#himalayas — Public Fediverse posts

NEW BOOK | 'Music and Dances from Central Nepal: The Works of Subi Shah, Volume 1' edited by Anna Marie Stirr, Mason Brown, Hikmat Khadka, and Lochan Rijal

This is the first English translation of Shah's analysis of Himalayan folk music & perfomance

Read freely or buy a copy: https://www.openbookpublishers.com/books/10.11647/obp.0246

#OpenAccess #FolkMusic #Himalayas

NEW BOOK | 'Music and Dances from Central Nepal: The Works of Subi Shah, Volume 1' edited by Anna Marie Stirr, Mason Brown, Hikmat Khadka, and Lochan Rijal

This is the first English translation of Shah's analysis of Himalayan folk music & perfomance

Read freely or buy a copy: https://www.openbookpublishers.com/books/10.11647/obp.0246

#OpenAccess #FolkMusic #Himalayas

NEW BOOK | 'Music and Dances from Central Nepal: The Works of Subi Shah, Volume 1' edited by Anna Marie Stirr, Mason Brown, Hikmat Khadka, and Lochan Rijal

This is the first English translation of Shah's analysis of Himalayan folk music & perfomance

Read freely or buy a copy: https://www.openbookpublishers.com/books/10.11647/obp.0246

#OpenAccess #FolkMusic #Himalayas

NEW BOOK | 'Music and Dances from Central Nepal: The Works of Subi Shah, Volume 1' edited by Anna Marie Stirr, Mason Brown, Hikmat Khadka, and Lochan Rijal

This is the first English translation of Shah's analysis of Himalayan folk music & perfomance

Read freely or buy a copy: https://www.openbookpublishers.com/books/10.11647/obp.0246

#OpenAccess #FolkMusic #Himalayas

Flood And Landslide Susceptibility Assessment And Multi Hazard Interaction Mapping Using Machine Learning And GIS For Sustainable Settlement Planning In Nepal
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https://doi.org/10.1007/s44288-026-00670-8 <-- shared paper
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H/T @Narayan Thapa | Earth Data Modeling
“Nepal lies within an active seismic zone and is influenced by most dynamic climatic systems in the world. It faces compounding floods and landslide threats. Impacts are worst where multi-hazard interactions create spatially linked corridors. Despite frequent co-occurrence, national-scale assessments remain limited. This study presents machine learning and GIS-based approach to map nationwide susceptibility to floods, landslides, and identify their potential interaction zones, and delineate critical multi-hazard flow zones through spatial adjacency analysis. Using Google Earth Engine, the Random Forest model integrates topographic, climatic, environmental, and hydrological datasets to overcome subjective expert-driven methods. The model achieved strong predictive accuracy (AUC: 0.84 for floods, 0.85 for landslides). The results showed 19% of Nepal’s lowlands are medium to very highly susceptible to inundation, threatening approximately 900,000 people and over 3.4 million buildings; whilst in the hilly terrains, 40% is susceptible to slope-failure endangering 200,000 people and about 0.6 million buildings. K-means clustering followed by spatial adjacency analysis identified four spatial zonation: 81% of national area as low-hazard zone, 9% as flood-only zone, 5% as landslide-only zone, and 5% as interaction zones. Critical multi-hazard flow zone covering 7,588 km² represents spatially connected corridors linking interaction zones to downstream flood-prone populated areas, affecting 88 km² built-up land and 1,722 km² cropland. These zones represent susceptibility-based spatial connectivity rather than physically simulated cascading processes. These findings support recommendations for risk-informed land-use planning, resilient infrastructure development and climate adaptation aligned to sustainable development and investment risk screening…”
#GIS #spatial #mapping #GoogleEarthEngine #MachineLearning #RemoteSensing #GeospatialAI #DisasterRiskReduction #MultiHazard #ClimateAdaptation #climatechange #extremeweather #LandUsePlanning #SustainableDevelopment #InfrastructurePlanning #RiskAssessment #NaturalHazards #Nepal #EarthObservation #HinduKushHimalaya #HKH #HinduKush #Himalayas #risk #hazard #assessment #national #regional #spatialanalysis #spatiotemporal #massmovement #landslide #assessment #mitigation #water #hydrology #flood #flooding #sustainability

Compound Hydrogeomorphic Cascades And Rapid Upstream To Downstream Hazard Coupling In The Eastern Himalaya
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https://doi.org/10.1038/s41598-026-52915-8 <-- shared paper
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https://doi.org/10.1007/s11600-022-00943-z <-- shared paper
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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...”
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“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
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https://doi.org/10.1038/s41598-026-52915-8 <-- shared paper
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https://doi.org/10.5194/esurf-13-1281-2025 <-- shared paper
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https://doi.org/10.1007/s11069-025-07766-3 <-- shared paper
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[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…”
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“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
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https://doi.org/10.1038/s44304-026-00217-4 <-- shared paper
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https://doi.org/10.1038/s41598-025-22051-w <-- shared (earlier) paper
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https://doi.org/10.1080/2150704X.2025.2488532 <-- shared (earlier) paper
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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/

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
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#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

A very cool wolf spider, just quietly moving around on moss. Allowed enough time for a decent picture (with an android phone)
Set on a typical gneiss'ish rock infused with hard white quartz crystals.

https://en.wikipedia.org/wiki/Wolf_spider

#wolfspider #mosstodon #geology #IndiasNatures #spider #nature #himalayas #nature #Lycosidae #gneiss #QuartzCrystals

Ice-Patch Collapse And Early-Warning Implications From A Himalayan Flash Flood - Emerging Cryo-Hydrological Hazards Under Deglaciation
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https://doi.org/10.1038/s44304-026-00191-x
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https://youtu.be/zZXER7DocfY?si=lYOE_a6YwigP3-mB
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#GIS #spatial #mapping #glacier #glacial #cryosphere #risk #hazard #flood #flooding #flashflood #earthobservation #cryohydrology #ice #snow #water #hydrogy #Himalaya #Himalayan #extremeweather #monitoring #risk #hazard #forecasting #DharaliFlashFlood #CryosphereScience #Deglaciation #EarlyWarning #RemoteSensing #Himalayas #NaturalHazards #ClimateChange #GlacierResearch #OpenScience #highmountain #mountain #slope #steepness #erosion #fluvial #nivation #Uttarakhand #India #SrikantaGlacier #DEM #elevation #satellite #chronology #reconstruction #ablation #debris #sedimentation #debrisflow #meltwater #debris #surge #massmovement #engineeringgeology #cryospherichazard #terrain #spatialanalysis #spatiotemporal #earlywarning #naturalhazard #channel #topography #geography #hydrogeomorphology #geomorphology #Dharali

#Movies #ClassicMovies . . .

Just rewatched #LostHorizon (1937) on #Tubi, a #FrankCapra movie starring #RonaldColeman & co-starring #JaneWyatt, for the 1s time in years.

I've got this #movie on #DVD but the one on Tubi is the restored 132 min movie; the one that I have on DVD is a shorter cut version.

The movie is about finding the mythical city of #ShangraLa in the #Himalayas. It's a great movie & a "must see," if you're a movie buff & if you've never seen it before.

It's in B&W. They have the full sound track but 6-7 mins of the film was never found in useable condition. I'd rate it 9 out of 10.

Improving Forest Loss Mapping In Nepal Using Landtrendr Time-Series And Machine Learning
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https://doi.org/10.1016/j.rsase.2025.101864 <-- share paper
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“HIGHLIGHTS:
• ViT-based forest mask, multispectral ensemble LandTrendr and terrain shadow mask.
• District-level RF/XGBoost model training with expert-weighted validation.
• Outperformed GFC and REDD + AI benchmarks in accuracy and F1 performance.
• RF excelled in High Mountains/Himalayas; XGBoost in the lower Mountain regions.
• NBR contributed the most; snow-impacted forest loss uncertainty was observed..."
#Forestdisturbance #forest #disturbance #remotesensing #LandTrendr #workflow #timeseries #ViT #RF #XGBoost #GEE #Nepal #ForestNepal #spatial #GIS #mapping #earthobservation #landsat #Himalayas #mountains #alpine #vegetation #AI #multispectral #monitoring #spatialanalysis #spatiotemporal #loss #change #machinelearning #NDR #conservation #planning #policy #mitagion #ecology #Karnali #Bagmati, #Darchula #Siwalik #GlobalForestChange #Degradation

Indian Towns with a European Vibe: Explore Charm, Luxury, and Culture in 2026–2027

https://indiasafaristrends.wordpress.com/2025/08/25/indian-towns-with-a-european-vibe-explore-charm-luxury-and-culture-in-2025-2026/

Landslide Susceptibility Assessment In The Marin Khola Watershed Of The Sub Himalaya, Central Nepal
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https://doi.org/10.3126/jist.v30i1.76264 <-- shared paper
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#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

"Psychological Effects of Sudden Himalayan Floods"
https://www.psychologytoday.com/us/blog/disaster-by-choice/202504/psychological-effects-of-sudden-himalayan-floods
#PhD #research by Aaliya Aaliya.
 
#GLOF #GLOFs #PhDLife #HKH #Himalayas #Floods #FloodRisk #DRR #DisasterPsychology #Hunza #HunzaValley #Pakistan

Climate change is contributing to the decline in bee populations in Nepal, leading to the loss of a cliff-side honey gathering tradition.

Fantastic photos of the villagers and the harvesting process

https://www.aljazeera.com/gallery/2024/6/6/photos-climate-crisis-stings-nepals-honey-gatherers-threatens-tradition

#ClimateChange #Bees #Tradition #Nepal #Himalayas #MadHoney #Deforestation #PesticideUse

The Changing Ecology Of A High Himalayan Valley - Challenges To The Sustainable Development Of The Kanchenjunga Conservation Area, Eastern Nepal
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https://doi.org/10.3390/su16062434 <-- shared paper
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#GIS #spatial #mapping #geology #geomorphology #infrastructure #change #Kanchenjunga #conservationarea #Nepal #sustainability #roads #adventuretourism #climatechange #wildlife #humanimpact #mountains #history #development #remotesensing #MPA #impactassessment #social #environment #glaciallakeoutburstflood #GLOF #Himalayas

Climate Change Impact Assessment On The Hydrological Regime Of The Kaligandaki Basin, Nepal
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https://doi.org/10.1016/j.scitotenv.2017.12.332 <-- shared paper
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“HIGHLIGHTS
• The rise in temperature and increase in precipitation is projected in future in Kaligandaki River basin.
• The water availability in the basin is not likely to decrease during this century.
• The change in water balance in the upper sub-basins of Kaligandaki River is higher.
• The output from this research could be beneficial for water resources management..."
#GIS #spatial #mapping #Nepal #Kaligandaki #riverbasin #basin #river #hydrology #model #modeling #numericmodeling #climatechange #temperature #precipitation #ET ##waterresources #water #watersecurity #waterbalance #impactassessment #humanimpacts #freshwater #HinduKush #himalayas #SWAT #prediction #projection #cimip5 #gcm #waterbalance #snowmelt #evapotranspiration #spatialanalysis #spatiotemporal