #mapping #building #outline #model #modeling
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

  5. Annual High-Resolution Global Ambient Population Estimates From 1975 To 2024
    --
    doi.org/10.31223/X5MV3R <-- shared paper
    --
    landscan.ornl.gov/ <-- shared webmap and data link (via download -> LandScan Mosaic Time Series)
    --
    gee-community-catalog.org/proj <-- shared link to GEE community catalog collection ‘LandScan Mosaic Annual Global Ambient Population Time Series’
    --
    H/T @andrew Zimmer || Geographer | Research Scientist @ Oak Ridge National Laboratory
    “LSM-TS provides annual global estimates of ambient population from 1975–2024 at ~90 m resolution, creating a spatially and temporally consistent reconstruction of population change designed for longitudinal analysis. Reconstruction of historical populations are driven by current LandScan Mosaic building-level population distributions, scaled by built-surface change from … and calibrated to annual national-level estimates from U.S. Census Bureau…”
    --
    “LandScan is a globally recognized, R&D100-winning population data platform developed at Oak Ridge National Laboratory (ORNL). Its datasets provide human population distribution estimates down to 100 meter grid resolution. LandScan supports disaster response, humanitarian aid, environmental analysis, and urban planning by providing insights into where people live and how they move…”
    --
    “Gridded population data support assessments of human exposure, settlement change, infrastructure demand, and access to services, yet global datasets combining annual coverage over multiple decades with fine spatial resolution remain limited. LandScan Mosaic Time Series provides 50 annual estimates of global ambient population distribution at 3 arc-second resolution from 1975 through 2024. The series is anchored to the 2024 LandScan Mosaic surface, produced through a building-level population modeling workflow. Historical surfaces are reconstructed using annualized changes in built surface and derived first-level administrative population trajectories. Every layer, including 2024, is normalized to administrative targets scaled to annual country totals from the U.S. Census Bureau International Database. The dataset is distributed as 50 single-band Cloud Optimized GeoTIFFs on an identical WGS84 grid, with values representing estimated persons per cell. Its common grid and methodology support fine-scale longitudinal analysis of ambient population distribution while documented validation and limitations guide appropriate reuse…”
    #1975 #2024
    @OAK Ridge National Laboratory | National Security Sciences at ORNL | @POPGRID Data Collaborative

  6. Scientists turn cockroaches into cyborg rescue medics

    University of Queensland scientists have created cyborg cockroaches, dubbed 'paraborgs,' fitted with injectors and cameras could join search-and-rescue teams to deliver lifesaving drugs to people trapped after disasters. #News #Reuters #Newsfeed #CyborgCockroaches #Paraborgs #UniversityOfQueensland #Brisbane #Australia #SearchAndRescue #BioRobotics #DisasterResponse #Cockroach #Robotics #ScienceNews #TechnologyNews

    fllics.com/en/video/scientists

  7. Scientists turn cockroaches into cyborg rescue medics

    University of Queensland scientists have created cyborg cockroaches, dubbed 'paraborgs,' fitted with injectors and cameras could join search-and-rescue teams to deliver lifesaving drugs to people trapped after disasters. #News #Reuters #Newsfeed #CyborgCockroaches #Paraborgs #UniversityOfQueensland #Brisbane #Australia #SearchAndRescue #BioRobotics #DisasterResponse #Cockroach #Robotics #ScienceNews #TechnologyNews

    fllics.com/en/video/scientists

  8. Scientists turn cockroaches into cyborg rescue medics

    University of Queensland scientists have created cyborg cockroaches, dubbed 'paraborgs,' fitted with injectors and cameras could join search-and-rescue teams to deliver lifesaving drugs to people trapped after disasters. #News #Reuters #Newsfeed #CyborgCockroaches #Paraborgs #UniversityOfQueensland #Brisbane #Australia #SearchAndRescue #BioRobotics #DisasterResponse #Cockroach #Robotics #ScienceNews #TechnologyNews

    fllics.com/en/video/scientists

  9. Scientists turn cockroaches into cyborg rescue medics

    University of Queensland scientists have created cyborg cockroaches, dubbed 'paraborgs,' fitted with injectors and cameras could join search-and-rescue teams to deliver lifesaving drugs to people trapped after disasters. #News #Reuters #Newsfeed #CyborgCockroaches #Paraborgs #UniversityOfQueensland #Brisbane #Australia #SearchAndRescue #BioRobotics #DisasterResponse #Cockroach #Robotics #ScienceNews #TechnologyNews

    fllics.com/en/video/scientists

  10. Scientists turn cockroaches into cyborg rescue medics

    University of Queensland scientists have created cyborg cockroaches, dubbed 'paraborgs,' fitted with injectors and cameras could join search-and-rescue teams to deliver lifesaving drugs to people trapped after disasters. #News #Reuters #Newsfeed #CyborgCockroaches #Paraborgs #UniversityOfQueensland #Brisbane #Australia #SearchAndRescue #BioRobotics #DisasterResponse #Cockroach #Robotics #ScienceNews #TechnologyNews

    fllics.com/en/video/scientists

  11. University of South Florida: New hurricane recovery technology being tested on Florida roads during peak season. “Working with transportation professionals across Florida, including those at the Florida Department of Transportation and Sarasota County, [Professor Hao] Zhou is developing AI tools to help transportation officials assess storm damage more efficiently, improve traffic signal […]

    https://rbfirehose.com/2026/08/27/university-of-south-florida-new-hurricane-recovery-technology-being-tested-on-florida-roads-during-peak-season/
  12. University of South Florida: New hurricane recovery technology being tested on Florida roads during peak season. “Working with transportation professionals across Florida, including those at the Florida Department of Transportation and Sarasota County, [Professor Hao] Zhou is developing AI tools to help transportation officials assess storm damage more efficiently, improve traffic signal […]

    https://rbfirehose.com/2026/08/27/university-of-south-florida-new-hurricane-recovery-technology-being-tested-on-florida-roads-during-peak-season/
  13. University of South Florida: New hurricane recovery technology being tested on Florida roads during peak season. “Working with transportation professionals across Florida, including those at the Florida Department of Transportation and Sarasota County, [Professor Hao] Zhou is developing AI tools to help transportation officials assess storm damage more efficiently, improve traffic signal […]

    https://rbfirehose.com/2026/08/27/university-of-south-florida-new-hurricane-recovery-technology-being-tested-on-florida-roads-during-peak-season/
  14. University of South Florida: New hurricane recovery technology being tested on Florida roads during peak season. “Working with transportation professionals across Florida, including those at the Florida Department of Transportation and Sarasota County, [Professor Hao] Zhou is developing AI tools to help transportation officials assess storm damage more efficiently, improve traffic signal […]

    https://rbfirehose.com/2026/08/27/university-of-south-florida-new-hurricane-recovery-technology-being-tested-on-florida-roads-during-peak-season/
  15. University of South Florida: New hurricane recovery technology being tested on Florida roads during peak season. “Working with transportation professionals across Florida, including those at the Florida Department of Transportation and Sarasota County, [Professor Hao] Zhou is developing AI tools to help transportation officials assess storm damage more efficiently, improve traffic signal […]

    https://rbfirehose.com/2026/08/27/university-of-south-florida-new-hurricane-recovery-technology-being-tested-on-florida-roads-during-peak-season/
  16. DATE: August 22, 2026 at 02:08AM
    SOURCE: SOCIALPSYCHOLOGY.ORG

    TITLE: How the United Nations is Using AI to Advance Human Rights

    URL: socialpsychology.org/client/re

    Source: United Nations News

    Across agencies, the United Nations is implementing artificial intelligence tools to help promote peace, security, and human rights. The U.N. is also using AI to detect land mines, assess disaster damage, identify suspicious financial transactions, and monitor radioactive contamination. But as technology advances, the U.N. is emphasizing equity, human rights, and ethics to ensure that AI promotes development instead of threatening peace and...

    URL: socialpsychology.org/client/re

    -------------------------------------------------

    Private, vetted email list for mental health professionals: clinicians-exchange.org

    Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

    -------------------------------------------------

    #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #UnitedNationsAI #HumanRights #AIforGood #EthicalAI #PeaceAndSecurity #DisasterResponse #AIInHumanRights #TechForDevelopment #AITransparency #DigitalEquity

  17. DATE: August 22, 2026 at 02:08AM
    SOURCE: SOCIALPSYCHOLOGY.ORG

    TITLE: How the United Nations is Using AI to Advance Human Rights

    URL: socialpsychology.org/client/re

    Source: United Nations News

    Across agencies, the United Nations is implementing artificial intelligence tools to help promote peace, security, and human rights. The U.N. is also using AI to detect land mines, assess disaster damage, identify suspicious financial transactions, and monitor radioactive contamination. But as technology advances, the U.N. is emphasizing equity, human rights, and ethics to ensure that AI promotes development instead of threatening peace and...

    URL: socialpsychology.org/client/re

    -------------------------------------------------

    Private, vetted email list for mental health professionals: clinicians-exchange.org

    Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

    -------------------------------------------------

    #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #UnitedNationsAI #HumanRights #AIforGood #EthicalAI #PeaceAndSecurity #DisasterResponse #AIInHumanRights #TechForDevelopment #AITransparency #DigitalEquity

  18. DATE: August 22, 2026 at 02:08AM
    SOURCE: SOCIALPSYCHOLOGY.ORG

    TITLE: How the United Nations is Using AI to Advance Human Rights

    URL: socialpsychology.org/client/re

    Source: United Nations News

    Across agencies, the United Nations is implementing artificial intelligence tools to help promote peace, security, and human rights. The U.N. is also using AI to detect land mines, assess disaster damage, identify suspicious financial transactions, and monitor radioactive contamination. But as technology advances, the U.N. is emphasizing equity, human rights, and ethics to ensure that AI promotes development instead of threatening peace and...

    URL: socialpsychology.org/client/re

    -------------------------------------------------

    Private, vetted email list for mental health professionals: clinicians-exchange.org

    Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

    -------------------------------------------------

    #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #UnitedNationsAI #HumanRights #AIforGood #EthicalAI #PeaceAndSecurity #DisasterResponse #AIInHumanRights #TechForDevelopment #AITransparency #DigitalEquity

  19. DATE: August 22, 2026 at 02:08AM
    SOURCE: SOCIALPSYCHOLOGY.ORG

    TITLE: How the United Nations is Using AI to Advance Human Rights

    URL: socialpsychology.org/client/re

    Source: United Nations News

    Across agencies, the United Nations is implementing artificial intelligence tools to help promote peace, security, and human rights. The U.N. is also using AI to detect land mines, assess disaster damage, identify suspicious financial transactions, and monitor radioactive contamination. But as technology advances, the U.N. is emphasizing equity, human rights, and ethics to ensure that AI promotes development instead of threatening peace and...

    URL: socialpsychology.org/client/re

    -------------------------------------------------

    Private, vetted email list for mental health professionals: clinicians-exchange.org

    Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

    -------------------------------------------------

    #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #UnitedNationsAI #HumanRights #AIforGood #EthicalAI #PeaceAndSecurity #DisasterResponse #AIInHumanRights #TechForDevelopment #AITransparency #DigitalEquity

  20. Lee Orders All-Out Response to Deadly Southern Coast Downpour

    President Lee Jae-myung delivers a commemorative address at the 81st Liberation Day ceremony held at Sejong Center for…
    #EuropeSays #Korea #KR #SouthKorea #climatechange #disasterresponse #geoje #LeeJaeMyung #PresidentLeeJae-myung #southerncoastrainfall #tongyeong #torrentialrain
    europesays.com/korea/122126/

  21. Socio-Hydrology Modeling Captures How Inequalities Impact Community Flood Resilience
    --
    doi.org/10.1029/2025WR041393 <-- shared paper
    --
    americanprogress.org/article/h <-- shared technical/opinion article
    --
    carbonbrief.org/us-flooding-in <-- shared technical/opinion article
    --
    headwaterseconomics.org/natura <-- shared technical/opinion article
    --
    youtu.be/8jVRsD8wgMM?si=qBHchW <-- shared opinion video
    --
    fedcommunities.org/lower-incom <-- shared technical/opinion article
    --
    H/T @matthew Preisser | PhD Civil Engineering, Natural Hazard Modeler and Socio-Hydrologists
    “How can we better understand the dynamic feedbacks between the environment and society?
    Socio-hydrology models are often built around the assumption that cities act as homogeneous entities, without capturing the variable capacity of communities with different underlying socioeconomic characteristics to respond to and recover from disasters.
    In this study, [the authors] developed a disaggregated approach to model community-specific adaptive capacity, allowing [them] to examine how inequalities influence flood recovery and resilience. This framework provide[d] a basis for exploring hypotheses about the relationships between growth, inequality, and community resilience in the face of flood hazards.
    [Their] results highlighted] the importance of considering community-level dynamics when developing flood mitigation and disaster response strategies that balance economic growth with equity. Many challenges remain in applying socio-hydrology models to real-world settings, but this work takes a step toward incorporating more realistic representations of socioeconomic inequality into human–water systems while preserving the generality and flexibility that make conceptual models useful…”
    #risk #hazard #water #hydrology #flood #society #flooding #USA #SocioHydrology #naturalhazard #socioeconomic #population #demographics #infrastructure #damage #disaster #disaggregated #model #modeling #community #adaptiveresponse #growth #inequality #communityresilience #floodhazard #floodmitigation #disasterresponse #equity #city #town #rural #urban #economy #cost

  22. Socio-Hydrology Modeling Captures How Inequalities Impact Community Flood Resilience
    --
    doi.org/10.1029/2025WR041393 <-- shared paper
    --
    americanprogress.org/article/h <-- shared technical/opinion article
    --
    carbonbrief.org/us-flooding-in <-- shared technical/opinion article
    --
    headwaterseconomics.org/natura <-- shared technical/opinion article
    --
    youtu.be/8jVRsD8wgMM?si=qBHchW <-- shared opinion video
    --
    fedcommunities.org/lower-incom <-- shared technical/opinion article
    --
    H/T @matthew Preisser | PhD Civil Engineering, Natural Hazard Modeler and Socio-Hydrologists
    “How can we better understand the dynamic feedbacks between the environment and society?
    Socio-hydrology models are often built around the assumption that cities act as homogeneous entities, without capturing the variable capacity of communities with different underlying socioeconomic characteristics to respond to and recover from disasters.
    In this study, [the authors] developed a disaggregated approach to model community-specific adaptive capacity, allowing [them] to examine how inequalities influence flood recovery and resilience. This framework provide[d] a basis for exploring hypotheses about the relationships between growth, inequality, and community resilience in the face of flood hazards.
    [Their] results highlighted] the importance of considering community-level dynamics when developing flood mitigation and disaster response strategies that balance economic growth with equity. Many challenges remain in applying socio-hydrology models to real-world settings, but this work takes a step toward incorporating more realistic representations of socioeconomic inequality into human–water systems while preserving the generality and flexibility that make conceptual models useful…”
    #risk #hazard #water #hydrology #flood #society #flooding #USA #SocioHydrology #naturalhazard #socioeconomic #population #demographics #infrastructure #damage #disaster #disaggregated #model #modeling #community #adaptiveresponse #growth #inequality #communityresilience #floodhazard #floodmitigation #disasterresponse #equity #city #town #rural #urban #economy #cost

  23. Socio-Hydrology Modeling Captures How Inequalities Impact Community Flood Resilience
    --
    doi.org/10.1029/2025WR041393 <-- shared paper
    --
    americanprogress.org/article/h <-- shared technical/opinion article
    --
    carbonbrief.org/us-flooding-in <-- shared technical/opinion article
    --
    headwaterseconomics.org/natura <-- shared technical/opinion article
    --
    youtu.be/8jVRsD8wgMM?si=qBHchW <-- shared opinion video
    --
    fedcommunities.org/lower-incom <-- shared technical/opinion article
    --
    H/T @matthew Preisser | PhD Civil Engineering, Natural Hazard Modeler and Socio-Hydrologists
    “How can we better understand the dynamic feedbacks between the environment and society?
    Socio-hydrology models are often built around the assumption that cities act as homogeneous entities, without capturing the variable capacity of communities with different underlying socioeconomic characteristics to respond to and recover from disasters.
    In this study, [the authors] developed a disaggregated approach to model community-specific adaptive capacity, allowing [them] to examine how inequalities influence flood recovery and resilience. This framework provide[d] a basis for exploring hypotheses about the relationships between growth, inequality, and community resilience in the face of flood hazards.
    [Their] results highlighted] the importance of considering community-level dynamics when developing flood mitigation and disaster response strategies that balance economic growth with equity. Many challenges remain in applying socio-hydrology models to real-world settings, but this work takes a step toward incorporating more realistic representations of socioeconomic inequality into human–water systems while preserving the generality and flexibility that make conceptual models useful…”
    #risk #hazard #water #hydrology #flood #society #flooding #USA #SocioHydrology #naturalhazard #socioeconomic #population #demographics #infrastructure #damage #disaster #disaggregated #model #modeling #community #adaptiveresponse #growth #inequality #communityresilience #floodhazard #floodmitigation #disasterresponse #equity #city #town #rural #urban #economy #cost

  24. Socio-Hydrology Modeling Captures How Inequalities Impact Community Flood Resilience
    --
    doi.org/10.1029/2025WR041393 <-- shared paper
    --
    americanprogress.org/article/h <-- shared technical/opinion article
    --
    carbonbrief.org/us-flooding-in <-- shared technical/opinion article
    --
    headwaterseconomics.org/natura <-- shared technical/opinion article
    --
    youtu.be/8jVRsD8wgMM?si=qBHchW <-- shared opinion video
    --
    fedcommunities.org/lower-incom <-- shared technical/opinion article
    --
    H/T @matthew Preisser | PhD Civil Engineering, Natural Hazard Modeler and Socio-Hydrologists
    “How can we better understand the dynamic feedbacks between the environment and society?
    Socio-hydrology models are often built around the assumption that cities act as homogeneous entities, without capturing the variable capacity of communities with different underlying socioeconomic characteristics to respond to and recover from disasters.
    In this study, [the authors] developed a disaggregated approach to model community-specific adaptive capacity, allowing [them] to examine how inequalities influence flood recovery and resilience. This framework provide[d] a basis for exploring hypotheses about the relationships between growth, inequality, and community resilience in the face of flood hazards.
    [Their] results highlighted] the importance of considering community-level dynamics when developing flood mitigation and disaster response strategies that balance economic growth with equity. Many challenges remain in applying socio-hydrology models to real-world settings, but this work takes a step toward incorporating more realistic representations of socioeconomic inequality into human–water systems while preserving the generality and flexibility that make conceptual models useful…”
    #risk #hazard #water #hydrology #flood #society #flooding #USA #SocioHydrology #naturalhazard #socioeconomic #population #demographics #infrastructure #damage #disaster #disaggregated #model #modeling #community #adaptiveresponse #growth #inequality #communityresilience #floodhazard #floodmitigation #disasterresponse #equity #city #town #rural #urban #economy #cost

  25. Socio-Hydrology Modeling Captures How Inequalities Impact Community Flood Resilience
    --
    doi.org/10.1029/2025WR041393 <-- shared paper
    --
    americanprogress.org/article/h <-- shared technical/opinion article
    --
    carbonbrief.org/us-flooding-in <-- shared technical/opinion article
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    headwaterseconomics.org/natura <-- shared technical/opinion article
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    youtu.be/8jVRsD8wgMM?si=qBHchW <-- shared opinion video
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    fedcommunities.org/lower-incom <-- shared technical/opinion article
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    H/T @matthew Preisser | PhD Civil Engineering, Natural Hazard Modeler and Socio-Hydrologists
    “How can we better understand the dynamic feedbacks between the environment and society?
    Socio-hydrology models are often built around the assumption that cities act as homogeneous entities, without capturing the variable capacity of communities with different underlying socioeconomic characteristics to respond to and recover from disasters.
    In this study, [the authors] developed a disaggregated approach to model community-specific adaptive capacity, allowing [them] to examine how inequalities influence flood recovery and resilience. This framework provide[d] a basis for exploring hypotheses about the relationships between growth, inequality, and community resilience in the face of flood hazards.
    [Their] results highlighted] the importance of considering community-level dynamics when developing flood mitigation and disaster response strategies that balance economic growth with equity. Many challenges remain in applying socio-hydrology models to real-world settings, but this work takes a step toward incorporating more realistic representations of socioeconomic inequality into human–water systems while preserving the generality and flexibility that make conceptual models useful…”