#spatiotemporal — Public Fediverse posts on home.social

💧🌏 Greg Cocks @[email protected] · 2026-09-04 · 02:28 UTC

To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
(Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
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https://www.science.org/content/article/predict-tree-death-scientists-tapped-gamma-rays-peer-underground <-- shared technical article
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https://doi.org/10.1029/2026GL122182 <-- shared paper
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H/T @hannah Richter
“Over an 18-month period starting in 2023, the dense forests of Western Australia [WA] experienced a record-setting drought. Jarrah trees towering 35 metres high died off in patchy brown splotches, turning 400 square kilometres - 3% of the forest - into brittle, fire-prone stands. The event led researchers to wonder whether there was a better way to predict where such die-offs might occur both there and in other forests, a problem that has long been tricky to solve because important factors such as soil depth are hidden underground…
Now, those same researchers have unveiled a surprising new tool for predicting tree mortality: gamma rays [link above.] Resulting from the natural decay of the potassium-40 isotope from granite-rich bedrock, the radiation acts as a proxy for soil depth, which in turn signals how much water a tree can access during drought. The new method could be applied to other highly weathered soils, which cover one-third of Earth’s ice-free land...”
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"... PLAIN LANGUAGE SUMMARY: During a record-breaking drought and heat event in 2023–2024, forests in southwestern Australia experienced widespread, patchy die-off. While we know that extreme weather triggers these events, it is often a hidden factor, the thickness of soil and the depth to underlying bedrock, that determines which trees live or die. Trees growing in shallow soil over solid rock are highly vulnerable due to limited water storage. Here, [they] show how to map these hidden zones from the air using gamma rays that are naturally emitted by potassium in the ground. Like southwestern Australia, many parts of the world have highly weathered soils where potassium has been washed out of the upper layers of soil. However, [they] showed that higher potassium areas signal that potassium-rich bedrock is closer to the surface and this is sensitive for tens of meters. By comparing gamma ray maps with ground-based geophysical surveys and satellite data, [they] showed that these potassium hotspots accurately predict where forests are most likely to experience die-off during a drought. These types of soils cover about one-third of the Earth's land, so the method provides a powerful new tool for managers to identify and protect vulnerable forests from future, hotter droughts…”
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #Australia #WesternAustralia #WA #forests #vegetation #bush #jarrah #karri #drought #heat #extremedrought #extremeweather #climatechange #water #waterresources #dieoff #soil #weathering #erosion #moisture #nutrients #airborne #gammarays #GRS #granite #gneiss #bedrock #geology #potassium40 #potassium #K #remotesensing #earthobservation #groundwater #interstitial #subsurface #waterstorage #electricalresistivitytomography

#gis #spatial #mapping #spatialanalysis #spatiotemporal #australia

💧🌏 Greg Cocks @[email protected] · 2026-09-03 · 04:13 UTC

Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
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https://science.nasa.gov/earth/earth-observatory/rising-waters-swamp-lake-naivasha/ <-- shared NASA 2026 technical article
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https://africasacountry.com/2026/04/the-human-cost-of-kenyas-expanding-lakes <-- shared 2026 technical article
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https://carrzee.org/wp-content/uploads/2021/11/kenyarisingwatermenr-scoping-report-latest-5-07-21.pdf <-- shared technical report
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https://earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
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https://doi.org/10.11648/j.ajrs.20180602.13 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
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https://apnews.com/article/kenya-water-hyacinth-invasive-fishing-2ea35d0203bc995a36ddbe32386c1141 <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
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https://apnews.com/article/kenya-rising-lakes-naivasha-baringo-cbfbb0b670f831b9a310309a810a0075 <-- shared 2025 media article
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https://www.sei.org/features/revisiting-the-rising-rift-valley-lakes-a-glimpse-into-kihotos-struggles/ <-- shared 2023 technical article
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https://www.theguardian.com/world/2022/mar/17/kenya-quiet-slide-underwater-great-rift-valley-lakes-east-africa-flooding <-- shared 2022 media rticle
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“Kenya's Lake Naivasha has long been a place of change and reinvention…
Now the lake faces another major change: rapidly fluctuating water levels. The name Naivasha comes from a Maasai word meaning "that which heaves," an apt description of the freshwater lake over the past 25 years. Satellite altimetry measurements of the lake's depth indicate an increase of about 7 metres (23 feet) since 2010, roughly the height of a two-story building. Over the same period, Landsat observed a roughly 40 percent increase in the lake's area, adding 50 kilometres² (19 miles²) of water, equivalent to roughly 15 Central Parks.
The human and economic toll of the rising water levels is considerable..”
#Kenya #LakeNaivasha #Africa #water #hydrology #hydrography #risingwater #waterlevels #GIS #spatial #mapping #spatialanalysis #spatiotemporal #humanimpacts #farming #agriculture #infrastructure #damage #community #satellite #altimetry #economy #cost #impact #change #flood #flooding #innundation
@nasa

#kenya #lakenaivasha #africa #water #hydrology #hydrography

💧🌏 Greg Cocks @[email protected] · 2026-08-19 · 04:50 UTC

WeatherNext – [An] AI Model Achieves Breakthrough In Forecasting Cyclones
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https://deepmind.google/blog/weathernext-ai-model-achieves-breakthrough-in-forecasting-cyclones/ <-- shared technical Google DeepMind blog post
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https://doi.org/10.1038/s41586-026-10953-2 <-- shared paper
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https://deepmind.google/science/weatherlab/ <-- shared data
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https://github.com/google-deepmind/weathernext <-- shared GitHub repository
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H/T @juliet Rothenberg | Product Director of Earth & Resilience AI at Google
[this post should not be considered an endorsement of a particular organisation or their approach]
“[The Google WeatherNext AI team] are showing how the WeatherNext AI model from Google DeepMind and Google Research has achieved state-of-the-art accuracy in predicting a cyclone's track, intensity, and wind structure. On average, the WeatherNext Cyclones model gives forecasters an extra day’s worth of predictive accuracy- delivering an advance equivalent to roughly a decade of historical meteorological progress 🌀
Here is how WeatherNext is transforming cyclone forecasting:
• Gaining an Extra Day of Advanced Warning: WN 3-day forecasts are as good as what prior models were able to provide for 2-day forecasts, giving critical time for emergency response.
• Overcoming Traditional Trade-offs: WN bridges the gap between massive global atmospheric currents (which steer a cyclone's path) and fine-grained thermodynamic processes around its core (which drive its intensity) into a single AI model.
• Unprecedented Ensemble Scale: Using Functional Generative Networks (FGNs), WN now generates 1,000-member ensembles in less than a minute on a TPU to capture rare, consequential tail-risks like sudden rapid intensification – which means forecasters can see a broader range of possible scenarios.
• Real-World Impact: During the 2025 Atlantic hurricane season, the WN model helped the National Hurricane Center (NHC) make a historic forecast for Hurricane Melissa by predicting rapid intensification and landfall five days in advance.
[The] teams are open sourcing the operationalized models (WeatherNext Cyclones and WeatherNext 2), alongside a compact version (WeatherNext 2-mini) that can run on a single TPU in a free public Colab notebook – all with a goal of empowering local organizations worldwide.
Weather affects everyone. By combining advanced AI with the real-world expertise of human forecasters, we can build a collaborative ecosystem that saves lives and helps communities adapt to a changing climate…”
#Google #DeepMind #GoogleResearch #AI #ensembles #FunctionalGenerativeNetworks #WeatherNext #cyclone #operationalised #model #modeling #forecasting #spatialanalyis #spatiotemporal #track #intensity #windstructure #hurricane #weather #climate #metrology #cyclonetrack #risk #hazard #emergencyresponse #planning #tool #earlywarning #scale #magnitude #path #track #thermodynamic #scenarios #opensource #impacts #tropicalcyclones #WeatherNextCyclones #weathermodel #atmospheric #predictions #mitigation #warning #robust #publicsafety #infrastructure
@Google | @WeatherNext

#google #deepmind #googleresearch #ai #ensembles #functionalgenerativenetworks

💧🌏 Greg Cocks @[email protected] · 2026-07-21 · 19:38 UTC

Refined Modeling of Arctic Circumpolar Building Stock Increases Estimated Mid-Century Permafrost Degradation Damages
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https://doi.org/10.1029/2026EF008578 <-- shared paper
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https://www.thearcticinstitute.org/climate-change-geopolitics-monitoring-thawing-permafrost/ | https://www.thearcticinstitute.org/dwindling-arctic-sea-ice-impacts-permafrost-health/ <-- shared technical articles
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https://www.theguardian.com/cities/2016/oct/14/thawing-permafrost-destroying-arctic-cities-norilsk-russia <-- shared media article
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https://news.grida.no/new-map-shows-extent-of-permafrost-in-northern-hemisphere <-- shared technical article
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H/T @elias Manos
“Why the increase?
Our understanding of climate risk is only as good as our understanding of our exposure to hazards. The better we can account for what is at risk, the better we can measure risk in a changing world.
In this new study [link above], [they] investigate[d] how damage to the building stock across the Arctic, a key impact of permafrost degradation, is underestimated because of underdeveloped exposure information. With National Science Foundation (NSF) supercomputers and 400 TB of Vantor satellite imagery, [they] detected building footprints across the Arctic and classified their use types using deep learning models. Then, using Polar Geospatial Center's ArcticDEM digital surface model, [they] estimated the total floor space of each residential building. This move from 2D to 3D representation of the building stock was the largest contributor to increased building damage.
Properly estimating this consequence is necessary for understanding the near future of the Arctic economy. Knowing the magnitude of damages is critical for sustaining the communities and livelihoods of more than 5 million people that call the Arctic home. There are also much broader implications. With the Arctic continuing to emerge as a strategic centerpiece in global affairs and the global economy, accurately quantifying the physical shocks to its built environment will allow researchers to more effectively represent the Arctic in global climate economic models. More precise international policymaking will also be enabled by these improvements.
Ultimately, this research highlights a similar challenge in completely different regions of the world (e.g., Southeast Asia, Sub-Saharan Africa) where exposure is constantly evolving alongside rapid population growth and urbanization. Building stock information can quickly become outdated as these changes occur; satellite remote sensing and AI are key players in keeping up with these changes and supporting data-driven disaster risk management…”
#arctic #circumpolar #permafrost #model #modeling #spatialanalysis #spatiotemporal #GIS #spatial #mapping #melting #degradation #damage #cost #economics #risk #hazard #climaterisk #climatechange #remotesensing #HPC #earthobservation #ArcticDEM #buildingfootprint #LLM #AI #machinelearning #engineering #economy #buildingstock #community #policy #planning #geopolitics #risk #management @UConn Research

#arctic #circumpolar #permafrost #model #modeling #spatialanalysis

💧🌏 Greg Cocks @[email protected] · 2026-07-15 · 02:49 UTC

Mapping Deforestation Probability And Understanding The Forest Dynamics In Gazipur, Bangladesh
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https://doi.org/10.1016/j.envc.2026.101568 <-- shared paper
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"ABSTRACT: Deforestation is a spiralling environmental catastrophe with impervious results for biodiversity, climate change, and human livelihoods, specifically in tropical regions. Being a tropical country, Bangladesh has experienced approximately 40% loss of its forest cover, at Gazipur since 1930, which contains about 86% of the country's Sal (Shorea robusta) forest, ranging approximately 4,300 hectares per year (2001–2010) to over 19,500 hectares per year (2011–2020), exemplifying an intensification of nearly 353%. The objective of this study is to map deforestation probability at the Gazipur district of Dhaka Division, Bangladesh, by utilising machine learning algorithms along with multi-source geospatial data, with the purpose of identifying high-risk zones and facilitating evidence-based forest governance, land-use development, and prioritizing conservation areas. This study integrated twelve conditioning factors, including biophysical, landscape, and anthropogenic. To identify susceptible zones the study trained and assessed five machine learning algorithms; RF, XGBoost, ANN, NB, and MLP and validating the result through different metrics like sensitivity, specificity, precision, accuracy, F1-score, AUC. The performance of the models was evaluated using Wilcoxon signed-rank tests and marginal response curves (MRC) were used to understand factor contributions. In the result, RF achieved highest performance with accuracy of 84% and AUC of 0.93, followed by XGBoost at 83% accuracy and 0.92 AUC. Rainfall and population density were most dominant conditioning factors among models. Pairwise statistical testing resulted that ensemble-based algorithms (RF, XGBoost) generated statistically comparable and significantly higher predictions compared to NB and MLP. Spatial probability maps indicate areas of high and very high risk in the south-western and north-eastern upazilas. The results can be applicable for forest management authorities, urban planners, and policymakers, and correspond with SDG Indicator 15. An inclusive governance framework containing land zoning, ecological area identification, and compliance with industrial EIA is proposed to persuade probability maps into adaptive forest management strategies…”
#deforestation #probability #machinelearning #algorithms #AI #Gazipur #Bangladesh #GIS #spatial #mapping #spatialanalysis #spatiotemporal #rainfall #precipitation #humanimpacts #populationpressure #risk #prediction #RandomForest #conservation #restoration #environment #biodiversity, #climatechange #human #livelihood #tropical #forestcover #sal #forest #vegetation #tree #upazila #spatialprobability #geostatistics #forestmanagement #planning #policy #urbanplanners #governance #zoning #ecology #habitat

#deforestation #probability #machinelearning #algorithms #ai #gazipur

💧🌏 Greg Cocks @[email protected] · 2026-07-10 · 22:36 UTC

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

#earthscience #remotesensing #himalayas #naturalhazards #climatechange #scientificreports

💧🌏 Greg Cocks @[email protected] · 2026-07-10 · 04:56 UTC

A Scale-Invariance-Based Algorithm Application For Land Surface Temperature Downscaling In Denmark
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https://doi.org/10.3390/rs18132263 <-- shared paper
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https://zenodo.org/records/20863040 <-- shared open data for downscaled LST dataset for Copenhagen
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H/T @CLIM4cities
#urbanclimate #downscaling #landsurfacetemperature #LST #AI #machinelearning #scaleinvariance #residualcorrection #Sentinel #Landsat #satellite #remotesensing #earthobservation #CLIM4cities #UrbanClimate #ClimateServices #MachineLearning #ClimateAdaptation #heatwave #temperature #ontheground #Copenhagen #Denmark #impervioussurface #asphalt #roof #concrete #albedo #heatabsorption #mitigation #urban #urbancentre #treecover #vegetation #urbanheatisland #planning #design #hotspots #monitoring #spatialanalysis #spatiotemporal #model #modeling #usecase #operational #climatechange #extremeweather #evidencebased #adapation #sustainability #urbanplanning #climateresilience #EssentialClimateVariable #ECV
@+ATLANTIC | @Danish Meteorological Institute | @ESA Φ-lab Collaborative Innovation Network | @CLIM4cities

#urbanclimate #downscaling #landsurfacetemperature #lst #ai #machinelearning

💧🌏 Greg Cocks @[email protected] · 2026-06-10 · 03:45 UTC

[G]lobal Decline In Endorheic Basin Water Storages
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https://doi.org/10.1038/s41561-018-0265-7 <-- shared paper
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https://en.wikipedia.org/wiki/Endorheic_basin <-- shared Wikipedia page
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“Endorheic (hydrologically landlocked) basins spatially concur with arid/semi-arid climates. Given limited precipitation but high potential evaporation, their water storage is vulnerable to subtle flux perturbations, which are exacerbated by global warming and human activities. Increasing regional evidence suggests a probably recent net decline in endorheic water storage, but this remains unquantified at a global scale. By integrating satellite observations and hydrological modelling, [they] reveal[ed] that during 2002–2016 the global endorheic system experienced a widespread water loss of about 106.3 Gt/yr, attributed to comparable losses in surface water, soil moisture and groundwater. This decadal decline, disparate from water storage fluctuations in exorheic basins, appears less sensitive to El Niño–Southern Oscillation-driven climate variability, which implies a possible response to longer-term climate conditions and human water management. In the mass-conserved hydrosphere, such an endorheic water loss not only exacerbates local water stress, but also imposes excess water on exorheic basins, leading to a potential sea level rise that matches the contribution of nearly half of the land glacier retreat (excluding Greenland and Antarctica). Given these dual ramifications, [they] suggest the necessity for long-term monitoring of water storage variation in the global endorheic system and the inclusion of its net contribution to future sea level budgeting…”
#water #hydrology #hydrography #global #waterresources #waterstorage #Endorheic #Basin #watersecurity #arid #semiarid #rainfall #precipitation #spatialanalysis #spatiotemporal #globalwarming #climatechange #humanimpacts #anthropogenic #regional #remotesensing #GIS #spatial #mapping #earthobservation #surfacewater #groundwater #soilmoisture #exorheic #watermanagement #hydrosphere #waterstress #SLR #sealevelrise #monitoring #waterbudgets

#water #hydrology #hydrography #global #waterresources #waterstorage

💧🌏 Greg Cocks @[email protected] · 2026-06-09 · 15:19 UTC

Study Highlights Growing Importance Of Multi-Day Storms In Future U.S. Flood Risk
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https://news.okstate.edu/articles/engineering-architecture-technology/2026/study-highlights-growing-importance-of-multi-day-storms-in-future-u.s.-flood-risk <-- shared technical article
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https://doi.org/10.1088/2752-5295/ae4f14 <-- shared paper
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“Extreme rainfall is projected to intensify as the climate warms, yet whether the greatest increases will occur in multi-day or single-day events remains uncertain. This knowledge gap is particularly pressing given recent catastrophic floods triggered by multi-day rainfall events, prompting the question of whether multi-day events could, in fact, intensify more than their daily counterparts, and by how much. This study addresses this question using an ensemble of 34 downscaled Earth System Models under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5), focusing on changes in extreme rainfall by the end of the century across ten regions of the contiguous United States. [Their] statistical framework evaluates model agreement, ensemble-mean changes, and the significance of these changes for both daily and multi-day rainfall extremes. Results show that extreme rainfall amounts are expected to increase for most regions and durations. The degree of intensification, however, depends strongly on event rarity and regional climate characteristics. Notably, in the U.S. western Gulf Coast region, very rare multi-day events (e.g., 500 year return period) are projected to intensify more than their daily counterparts, a phenomenon that could be explained by increased stalling of tropical cyclones, which can prolong heavy rainfall over multiple days. These results challenge the assumption that daily extremes dominate future risk and highlight the need to consider event duration when updating flood-hazard maps, design standards, and adaptation planning…”
#Flooding #FloodRisk #FloodInsurance #FloodAwareness #Explore #FloodPreparedness #FlashFlooding #ClimateResilience #climatechange #extremeweather #DisasterPreparedness #StormwaterManagement #FloodSafety #CommunityResilience #risk #hazard #model #modeling #floodrisk #multiday #rainfall #precipitation #storm #water #hydrology #hydrography #planning #policy #regulations #climatemodel #CONUS #USA #publicsafety #cost #economics #damage #loss #infrastructure #spatiotemporal #spatialanalysis #earthsystemmodels #forecasting #meteorology #designstandards #floodmapping #mitigation #flood

#flooding #floodrisk #floodinsurance #floodawareness #explore #floodpreparedness

💧🌏 Greg Cocks @[email protected] · 2026-06-02 · 03:20 UTC

Climatology And Trends Of Annual Maximum Sub-Daily Precipitation In The Western United States
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https://doi.org/10.1016/j.wace.2026.100915 <-- shared paper
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#USWest #western #usa #rainfall #climatology #spatialanalysis #spatiotemporal #spatial #mapping #precipitation #risk #hazard #flood #flooding #soil #slopes #debrisflow #saturated #monitoring #climatechange #extremeweather #monsoon #intensity #California #publicsafety #infrastructure #flashflooding #massmovement #landslides #engineeringgeology #hydrogeomorpholgy #mudslide #topography #elevation #geomorphmetry #extremerainfall #seasonal #thermodynamic

#uswest #western #usa #rainfall #climatology #spatialanalysis

💧🌏 Greg Cocks @[email protected] · 2026-05-20 · 03:45 UTC

Sea Levels Rising Dramatically In Some Areas Due To Land Subsidence [global]
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https://phys.org/news/2026-05-sea-areas-due-subsidence.html <-- shared technical article
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https://doi.org/10.1038/s41467-026-72293-z <-- shared paper
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[#VLM = vertical land motion; #ASL = absolute sea-level; #RSL = relative sea-level; #GIA = (global) Glacial Isostatic Adjustment; #inSAR = Interferometric Synthetic Aperture Radar; #GNSS = Global Navigation Satellite System (~GPS); #OE24 = paper, https://doi.org/10.1038/s41561-023-01357-2, interpolated VLM reconstruction based on the joint analysis of GNSS, tide gauges (TGs), and satellite altimetry]
#GIS #spatial #mapping #remotesensing #earthobservation #sealevel #verticallandmotion #absolutesealevel #relativesealevel #GlacialIsostaticAdjustment #geomorphometry #SLR #sealevelrise #coast #coastal #flood #flooding #subsidence #landmass #landsubsidence #global #globalsealevelrise #climatechange #city #urban #farmlands #population #demographics #cities #planning #community #elevation #monitoring #spatialanalysis #spatiotemporal #altimetry

#vlm #asl #rsl #gia #insar #gnss

💧🌏 Greg Cocks @[email protected] · 2026-05-15 · 18:02 UTC

Water Velocity And Discharge From Tidal Freshwater Creeks In Forested And Herbaceous Wetlands
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https://doi.org/10.1007/s12237-026-01690-w <-- shared paper
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#water #hydrology #tide #tidal #ecosystem #wildlife #fish #fisheries #nursery #nutrients #trophicenergy #discharge #ColumbiaRiver #Oregon #Washington #USA #fluvial #tidalfreshwater #TFW #habitat #restoration #flowregime # herbaceous #forested #wetland #marsh #aquatic #sediment #sedimentation #estuary #inundation #monitoring #measurement #velocity #discharge #volume #spatialanalysis #spatiotemporal #river #riverine #hydraulic #pluvial #precipitation #upstream #subtidal #wavelet #tidalcreek #AcousticDopplerCurrentProfiler #instrumentation #elevation #spatial #mapping

#water #hydrology #tide #tidal #ecosystem #wildlife

💧🌏 Greg Cocks @[email protected] · 2026-04-30 · 02:28 UTC

The Cascadia Subduction Zone Isn’t Shutting Down – But It’s More Complicated Than We Thought
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https://theconversation.com/the-cascadia-subduction-zone-isnt-shutting-down-but-its-more-complicated-than-we-thought-279730 <-- shared technical article
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https://doi.org/10.1126/sciadv.ady8347 <-- shared paper
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#SciComm #ScienceCommunication #Earthquakes #engineeringgeology #geology #risk #hazard #fault #faulting #Vancouver #VancouverIsland #BritishColumbia #Seattle #OlympicPeninsula #PugetSound #WashingtonState #PNW #PacificNorthwest #NorthAmerica #plateboundary #subduction #platetectonics #spatialanalysis #spatiotemporal #seismicity #seismic #geophysics #offshore #remotesensing #Cascadia #CascadiaSubductionZone #mechanics #lithosphere##

#scicomm #sciencecommunication #earthquakes #engineeringgeology #geology #risk

💧🌏 Greg Cocks @[email protected] · 2026-04-22 · 03:13 UTC

Detecting Land Use And Land Cover Changes And Quantifying Soil Erosion And Sediment Export Using GIS And Remote Sensing In The GERD Catchment, Ethiopia
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https://doi.org/10.1016/j.iswcr.2026.100657 <-- shared paper
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https://infonile.org/en/2023/05/battling-for-survival-along-the-warming-source-of-the-blue-nile/ <-- shared technical media article
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https://doi.org/10.1007/978-3-031-65241-7_4 <-- shared technical book chapter
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https://doi.org/10.3390/rs8121020 <-- shared 2016 paper
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#landuse #landcover #RUSLE #model #soil #erosion #sedimentation #GERD #catchment #NorthAfrica #Ethiopia #AbbayBasin #sustainability #landmanagement #agriculture #farmland #foodsecurity #water #hydrogology #reservior #watermanagement #watersecurity #waterresources #catchment #GrandEthiopianRenaissanceDam #BlueNile #hydrography #impoundment #GIS #spatial #mapping #remotesensing #earthobservation #thematic #spatialanalysis #spatiotemporal #landsat #elevation #DEM #CHIRPS #rainfall #precipitation #LULC #AI #forest #grazing #grassland #field #crops #cropland #waterbodies #urban #biophysical #risk #hazard #mitigation #soilquality

#landuse #landcover #rusle #model #soil #erosion

💧🌏 Greg Cocks @[email protected] · 2026-03-19 · 04:42 UTC

Observing The Tidal Pulse Of Rivers From Wide-Swath Satellite Altimetry
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https://doi.org/10.1038/s41586-026-10287-z <-- shared paper
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https://dahiti.dgfi.tum.de/en/products/river-tides/map/ <-- shared interactive map, ‘River Tides from SWOT’
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#SWOT #RemoteSensing #Hydrology #EarthObservation #ClimateScience #CoastalSystems #Rivers #OpenScience #opendata #tide #tidal #dynamics #exchange #estuary #estuarine #webmap #wetlands #ecosystems #habitat #elevation #marine #freshwater #water #hydrography #hydrology #river #GIS #spatial #mapping #satellite #altimetry #coast #coastal #GIS #spatial #mapping #spatialanalysis #spatiotemporal #SurfaceWaterandOceanTopography #global #coverage #monitoring #model #modeling #riverine #fluvial #carbonbudgets #nitrogencycle #sedimentation #sealevelrise #SLR #megadroughts #extraction #pumping #regulations #groundwater #intrusion #risk #hazard #naturalhazards #stormsurge #waterresources #tidalrange #rivermouth

#swot #remotesensing #hydrology #earthobservation #climatescience #coastalsystems

💧🌏 Greg Cocks @[email protected] · 2026-02-25 · 00:10 UTC

Growing Meltwater Reservoirs – Glacial Lakes Are Both A Resource And A Habitat Worthy Of Protection
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https://www.uni-potsdam.de/en/headlines-and-featured-stories/detail/2026-01-28-growing-meltwater-reservoirs-glacial-lakes-are-both-a-resource-and-a-habitat-worthy-of-protection <-- shared technical article
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https://doi.org/10.1038/s44221-025-00578-6 <-- shared paper
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https://github.com/geveh/LakeVolumes <-- shared GitHub ‘code base’
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#glaciallakes #GLOF #geomorphology #glaciers #hydrology #waterresources #glacier #melting #retreating #hydrogeomorphology #GIS #spatial #mapping #global #spatialanalysis #global #cryosphere #ice #water #hydrology #mountains #highaltitude #naturalresource #freshwater #reservoir #sediment #sedimentation #spatiotemporal #remotesensing #earthobservation #landcover #Arctic #coastal #meltwater #lake #longevity #watersecurity #risk #hazard #ecosystem #habitat #naturalhazard #planning #tourism #economy #usecase #watersupply #worldwide #population #demographics #glacial
@University of Potsdam | @University Of Leeds

#glaciallakes #glof #geomorphology #glaciers #hydrology #waterresources

💧🌏 Greg Cocks @[email protected] · 2026-02-06 · 03:41 UTC

Changes In Dominant Streamflow Drivers As Network-Scale Flow Regime Shifts From Intermittent To Ephemeral Across A Multi-Year Drought
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https://doi.org/10.1002/hyp.70413 <-- shared paper
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#GIS #spatial #mapping #water #hydrology #fluvial #pluvial #precipitation #extremeweather #California #USA #semiarid #watershed #headwaters #weather #metrology #spatialanalysis #spatiotemporal #model #modeling #geostatistics #monitoring #sensors #instrumentation #insitu #drought #streamflow #ephemeral #intermittent #catchments #waterresources #watermanagement #watersecurity #planning
#coast #coastal #hydrogeomorphic #geology #climate

#gis #spatial #mapping #water #hydrology #fluvial

💧🌏 Greg Cocks @[email protected] · 2025-12-30 · 03:23 UTC

Provisional Land Use Data From Water Year 2024 Is Now Available On [CA]DWR Atlas, CNRA Open Data, And SGMA Data Viewer For Public Use
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https://gis.water.ca.gov/app/CADWRLandUseViewer/?page=home <-- shared web-based CDWR datasets / map
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“The collected data is used by various federal, state, and local agencies, academic researchers and private consultants , and can help estimate the amount of water available for agriculture. Using this information, farmers can adapt and make decisions to better manage scarce water supplies more effectively.”
#GIS #spatial #mapping #California #download #opendata #water #hydrology #datause #datasharing #download #landuse #spatialanalysis #spatiotemporal #wateryear #DWRAtlas #statewide #CNRA #SGMA #publicdata #publicgood #usecase #crops #croplands #cropmapping #counties #countysurvey #CADWR #DWR #groundwater #irrigation #wateruse #watermanagement #federal #state #local #webmapping #agriculture #watersecurity #foodsecurity #watersupply
#CaliforniaDepartmentOfWaterResources

#gis #spatial #mapping #california #download #opendata

💧🌏 Greg Cocks @[email protected] · 2025-12-20 · 02:50 UTC

Rapid Mass Movements Triggered By An Atmospheric River In Disko Island, West Greenland
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https://doi.org/10.1002/esp.70201 <-- shared paper, 2023 event(s)
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https://doi.org/10.1007/s10346-022-01922-7 <-- shared paper, 2021 event(s)
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https://www.polarresearch.at/the-great-landslide-of-assapaat/ <-- shared technical article
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#landslide #massmovement #thawing #permafrost #extremewweather #cryosphere #Qeqertarsuaq #ArcticDEM #DiskoIsland #Greenland #ERA5 #CARRA #fluvial #pluvial #precipitation #rainfall #snow #ice #glacier #glacial #temperature #slushflow #GIS #spatial #mapping #geomorphology #elevation #slope #atmosphericriver #climate #weather #snowmelt #island #coast #coastal #damage #humanimpacts #infrastructure #arctic #monitoring #geohazard #risk #hazard #engineeringgeology #polar #change #remotesensing #spatialanalysis #spatiotemporal #earthobservation #debrisflow #remoteareas
#GreenlandEcosystemMonitoring | @europeanspaceagency | #CopernicusECMWF #Copernicus

#landslide #massmovement #thawing #permafrost #extremewweather #cryosphere

💧🌏 Greg Cocks @[email protected] · 2025-12-16 · 04:10 UTC

Peak Glacier Extinction In The Mid-Twenty-First Century
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https://doi.org/10.1038/s41558-025-02513-9 <-- shared paper
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“📉 KEY FINDINGS
• At +4 °C, only ~18,000 glaciers remain worldwide by 2100
• At +1.5 °C, ~100,000 glaciers survive
• [They] identif[ed] “Peak Glacier Extinction”:
– ~2041 at +1.5 °C (~2,000 glaciers lost per year)
– ~2055 at +4 °C (~4,000 glaciers lost per year)
🏔️ THE ALPS
• At +2.7 °C, only ~110 glaciers remain by 2100.
• At +4 °C, this drops to just ~20.
Can you imagine the Alps with almost no glaciers left?...”
#model #modeling #global #glacier #loss #glacial #cryosphere #spatialanalysis #spatiotemporal #GloGEM #OGGM #PyGEM #extinction #climate #climatechange #globalwarming #water #hydrology #freshwater #surfacewater #count #metrics #volume #thickness #size #sealevelrise #tourism #culture #usecase #waterresources #Alps #TheAlps #worldwide #melted #melting