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#spatiotemporal — Public Fediverse posts

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

  1. 💧🌏 Greg Cocks @[email protected] ·

    To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
    (Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
    --
    science.org/content/article/pr <-- shared technical article
    --
    doi.org/10.1029/2026GL122182 <-- shared paper
    --
    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...”
    --
    "... 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
  2. 💧🌏 Greg Cocks @[email protected] ·

    To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
    (Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
    --
    science.org/content/article/pr <-- shared technical article
    --
    doi.org/10.1029/2026GL122182 <-- shared paper
    --
    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...”
    --
    "... 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
  3. 💧🌏 Greg Cocks @[email protected] ·

    To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
    (Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
    --
    science.org/content/article/pr <-- shared technical article
    --
    doi.org/10.1029/2026GL122182 <-- shared paper
    --
    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...”
    --
    "... 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

    #electricalresistivitytomography #waterstorage #subsurface #interstitial #groundwater #earthobservation
  4. 💧🌏 Greg Cocks @GregCocks ·

    To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
    (Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
    --
    science.org/content/article/pr <-- shared technical article
    --
    doi.org/10.1029/2026GL122182 <-- shared paper
    --
    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...”
    --
    "... 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
  5. 💧🌏 Greg Cocks @[email protected] ·

    To Predict Tree Death, Scientists Tapped Gamma Rays To Peer Underground
    (Airborne radiation sensors could help forecast and prevent drought-driven tree mortality_
    --
    science.org/content/article/pr <-- shared technical article
    --
    doi.org/10.1029/2026GL122182 <-- shared paper
    --
    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...”
    --
    "... 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
  6. 💧🌏 Greg Cocks @[email protected] ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “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
  7. 💧🌏 Greg Cocks @[email protected] ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “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
  8. 💧🌏 Greg Cocks @[email protected] ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “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
  9. 💧🌏 Greg Cocks @[email protected] ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “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

    #innundation #flooding #flood #change #impact #cost
  10. 💧🌏 Greg Cocks @GregCocks ·

    Rising Waters Swamp Lake Naivasha [Kenya] [earth observation]
    --
    science.nasa.gov/earth/earth-o <-- shared NASA 2026 technical article
    --
    africasacountry.com/2026/04/th <-- shared 2026 technical article
    --
    carrzee.org/wp-content/uploads <-- shared technical report
    --
    earth.gsfc.nasa.gov/gwm/lake/91 <-- shared charting, lake water levels
    --
    doi.org/10.11648/j.ajrs.201806 <-- shared 2018 paper, ‘An Assessment of the Role of Water Hyacinth in the Water Level Changes of Lake Naivasha Using GIS and Remote Sensing’
    --
    apnews.com/article/kenya-water <-- shared 2025 media article, ‘How the invasive water hyacinth is threatening fishermen’s livelihoods on … Kenyan [Lake Naivasha]…’
    --
    apnews.com/article/kenya-risin <-- shared 2025 media article
    --
    sei.org/features/revisiting-th <-- shared 2023 technical article
    --
    theguardian.com/world/2022/mar <-- shared 2022 media rticle
    --
    “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..”

    @nasa

    #kenya #lakenaivasha #africa #water #hydrology #hydrography
  11. 💧🌏 Greg Cocks @[email protected] ·

    The Radiative Effects Of Water Vapour From Terrestrial Evapotranspiration
    --
    doi.org/10.1088/1748-9326/adde <-- shared paper/letter
    --
    zenodo.org/records/15413219 | zenodo.org/records/15416936 <-- shared open data, for “Model information and output for "The radiative effects…” ”
    --
    doi.org/10.1007/s11269-025-041 <-- shared paper
    --
    H/T @jan Umsonst | Earth System Nerd
    “Water vapour accounts for roughly 50% of the modern greenhouse effect. Over continental regions, evapotranspiration (ET) is often limited by water availability. In this study, [the authors] spatially quantify how much of the total atmospheric water vapour evaporated most recently from land and calculate the relative contribution of that water vapour to the atmospheric radiative budget. Using a combination of tracer-enabled Earth system model simulations and radiative transfer calculations, [they were] able to explicitly quantify the 3D distribution of terrestrial vs. oceanic water vapour, and the spatial contribution of each to the surface and top of atmosphere radiative budgets. [They found] that over many continental regions, more than half of the total column-integrated water vapour originates from land ET, and that this vapour contributes up to 30 W/m² of longwave radiation into the surface in the annual mean (about 10% of the total). Understanding how terrestrial ET impacts the base-state of water vapour distribution and the water vapour greenhouse effect is critical to understanding how and where changes in terrestrial ET, driven by climate change, land use, etc, will modify the radiative properties of the atmosphere and thus the climate system…”
    #water #hydrology #greehouseeffect #highperformancecomputing #HPC #evapotranspiration #Radiative #WaterVapour #spatial #spatialanalysis #spatiotemporal #atmosphere #model #modeling #earthsystemmodelling #terrestrial #oceanic #vapour #climatechange #landuse #changes #climatesystem

    #water #hydrology #greehouseeffect #highperformancecomputing #hpc #evapotranspiration
  12. 💧🌏 Greg Cocks @[email protected] ·

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

    #ghsl #demographics #change #spatiotemporal #population #grid
  13. 💧🌏 Greg Cocks @[email protected] ·

    Mapping Flood Agents In The Northern Pantanal Wetland Using Multiple Spatio-Temporal GIS And Remote Sensing Techniques
    --
    doi.org/10.1007/s13157-026-020 <-- shared paper
    --
    H/T @renato Gatto de Morais | Geógrafo | Mestre em Recursos Hídricos | Doutorando em Geografia
    “Combining MODIS data, TRMM, river discharge, a digital terrain model, and multinomial logistic regression, [the authors] identified three predominant classes of flood origin: local rainfall, bank overflow, and mixed areas. The model achieved a Nagelkerke Pseudo-R² of 0.63 and a classification accuracy of up to 81.2% (10-fold cross-validation). To the best of [their] knowledge, this is the first explicit approach to mapping flood agents for this wetland, a component that has historically remained unmapped despite its recognized influence on habitats and biodiversity…”
    --
    “The mapping of functional hydrologic units is crucial for enhancing our understanding of flooding and hydroecological processes in large wetlands. These units are typically defined by flooding frequency, duration, and magnitude, but another important hydrologic characteristic is the origin of flooding, known as the flood agent. This study presents an empirical framework utilizing remote sensing and GIS procedures for modeling flood agents in the northern Pantanal wetland. Eleven spatial data layers were derived from multi-year MODIS flood maps, daily rainfall estimates from the TRMM 3B42 grid, in situ discharge data, the BEST Digital Terrain Model, and a hydrographic network layer. These layers were tested for their predictive power in a multinomial logistic regression mapping model. Model performance metrics, along with qualitative validation of mapping outcomes using in situ flooding measurements, and vegetation and soil data from field test sites, support the plausibility of the proposed mapping scheme. However, they also highlight the challenges of flood agent mapping in large tropical wetlands…”
    #GIS #spatial #mapping #MODIS #TRMM #riverdischarge #digitalterrainmodel #multinomiallogisticregression #geostatistics #Pantanal #Cuiaba #Brazil #water #hydrology #spatialanalysis #spatiotemporal #remotesensing #earthobservation #flood #flooding #source #type #floodagent #tropical #wetland #habitat #biodiversity #ecosystem #hydrologicunit #hydroecology #model #modeling #rainfall #precipitation #weather #climate #discharge #network #metrics

    #gis #spatial #mapping #modis #trmm #riverdischarge
  14. 💧🌏 Greg Cocks @[email protected] ·

    Historic Snowfall Map Shows States Bracing For Significant Snow Amid El Niño [North America]
    --
    mensjournal.com/news/historic- <-- shared technical media article
    --
    cpc.ncep.noaa.gov/products/ana <-- shared link to NOAA release ‘El Niño/Southern Oscillation (Enso) Diagnostic Discussion - issued By Climate Prediction Center/NCEP/NWS | 13 August 2026’
    --
    cnn.com/2026/08/20/weather/sup <-- shared media article
    --
    H/T @Mens Journal
    “The National Oceanic and Atmospheric Association [NOAA] updated its prediction for the El Niño, which is strengthening and now has a greater than 90% chance of a very strong event during the Northern Hemisphere fall and winter 2026-27…
    Additionally, the NOAA revealed that during the October-December 2026 season, there is now a 69% chance of a historic event that would exceed the strength of previous El Niño events dating back to 1950. Historical records from the NOAA only date back to 1950, but other reports suggest this could be one of the strongest El Niños in history.
    This El Niño “is something that’s very unusual, if not a once in a lifetime type of (strength),” according to Nat Johnson, a meteorologist with the Geophysical Fluid Dynamics Laboratory at the National Oceanic and Atmospheric Administration.
    El Niño is a natural climate cycle marked by warmer than average water temperatures along the equator in the Pacific Ocean. The warmer water triggers corresponding shifts in the atmosphere that have a domino-like influence on weather patterns around the globe – usually in ways that are largely predictable well in advance…”
    #weather #climate #USA #forecast #fedscience #fedservice #NOAA #ElNiño #ElNino #snow #snowfall #climatecycle #water #hydrology #rainfall #precipitation #NorthAmerica #atmosphere #weatherpatterns #model #modeling #spatialanalysis #spatiotemporal #spatial #mapping #NorthernHemisphere #global
    @NOAA | @nws

    #weather #climate #usa #forecast #fedscience #fedservice
  15. 💧🌏 Greg Cocks @[email protected] ·

    Anthropogenic River Flows
    --
    doi.org/10.1088/3033-4942/ae94 <-- shared technical perspective
    --
    H/T @Homero Paltán | Water, Energy, Land & Infrastructure Systemic Risks | Lecturer
    “Are global river flows no longer natural? Can we really talk about natural rivers? [The authors] started asking ourselves these questions a few years ago over wonderful discussion sessions.
    [They] argue that global river systems have entered a new phase, one of Anthropogenic River Flows, where flow regimes arise from the persistent interaction of:
    • the physical alteration of river systems,
    • the institutional and socio-technical organisation of water use and allocation
    • broader global and systemic processes operating across scales.
    In the Anthropocene, these domains do not operate independently because a change in one alters how the other two function. Global water risks and river flow properties then become an emergent property of these interactions.
    As a result, [the authors] call for a rethinking of how we study, understand, and manage river flows to better reflect this new reality…”
    #water #hydrology #Anthropogenic #River #Flow #spatial #mapping #spatialanalysis #spatiotemporal #flowregimes #risk #waterrisk #global #climatechange #watersecurity #baseline #humanimpacts #magnitude, #seasonality #variability #waterquality #sociohydrology #hydroclimate #regulation #waterresources #engineering #governance #pumping #alteration

    #water #hydrology #anthropogenic #river #flow #spatial
  16. 💧🌏 Greg Cocks @[email protected] ·

    Modeling Climate Change Impacts On Blue And Green Water In The Ethiopian Upper Blue Nile Basin
    --
    doi.org/10.1016/j.ejrh.2026.10 <-- shared paper
    --
    H/T @Dessalegn worku Ayalew
    “The present study assesses the impacts of climate change on blue and green water in the Kessie Watershed of the Ethiopian Upper Blue Nile Basin using the SWAT+ model.
    [The authors] set up [a] SWAT+ model using quality-controlled and homogenized observational climate time series… and calibrated it using a multisite calibration approach. [They] selected CMIP6 climate models for future simulations and bias-correction methods through a comprehensive performance assessment... Building on these previous studies, the present research further evaluates the reliability of combining robust climate-model selection with optimal bias-correction methods to improve the reliability of hydrological simulations. [They] then used the best-performing climate models, bias-corrected using the optimal methods, to project future changes in blue and green water in the study area…
    KEY FINDINGS:
    • SWAT+ effectively represented hydrological processes across multiple gauging stations in the Ethiopian Upper Blue Nile Basin.
    • Ensembles of CMIP6 climate models improved the reliability of hydrological simulations compared with individual climate models.
    • Optimized climate-model selection reduced biases in hydrological simulations more than bias correction alone.
    • Arbitrary selection of climate models can degrade hydrological simulations, even when their outputs are bias-corrected using robust methods.
    • Both blue and green water are projected to increase under future climate change in the Ethiopian Upper Blue Nile Basin.
    • Blue water exhibits greater seasonality and climate sensitivity than green water flow and green water storage.
    The study also provides sustainable water management options for adapting to the impacts of climate change, with implications for water resource planning and management in the Upper Blue Nile Basin…”
    #Bluewater #Greenwater #CMIP6 #GCMs #Modelensemble #SSPscenarios #SWAT #Ethopia #UpperNile #Nile #NileBasin #gaging #gauging #Africa #climatechange #impacts #water #hydrology #KessieWatershed #EthiopianUpperBlueNileBasin #model #modeling #spatialanalysis #spatiotemporal #CMIP6 #waterresources #watermanagement #ecosystem #habitat #environment

    #bluewater #greenwater #cmip6 #gcms #modelensemble #sspscenarios
  17. 💧🌏 Greg Cocks @[email protected] ·

    Comparing DESIS Hyperspectral and Landsat 10 Simulated Superspectral Data for Crop Type Classification in California’s Central Valley
    --
    doi.org/10.3390/rs18142282 <-- shared paper
    --
    usgs.gov/publications/comparin <-- shared USGs publication page
    --
    H/T @USGS
    “How can we get better at classifying crops from space? 🛰️🌽
    Some types of satellite imagery are better at distinguishing crops than others. A USGS study compared two approaches and found one produced more accurate crop maps.
    Here's what the researchers found:
    • Hyperspectral imagery achieved 86% accuracy, compared to 75% for simulated superspectral imagery.
    • Using just 14 carefully selected hyperspectral bands produced nearly the same results as using all 60 DLR Earth Sensing Imaging Spectrometer (DESIS) bands, showing those wavelengths contain much of the information needed to distinguish crop types.
    • Using superspectral imagery on the upcoming Landsat 10 mission will allow for routine tracking of crops and enhance finer crop mapping.
    • The findings help scientists identify which wavelengths provide the most useful information for crop mapping and future remote sensing applications.
    Better crop maps will help governments and scientists track global agriculture, monitor the current crop season, and study agricultural trends…”
    --
    “HIGHLIGHTS:
    • What are the main findings?
    - The 14 DESIS hyperspectral narrowbands (10 nm) aligned with the Landsat 10 (formerly Landsat Next) spectral dataset produced similar accuracy results to the full 60-band DESIS hyperspectral dataset for classifying crop types. These 14 DESIS narrowbands resulted in higher accuracy than the 14 simulated Landsat 10 superspectral broadbands.
    - When using DESIS narrowbands, Support Vector Machine (SVM) resulted in higher accuracy than Random Forest (RF).
    • What are the implications of the main findings?
    - A carefully selected set of 14 DESIS hyperspectral narrowbands (10 nm) can achieve classification accuracy comparable to those obtained using all 60 DESIS narrowbands across the 400–1000 nm range. These 14 strategically positioned narrowbands classified crop types with higher classification accuracy than the corresponding 14 Landsat 10 superspectral broadbands within the same spectral range.
    - This study underscores the importance of multi-temporal imagery across the full crop-growing season for achieving more detailed and accurate crop type classifications. Such temporal coverage is more feasible with the planned Landsat 10 routine acquisition of broadband imagery than with task-based hyperspectral collections…”
    #hyperspectral #superspectral #optimalbands #randomforest #supportvectormachine #agriculture #crops #croptype #classifaction #croplands #California #CentralValley #GIS #spatial #mapping #remotesensing #earthobservation #imagery #DESIS #Landsat #Landsat10 #satellite #spatialanalysis #spatiotemporal #global #AI #machinelearning #model #modeling #SupportVectorMachine #SVM #RandomForest #RF #GoogleEarthEngine
    @USGS

    #hyperspectral #superspectral #optimalbands #randomforest #supportvectormachine #agriculture
  18. 💧🌏 Greg Cocks @[email protected] ·

    WeatherNext – [An] AI Model Achieves Breakthrough In Forecasting Cyclones
    --
    deepmind.google/blog/weatherne <-- shared technical Google DeepMind blog post
    --
    doi.org/10.1038/s41586-026-109 <-- shared paper
    --
    deepmind.google/science/weathe <-- shared data
    --
    github.com/google-deepmind/wea <-- shared GitHub repository
    --
    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
  19. 💧🌏 Greg Cocks @[email protected] ·

    Spatiotemporal Distribution, Climatic Factors, And Seasonal Precipitation Patterns Characterizing 66 Years Of Widespread Shallow Landslide Events In Piedmont (Northwestern Italy)
    --
    doi.org/10.3389/feart.2026.188 <-- shared paper
    --
    “Widespread shallow landslide events constitute one of the primary drivers of recurrent societal and economic losses in mountain regions. Although the influence of climate variability on landslide frequency and magnitude has been widely recognized, long-term, event-level analyses linking spatiotemporal landslide patterns to precipitation climatology at the regional scale remain scarce. This study presents a statistical analysis of 128 widespread shallow landslide events recorded in Piedmont, northwestern Italy, over the 66-year period 1960–2025, cross-referenced against the regional precipitation climatology. Events were characterized by season, primary physiographic unit, provincial coverage, and an ordinal magnitude index (scale 1–7) encoding combined spatial extent and estimated landslide count. Results indicate that no statistically significant monotonic trend in event frequency was detected over the study period (mean rate: 1.97 events yr⁻1); however, a moderate positive correlation was established between event magnitude and the number of provinces affected (R2 = 0.51, p < 0.00), validating the magnitude index as a proxy for spatial footprint. Mean event magnitude reached its highest value in the 2010s (3.71), while all five events of magnitude ≥ 6 occurred in autumn. The summer fraction of the catalogue increased markedly, from 6% in the 1960s to 31% in the 2000s and 25% in the 2020s, concurrent with stable or declining summer mean precipitation totals, consistent with Clausius–Clapeyron amplification of convective intensity under documented regional warming. Cross-analysis with regional records identifies three tiers of rainfall–landslide coupling: a stationary direct seasonal coupling; a non-stationary, strengthening intensity-mediated summer coupling; and a structural susceptibility-mediated spatial decoupling whereby the driest provinces generate the highest landslide occurrence frequencies due to the lower triggering thresholds characteristic of Tertiary Piedmont Basin sedimentary environments. A post-hoc assessment of the triggering thresholds used for regional shallow landslide early warning system demonstrates superior detection performance for high-magnitude autumn events (hit rate up to 89% for the 2000–2025 sub-period) and identifies sub-daily convective accumulation windows in summer as the primary domain requiring threshold recalibration…”
    #massmovement #landslide #engineeringgeology #Italy #Piedmont #NorthernItaly #weather #rainfall #precipitation #climate #risk #hazard #corrleation #relationship #earlywarningsystems #damage #loss #community #infrastructure #mountain #spatiotemporal #mapping #spatialanalysis #statistics #geostatistics #climatology #regional #scale #weatherpatterns #physiography #geomorphology #water #hydrology #hydrogeomorphology #geology #soils

    #massmovement #landslide #engineeringgeology #italy #piedmont #northernitaly
  20. 💧🌏 Greg Cocks @[email protected] ·

    Widespread Landslide Activity in an Extreme Wet Season and Implications for Regional Sediment Management, Eastern San Francisco Bay Area, California
    --
    doi.org/10.1029/2026EA005227 <-- shared paper
    --
    H/T @amy East, Ph.D., P.G. | Researcher integrating geoscience and climate-change preparedness
    “[This paper (link above) is] a collaboration with [the H/T’s] colleagues from [the] USGS Landslide Hazards Program, who mapped over 8,900 landslides in the eastern San Francisco Bay Area during an extreme wet winter.
    How much sediment does such an extreme winter produce, from landslides or in stream discharge? How does that compare with long-term sediment production and landscape denudation rates?
    [They] f[o]nd that landslide sediment mobilization is comparable to long-term denudation rates, emphasizing the role of extreme events in long-term sediment production. However, one extreme wet year has a negligible effect toward counteracting ongoing problems of sediment deficit in San Francisco Bay: to keep pace with sea-level rise, extreme wet conditions would need to occur in 50 out of the next 75 years…”
    --
    "PLAIN LANGUAGE SUMMARY: Watersheds will likely produce more sediment in a warmer future with more extreme rain, primarily through landslides in steep terrain. This study examines how an extremely wet season affected sediment production and transport in the eastern San Francisco Bay area, California. By mapping and measuring 8,928 landslides, [they] found that rare, extreme rain conditions are likely responsible for the vast majority of long-term hillslope erosion rates in this region. However, due to long residence times for sediment on hillslopes and in stream channels, a maximum of 1%–2% of that newly mobilized landslide material could have potentially contributed to sediment carried by streams into the Bay that year. Even extremely wet years cannot provide enough sediment for Bay wetlands and shorelines to keep pace with rising sea levels. To meet the demand for sediment in the Bay, such extreme rain and sediment production would need to occur in most years, which is not realistic. To restore wetlands and protect shorelines, managers likely will need to supplement the coastal system with repurposed dredged material…”
    #massmovement #soil #water #hydrology #hydrography #geology #soils #geomorphometry #hydrogeomorphology #geomorphology #landslide #masswasting #climatechange #extremeweather #precipitation #rainfall #weather #climate #mapping #engineeringgeology #mapping #SanFrancisco #BayArea #USA #California #fedscience #fedservice #oublicgood #sediment #stream #discharge #extremewinter #sealevelrise #SLR #hillslope #erosion #sedimentation #tidal #wetlands #coast #coastline #shoreline #GIS #spatial #spatialanalysis #spatiotemporal #watershed
    #USGS | #USGSLandslideHazardsProgram

    #massmovement #soil #water #hydrology #hydrography #geology
  21. 💧🌏 Greg Cocks @[email protected] ·

    The Portrait of Flood Risk in Italy - Past, Present and Future, From 1870 to 2100
    --
    doi.org/10.1029/2026GL122987 <-- shared paper
    --
    “ABSTRACT: Among European countries, Italy ranks as one of the most susceptible to flood risk. While this figure is already substantial, climate change and rapid urbanization in flood-prone areas have been identified as the two main drivers expected to elevate the number of individuals at risk. This study offers a comprehensive assessment of these two drivers of flood risk in Italy over 230 years, from 1870 to 2100, focusing on how they interact to increase risk. Using the large-scale flood risk model RESCUE-FR, [the authors] analyze[d] the population at risk under the 200-year return period scenario to provide a targeted assessment of population risk, how it has evolved in the past, and its projection in the future. [Their] findings indicate that while historical flood risk in Italy has primarily been influenced by population growth and migration into at-risk areas, future projections suggest that climate change will become the dominant driver of flood risk.
    PLAIN LANGUAGE SUMMARY: Italy is one of the European countries most at risk of flooding. This study examines the impact of two risk factors on flood risk in Italy over the long term, from 1870 to 2100: climate change and the evolution of population in areas prone to flooding. Using a large-scale flood risk model, [they] simulated different scenarios for different time periods, such as with and without climate change, to estimate how each factor contributes to the number of people exposed to floods in the past and future. [Their] results show that population growth and migration into flood-prone areas were the main reasons for the increased risk in the past. In the future, however, climate change is likely to become the dominant factor, putting more people at risk. Understanding how these factors interact can help communities to plan more effectively for floods and reduce the number of people affected…”
    #flood #flooding #risk #hazard #Italy #Europe #national #history #historic #cost #damage #infrastructure #floodrisk #population #urbanisation #development #climatechange #extremeweather #dominantfactor #floodprone #national #regional #spatialanalysis #spatiotemporal #model #RESCUEFR #modeling #factors #parameters #drivers #publicsafety

    #flood #flooding #risk #hazard #italy #europe
  22. 💧🌏 Greg Cocks @[email protected] ·

    Impact Of Urbanization Driven Land Use And Land Cover Change On Ecological Environmental Quality In Rupandehi Nepal Assessed Using The Remote Sensing Ecological Index
    --
    doi.org/10.1007/s44288-026-006 <-- shared paper
    --
    kathmandupost.com/money/2026/0 <-- shared media article
    --
    H/T@ Gaurav Parajulim
    “[The authors] studied how the ecological quality of Nepal's Rupandehi District has changed over three decades (1993–2023), using satellite imagery and the Remote Sensing Ecological Index (RSEI) to track the health of the landscape year by year and to understand how urbanization-driven land use change has reshaped it.
    What [they] found tells a nuanced story: as Butwal and Bhairahawa grew and built-up land expanded, ecological quality shifted in ways that a single number can't capture, some areas recovered, others declined, and the patterns rarely moved in a straight line…”
    --
    “Rapid urbanization and population growth are major drivers of land use and land cover (LULC) change and can substantially alter ecological environmental quality (EEQ). This study assessed the spatiotemporal dynamics of LULC and their effect on EEQ in Rupandehi District, Nepal, over a 30-year period (1993–2023). Four ecological indicators representing greenness, wetness, dryness, and heat were derived from Landsat imagery in Google Earth Engine (GEE), and LULC was classified using a Support Vector Machine (SVM). The Remote Sensing Ecological Index (RSEI) was then constructed from these indicators using Principal Component Analysis (PCA) in ArcGIS Pro, and its spatial structure was examined using global and local spatial autocorrelation. The mean RSEI followed a non-linear trajectory, rising from 0.59 in 1993 to 0.635 in 2004, declining to 0.55 in 2013, and recovering to 0.67 in 2023, indicating an overall improvement in EEQ with a temporary mid-period decline. Over the same period, built-up areas expanded substantially and agricultural land declined, whereas forest cover fluctuated but showed a slight net increase by 2023, and barren land decreased markedly. Higher EEQ was concentrated in the forested northern hills, while lower values occurred in the urban centers of Butwal and Bhairahawa, closely matching the spatial pattern of LULC change. The results indicate that ecological quality reflects the combined influence of all land cover classes rather than any single class. This study provides a transferable and reproducible workflow for long-term ecological assessment based on openly available Landsat data, with the analysis code shared in a public repository, offering practical guidance for sustainable land management and environmentally responsible urban development...”
    #GIS #spatial #mapping #RemoteSensing #GIS #RSEI #EnvironmentalMonitoring #Nepal #Research #GoogleEarthEngine #ArcGIS #EcologicalQuality #spatialautocorrelation #ecology #environment #earthobservation #RemoteSensingEcologicalIndex #landscape #urbanisation #urban #development #landuse #change #spatialanalysis #spatiotemporal

    #gis #spatial #mapping #remotesensing #rsei #environmentalmonitoring
  23. 💧🌏 Greg Cocks @[email protected] ·

    Geospatial Analysis of Carbon Offset Projects - A Broader Scientific Outlook
    --
    eldhollow.com/blogs/geospatial <-- shared technical blog
    --
    [this post should not be considered an endorsement of a particular organisation, rather scrutinising the spatial use case & technical approach]
    H/T @kyle Arvisais | Forest Carbon Scientist
    “Geospatial analysis is at the core of [the H/T’s company’s] project quality assessments, and [the author is] constantly finding ways to make the pipeline better and ways to use it. [They are] obviously not the only one who uses these types of tools, but to be perfectly honest, the quality of models [they have] seen over the years has been all over the place.
    This blog makes a casual introduction to [their] pipeline while talking about the field at large…”
    --
    “The world has committed to protecting and restoring nature at an unprecedented scale. Whether that commitment delivers what it promises comes down project execution on the ground. Local socioeconomics and forest ecology intertwine to create complex challenges for projects to overcome during implementation, and at the end of the day, projects boil all of these complexities down to one single unit: the carbon credit. So the question becomes: can we actually measure what is happening to a forest, accurately and honestly, and everywhere at once?
    For a long time, the honest answer has been no. Historically, many forest carbon projects overstated their impact. Usually it was because the baseline was too generous, or because the measurements underneath were flawed. For anyone with a stake in nature markets, that uncertainty is one of the core risks.
    Robust geospatial analysis can help mitigate that risk. If you treat a carbon credit as what it really is, a scientific claim, then we can hold it to that standard and assess it objectively. [Their] geospatial pipeline turns satellite data and ground truth data into models about how much forest is standing, how it is changing, and what might put it at risk in the future. The pipeline does this anywhere on Earth…”
    #GIS #spatial #mapping #usecase #carbonoffset #spatialanalysis #spatiotemporal #qualityassessment #objectivity #projectpipeline #model #modeling #application #nature #environment #ecosystems #ecology #local #regional #factors #socioeconomics #forestecology #vegetation #forest #tree #carboncredit #climatechange #climatecrisis #forestcarbonprojects #global

    #gis #spatial #mapping #usecase #carbonoffset #spatialanalysis
  24. 💧🌏 Greg Cocks @[email protected] ·

    Classification And Conceptualization Of Karst Recharge Processes Through Spectral And Change Point Analysis Of Drip Water Dynamics
    --
    doi.org/10.1029/2025WR042816 <-- shared paper
    --
    H/T @ Danyang Sun | UNSW-PhD student
    “… [The authors] analysed one year of drip water monitoring data from 46 monitoring sites across six karst regions in southeastern Australia. By integrating fast Fourier analysis, cross-wavelet transform and change point analysis, [they] identified five characteristic recharge behaviours and developed a conceptual framework linking temporal drip dynamics with recharge mechanisms. [They] hope this framework will contribute to a better understanding of recharge heterogeneity in karst systems and support future groundwater research under a changing climate…”
    #karst #Australia #water #hydrology #underground #subsurface #recharge #dynamics #spectral #changepoint #cave #dripwater #analysis #spatiotemporal #groundwater #research #climatechange #extremeweather #flow #storage #vadose #epikarst #watertable #aquifer #percolation #rainfall #precipitation #climate #lithology #geology #spatialanalysis

    #karst #australia #water #hydrology #underground #subsurface
  25. 💧🌏 Greg Cocks @[email protected] ·

    Coastal Flooding At Predictable Hours
    --
    doi.org/10.1038/s41467-026-757 <-- shared paper
    --
    H/T @bruna Alves | Nature Communications | Editor
    “When do coastal floods happen? ⏱️🌊
    A new study [link above] shows that, in many tide-dominated coastal regions, flooding tends to occur at specific and recurring times of day. Rather than being completely random, flood events often cluster around predictable hours driven by local tidal patterns.
    By analysing coastal flood observations from the UK and the US, [the authors] show[ed] that the timing of flood events can be highly structured, with some locations experiencing floods disproportionately during certain parts of the day.
    This adds a temporal dimension to coastal flood risk. We often focus on how frequently floods occur, how severe they are, and where they happen. This study highlights that when they occur may also matter, particularly as rising sea levels increase the frequency of coastal flooding.
    The findings provide a useful perspective for coastal adaptation, risk communication, and emergency planning…”
    --
    “Flooding is typically perceived as a sudden and unpredictable hazard. Here, [they] show that recurrent flooding can occur at highly predictable times in tidally dominated coastal systems. This predictability stems from phase-locking of tidal constituents and constituent pairs with the solar day, causing peak tides to recur at consistent local times set by regional tidal propagation. Using tide-gauge records from the United States and the United Kingdom, [they] quantif[ied] the intraday timing of coastal flood events and show strong clustering at specific hours, particularly where semidiurnal or mixed tides dominate. For example, floods in Boston cluster around noon and midnight, whereas in southern California they occur in the morning. Sites with stronger non-tidal variability show weaker clustering. This temporal predictability extends beyond nuisance flooding to larger consequential events involving inundation, road closures and infrastructural damage, highlighting opportunities for anticipatory risk communication, emergency planning and time-sensitive coastal adaptation…”
    #coast #coastal #flood #flooding #spatialanalysis #spatiotemporal #time #statistics #geostatistics #tide #tidal #timing #temporal #floodrisk #risk #hazard #sealevel #sealevelrise #climatechange #emergency #planning #tideguage #UK #USA #innundation #infrastructure #transportation #riskcommunication

    #coast #coastal #flood #flooding #spatialanalysis #spatiotemporal
  26. 💧🌏 Greg Cocks @[email protected] ·

    The Latest Data Confirms - Forest Fires Are Getting Worse
    --
    wri.org/insights/global-trends <-- shared technical article
    --
    alturl.com/efp6m <-- shared (focused) #GlobalNatureWatch web map
    --
    science.nasa.gov/earth/explore <-- shared NASA technical article, ‘Wildfires and Climate Change’
    --
    doi.org/10.3389/frsen.2022.825 <-- shared paper
    --
    doi.org/10.1073/pnas.2505418122 <-- shared paper
    --
    doi.org/10.1088/1748-9326/add6 <-- shared paper
    --
    globalnaturewatch.org/dashboar <-- shared Global Nature Watch dashboard
    --
    youtu.be/-0-pv1Bqm-U?si=IHcZJN <-- shared overview video
    --
    grist.org/wildfires/the-us-has <-- shared technical article, ‘Fire is responsible for a quarter of US forest loss since 2021’
    --
    nytimes.com/2026/04/29/climate <-- shared media article
    --
    H/T @ World Resources Institute
    [‘topical’ - Europe, North America, indeed globally, more & more…]
    “New data shows that forest fires are getting worse, burning more than twice as much tree cover today as they did 20 years ago, largely due to climate change…
    The latest data [2nd link above] confirms [that] forest fires are becoming more widespread and destructive around the globe. Updated data from researchers [3rd link above] shows that between 2001 and 2025 forest fires now burn over twice as much tree cover each year as they did two decades ago, and more than three times as much in the tropics.
    This increased fire activity has been starkly visible in recent years. Record-setting blazes are becoming the norm, with four of the five worst years for global forest fires occurring since 2021. As fires worsen - including in historically low-risk areas, like rainforests - they are becoming an increasingly prevalent driver of global forest loss…”
    #GlobalForestWatch #GlobalNatureWatch #deforestation #fire #wildfire #forest #vegetation #climatechange #risk #hazard #loss #ecosystems #GIS #spatial #mapping #remotesensing #earthobservation #spatialanalysis #spatiotemporal #global #worldwide #forestfire #damage #destruction #fireactivity #forestLOSS
    @WRI | @Global Nature Watch

    #globalnaturewatch #globalforestwatch #deforestation #fire #wildfire #forest
  27. 💧🌏 Greg Cocks @[email protected] ·

    From Fragmentation To Integration - A Review Of Data–Model Integration In Land Subsidence Research
    --
    doi.org/10.1016/j.ancene.2026. <-- shared paper
    --
    H/T @manonzero current drought conditions, increasing pressure on ecosystems, and ongoing climate adaptation challenges, land subsidence is receiving growing attention worldwide.
    For anyone wanting to learn more about land subsidence, or get a refresher, [the authors] provide an overview of the processes involved, the ways it can be measured or estimated, the models used to simulate it, and how observations and models can be combined, [their] new [#openaccess] review paper [link above] may be of interest!
    A central message of the paper is that understanding and managing land subsidence requires bringing these different sources of information together…”
    --
    “HIGHLIGHTS:
    • Presents a comprehensive synthesis that unifies all major elements of integral land-subsidence research.
    • Defines the methodological steps needed for full integration and positions them within the broader challenges posed by subsidence.
    • Brings together and distills the key components of data, modelling, and integration into a coherent framework.
    ABSTRACT: Land subsidence, the sinking of the Earth’s surface, is a multi-faceted hazard driven by both natural and anthropogenic factors, and poses significant risk to environments, ecosystems, and society. Despite decades of growing research output, substantial gaps persist between investigations on the diversity of causes, reflected in data and model insufficiency. These gaps hinder the understanding of the issue and impede the effectiveness of mitigation measures. Many studies have urged to include all identified subsidence processes acting in a single area in an integral framework, for which a complex analysis has not systematically been outlined before. Therefore, [they] focus here on bridging the gaps between various technical research disciplines involved. [They] stress the urgency for an integral approach that combines observations with subsurface information of all known subsidence processes in an area, and [they] appeal for utilizing them in physics-guided data integrations. Only then can all subsidence drivers be understood, and effective mitigation measures designed. [They] outline the elements for an integral approach in categorical tables and schematized figures, and [they] discuss the main opportunities and challenges in a stepwise workflow. Leveraging these opportunities naturally leads to more robust, scalable, and policy-relevant solutions and fosters a more sustainable future…”
    #Land #subsidence #processes #Verticallandmotion #SLR #sealevel #sealevelrise #relativesealevelrise #modeling #data #model #InSAR #elevation #holistic #GIS #spatial #mapping #climate #drought #extremeweather #climatechange #climateadaption #ecosystems #measurement #monitoring #research #review #framework #overview #risk #hazard #anthropogenic #mitigation #engineering #water #hydrology #policy #planning #design #remotesensing #spatialanalysis #spatiotemporal

    #land #subsidence #processes #verticallandmotion #slr #sealevel
  28. 💧🌏 Greg Cocks @[email protected] ·

    Flood And Landslide Susceptibility Assessment And Multi Hazard Interaction Mapping Using Machine Learning And GIS For Sustainable Settlement Planning In Nepal
    --
    doi.org/10.1007/s44288-026-006 <-- shared paper
    --
    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

    #gis #spatial #mapping #googleearthengine #machinelearning #remotesensing
  29. 💧🌏 Greg Cocks @[email protected] ·

    Enhancements To The USGS Landsat Level 2 Surface Temperature And Emissivity Product For Collection3 Reprocessing
    --
    doi.org/10.1016/j.rse.2026.115 <-- shared paper
    --
    H/T @terry Sohl | USGS EROS Science Branch Chief
    “HIGHLIGHTS:
    • C3 advances Landsat TIR atmospheric correction, emissivity correction, and uncertainty estimates.
    • C3 enables global surface temperature products, including polar regions.
    • C3 retrievals improve accuracy and consistency across validation sites.
    • Split window and single channel methods diverge at extreme temperature conditions.
    • C3 and Landsat 10 support multi-decadal climate monitoring.
    ABSTRACT: The Landsat program provides the longest continuous global record of thermal infrared observations of the Earth's surface, underpinning critical applications in climate monitoring, water resources, ecosystem dynamics, urban heat analysis, and natural hazard assessment. The release of a global inventory of Landsat Collection 2 Level 2 surface temperature products by the U.S. Geological Survey (USGS) marked a major milestone in operational provision of Landsat thermal infrared analysis-ready data. Ongoing validations and community uses of Collection 2 have identified opportunities to further improve accuracy, uncertainty characterization, and emissivity correction across diverse atmospheric and surface conditions. In preparation for the planned Landsat Collection 3 reprocessing of the Landsat data record in the late 2020s, the USGS is implementing a coordinated set of enhancements to the Level 2 surface temperature products. These include revised emissivity estimation that leverages external datasets, improved atmospheric characterization and uncertainty propagation, expanded dynamic range for high temperature targets, consideration of split window atmospheric correction algorithm for Landsat 8 and 9, and decoupling of thermal infrared processing from visible to shortwave infrared constraints to enable surface temperature retrievals under low or no solar illumination conditions. These changes are designed to improve product quality and consistency across the Landsat record. Beyond near-term performance gains, the Collection 3 design establishes a scalable processing architecture to accommodate the expanded spectral and radiometric measurement capabilities of the forthcoming Landsat 10 mission. By preserving continuity across the Landsat 4–9 record while enabling future algorithm evolution, Landsat Collection 3 will provide a foundation for long-term, multi-decadal Earth system thermal infrared observations…”
    #GIS #spatial #mapping #satellite #remotesening #earthobservation #Landsat #thermalinfrared #TIR #surface #temperature #emissivity #thermal #infrared #analysisreadydata #Collection2 #Collection3 #opendata #atmosphericcorrection #global #climate #monitoring #waterresources #ecosystems #dynamics #urbanheat #spatialanalysis #spatiotemporal #naturalhazards #updates #EROS #USGS
    @USGS EROS | @USGS

    #gis #spatial #mapping #satellite #remotesening #earthobservation
  30. 💧🌏 Greg Cocks @[email protected] ·

    Modeling Flood Susceptibility Utilizing Advanced Ensemble Machine Learning Techniques in the Marand Plain [Iran]
    --
    doi.org/10.3390/geosciences150 <-- 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…”
    --
    “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

    #floodsusceptibility #floodrisk #machinelearning #gis #naturalhazards #disastermanagement
  31. 💧🌏 Greg Cocks @[email protected] ·

    [Open] Data Related To Flood Mapping [Canada]
    --
    natural-resources.canada.ca/sc <-- shared link to technical details
    --
    app.geo.ca/en-ca/map-browser/r <-- shared map/data-portal link, Canada Flood Map Inventory (CFM)
    --
    open.canada.ca/data/en/dataset <-- shared data-portal link, Canada Flood Susceptibility Index
    --
    doi.org/10.3390/ECWS-7-14235 <-- shared (2023) paper
    --
    doi.org/10.1002/2017WR020917 <-- shared (2017) paper
    --
    H/T @Michael DePue | VP & AtkinsRéalis Fellow for Water Resources Engineering | PE, PMP, CFM
    “At the Canadian Water Resources Association National Conference in Winnipeg, colleagues shared insights from Canada's Flood Hazard Identification and Mapping Program. This initiative has seen over 400 flood mapping projects and more than 1,000 flood hazard maps produced, supported by a substantial investment of $164.2 million from 2024 to 2028.
    Two key datasets:
    • The Canada Flood Map Inventory, which records the locations of flood hazard maps and provides information on how to access them.
    • The national Flood Susceptibility Index, a machine-learning assessment of flood-prone areas, including regions that have not been mapped in detail.
    When these two layers are combined on a single screen, it becomes clear where future mapping efforts should be directed — specifically, areas with high susceptibility that currently lack detailed maps…”
    #water #hydrography #flood #flooding #risk #hazard #model #modeling #fedscience #publicsafety #humaninpacts #opendata #Canada #GIS #spatial #mapping #damage #infrastructure #floodmapping #prediction #spatialanalysis #spatiotemporal #historic #current #future #preduction #extremeweather #metrology #rainfall #precipitation #atmosphericriver #FloodMapInventory #CFM #floodhazard #FloodSusceptibilityIndex #floodprone #research #susceptibility
    @NRCAN

    #water #hydrography #flood #flooding #risk #hazard
  32. 💧🌏 Greg Cocks @[email protected] ·

    Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome
    --
    openscholar.uga.edu/record/269 <-- shared technical publication / dissertation
    --
    aag.org/award-grant/william-l- <-- shared @AAG William L. Garrison Award for Best Dissertation in Computational Geography
    --
    [again, way outside any expertise I might have, but fascinating spatial analysis use case…]
    H/T @Jielu Zhang | Postdoctoral Researcher @ Harvard University
    “[The authors] Ph.D. dissertation "Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome" [1st link above] has received the 2026 biennial William L. Garrison Award for Best Dissertation in Computational Geography from the American Association of Geographers… [2nd link above.]
    In [their] research, [they] develop[ed] Explainable GeoAI and Causal GeoAI methods that combine geographic data and artificial intelligence to expose and ameliorate health disparities by delivering models that not only predict risks but also illuminate how and where to intervene. While [their] dissertation focused on cardiovascular disease, these approaches are broadly applicable to public health, medicine, urban planning, environmental exposure, and resilience research…”
    #explainable #causal #AI #model #modeling #PublicHealth #GIS #spatial #mapping #spatialanalysis #spatiotemporal #AAG2026 #AAG #Award #geostatistics #Georgia #health #risk #hazard #cardiacarrest #cardiovacscular #usecase #metrics #midocine #urbanplanning #resilience #survival #OutofHospital #PhD #Dissertation #CardiacArrest #AutomatedExternalDefibrillator #SpatialOptimization #GeographicallyExplainableArtificialIntelligence #GeoAI #GeoXAI #SpatiallyAwareCausalInference #OverlayedSpatioTemporalOptimization #healthcare #medical #intervention #GIS #spatial #mappingt #spatialanalysis #spatiotemporal #heart #heartattack #AED #survival #survivaloutcomes #machinelearning #AI #publichealth #healthgeographers #counterfactual #explainable #deeplearning #model #modeling

    #explainable #causal #ai #model #modeling #publichealth
  33. 💧🌏 Greg Cocks @[email protected] ·

    A National-Scale Database Of Groundwater Level Data For Switzerland
    --
    doi.org/10.1038/s41597-026-073 <-- shared paper
    --
    H/T @RaoulCollenteur | Groundwater Hydrologist at Collenteur HydroConsult GmbH
    “Looking for a ready-to-use FAIR dataset with groundwater levels, signatures, and meteorological drivers to test new models and analysis methods to learn from groundwater level data? Why not try [the authors’] new Swiss Groundwater Database with almost 1,000 piezometers in diverse climatological and hydrogeological settings within Switzerland? 💡
    💧 Long groundwater level time series with frequent measurements
    💧 Meteorological drivers included
    💧Unique dataset in terms of hydrogeological data in an alpine setting
    … [They] hope [that they] can develop the database in the future with other variables (i.e., groundwater temperature, spring discharge, etc.) and welcome additions and collaborations to make this happen. 🌊…”
    --
    “Groundwater is a vital component of the global supply of freshwater, playing a critical role for human populations, agriculture, and ecosystems. Due to the complex interactions between groundwater, surface water, climate, and human activity, these systems are frequently studied using advanced data analysis and modeling techniques. The effectiveness of these methods is generally enhanced by the availability and quality of data. In Switzerland, the focus area of this study, groundwater data is fragmented and lacks a standardized nationwide compilation. Consequently, the process of conducting nationwide studies with substantial sample sizes is both resource-intensive and time-consuming. In this paper, [they] introduce the Swiss Groundwater Database, a comprehensive compilation of groundwater time series and associated metadata throughout Switzerland. The current database consists of groundwater level data from 985 monitoring wells, which were completed with additional static and time-varying variables. The environmental characteristics and climate indices were compiled and determined for each monitoring well. The database is designed to facilitate and support large-sample hydrological research related to groundwater in Switzerland and beyond…”
    #water #hydrography #database #GIS #spatial #mapping #groundwater #Switzerland #FAIR #SwissGroundwaterDatabase #opendata #hydrogeology #meteorology #weather #climate #alpine #waterresources #agriculture #ecosystems #humanimpacts #spatialanalysis #spatiotemporal #model #modeling #dataanalysis #nationwide #metadata #monitoring #wells
    @Federal Office for the Environment FOEN | @Federal Office of Meteorology and Climatology MeteoSwiss

    #water #hydrography #database #gis #spatial #mapping
  34. 💧🌏 Greg Cocks @[email protected] ·

    Unraveling The Drivers Of Water Shortage Across Spatial Scales And Sectors In Colorado's West Slope River Basins
    --
    doi.org/10.1029/2026EF008137 <-- shared paper
    --
    ['sorry' about your Kentucky Bluegrass, almonds, etc... /s]
    H/T Sai Veena Sunkara | Postdoctoral Associate
    “…Colorado’s West Slope basins provide nearly 70% of the inflows to Lake Powell and are also essential to communities, agriculture, industry, hydropower, and downstream Colorado River users.
    To examine the wide range of possible futures, [they] simulated 2.1 million years, defining 20,000 plausible scenarios applying changes to streamflow, snowmelt timing, drought persistence, and agricultural, municipal, and industrial water demand.
    A key finding is that there is 𝗻𝗼 𝘀𝗶𝗻𝗴𝗹𝗲 𝗰𝗮𝘂𝘀𝗲 𝗼𝗳 𝗳𝘂𝘁𝘂𝗿𝗲 𝘄𝗮𝘁𝗲𝗿 𝘀𝗵𝗼𝗿𝘁𝗮𝗴𝗲𝘀. The most influential drivers vary by basin, sector, and water user. In some areas, shortages are driven primarily by persistent low-flow conditions or changing snowmelt timing. In others, increasing municipal, industrial, or irrigation demand plays a larger role. This suggests that adaptation strategies must be tailored to specific basins and users rather than relying on a single, system-wide solution. Other major findings are
    • West Slope deliveries to Lake Powell could fall more than 50% below the current median baseline
    • Storage in major West Slope reservoirs could decline 40–55% below historical medians
    These results underscore the need for water-planning approaches that account for deep uncertainty, persistent drought, shifting snowmelt patterns, and sector-specific demand…”
    #Colorado #waterallocation #StateMod #USWest #USA #WesternSlope #waterresources #watersecurity #watershortage #drought #snowmelt #rainfall #precipitation #riverbasin #water #hydrography #hydrology #reasons #agriculture #industry #hydropower #streamflow #surfacewater #municipal #irrigation #adaptationstrategies #planning #policy #mitigation #ColoradoRiver #basins #climatechange #extremeweather #populationpressure #waterdemand #waterrights #model #modeling #HiddenMarkovModel #stochastic #projecteddemand #ColoradoRiverBasin #wateruse #spatial #mapping #spatialanalysis #spatiotemporal #strategy

    #colorado #waterallocation #statemod #uswest #usa #westernslope
  35. 💧🌏 Greg Cocks @[email protected] ·

    Coupled Hydrological And Public Health Risks From Urban Flooding - Integrated Remote Sensing, Machine Learning, And Hydrodynamic–Ecological Modelling
    --
    doi.org/10.1016/j.jhydrol.2026 <-- shared paper
    --
    youtu.be/VHzYLvSYR7k?si=5oGGPe <-- recent overview video created about the research
    --
    doi.org/10.1016/j.wroa.2025.10 <-- share (earlier) paper
    --
    H/T @RAHUL DEOPA | Research Scholar (IIT Roorkee)
    “… [U]rban floods are not merely hydraulic events; they also transport sewage, pathogens, and other contaminants across streets and communities, leading to significant public health risks…
    How do we quantify microbial contamination in near real time during a flood event, when emergency conditions make field sampling unsafe, sparse, or even impossible?...
    [The authors] explored whether Earth observation data, combined with machine learning, could bridge this critical monitoring gap. By combining Landsat-derived water surface temperature, machine learning, a coupled MIKE+ Flood–ECO Lab hydrodynamic–ecological model, and Quantitative Microbial Risk Assessment (QMRA), [they] estimated microbial concentrations (𝘌. 𝘤𝘰𝘭𝘪), simulated their fate and transport during floods, and quantified the associated human health risks.
    The takeaway: predicting flood risk isn't just about where the water goes; it's about what it's carrying and who it puts in harm's way. Earth observation and machine learning can help close that gap when it matters most, during the emergency, not weeks after…”
    #publichealth #risk #hazard #watersecurity #Floodrisk #Humanhealthrisk #Urbanflooding #Hydrodynamicmodelling #waterquality #model #modeling #SupportVectorRegression #flood #flooding #urban #city #sewage #pathogens #contaminant #disease #streets #community #quantification #remotesensing #GIS #spatial #mapping #earthobservation #spatialanalysis #water #hydrology #climatechange #extremeweather #spatiotemporal #AI #machineleraning #fateandtransport #hydrodynamic #microbial #rainfall #drainage #streamflow #topography #hydrogeomorphology #Delhi #India #floodplain

    #publichealth #risk #hazard #watersecurity #floodrisk #humanhealthrisk
  36. 💧🌏 Greg Cocks @[email protected] ·

    Busy Beavers - The Turbidity Signature Of Ecosystem Engineers At Work
    --
    doi.org/10.1002/hyp.70661 <-- shared paper
    --
    H/T @alan Puttock
    “Beavers are the quintessential ecosystem engineers. In slow-flowing streams, they create complex wetlands with ponds by building dams and canals that can positively impact biodiversity, hydrology and water quality. These activities can interchangeably capture or release sediment along the watercourse. To date this has not been quantified at the resolution of rainfall events or beaver activity. This study used 15-min frequency, sustained monitoring upstream and downstream of a newly establishing beaver wetland to measure episodic changes in water turbidity at an event resolution. Monitoring showed no significant differences between upstream and downstream turbidity over 160 days when the first pair of beavers, known not to be building dams or canals, were resident. Shortly after introduction of another beaver pair, however, dam building, burrows and canal excavations were quickly observed, resulting in the creation of a complex beaver wetland between 2021 and 2024. Monitoring over 375 days during this period showed significant differences. Downstream turbidity was significantly higher overall than upstream: 13.1 Nephelometric Turbidity Units (NTU) compared to 4.2 NTU. Stochastic spikes in downstream turbidity during the study period not recorded upstream were associated with dam building and burrowing. Overall, there was no significant difference in turbidity loads, which was at least partially explained by a reduction in discharge downstream, particularly in higher flows, during the dam building period. This demonstrates a complex system with the trapping of influent sediment, the storing of water and the periodic release of beaver wetland sediment leading to net balance in loads. These results help provide context for other studies which have used temporally discrete sampling campaigns rather than continuous high-frequency monitoring. They provide a unique insight into the downstream impacts of a rapidly developing beaver wetland over its first three and a half years in a landscape that hasn't had beavers for over 400 years…"
    #hydromorphic #water #hydrology #dam #beaverdam #waterquality #biodiversity #ecology #benefits #NatureBasedSolutions #Wetlands #Ecology #Biodiversity #EnvironmentalScience #Wildlife #Ecosystem #bioviversity #conservation #restoration #landscaperecovery #floodmanagement #FloodMitigation #flooding #energy #floodrisk #sustainability #wetlands #hydrography #dams #impoundment #deadwood #waterresources #landscapeengineer #benefits #vegetation #ecology #ecosystem #riversystemsstabilisation #naturalwaterregulation #resilience #valleysreborn #fisheries #invertebrates #extremeweather #floodflows #sediment #baseflow #drought #landmanagement #naturalsystems #landuse #monitoring #spatialanalysis #spatiotemporal

    #hydromorphic #water #hydrology #dam #beaverdam #waterquality
  37. 💧🌏 Greg Cocks @[email protected] ·

    Busy Beavers - The Turbidity Signature Of Ecosystem Engineers At Work
    --
    doi.org/10.1002/hyp.70661 <-- shared paper
    --
    H/T @alan Puttock
    “Beavers are the quintessential ecosystem engineers. In slow-flowing streams, they create complex wetlands with ponds by building dams and canals that can positively impact biodiversity, hydrology and water quality. These activities can interchangeably capture or release sediment along the watercourse. To date this has not been quantified at the resolution of rainfall events or beaver activity. This study used 15-min frequency, sustained monitoring upstream and downstream of a newly establishing beaver wetland to measure episodic changes in water turbidity at an event resolution. Monitoring showed no significant differences between upstream and downstream turbidity over 160 days when the first pair of beavers, known not to be building dams or canals, were resident. Shortly after introduction of another beaver pair, however, dam building, burrows and canal excavations were quickly observed, resulting in the creation of a complex beaver wetland between 2021 and 2024. Monitoring over 375 days during this period showed significant differences. Downstream turbidity was significantly higher overall than upstream: 13.1 Nephelometric Turbidity Units (NTU) compared to 4.2 NTU. Stochastic spikes in downstream turbidity during the study period not recorded upstream were associated with dam building and burrowing. Overall, there was no significant difference in turbidity loads, which was at least partially explained by a reduction in discharge downstream, particularly in higher flows, during the dam building period. This demonstrates a complex system with the trapping of influent sediment, the storing of water and the periodic release of beaver wetland sediment leading to net balance in loads. These results help provide context for other studies which have used temporally discrete sampling campaigns rather than continuous high-frequency monitoring. They provide a unique insight into the downstream impacts of a rapidly developing beaver wetland over its first three and a half years in a landscape that hasn't had beavers for over 400 years…"
    #hydromorphic #water #hydrology #dam #beaverdam #waterquality #biodiversity #ecology #benefits #NatureBasedSolutions #Wetlands #Ecology #Biodiversity #EnvironmentalScience #Wildlife #Ecosystem #bioviversity #conservation #restoration #landscaperecovery #floodmanagement #FloodMitigation #flooding #energy #floodrisk #sustainability #wetlands #hydrography #dams #impoundment #deadwood #waterresources #landscapeengineer #benefits #vegetation #ecology #ecosystem #riversystemsstabilisation #naturalwaterregulation #resilience #valleysreborn #fisheries #invertebrates #extremeweather #floodflows #sediment #baseflow #drought #landmanagement #naturalsystems #landuse #monitoring #spatialanalysis #spatiotemporal

    #hydromorphic #water #hydrology #dam #beaverdam #waterquality
  38. 💧🌏 Greg Cocks @[email protected] ·

    Busy Beavers - The Turbidity Signature Of Ecosystem Engineers At Work
    --
    doi.org/10.1002/hyp.70661 <-- shared paper
    --
    H/T @alan Puttock
    “Beavers are the quintessential ecosystem engineers. In slow-flowing streams, they create complex wetlands with ponds by building dams and canals that can positively impact biodiversity, hydrology and water quality. These activities can interchangeably capture or release sediment along the watercourse. To date this has not been quantified at the resolution of rainfall events or beaver activity. This study used 15-min frequency, sustained monitoring upstream and downstream of a newly establishing beaver wetland to measure episodic changes in water turbidity at an event resolution. Monitoring showed no significant differences between upstream and downstream turbidity over 160 days when the first pair of beavers, known not to be building dams or canals, were resident. Shortly after introduction of another beaver pair, however, dam building, burrows and canal excavations were quickly observed, resulting in the creation of a complex beaver wetland between 2021 and 2024. Monitoring over 375 days during this period showed significant differences. Downstream turbidity was significantly higher overall than upstream: 13.1 Nephelometric Turbidity Units (NTU) compared to 4.2 NTU. Stochastic spikes in downstream turbidity during the study period not recorded upstream were associated with dam building and burrowing. Overall, there was no significant difference in turbidity loads, which was at least partially explained by a reduction in discharge downstream, particularly in higher flows, during the dam building period. This demonstrates a complex system with the trapping of influent sediment, the storing of water and the periodic release of beaver wetland sediment leading to net balance in loads. These results help provide context for other studies which have used temporally discrete sampling campaigns rather than continuous high-frequency monitoring. They provide a unique insight into the downstream impacts of a rapidly developing beaver wetland over its first three and a half years in a landscape that hasn't had beavers for over 400 years…"
    #hydromorphic #water #hydrology #dam #beaverdam #waterquality #biodiversity #ecology #benefits #NatureBasedSolutions #Wetlands #Ecology #Biodiversity #EnvironmentalScience #Wildlife #Ecosystem #bioviversity #conservation #restoration #landscaperecovery #floodmanagement #FloodMitigation #flooding #energy #floodrisk #sustainability #wetlands #hydrography #dams #impoundment #deadwood #waterresources #landscapeengineer #benefits #vegetation #ecology #ecosystem #riversystemsstabilisation #naturalwaterregulation #resilience #valleysreborn #fisheries #invertebrates #extremeweather #floodflows #sediment #baseflow #drought #landmanagement #naturalsystems #landuse #monitoring #spatialanalysis #spatiotemporal

    #hydromorphic #water #hydrology #dam #beaverdam #waterquality
  39. 💧🌏 Greg Cocks @[email protected] ·

    Busy Beavers - The Turbidity Signature Of Ecosystem Engineers At Work
    --
    doi.org/10.1002/hyp.70661 <-- shared paper
    --
    H/T @alan Puttock
    “Beavers are the quintessential ecosystem engineers. In slow-flowing streams, they create complex wetlands with ponds by building dams and canals that can positively impact biodiversity, hydrology and water quality. These activities can interchangeably capture or release sediment along the watercourse. To date this has not been quantified at the resolution of rainfall events or beaver activity. This study used 15-min frequency, sustained monitoring upstream and downstream of a newly establishing beaver wetland to measure episodic changes in water turbidity at an event resolution. Monitoring showed no significant differences between upstream and downstream turbidity over 160 days when the first pair of beavers, known not to be building dams or canals, were resident. Shortly after introduction of another beaver pair, however, dam building, burrows and canal excavations were quickly observed, resulting in the creation of a complex beaver wetland between 2021 and 2024. Monitoring over 375 days during this period showed significant differences. Downstream turbidity was significantly higher overall than upstream: 13.1 Nephelometric Turbidity Units (NTU) compared to 4.2 NTU. Stochastic spikes in downstream turbidity during the study period not recorded upstream were associated with dam building and burrowing. Overall, there was no significant difference in turbidity loads, which was at least partially explained by a reduction in discharge downstream, particularly in higher flows, during the dam building period. This demonstrates a complex system with the trapping of influent sediment, the storing of water and the periodic release of beaver wetland sediment leading to net balance in loads. These results help provide context for other studies which have used temporally discrete sampling campaigns rather than continuous high-frequency monitoring. They provide a unique insight into the downstream impacts of a rapidly developing beaver wetland over its first three and a half years in a landscape that hasn't had beavers for over 400 years…"
    #hydromorphic #water #hydrology #dam #beaverdam #waterquality #biodiversity #ecology #benefits #NatureBasedSolutions #Wetlands #Ecology #Biodiversity #EnvironmentalScience #Wildlife #Ecosystem #bioviversity #conservation #restoration #landscaperecovery #floodmanagement #FloodMitigation #flooding #energy #floodrisk #sustainability #wetlands #hydrography #dams #impoundment #deadwood #waterresources #landscapeengineer #benefits #vegetation #ecology #ecosystem #riversystemsstabilisation #naturalwaterregulation #resilience #valleysreborn #fisheries #invertebrates #extremeweather #floodflows #sediment #baseflow #drought #landmanagement #naturalsystems #landuse #monitoring #spatialanalysis #spatiotemporal

    #spatiotemporal #spatialanalysis #monitoring #landuse #naturalsystems #landmanagement
  40. 💧🌏 Greg Cocks @GregCocks ·

    Busy Beavers - The Turbidity Signature Of Ecosystem Engineers At Work
    --
    doi.org/10.1002/hyp.70661 <-- shared paper
    --
    H/T @alan Puttock
    “Beavers are the quintessential ecosystem engineers. In slow-flowing streams, they create complex wetlands with ponds by building dams and canals that can positively impact biodiversity, hydrology and water quality. These activities can interchangeably capture or release sediment along the watercourse. To date this has not been quantified at the resolution of rainfall events or beaver activity. This study used 15-min frequency, sustained monitoring upstream and downstream of a newly establishing beaver wetland to measure episodic changes in water turbidity at an event resolution. Monitoring showed no significant differences between upstream and downstream turbidity over 160 days when the first pair of beavers, known not to be building dams or canals, were resident. Shortly after introduction of another beaver pair, however, dam building, burrows and canal excavations were quickly observed, resulting in the creation of a complex beaver wetland between 2021 and 2024. Monitoring over 375 days during this period showed significant differences. Downstream turbidity was significantly higher overall than upstream: 13.1 Nephelometric Turbidity Units (NTU) compared to 4.2 NTU. Stochastic spikes in downstream turbidity during the study period not recorded upstream were associated with dam building and burrowing. Overall, there was no significant difference in turbidity loads, which was at least partially explained by a reduction in discharge downstream, particularly in higher flows, during the dam building period. This demonstrates a complex system with the trapping of influent sediment, the storing of water and the periodic release of beaver wetland sediment leading to net balance in loads. These results help provide context for other studies which have used temporally discrete sampling campaigns rather than continuous high-frequency monitoring. They provide a unique insight into the downstream impacts of a rapidly developing beaver wetland over its first three and a half years in a landscape that hasn't had beavers for over 400 years…"

    #hydromorphic #water #hydrology #dam #beaverdam #waterquality
  41. 💧🌏 Greg Cocks @[email protected] ·

    Quantifying UK Coastal Flood Exposure Under Future Sea-Level Rise To [2100 and] 2300
    --
    doi.org/10.1038/s41467-026-749 <-- shared paper
    --
    theguardian.com/environment/20 <-- shared media article
    --
    H/T @University of Bristol School of Geographical Sciences
    “🌊 New research on long-term coastal flooding as a result of climate inaction 🌊
    … The researchers found:
    🔷 By 2100 at least an additional 0.5 million people exposed to the 1-in-200 year undefended flood extent - a 25% increase compared to present day.
    🔷 Under the most pessimistic storyline by 2300 involving significant ice-sheet instability, an additional 13 million people could be exposed to the 1-in-200 year undefended flood event.
    🔷 Under some scenarios there is a need for large-scale movement of populations and settlements away from the coast in the coming centuries…”
    --
    “Up to 13 million people in the UK face the long-term risk of coastal flooding due to the climate crisis, scientists have warned, with a ‘reasonable worst-case scenario’ suggesting the need for the large-scale movement of populations away from a dramatically reshaped coast…
    Sea level has risen by about 20cm around the UK in the last century and is accelerating. A further 40cm to 60cm by 2100 is already baked in, meaning about half a million more people will be at risk of their homes being flooded, on top of the 2.5 million already in danger near the coasts. Lincolnshire and the Humber estuary are most in danger…”
    --
    “The latest Intergovernmental Panel on Climate Change assessment report highlighted the potential for more than 15 metres of global sea-level rise by 2300. In this study, [the authors] explore the implications for UK coastal flood exposure by combining national-scale flood modelling with physically-based storylines of UK sea-level rise. By 2100 all storylines show broadly similar results with at least an additional ½ million people exposed to the 1-in-200 year undefended flood extent, which represents a 25% increase compared to present day. Under the most pessimistic storyline by 2300 involving significant ice-sheet instability, an additional 13 million people could be exposed to the 1-in-200 year undefended flood event. This would imply the potential need for large-scale movement of populations and settlements away from the coast in the coming centuries. Given current global emissions pledges, exposure increases by 1.7 million people by 2300, however up to 1 million could be avoided if Paris Agreement targets for greenhouse gas emissions are met…”
    #coast #coastal #innundation #climatechange #global #sealevel #sealevelrise #SLR #flood #flooding #climatechange #population #infrastructure #UK #England #Scotland #Wales #NorthernIreland #Lincolnshire #Humber #estuary #settlement #city #urban #mitigation #planning #policy #infrastructure #risk #hazard #humanimpacts #spatialanalysis #spatiotemporal #GIS #spatial #mapping #coastalflooding #climatecrisis #model #modeling #elevation #DEM

    #coast #coastal #innundation #climatechange #global #sealevel
  42. 💧🌏 Greg Cocks @[email protected] ·

    Impact Of Reservoir Storage On Propagation From Meteorological To Hydrological Drought
    --
    doi.org/10.1016/j.jhydrol.2026 <-- shared paper
    --
    H/T @DrAjayGupta | Post Doctoral Fellow, IIT Bombay | Ph.D. in Hydrology, IIT Roorkee | Commonwealth Split-site Fellow, University of Birmingham I M.Tech in Water Resources Engineering, NIT Silchar | B.E. in Civil Engineering, PCE Nagpur.
    “🌍 Why is this important?
    While reservoirs are widely recognized for mitigating drought impacts, their role in controlling how drought propagates through the hydrological cycle has remained largely unexplored. In this study, [the authors] investigate how reservoir storage influences the transition of drought from meteorological to agricultural to reservoir to streamflow drought across the semi-arid Krishna River Basin, India.
    🔍 THIS STUDY ADDRESSES TWO KEY RESEARCH QUESTIONS:
    ✅ How do drought propagation time (initiation, peak, and termination) change from meteorological to agricultural, reservoir, and streamflow droughts across different timescales and threshold values?
    ✅ How does reservoir storage influence drought propagation between upstream and downstream reservoirs using the Downstreamness concept?
    📌 KEY FINDINGS
    🔹 Drought propagation differs substantially across drought types because each component of the hydrological system responds at different rates.
    🔹 Reservoirs significantly delay the propagation of drought by buffering water deficits, particularly between agricultural and streamflow drought.
    🔹 Mild and moderate upstream reservoir droughts rarely propagate downstream, whereas severe upstream droughts consistently transmit downstream, leading to longer duration, greater severity, and delayed onset.
    🔹 The downstreamness analysis reveals dynamic shifts in water storage between upstream and downstream reservoirs throughout drought development and recovery, providing valuable insights for reservoir operation and basin-scale drought management…”
    --
    “HIGHLIGHTS
    • Reservoir storage impact on drought propagation from meteorological-to-hydrological drought.
    • Drought propagation timeframe: initiation, peak and termination are checked.
    • Impact assessment using hydrological connection: upstream to downstream reservoirs.
    • Severe upstream droughts propagate downstream with increased duration and severity.
    • During drought periods water-storage concentration shifts from downstream to upstream..."
    #Drought #DroughtPropagation #Reservoirs #WaterResources #WaterManagement #RiverBasinManagement #KrishnaRiverBasin #Downstreamness #India #climatechange #reservoir #storage #hydrology #water #hydrologiccycle #watersecurity #planning #policy #KrishnaRiver #weather #climate #metrology #agriculture #farming #streamflow #model #modeling #spatiotemporal #spatialanalysis

    #drought #droughtpropagation #reservoirs #waterresources #watermanagement #riverbasinmanagement
  43. 💧🌏 Greg Cocks @[email protected] ·

    Closure Of The Strait Of Hormuz May Trigger A Bioinvasion Super-Spreader Event
    --
    doi.org/10.1007/s10530-026-038 <-- shared paper / brief report
    --
    theguardian.com/environment/20 <-- shared media article
    --
    ecomagazine.com/news/coastal/i <-- shared technical article
    --
    thedeepdraft.com/2026/06/08/th <-- shared technical article
    --
    youtube.com/watch?v=1aGz7pBF08k <-- shared technicial overview video
    --
    timesofindia.indiatimes.com/sc <-- shared media article
    --
    H/T @alejandro Bortolus | Investigador Principal CONICET
    [“consequences”, fascinating, illuminating and scary frankly!!]
    “The ongoing conflicts in the Middle East are causing substantial humanitarian, economic, and geopolitical impacts and disrupting global trade. While the human and economic effects remain the focus of most immediate concern, a pending ecological crisis is also unfolding. The closure of the Strait of Hormuz on February 28, 2026, stranded an estimated 1,500 ships in the Persian/Arabian Gulf, with hundreds more anchored in the Gulf of Oman. Prolonged stationary periods lead to substantial biofouling penalties for ships, as marine microbes, algae, and invertebrates rapidly colonize and grow on submerged surfaces. This accumulation not only impairs vessel operations but also creates significant environmental risks. A major concern is the high likelihood that these idle ships will facilitate the extensive spread of economically and ecologically damaging invasive species as they re-enter the global shipping network. Given the unprecedented scale and duration of this mass lay-up of ships, conditions are primed for a large-scale, marine bioinvasion “super-spreader” event as regular maritime trade in the region resumes. The combination of extensive biofouling growth and species accumulation, and the sheer number, size, and global reach of affected vessels, has created an immense international biosecurity threat. Here, [they] highlight the biosecurity risks arising from the closure of the Strait and provide recommendations to mitigate them. [They] urge relevant stakeholders worldwide, including ship operators, port authorities, and environmental managers, to prepare now for the backlog of ship biofouling management requirements and to implement appropriate actions to abate this extraordinary biosecurity threat...”
    #bioinvasion #superspreader #spatialanalysis #spatiotemporal #mapping #global #worldwide #conflict #MiddleEast #biofouling #stationary #warmwater #marine #ship #shipping #cargo #transportation #StraitofHormuz #ecology #crisis #vessel #environmental #risk #hazard #economy #impact #humanimpacts #largescale #maritime #trade #international #biosecurity

    #bioinvasion #superspreader #spatialanalysis #spatiotemporal #mapping #global
  44. 💧🌏 Greg Cocks @[email protected] ·

    Beyond The 100-Year Flood - Probabilistic Flood Hazard Assessment For King And Pierce Counties Under Future Climate Scenarios
    --
    doi.org/10.5194/nhess-26-3231- <-- shared #openacess paper
    --
    [part of my old stomping ground as an engineering geologist]
    H/T @Kees Nederhoff
    “Flood maps are usually built from a single design storm. For King and Pierce Counties in the Pacific Northwest (USA), [the authors] tried the opposite - simulate 82 years of actual coastal and river conditions (plus 18 synthetic years) with SFINCS and let the statistics fall out cell by cell. That took about 5,400 yearly simulations and 194,000 CPU hours on USGS's Hovenweep HPC. Worth it!
    The design-event shortcut turns out to hide a real hazard. A deterministic 10-year event underestimated flood depths by up to half a meter compared to the continuous runs.
    The bigger surprise [to the authors] was how one-sided the climate signal is. One metre of sea level rise takes King County's expected annual flooded area from 161 --> 787 hectares, almost a factor of five. Changes in storminess over the same horizon barely register. And somewhere between 100 and 150 cm of SLR, land that never floods today starts flooding fast. If you plan adaptation in Puget Sound, that threshold matters more than any single return-period map.
    [They] also propose Expected Annual Flooded Area (EAFA) as a probability-weighted alternative to the binary "inside or outside the 100-year zone" label…”
    #USGS #supercomputing #Hovenweep #HPC #coast #coastal #PNW #Seattle #PacificNorthwest #risk #hazard #riskmanagement #model #modeling #CFRM #deterministic #probabilistic #climatechange #extremeweather #fedscience #WA #KingCounty #PierceCounty #WashingtonState #USA #flood #flooding #compoundflooding #floodmaps #SFINCS #storm #weather #climate #climatechange #rainfall #precipitation #sealevel #sealevelrise #SLR #100yearflood #floodhazardmapping #returnperiods #pluvial #fluvial #spatialanalysis #spatiotemporal #remotesensing #streamgage #history #historicflooding #projections #predictions
    #USGS

    #openacess #usgs #supercomputing #hovenweep #hpc #coast
  45. 💧🌏 Greg Cocks @[email protected] ·

    Mapping Deforestation Probability And Understanding The Forest Dynamics In Gazipur, Bangladesh
    --
    doi.org/10.1016/j.envc.2026.10 <-- shared paper
    --
    "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
  46. 💧🌏 Greg Cocks @[email protected] ·

    A Scale-Invariance-Based Algorithm Application For Land Surface Temperature Downscaling In Denmark
    --
    doi.org/10.3390/rs18132263 <-- shared paper
    --
    zenodo.org/records/20863040 <-- shared open data for downscaled LST dataset for Copenhagen
    --
    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
  47. 💧🌏 Greg Cocks @[email protected] ·

    Statistical Characterization Of High Flow Volumes Across The Conterminous United States Supporting Managed Aquifer Recharge
    --
    doi.org/10.1029/2025WR041955 <-- shared paper
    --
    latimes.com/environment/story/ <-- shared media article
    --
    #water #hydrology #groundwater #watersecurity #waterresources #watersupply #watermanagement #USA #CONUS #aquifer #ManagedAquiferRecharge #MAR #FloodMAR #depletion #overpumping #flood #flooding #recharge #planning #policy #streamflow #extremes #hydrography #highflowvolumes #HFV #model #modeling #uncertainly #siting #screening #usecase #spatialanalysis #geostatics #spatiotemporal #mapping #hydrogeomorphology

    #water #hydrology #groundwater #watersecurity #waterresources #watersupply
  48. 💧🌏 Greg Cocks @[email protected] ·

    Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- shared paper
    --
    “HIGHLIGHTS:
    • [they] compare[d] Sentinel-1 and Sentinel-2 time series to detect farming practices.
    • HyBRIS index is introduced, temporally weighting BSI and VH/VV into a daily index.
    • Time-series minima and maxima are used to predict sowing, harvest, and tillage.
    • Validation is performed across several years, crop types, and European locations.
    • Phenology detection is improved compared to HRL-Cropland.
    ABSTRACT: Arable farming practices dictate both crop cycles and soil dynamics, and are central to agriculture's environmental impact and its mitigation. Sowing and harvesting mark the beginning and end of the growing season, while tillage modifies soil structure during the dormant period. Although well-established methods exist for delineating the growing season using phenology and optical data, the detection of farming practices, particularly tillage, remains underexplored. This study investigates the strengths of radar and optical data to retrieve sowing, harvest, and tillage dates at the field level, and proposes a novel Hybrid Bare Soil Radar Index (HyBRIS). Based on Sentinel-1 and Sentinel-2, HyBRIS merges optical and radar data into a single index using a temporally weighted mean. Local minima and maxima of the time series are used to detect farming practices across European sites. Validation is carried out against a reference dataset comprising 238 fields in 11 EU countries, including 462 sowing, 374 harvest, and 388 tillage events covering more than 40 crop types over 8 years. Compared to the Copernicus High Resolution Layer Croplands product (HRL-Cropland), the proposed method based on HyBRIS time series improved sowing and harvest dates detection (MAE 26 and 23 days, respectively). Additionally, this method enabled tillage dates estimation during dormant periods (MAE = 28 days), but tended to overestimate the number of tillage events (producer's accuracy = 97%, user's accuracy = 70%). Incorporating soil moisture data is advised for reducing false positives. The results highlight the potential of optical, radar, and hybrid indices for monitoring agricultural management and supporting environmental stewardship…”
    #Sowing #Harvest #tillage #tillagedetection #cropland #CroplandManagement #remotesensing #earthobservation #sentinel #Copernicus #cropland #satellite #optical #radar #sensor #landuse #landcover #landsurface #phenology #agricultural #monitoring #GIS #spatial #mapping #spatialanalysis #spatiotemporal #arable #farming #agriculture #soil #substrate #environment #sustainability #environmentalstewardship #growingseason #Europe #region #model #modeling

    #sowing #harvest #tillage #tillagedetection #cropland #croplandmanagement
  49. 💧🌏 Greg Cocks @[email protected] ·

    Remote Sensing, Real Impact - Technology-Driven Conservation At The Jane Goodall Institute
    (How the Jane Goodall Institute [JGI] is using satellite imagery and spatial technology to help people and animals thrive.)
    --
    geoweeknews.com/news/conservat <-- shared technical article
    --
    iceye.com/blog/government/solu <-- shared technical article
    --
    [this post should not be seen as endorsement of a particular provider and/or approach]
    “Dr. Jane Goodall’s groundbreaking research at Gombe National Park in Tanzania began in 1960, and transformed our understanding of chimpanzees and redefined the relationship between humans and animals. Dr. Goodall dedicated her life to conservation and community empowerment. Her recent passing marks the end of an extraordinary career in ethology and conservation science. Yet her legacy lives on powerfully through the Jane Goodall Institute [JGI] and the countless individuals and communities she inspired worldwide. Her pioneering work revealed that chimpanzees make and use tools, have complex social structures, and possess individual personalities; discoveries that fundamentally challenged our understanding of what it means to be human, for the better…
    The institute's current work embodies Dr. Goodall's profound philosophy: that humanity can only reach its full potential "when our clever brains and our compassionate hearts are connected."
    This principle guides every aspect of JGI's conservation science strategy, from analyzing satellite data to providing local communities with the tools they need to strengthen their environment. Dr. Goodall's vision that conservation must be rooted in compassion, scientific rigor, and respect for local communities continues to shape the institute's innovative approach to using technology for conservation action.
    As time has gone on, geospatial technologies have become increasingly indispensable to this mission, enabling JGI to monitor forest health in real-time, map critical chimpanzee habitats and migration corridors, and measure the tangible impact of community-led conservation initiatives. But perhaps most importantly, these technologies help the communities understand that the lives of people, animals and their shared environment are all interconnected…”
    #ConservationTechnology #illegal #Deforestation #hunting #mining #GombeNationalPark #remotesensing #radar #earthobservation #chimpanzee #conservation #communityempowerment #JaneGoodallInstitute #JGI #satellite #spatialanalysis #spatiotemporal #GIS #spatial #mapping #habitat #destruction #migration #corridors #monitoring #conservationscience #strategy #resource #cloudcover #alerts #foresthealth #protection #SAR #vegetation #ecosystems #rainforest #greatape #disease #foodsecurity #DRC #Tanzania #CongoBasin #nationalpark #ranger #parkranger #security #safety #alerts #wildlifetrafficking
    @JaneGoodallInstitute @iceeye

    #conservationtechnology #illegal #deforestation #hunting #mining #gombenationalpark
  50. 💧🌏 Greg Cocks @[email protected] ·

    How Space Weather Could Bust The AI Boom
    --
    spacenews.com/how-space-weathe <-- shared technical article
    --
    futurism.com/artificial-intell <-- shared technical article, “AI Data Centers Pushing Electric Grid Into Meltdown”
    --
    doi.org/10.1146/annurev-earth- <-- shared 2026 paper, “Magnetic Storms and Geoelectric Hazards”
    --
    #AI #datcenters #infrastructure #impacts #solarstorms #spaceweather #risk #hazards #overloading #electricity #energy #powersupply #energygrid #vulnerable #transmission #energy #demand #consumers #geoelectrical #geomagnetism #blackout #damage #cost #economics #equipment #transformers #carringtonevent #NERC #grid #reliability #electricaldemand #utilities #magneticstorm #electromagneticinduction #extremeevent #historicalevent #hazardanalysis #spaceweather #history #Carrington #geoelectric #humanimpacts #risk #hazard #monitoring #network #geology #geomagnetism #impedance #rock #soil #utilities #electricaltransmission #powerlines #magnetotelluric #sensor #blackout #brownout #energy #geoelectrichazard #geoelectric #GIS #spatial #mapping #spatialanalysis #spatiotemporal #model #modeling #geomagnetism #geomagneticstorm #telecommunication #electronics #hardened #geography #mitigation #preparedness #geomorphology #geomorphometry #surfacegeology #cost #economics #disaster #impacts #technology #InternetOfThings #internet #USA #review #CONUS #numericalmodeling #realtimemonitoring #AIBoom #Bust
    @North American Electric Reliability Corporation (NERC)

    #ai #datcenters #infrastructure #impacts #solarstorms #spaceweather