#himalayas — Public Fediverse posts

Nepal is Paying the Price for a Climate Crisis It Did Little to Create https://www.byteseu.com/2350501/ #ClimateChange #ClimateChangeHimalayas #ClimateCrisis #environment #Himalayas #JammuAndKashmir #Nepal #NepalFloods

⛺️ NEW: #Everest Base Camp becomes a temporary settlement of about 1,600 tents on the #Khumbu Glacier each #spring for roughly 50 days.

Heat from burned fuel and warm urine contributes to local #glacier melt, with fuel responsible for about 94% of the modeled human-caused #warming. Surface temps there are rising faster than in surrounding glacier areas, and researchers suggest the camp could be relocated.

👉 https://www.zmescience.com/science/news-science/human-urine-and-fuel-are-melting-the-glacier-beneath-everest-base-camp/

#glacier #climatechange #climate #science #mountains #himalayas #glaciology #environment #earthscience #geography #climbing #research #nature #heat #ice

⛺️ NEW: #Everest Base Camp becomes a temporary settlement of about 1,600 tents on the #Khumbu Glacier each #spring for roughly 50 days.

Heat from burned fuel and warm urine contributes to local #glacier melt, with fuel responsible for about 94% of the modeled human-caused #warming. Surface temps there are rising faster than in surrounding glacier areas, and researchers suggest the camp could be relocated.

👉 https://www.zmescience.com/science/news-science/human-urine-and-fuel-are-melting-the-glacier-beneath-everest-base-camp/

#glacier #climatechange #climate #science #mountains #himalayas #glaciology #environment #earthscience #geography #climbing #research #nature #heat #ice

⛺️ NEW: #Everest Base Camp becomes a temporary settlement of about 1,600 tents on the #Khumbu Glacier each #spring for roughly 50 days.

Heat from burned fuel and warm urine contributes to local #glacier melt, with fuel responsible for about 94% of the modeled human-caused #warming. Surface temps there are rising faster than in surrounding glacier areas, and researchers suggest the camp could be relocated.

👉 https://www.zmescience.com/science/news-science/human-urine-and-fuel-are-melting-the-glacier-beneath-everest-base-camp/

#glacier #climatechange #climate #science #mountains #himalayas #glaciology #environment #earthscience #geography #climbing #research #nature #heat #ice

⛺️ NEW: #Everest Base Camp becomes a temporary settlement of about 1,600 tents on the #Khumbu Glacier each #spring for roughly 50 days.

Heat from burned fuel and warm urine contributes to local #glacier melt, with fuel responsible for about 94% of the modeled human-caused #warming. Surface temps there are rising faster than in surrounding glacier areas, and researchers suggest the camp could be relocated.

👉 https://www.zmescience.com/science/news-science/human-urine-and-fuel-are-melting-the-glacier-beneath-everest-base-camp/

#glacier #climatechange #climate #science #mountains #himalayas #glaciology #environment #earthscience #geography #climbing #research #nature #heat #ice

⛺️ NEW: #Everest Base Camp becomes a temporary settlement of about 1,600 tents on the #Khumbu Glacier each #spring for roughly 50 days.

Heat from burned fuel and warm urine contributes to local #glacier melt, with fuel responsible for about 94% of the modeled human-caused #warming. Surface temps there are rising faster than in surrounding glacier areas, and researchers suggest the camp could be relocated.

👉 https://www.zmescience.com/science/news-science/human-urine-and-fuel-are-melting-the-glacier-beneath-everest-base-camp/

#glacier #climatechange #climate #science #mountains #himalayas #glaciology #environment #earthscience #geography #climbing #research #nature #heat #ice

The first silence I experienced wasn't quiet.

When I stopped speaking, what rose up was everything I'd been drowning out.

Have you ever sat with real silence, not just quiet but the kind that reveals what you've been avoiding?

Read more

https://medium.com/@clarainsweden/what-the-himalayas-whispered-4e0b51998b2c

#silenceretreat #meditation #himalayas
#mindfulness #contemplativepractice #innerwork
#spiritualpractice #yogaphilosophy #solitude

Compound Hydrogeomorphic Cascades And Rapid Upstream To Downstream Hazard Coupling In The Eastern Himalaya
--
https://doi.org/10.1038/s41598-026-52915-8 <-- shared paper
--
https://doi.org/10.1007/s11600-022-00943-z <-- shared paper
--
H/T @Kuldeep Dutta | Geology-Earth Science
“… In hilly regions transitioning rapidly to low gradient alluvial plains, localized hydrometeorological triggers can instantly scale into devastating basin wide disasters. This study dissects the September 2020 cascading hazard in parts of the Arunachal Pradesh-Assam corridor to quantify the rapid coupling between upstream hillslopes and downstream floodplains.
Check out the [attached graphical abstract figure] for an integrated visual workflow of the entire disaster continuum from hillslope failure to floodplain transformation...”
--
“Extreme precipitation in the Eastern Himalaya is increasingly associated with coupled hillslope-floodplain hazards. This study examines the 17th-18th September 2020 rainfall event in Arunachal Pradesh initiating landslides and its downstream impacts in Assam, India, using multi-sensor satellite data and long-term rainfall records. Sentinel-2 imagery was used to map landslides and debris flows, Sentinel-1 SAR data to delineate flood extent, and IMD gridded rainfall (1996–2020) to analyse rainfall spell characteristics. The event triggered widespread slope failures, localized landslide damming, and a subsequent breach, generating sediment-laden flows that inundated ~ 100 km² of the Dhemaji floodplain. A backscatter-derived Relative Flood Volume Index (RFVI) indicates spatial variability in inundation intensity, although it does not represent absolute flood volume. Rainfall analysis suggests that antecedent wetness from preceding spells preconditioned slopes, while peak daily rainfall (> 170 mm day−1) initiated landsliding. Power-law scaling shows negligible dependence of intensity on duration (R2 ≈ 0.0004), whereas cumulative rainfall exhibits a stronger relationship with duration (R2 ≈ 0.54). These results indicate distinct roles of rainfall intensity and accumulation in controlling landslide initiation and downstream flooding, respectively, highlighting the importance of compound rainfall forcing in rapid hydrogeomorphic cascades…”
#EarthScience #RemoteSensing #Himalayas #NaturalHazards #ClimateChange #ScientificReports #GeospatialAnalysis #DisasterMitigation #Landslide #trigger #Flooding #massmovement #extremeweather #engineeringgeology #floodplain #innundation #hillslope #fluvial #pluvial #alluvial #sediment #sedimentation #hydrometeorology #ArunachalPradesh #Assam #India #Brahmaputra #risk #hazard #geology #engineeringgeology #remotesensing #earthobservation #spatialanalysis #spatiotemporal #disaster #hydrogeomorphology #workflow

Compound Hydrogeomorphic Cascades And Rapid Upstream To Downstream Hazard Coupling In The Eastern Himalaya
--
https://doi.org/10.1038/s41598-026-52915-8 <-- shared paper
--
https://doi.org/10.5194/esurf-13-1281-2025 <-- shared paper
--
https://doi.org/10.1007/s11069-025-07766-3 <-- shared paper
--
[I recognise that the photo is instead for the floods, etc in Lubra, Nepal - but felt it better showed the hydrogeomorphical setting (sic) for the 'casual' post viewer...]
H/T @Kuldeep Dutta
“In hilly regions transitioning rapidly to low gradient alluvial plains, localized hydrometeorological triggers can instantly scale into devastating basin wide disasters. This study dissects the September 2020 cascading hazard in parts of the Arunachal Pradesh-Assam corridor to quantify the rapid coupling between upstream hillslopes and downstream floodplains…”
--
“Extreme precipitation in the Eastern Himalaya is increasingly associated with coupled hillslope-floodplain hazards. This study examines the 17th-18th September 2020 rainfall event in Arunachal Pradesh initiating landslides and its downstream impacts in Assam, India, using multi-sensor satellite data and long-term rainfall records. Sentinel-2 imagery was used to map landslides and debris flows, Sentinel-1 SAR data to delineate flood extent, and IMD gridded rainfall (1996–2020) to analyse rainfall spell characteristics. The event triggered widespread slope failures, localized landslide damming, and a subsequent breach, generating sediment-laden flows that inundated ~ 100 km2 of the Dhemaji floodplain. A backscatter-derived Relative Flood Volume Index (RFVI) indicates spatial variability in inundation intensity, although it does not represent absolute flood volume. Rainfall analysis suggests that antecedent wetness from preceding spells preconditioned slopes, while peak daily rainfall (> 170 mm/day/) initiated landsliding. Power-law scaling shows negligible dependence of intensity on duration (R² ≈ 0.0004), whereas cumulative rainfall exhibits a stronger relationship with duration (R² ≈ 0.54). These results indicate distinct roles of rainfall intensity and accumulation in controlling landslide initiation and downstream flooding, respectively, highlighting the importance of compound rainfall forcing in rapid hydrogeomorphic cascades...”
#EarthScience #RemoteSensing #Himalayas #NaturalHazards #ClimateChange #ScientificReports #GeospatialAnalysis #DisasterMitigation #Landslide #Flooding #alluvial #fluvial #water #hydrology #hydrography #flood #flooding #spatialanalysis #spatiotemporal #mountain #plain #hydrometeorological #hydrogeomorphology #ArunachalPradesh #Assam #India #hillslope #floodplain #rainfall #precipitation #extremeweather #engineeringgeology #massmovement #landslide #debrisflow #risk #hazard #monitoring #GIS #spatial #mapping #remotesensing #satellite #Sentinel #sedimentation #humanimpacts #infrastructure #damage #cost #economics #public #safety #model #modeling #downstream

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

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

What Are Some Popular Trekking Destinations in the Himalayan Region?

https://indiasafaristrends.wordpress.com/2026/06/07/what-are-some-popular-trekking-destinations-in-the-himalayan-region/

🥶🔍 Oh no, the #Himalayas are turning into a barren #wasteland because winter is slacking off on snow duty! Scientists "warn" us with their serious faces while we all collectively yawn and scroll past the BBC's infinite scrolling chaos. Remember, if it's not melting faster than your ice cream on a hot day, it's probably not newsworthy. 🌍🔬
https://www.bbc.com/news/articles/clyndv7zd20o #ClimateChange #SnowShortage #EnvironmentalCrisis #ScientificWarning #HackerNews #ngated

The #Technosphere: The Hidden #CarbonSink : Medium

#SpatialIntelligence Is #AI’s Next #Frontier : Time

How Did the #CIA Lose a #Nuclear Device in the #Himalayas? : NY Times

Latest #KnowledgeLinks

https://knowledgezone.co.in/resources/bookmarks

Here's a potato-quality photograph of one of them. But mostly the view we had was of them streaking past.
#nature #wildlife #photography #himalayas #mustelid

A pair of Yellow-Bellied Weasels (Mustela kathiah) decided to spend a few days in our backyard. They were lightning-quick, utterly unafraid of humans being nearby, and systematically investigated every drainage hole in the retaining wall.
#nature #wildlife #photography #himalayas #mustelid

🌏 Work from the Himalayas!🏔️👨🏻‍💻✨

Nepal is set to introduce a digital nomad visa within the next year, welcoming remote workers to experience its breathtaking landscapes and rich culture.

This initiative aims to boost tourism and attract global talent, making Nepal a top destination for digital nomads seeking adventure and tranquillity.

Why Nepal?
— Stunning natural beauty
— Affordable living
— Vibrant culture
— Warm hospitality

https://kathmandupost.com/money/2025/05/28/nepal-eyes-tourism-economic-boost-with-new-digital-nomad-visa-policy

https://risingnepaldaily.com/news/62749

#Nepal #DigitalNomad #Nomad #NomadLife #DigitalNomafLife #DigitalNomadLifestyle #Visa #NepalVisa #Himalaya #Himalayas #Tourism #NepalTourism #NaturalBeauty #Himal #Mountains #Adventure #Culture #VisaPolicy #NomadicLife #NomadicLove #NomadicLifestyle #HimalayanRepublic #NepaliCulture #VibrantCulture #VisitNepal #Nomads #RemoteWork #RemoteWorkLife #NepalHimalayas #नेपाल #हिमालय

Landslide Susceptibility Assessment In The Marin Khola Watershed Of The Sub Himalaya, Central Nepal
--
https://doi.org/10.3126/jist.v30i1.76264 <-- shared paper
--
#GIS #spatial #mapping #geology #engineeringgeology #massmovement #landslides #Nepal #susceptibility #MarinKhola #watershed #InfoVal #Siwaliks #Himalayas #risk #hazard #cost #infrastructure #publicsafety #lossoflife #propertydamage #damage #geomorphology #water #hydrology #geomorphometry #casestudies #spatialanalysis #water #hydrology #factors #topography #geology #soil #landuse #landcover #model #modeling #accuracy

The classic view of Mount Everest from the top of Kala Patthar

For prints and licence to use this photo, check: https://radekkucharski.picfair.com/albums/208704-everest-region-all-photos

#MountEverest #landscapephotography #landascape #mountains #mountainphotograpy #Himalayas #trekking #trekkinginNepal #Khumbu

Earthquakes Impact Forest Resilience For Decades Post-Event, Research Suggests
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https://phys.org/news/2024-02-earthquakes-impact-forest-resilience-decades.html <-- shared technical article
--
https://doi.org/10.1038/s41561-024-01380-x <-- shared paper
--
#GIS #spatial #mapping #spatialanalysis #global #earthquakes #trees #forests #impacts #earthquakeffects #forestrecovery #recovery #water #damage #nutrition #massmovement #dendroclimatology #dataing #dendrology #MMI #corrleation #historic #ringoffire #circumpacific #Himalayas #NewZealand #spatiotemporal #resilence

RT @i_ameztoy: 14 x 8000 | #NangaParbat 🏔️ 8,126 m

Also called the "Naked Mountain" it is the ninth-highest mountain on Earth & is the westernmost major peak of the #Himalayas. It lies south of the Indus River in the Diamer District of Gilgit–Baltistan.

@CopernicusEU #Sentinel2 🛰️ 2023-03-11

🐦🔗: https://n.respublicae.eu/CopernicusEU/status/1644746133963456513

Book your stay now and save more...

#TheGuidingMonkStays

#TheGuidingMonk #ChaloGhoomneChalenge #ChaloGhoomneChalein #darjeelingdiaries #Darjeeling #QueenOfHills #kalimpong #Kurseong #Mirik #Siliguri #dooars #DarjeelingTourism #Tourism #Himalayas #India #Nature #Travel #Landscape #Hillstation #Greens #Forest #Trees #snow #mountains #hills #lakes #hilltown #homestay