#riskassessment — Public Fediverse posts

Society must anticipate: prepare not for this year's climate but for the future climates. 🧵

#livability #climatePolicy #riskManagement #riskAssessment #policy #adaptation #forests #climateDrift #climateChange #heatwaves #naturalDisasters #resilience #agriculture #wildfires #poliSky #foresight

Society must anticipate: prepare not for this year's climate but for the future climates. 🧵

#futures #risks #risk #riskManagement #riskAssessment #livability #habitability #climatePolicy #policy #adaptation #plantations #forestry #climateDrift #climateChange #climateFailure #climateCollapse #drought #heatwaves #naturalDisasters #resilience #agriculture #megafires #wildfire #wildfires

…
The EU's adaptation framework serves as a distraction. The cover for treating adaptation as purely technical is thinner than it has been in years. This summer ongoing disasters offer an opening to:
* discuss adaptation;
* look at the perpetrators: https://fed.brid.gy/r/https://bsky.app/profile/did:plc:ghfylraepxvzz7zjex4nelzw/post/3msbmrpwlhc2v

_References_

The present thread was inspired by two other voices about the same technocratic output: http://strategicclimaterisks.substack.com/p/how-the-eu-adaptation-framework-vastly

Here is the announcement of the report from the European Scientific Advisory Board on Climate Change, 'Strengthening resilience to climate change – Recommendations for an effective EU adaptation policy framework': https://climate-advisory-board.europa.eu/news/escalating-climate-impacts-demand-urgent-coordinated-adaptation-across-the-eu

#climatePolicy #adaptation #climateChange #livability #policy #climate #riskAssessment #governance #uncertainty #EU #EuropeanUnion #Europe

Modeling Flood Susceptibility Utilizing Advanced Ensemble Machine Learning Techniques in the Marand Plain [Iran]
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https://doi.org/10.3390/geosciences15030110 <-- shared paper
--
H/T @Geosciences MDPI
“This study applies advanced machine learning algorithms to map flood susceptibility in northwest Iran. The results demonstrate strong predictive performance, with the Locally Weighted Linear model delivering the highest accuracy and providing valuable guidance for flood-risk management and disaster mitigation…”
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“Flooding is one of the most significant natural hazards in Iran, primarily due to the country’s arid and semi-arid climate, irregular rainfall patterns, and substantial changes in watershed conditions. These factors combine to make floods a frequent cause of disasters. In this case study, flood susceptibility patterns in the Marand Plain, located in the East Azerbaijan Province in northwest Iran, were analyzed using five machine learning (ML) algorithms: M5P model tree, Random SubSpace (RSS), Random Forest (RF), Bagging, and Locally Weighted Linear (LWL). The modeling process incorporated twelve meteorological, hydrological, and geographical factors affecting floods at 485 identified flood-prone points. The data were analyzed using a geographic information system, with the dataset divided into 70% for training and 30% for testing to build and validate the models. An information gain ratio and multicollinearity analysis were employed to assess the influence of various factors on flood occurrence, and flood-related variables were classified using quantile classification. The frequency ratio method was used to evaluate the significance of each factor. Model performance was evaluated using statistical measures, including the Receiver Operating Characteristic (ROC) curve. All models demonstrated robust performance, with an area under the ROC curve (AUROC) exceeding 0.90. Among the models, the LWL algorithm delivered the most accurate predictions, followed by RF, M5P, Bagging, and RSS. The LWL-generated flood susceptibility map classified 9.79% of the study area as highly susceptible to flooding, 20.73% as high, 38.51% as moderate, 29.23% as low, and 1.74% as very low. The findings of this research provide valuable insights for government agencies, local authorities, and policymakers in designing strategies to mitigate flood-related risks. This study offers a practical framework for reducing the impact of future floods through informed decision-making and risk management strategies…”
#FloodSusceptibility #FloodRisk #MachineLearning #GIS #NaturalHazards #DisasterManagement #FloodModeling #Hydrology #EnvironmentalMonitoring #RiskAssessment #GeospatialAnalysis #ClimateResilience #GIS #spatial #mapping #Iran #MarandPlain #EastAzerbaijan #machinelearning #AI #floodhazard #floodvulnerability #flood #flooding #water #hydrography #hydrology #model #modeling #risk #hazard #rainfall #precipitation #extremeweather #spatialanalysis #spatiotemporal #modelperformance #policy #planning #mitigation #design #riskmanagement

Hydroclimate Volatility On A Warming Earth
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https://doi.org/10.1038/s43017-024-00624-z <-- shared 2025 paper
--
https://newsroom.ucla.edu/releases/floods-droughts-fires-hydroclimate-whiplash-speeding-up-globally <-- shared UCLA article, “Floods, Droughts, Then Fires: Hydroclimate Whiplash Is Speeding Up Globally “
--
H/T @Daniel Swain
“Hydroclimate volatility refers to sudden, large and/or frequent transitions between very dry and very wet conditions. In this Review, we examine how hydroclimate volatility is anticipated to evolve with anthropogenic warming. Using a metric of ‘hydroclimate whiplash’ based on the Standardized Precipitation Evapotranspiration Index, global-averaged subseasonal (3-month) and interannual (12-month) whiplash have increased by 31–66% and 8–31%, respectively, since the mid-twentieth century. Further increases are anticipated with ongoing warming, including subseasonal increases of 113% and interannual increases of 52% over land areas with 3 °C of warming; these changes are largest at high latitudes and from northern Africa eastward into South Asia. Extensive evidence links these increases primarily to thermodynamics, namely the rising water-vapour-holding capacity and potential evaporative demand of the atmosphere. Increases in hydroclimate volatility will amplify hazards associated with rapid swings between wet and dry states (including flash floods, wildfires, landslides and disease outbreaks), and could accelerate a water management shift towards co-management of drought and flood risks. A clearer understanding of plausible future trajectories of hydroclimate volatility requires expanded focus on the response of atmospheric circulation to regional and global forcings, as well as land–ocean–atmosphere feedbacks, using large ensemble climate model simulations, storm-resolving high-resolution models and emerging machine learning methods…
#water #hydrology #hydroclimate #whiplash #global #spatialanalysis #spatiotemporal #weatherwhiplash #ecogeomorphology #sustainability #ecology# ###
#water #hydrology #hydroclimate #volatility #dry #wet #drought #flood #flooding #wildfire #landslide #massmovement #whiplash #global #spatialanalysis #spatiotemporal #weatherwhiplash #ecogeomorphology #sustainability #ecology #hydrogeomorphology #climatechange #extremeweather #anthropogenicwarming #climate #weather #connection #StandardizedPrecipitationEvapotranspiration #precipitation #rainfall #research #evapotranspiration #risk #hazard #riskassessment #disease #pandemic #publichealth #publicsafety #waterquality #watersecurity #watermanagement #hydrography #atmospheric #regional #global #forcing #climatemodel #model #modeling #AI #machinelearning

Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
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https://doi.org/10.1038/s44304-026-00217-4 <-- shared paper
--
https://doi.org/10.1038/s41598-025-22051-w <-- shared (earlier) paper
--
https://doi.org/10.1080/2150704X.2025.2488532 <-- shared (earlier) paper
--
H/T @abhinav Alangadan
“Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
[The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
[Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
#permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
--
https://doi.org/10.1038/s44304-026-00217-4 <-- shared paper
--
https://doi.org/10.1038/s41598-025-22051-w <-- shared (earlier) paper
--
https://doi.org/10.1080/2150704X.2025.2488532 <-- shared (earlier) paper
--
H/T @abhinav Alangadan
“Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
[The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
[Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
#permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
--
https://doi.org/10.1038/s44304-026-00217-4 <-- shared paper
--
https://doi.org/10.1038/s41598-025-22051-w <-- shared (earlier) paper
--
https://doi.org/10.1080/2150704X.2025.2488532 <-- shared (earlier) paper
--
H/T @abhinav Alangadan
“Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
[The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
[Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
#permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
--
https://doi.org/10.1038/s44304-026-00217-4 <-- shared paper
--
https://doi.org/10.1038/s41598-025-22051-w <-- shared (earlier) paper
--
https://doi.org/10.1080/2150704X.2025.2488532 <-- shared (earlier) paper
--
H/T @abhinav Alangadan
“Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
[The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
[Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
#permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
--
https://doi.org/10.1038/s44304-026-00217-4 <-- shared paper
--
https://doi.org/10.1038/s41598-025-22051-w <-- shared (earlier) paper
--
https://doi.org/10.1080/2150704X.2025.2488532 <-- shared (earlier) paper
--
H/T @abhinav Alangadan
“Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
[The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
[Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
#permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

Climate Warming and Ice Weakening Trigger Alpine Glacier Collapses - The Marmolada Case [Dolomites, Northern Italy]
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https://doi.org/10.1029/2025GL121279 <-- shared paper
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https://doi.org/10.5194/nhess-25-3027-2025 <-- shared technical article
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https://en.wikipedia.org/wiki/2022_Marmolada_serac_collapse <-- shared Wikipedia page
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[anecdotal – in the early 1990s, I chose to spend a winter as a ski bum/guide, living in Arabba, Dolomites, Sud Tyrol; I still remember the excellent days when I got to ski on the Marmolada]
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“PLAIN LANGUAGE SUMMARY: On 3 July 2022, a portion of the Marmolada glacier, near Punta Rocca, collapsed and caused the death of 11 mountaineers. This dramatic event had a considerable impact on the media, and authorities were concerned about the risk that other collapses might occur in this and other glaciers of the Dolomites, a well-renowned mountain region of the southeastern Alps and one of the UNESCO World Heritage sites. [They] analyzed the possible causes of the collapse by developing a three-dimensional thermo-mechanical model. The analysis concluded that the collapse was caused by increased internal ice temperature and the development of a dense network of fractures, reducing the ice shear strength, with melting water that possibly contributed by increasing the basal pressure. [They] also showed that collapsing conditions can be identified with a simplified model version approximating the sliding basal surface as a plane with a slope equal to the surface slope. The developed approach can be used in hazard identification and risk analysis of mountain glaciers…”
#EngineeringGeology #RockMechanics #GlacierCollapse #RiskAssessment #italy #Dolomites #SudTyrol #glacier #melting #massmovement #risk #hazard #analysis #Marmolada #glaciercollapse #cryosphere #warning #mitigation #hazardassessment #alpine #climatechange #globalwarming #massloss #instability #model #modeling #thermomechanical #spatialanalysis #temperature #parameters #ice #shearstrength #water #hydrology #hydrography #basal #waterpressure #meltwater #fracturing #riskanalysis #mountainglaciers

#NoNaturalDisasters [UN]
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https://www.undrr.org/our-impact/campaigns/no-natural-disasters | https://www.nonaturaldisasters.com/ <-- shared technical articles
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#Resilience #ClimateAction #Governance #risk #hazard #riskassessment #naturalhazard #disaster #humanimpacts #engineeringgeology #NoNaturalDisasters #natural #nature #earthquake #storm #flood #flooding #tsunami #volcano #desertification #wildfire #fires #publicsafety #planning #policy #preparedness #ISO31000 #monitoring #buildingcodes #engineering #landuse #earlywarning #humanmaderisk #exposure #vulnerability #socioeconomic #ecosystems #habitat #livelihoods #farming #infrastructure #buildings #structures #industrial #cost #recovery #economics #homes #extremeweather #hurricane #tornado #resilience #sustainability #poverty #assessment #UNDRR #UN #riskreduction
@United Nations Office for Disaster Risk Reduction

Hanging Glaciers In Himalaya Reveal Rising Avalanche Risk
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https://www.nature.com/articles/d44151-026-00072-2 <-- shared technical article
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https://doi.org/10.1038/s44304-026-00205-8 <-- shared paper
--
#GIS #spatial #mapping #risk #hazard #monitoring #engineeringgeology #naturalhazard #Himalaya #Himalayas #Alaknanda #basin #Garhwal #India #ice #cryosphere #massmovement #avalanche #glacier #hangingglacier #cryosphere #remotesensing #spatialanalysis #spatiotemporal #sentinel2 #DEM #elevation #model #modeling #GlabTop2 #unstable #hanging #BadrinathMana #impact #infrastructure #damage #HEP #urbanisation #development #population #publicsafety #demographics #glacialretreat #melting #Chamoli #disaster #earlywarningsystems #Himalayan #glaciers #instability #warming #climatechange #riskassessment #riskclassification #framework #avaflow #runout #downstream #downslope #water #hydrology #planning #policy #mitigation #geomorphology #geomorphometry

#FYI #ClimateChat #DanMiller #LeonSimons #EliRabani #StaceyRandecker #strategy #sustainability #riskAssessment #profit #corruption #humanRights

Interview with #AlisonTaylor on #business #ethics and its impact on #climateChange

https://www.youtube.com/watch?v=4c2YT_pZZ8k

#climatechange #ClimateEmergency #ClimateCrisis #ClimateBreakdown #ClimateDisruption #globalWarming #globalHeating #ExtremeWeather #polycrisis

Karst Flash Floods - An Example From The Dinaric Karst (Croatia)
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https://doi.org/10.5194/nhess-6-195-2006 <-- shared (older) paper
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#flood #flooding #pluvial #fluvial #subsurface #risk #hazard #naturalhazard #disaster #flashflood #infrastructure #damage #building #destabilisation #foundations #karstburst #Marina #Dinaric #Croatia #extremeweather #climatechange #intense #prolonged #rainfall #precipitation #speed #fast #caves #conduits #fractures #aquifers #water #hydrology #groundwater #hydrogeology #waterpressure #sinkhole #subsidence #massmovement #landslide #monitoring #mapping #geology #engineeringgeology #hydroseismic #humanimpacts #lossoflife #death #karstterrain #springs #debris #sediment #cavities #riskassessment #Grazalema #Andalusia #Cadíz #Spain #StormLeonard #emergencymanagement #planning

Mapping Current And Future Flood Exposure Using A 5 Metre Flood Model And Climate Change Projections [Vancouver, Canada]
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https://nhess.copernicus.org/articles/24/699/2024/ <-- shared technical article
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https://www.theguardian.com/environment/2021/nov/17/pacific-north-west-flooding-british-columbia-washington-state-canada <-- shared 2021 technical media article, PNW flooding
--
[this post should not be considered an endorsement of a specific vendor, etc]
#water #hydrology #flood #flooding #risk #hazard #Vancouver #BritishColumbia #Canada #climatechange #extremeweather #localfloods #GIS #spatial #mapping #riskassessment #spatialanalysis #floodexposure #riskmapping #model #modeling #floodriskmanagement #riskmanagement #naturaldisaster #rainfall #precipitation #stormsurge #hazardmapping #floodmapping #floodrisk #infrastructure #cost #economics #fluvial #pluvial #geomorphology #elevation #geomorphometry #regulatory #regulations #spatiotemporal

New Research Aims To Better Predict And Understand Cascading Land Surface Hazards
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https://phys.org/news/2025-06-aims-cascading-surface-hazards.html <-- shared technical article
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https://doi.org/10.1126/science.adp9559 <-- shared paper
--
#interconnected #geology #engineeringgeology #landcover #landsurface #GIS #spatial #mapping #landcover #hydrology #water #geomorphology # geomiorphmetry #risk #hazard #extremeweather #climatechange #cascading #cascadinghazards #debrisflow #wildfire #massmovement #landslides #flood #flooding #mudflow #susceptibility #chainreaction #spatialanalysis #spatiotemporal #prediction #management #planning #mitigation #multifactor #sediment #erosion #fluvial #earthquake #fault #faulting #hazardassessment #riskassessment #volcano #vulcanism #sealevelchange #cryosphere #ice #snow #GLOF #humanimpacts #urban #infrastructure #cost #economics #loss #damage #earthobservation #remotesensing #LiDAR #UAV

More Faults, More Resolution, More Features - The New Zealand Active Faults Database Webmap Gets A Major Upgrade
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https://www.gns.cri.nz/news/more-faults-more-resolution-more-features-the-nz-active-faults-database-webmap-gets-a-major-upgrade/ <-- shared technical article
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https://data.gns.cri.nz/af/ <-- New Zealand Active Faults home page/ webmap
--
#GIS #spatial #mapping #spatiotemporal #fault #faulting #NewZealand #earthquake #geology #risk #hazard #groundsurface #webmap #record #database #surfacetrace #geomorphology #geomorphmetry #NZAFD #infrastructure #earthquakeengineering #engineeringgeology #planning #urbanplanning #regulations #geotechnical #landuse #permits #slip #frequency #riskassessment #GNS
@gnsscience

Comprehensive Risk Evaluation In Rapti Valley, Nepal - A Multi-Hazard Approach
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https://doi.org/10.1016/j.pdisas.2024.100346 <-- shared paper
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#GIS #spatial #mapping #rapti #lumbini #risk #hazard #nepal #suspectibility #vulnerability #flood #flooding #water #hydrology #multihazard #riskassessment #geology #engineeringgeology #massmovement #landslides #debrisflows #erosion #model #modeling #map #spatialanalysis #spatiotemporal #remotesensing #susceptibility #planning #development #mitigation #urbanplanning #naturalhazards #probability #geostatistics #forestfire #wildfire #bushfire #extremeweather #climatechange #vulnerability #physical #social #publicsafety #economic #environmental #riskzones

The Science Data Team at @whn has created a #wastewater dashboard to help #tracking and #predicting new #COVID19 #infections.

Find it here: https://whn.global/estimation-of-infections-based-on-wastewater-data/

#science #TrackingCOVID19 #data #epidemiology #InfectiousDisease #RiskAssessment #PublicHealth #FediScience #COVIDresources

Flood Protection Based On Historical Records Is Flawed – We Need A Risk Model Fit For Climate Change
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https://theconversation.com/flood-protection-based-on-historical-records-is-flawed-we-need-a-risk-model-fit-for-climate-change-212454 <-- shared technical article
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#GIS #spatial #mapping #water #hydrospatial #hydrology #flood #flooding #model #modeling #planning #mitigation #naturalhazard #humanimpacts #climatechange #extremeweather #regulations #prediction #floodengineering #floodrisk #floodriskassessment #assessment #risk #hazard #riskassessment #floodmanagement #floodprotection #floodsafety #publicsafety #spatialanalysis #spatiotemporal #weatherforecast #climatechangesolutions #climateadaptation #infrastructure #flooddamage

Global News BC: Alberta wildfire-mapping tool points out where communities are at risk https://globalnews.ca/news/9753941/alberta-wildfire-mapping-tool-fuel-spread-communities/ #globalnews #britishcolumbia #news #WildfireAnalyticsTeam #UniversityofAlberta #albertawildfiremap #AlbertaWildfires #Albertawildfire #Wildfirescience #RiskAssessment #wildfirerisk #Wildfires #firefuel #Science #Nordegg #Canada #Hinton #Jasper #Fire #Tech

Global News BC: Alberta wildfire-mapping tool points out where communities are at risk https://globalnews.ca/news/9753941/alberta-wildfire-mapping-tool-fuel-spread-communities/ #globalnews #britishcolumbia #news #WildfireAnalyticsTeam #UniversityofAlberta #albertawildfiremap #AlbertaWildfires #Albertawildfire #Wildfirescience #RiskAssessment #wildfirerisk #Wildfires #firefuel #Science #Nordegg #Canada #Hinton #Jasper #Fire #Tech

Global News BC: Alberta wildfire-mapping tool points out where communities are at risk https://globalnews.ca/news/9753941/alberta-wildfire-mapping-tool-fuel-spread-communities/ #globalnews #britishcolumbia #news #WildfireAnalyticsTeam #UniversityofAlberta #albertawildfiremap #AlbertaWildfires #Albertawildfire #Wildfirescience #RiskAssessment #wildfirerisk #Wildfires #firefuel #Science #Nordegg #Canada #Hinton #Jasper #Fire #Tech

Global News BC: Alberta wildfire-mapping tool points out where communities are at risk https://globalnews.ca/news/9753941/alberta-wildfire-mapping-tool-fuel-spread-communities/ #globalnews #britishcolumbia #news #WildfireAnalyticsTeam #UniversityofAlberta #albertawildfiremap #AlbertaWildfires #Albertawildfire #Wildfirescience #RiskAssessment #wildfirerisk #Wildfires #firefuel #Science #Nordegg #Canada #Hinton #Jasper #Fire #Tech

Hazard Exposure and Reporting Analytics (HERA) [USGS, USA]
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https://www.usgs.gov/apps/hera/ <-- HERA web site
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#GIS #spatial #mapping #opendata #openaccess #webmap #USGS #HERA #risk #hazard #exposure #community #digital #data #development #future #security #safety #infrastructure #analytics #property #disastermanagement #disasterplanning #riskassessment #riskmanagement #USA #spatialanalysis #spatialdata #spatiotemporal #planning #publicsafety #naturalhazards #hazardreduction #USGS #coastal #coast #flood #flooding #groundwater #saltwater #saltwaterintrusion

What is a #RiskAssessment? For us, the key 🔑that ensures the efficient deployment of resources & optimal prioritisation of control efforts for fisheries #sustainability.

Learn more and do not miss our new #corporatevideo 📺

#WeCoordinate🎣 #CommonFisheriesPolicy 🇪🇺

🐦🔗: https://n.respublicae.eu/EFCA_EU/status/1549018478719426560

What is a #RiskAssessment? For us, the key 🔑that ensures the efficient deployment of resources & optimal prioritisation of control efforts for fisheries #sustainability.

Learn more and do not miss our new #corporatevideo 📺

#WeCoordinate🎣 #CommonFisheriesPolicy 🇪🇺

🐦🔗: https://n.respublicae.eu/EFCA_EU/status/1549018478719426560

What is a #RiskAssessment? For us, the key 🔑that ensures the efficient deployment of resources & optimal prioritisation of control efforts for fisheries #sustainability.

Learn more and do not miss our new #corporatevideo 📺

#WeCoordinate🎣 #CommonFisheriesPolicy 🇪🇺

🐦🔗: https://n.respublicae.eu/EFCA_EU/status/1549018478719426560

What is a #RiskAssessment? For us, the key 🔑that ensures the efficient deployment of resources & optimal prioritisation of control efforts for fisheries #sustainability.

Learn more and do not miss our new #corporatevideo 📺

#WeCoordinate🎣 #CommonFisheriesPolicy 🇪🇺

🐦🔗: https://nitter.eu/EFCA_EU/status/1549018478719426560

What is a #RiskAssessment? For us, the key 🔑that ensures the efficient deployment of resources & optimal prioritisation of control efforts for fisheries #sustainability.

Learn more and do not miss our new #corporatevideo 📺

#WeCoordinate🎣 #CommonFisheriesPolicy 🇪🇺

🐦🔗: https://nitter.eu/EFCA_EU/status/1549018478719426560

What is a #RiskAssessment? For us, the key 🔑that ensures the efficient deployment of resources & optimal prioritisation of control efforts for fisheries #sustainability.

Learn more and do not miss our new #corporatevideo 📺

#WeCoordinate🎣 #CommonFisheriesPolicy 🇪🇺

🐦🔗: https://nitter.eu/EFCA_EU/status/1549018478719426560