#spatiotemporal — Public Fediverse posts on home.social

💧🌏 Greg Cocks @[email protected] · 2026-08-18 · 03:21 UTC

Spatiotemporal Distribution, Climatic Factors, And Seasonal Precipitation Patterns Characterizing 66 Years Of Widespread Shallow Landslide Events In Piedmont (Northwestern Italy)
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https://doi.org/10.3389/feart.2026.1884300 <-- shared paper
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“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

💧🌏 Greg Cocks @[email protected] · 2026-08-18 · 03:01 UTC

Widespread Landslide Activity in an Extreme Wet Season and Implications for Regional Sediment Management, Eastern San Francisco Bay Area, California
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https://doi.org/10.1029/2026EA005227 <-- shared paper
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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…”
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"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

💧🌏 Greg Cocks @[email protected] · 2026-08-14 · 03:26 UTC

Impact Of Urbanization Driven Land Use And Land Cover Change On Ecological Environmental Quality In Rupandehi Nepal Assessed Using The Remote Sensing Ecological Index
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https://doi.org/10.1007/s44288-026-00650-y <-- shared paper
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https://kathmandupost.com/money/2026/02/18/rupandehi-s-continued-urban-sprawl-comes-at-a-cost-for-agriculture-in-the-periphery <-- shared media article
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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…”
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“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

💧🌏 Greg Cocks @[email protected] · 2026-08-07 · 04:38 UTC

The Latest Data Confirms - Forest Fires Are Getting Worse
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https://www.wri.org/insights/global-trends-forest-fires <-- shared technical article
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http://alturl.com/efp6m <-- shared (focused) #GlobalNatureWatch web map
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https://science.nasa.gov/earth/explore/wildfires-and-climate-change/ <-- shared NASA technical article, ‘Wildfires and Climate Change’
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https://doi.org/10.3389/frsen.2022.825190 <-- shared paper
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https://doi.org/10.1073/pnas.2505418122 <-- shared paper
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https://doi.org/10.1088/1748-9326/add606 <-- shared paper
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https://globalnaturewatch.org/dashboards/global/ <-- shared Global Nature Watch dashboard
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https://youtu.be/-0-pv1Bqm-U?si=IHcZJNiVphosbeVt <-- shared overview video
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https://grist.org/wildfires/the-us-has-lost-a-quarter-of-its-forest-cover-to-fire-since-2001/ <-- shared technical article, ‘Fire is responsible for a quarter of US forest loss since 2021’
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https://www.nytimes.com/2026/04/29/climate/wri-report-forest-loss.html <-- shared media article
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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

💧🌏 Greg Cocks @[email protected] · 2026-08-05 · 05:02 UTC

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

#gis #spatial #mapping #googleearthengine #machinelearning #remotesensing

💧🌏 Greg Cocks @[email protected] · 2026-08-04 · 04:55 UTC

[Open] Data Related To Flood Mapping [Canada]
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https://natural-resources.canada.ca/science-data/science-research/natural-hazards/flood-mapping/data-related-flood-mapping <-- shared link to technical details
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https://app.geo.ca/en-ca/map-browser/record/a13a2575-5bda-4bfd-a9b1-5bd2dd583f09 <-- shared map/data-portal link, Canada Flood Map Inventory (CFM)
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https://open.canada.ca/data/en/dataset/1074f781-85d3-4c86-86cb-fd1c339197dc <-- shared data-portal link, Canada Flood Susceptibility Index
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https://doi.org/10.3390/ECWS-7-14235 <-- shared (2023) paper
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https://doi.org/10.1002/2017WR020917 <-- shared (2017) paper
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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

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

Using Geospatial Analysis and Explainable Machine Learning to Examine Risk Factors of Out-of-Hospital Cardiac Arrest Survival Outcome
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https://openscholar.uga.edu/record/26998/files/Zhang_uga_0077E_16145.pdf <-- shared technical publication / dissertation
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https://www.aag.org/award-grant/william-l-garrison-award-for-best-dissertation-in-computational-geography/ <-- shared @AAG William L. Garrison Award for Best Dissertation in Computational Geography
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[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

💧🌏 Greg Cocks @[email protected] · 2026-08-04 · 04:36 UTC

A National-Scale Database Of Groundwater Level Data For Switzerland
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https://doi.org/10.1038/s41597-026-07353-6 <-- shared paper
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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. 🌊…”
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“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

💧🌏 Greg Cocks @[email protected] · 2026-07-28 · 05:07 UTC

Busy Beavers - The Turbidity Signature Of Ecosystem Engineers At Work
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https://doi.org/10.1002/hyp.70661 <-- shared paper
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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

💧🌏 Greg Cocks @[email protected] · 2026-07-14 · 03:14 UTC

Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
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https://doi.org/10.1038/s43247-026-03515-x <-- shared paper
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H/T @Peter Potapov | Researcher at the World Resources Institute (WRI)
“This paper is] a strong example of multifunctionality analysis applied to conservation planning. The study mapped six ecosystem functions, including carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity. [The author] combined satellite data, field soil sampling, and spatial modeling for this comprehensive analysis.
Two findings stand out.
1. Old-growth forests had the highest multifunctionality index of any land cover type.
2. 78.5% of the top multifunctionality hotspots fall outside the region's protected areas, even though PAs already cover more than 54% of the territory.
Together, these results make a clear case for expanding conservation of the remaining Intact Forest Landscapes and primary forests in Patagonia and elsewhere…”
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“Remote forest landscapes provide critical references for understanding ecosystem functions (EFs) under low anthropogenic pressure, yet their capacity to sustain multiple EFs simultaneously remains poorly understood. [They] assessed landscape multifunctionality in western Patagonia by integrating satellite indicators, field data, and spatial modeling. Six EFs (carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity) were mapped, and their spatial relationships and hotspot distribution within and outside protected areas (PAs) were analyzed. Old-growth and secondary forests showed the highest functional performance. Strong synergies (ρ ≥ 0.6) between carbon storage and nutrient availability covered >50% of the landscape, whereas strong trade-offs (ρ ≤ –0.6) were spatially limited ( < 6%). Notably, 78% of multifunctionality hotspots occurred outside PAs, indicating that high-functional-value areas extend beyond formal conservation boundaries. These findings reveal spatial mismatches between multifunctionality and protection status and provide a replicable framework for integrating multifunctionality into conservation planning under global change…”
#Patagonia #chile #aysen #coyhaique #landcover #mapping #spatial #spatialpatterns #spatiotemporal #spatialanalysis #forest #vegetation #oldgrowth #secondgrowth #shrubland #grassland #steppe #ecosystem #habitat #nutrients #water #hydrology #erosion #multifunctionality #multifunctionalityanalysis #protectedareas #landuse #conservationplanning #conservation #ecology #carbonstorage #nutrientavailability #waterregulation #erosioncontrol #habitatquality #ecologicalconnectivity #remotesensing #satellite #earthobservation #modeling

#patagonia #chile #aysen #coyhaique #landcover #mapping

💧🌏 Greg Cocks @[email protected] · 2026-07-14 · 03:06 UTC

GMIA-NEXT - Next-Generation Global Map of Irrigated Areas |
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https://doi.org/10.21203/rs.3.rs-10085674/v1 <-- shared paper
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https://zenodo.org/records/17627111 <-- shared open data
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H/T @kyle Davis
“Irrigation plays a critical role in global food production and climate adaptation and exercises profound influence over humanity's water use. Yet despite its critical importance, there is a persistent lack of understanding of fine-scale irrigation patterns across the planet, knowledge which is essential for informing global food security and sustainability targets. Utilizing either statistical downscaling or remote sensing approaches, existing global irrigation datasets are constrained by coarse spatial resolutions, a lack of timeliness, or varying robustness and reliability. To address this gap, here [they] integrate[d] multi-source Earth observation and environmental datasets and use[d] machine learning to develop a medium-resolution (30 metre) global irrigated area dataset for the 2023/24 growing season. Within existing cropland extent, we leverage a newly compiled set of georeferenced irrigated (N=230,683) and non-irrigated (N=153,194) ground-truth points and integrate seasonal vegetation metrics derived from Landsat 8/9 imagery with agroecological-zone information and hydroclimatic and topographic variables. [They] subsequently develop and evaluate two machine-learning frameworks, a continental Agro-Ecological Zone (AEZ) tile-based framework and a continental-scale framework, and apply the best-performing approach for each continent. Evaluation using held-out test samples yielded a global accuracy of 80.5 ± 2.1%. The resulting maps were also validated against independent global and national irrigation datasets and statistics, demonstrating broad agreement in the spatial distribution of irrigated areas. This approach is robust and reliable because it is built on a harmonized global ground-truth database, incorporates multiple predictors, and is rigorously validated using independent datasets. All code, ground-truth, and data products are freely and publicly available [link above] and can serve as a robust, scale-neutral, and fully reproducible framework for fine-resolution irrigation mapping. These advances provide the critical and long-needed foundation for near-real-time monitoring and early warning systems, and fine-scale land and water resource management…”
#IrrigatedAreas #Mapping #GIS #spatial #mapping #spatialanalysis #spatiotemporal #global #irrigation #water #hydrology #hydrography #waterresources #farming #agriculture #opendata #remotesensing #earthobservation #geomorphometry #AI #machinelearning #LLM #model #modeling #WaterManagement #opendata #AgroEcologicalZone #AEZ #cropland #irrigatedareas #foodproduction #wateruse #humanimpacts #EarthObservation #remotesensing #earlywarning #monitoring #FoodandAgricultureOrganizationFAO #FAO
@FAO - Food and Agriculture Organization

#irrigatedareas #mapping #gis #spatial #spatialanalysis #spatiotemporal

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

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

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

💧🌏 Greg Cocks @[email protected] · 2026-07-09 · 05:39 UTC

A Century Of Landslide Records In Calabria, Southern Italy, Looking For Changes And Trends Through A Dynamic Analysis
--
https://doi.org/10.5194/nhess-26-3077-2026 <-- shared paper / brief communication
--
https://doi.org/10.5194/nhess-15-2313-2015 <-- shared 2015 paper that this communication updates/adds-to
--
https://doi.org/10.1007/s12665-023-10844-z <-- shared paper
--
H/T @StefanoLuigiGariano
“This study updates an article published in NHESS journal in 2015 [link above] and investigates long-term changes in landslide-triggering rainfall conditions in Calabria (southern Italy) over 1921–2020. A catalogue of 3,006 rainfall events associated with landslides (RELs) was reconstructed using 9,530 landslide records and daily rainfall measurements from 318 gauges. Rainfall thresholds were calculated for 15 30-year moving windows to investigate the triggering conditions of the RELs. Results show a marked increase in the number of RELs after 2009, shifts in seasonal occurrence, and decreasing rainfall duration and cumulative amounts. Triggering rainfall shows an overall decreasing trend over the years…”
#Calabria #Italy #massmovement #records #landslides #geology #engineeringgeology #spatiotemporal #spatialanalysis #rainfall #precipitation #extremeweather #trigger #monitoring

#calabria #italy #massmovement #records #landslides #geology

💧🌏 Greg Cocks @[email protected] · 2026-07-02 · 19:07 UTC

Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
--
https://doi.org/10.1016/j.rse.2026.115553 <-- 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

💧🌏 Greg Cocks @[email protected] · 2026-06-25 · 03:43 UTC

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

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

💧🌏 Greg Cocks @[email protected] · 2026-06-25 · 03:43 UTC

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

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

💧🌏 Greg Cocks @[email protected] · 2026-06-25 · 03:43 UTC

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

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

💧🌏 Greg Cocks @[email protected] · 2026-06-25 · 03:43 UTC

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

#downstream #modeling #model #safety #public #economics

💧🌏 Greg Cocks @GregCocks · 2026-06-25 · 03:43 UTC

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

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

💧🌏 Greg Cocks @[email protected] · 2026-06-18 · 03:09 UTC

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

#water #hydrology #hydroclimate #whiplash #global #spatialanalysis

💧🌏 Greg Cocks @[email protected] · 2026-06-17 · 05:37 UTC

NASA’s Nancy Grace Roman Space Telescope's ‘Spy Mirror’ Could Transform How We Map The Universe
--
https://www.discovermagazine.com/nasa-s-nancy-grace-roman-space-telescope-s-spy-mirror-could-transform-how-we-map-the-universe-49239 <-- shared technical article
--
https://www.mos.org/article/ready-roman-nancy-grace-roman-space-telescope <-- shared technical article
--
https://www.space.com/space-exploration/the-nancy-grace-roman-space-telescope-nasas-next-great-observatory-is-finally-complete <-- shared technical article
--
https://youtu.be/TcjuucVEB5g?si=I93BjarghNcYKKqj <-- shared NASA Goddard technical overview video
--
https://youtu.be/lBAuc057pVA?si=IghhCWC915FO3y3C <-- shared media video
--
“… Roman is set to launch on August 30, 2026, and will help us gain a wider view of the universe and collect data faster than its predecessors, such as the Hubble Space Telescope. The telescope will do so thanks to the incredible equipment and instruments built into it.
These instruments include the primary mirror, which was gifted to NASA by a U.S. intelligence agency, the Wide Field Instrument, and an advanced coronograph. Altogether, these instruments could help us map out more of the universe than we ever imagined.
“It is an incredible feat of precision engineering. It's quite possibly the most complex scientific instrument that NASA has ever built,” Dominic Benford, …program scientist for the Nancy Grace Roman Space Telescope…”
--
“Named after NASA’s first chief astronomer, the ‘mother of the Hubble Space Telescope,’ the Nancy Grace Roman Space Telescope will have a field of view at least 100 times larger than Hubble's, potentially measuring light from a billion galaxies in its lifetime. This observatory will also be able to block starlight to directly see exoplanets and planet-forming disks, complete a statistical census of planetary systems in our galaxy, and settle essential questions in the areas of dark energy, exoplanets, and infrared astrophysics…”
--
The Roman Space Telescope is engineered to investigate the biggest mysteries in astrophysics:
• Dark Energy & Dark Matter: By surveying billions of galaxies and mapping their distribution, Roman will explore why the universe's expansion is accelerating and trace cosmic history.
• Exoplanets: It will utilize gravitational microlensing to complete a statistical census of planetary systems in our galaxy, aiming to find thousands of exoplanets, including elusive rogue planets.
• Infrared Astrophysics: The telescope's deep, crisp infrared vision will help astronomers measure light from up to a billion galaxies over its lifetime.
#coronograph #astronomy #mapping #exoplanets #universe #telescope #spacetelescope #darkenergy #darkmatter #NancyGrace #NASA #Roman #astrophysics #cosmic #infrared #launch #WideFieldInstrument #instumentation #exploration extraterrestrial observatory #space #remotesensing #galacticbulge #spatialanalysis #spatiotemporal #supernova
@nasa @nasa Goddard @Discover Magazine

#coronograph #astronomy #mapping #exoplanets #universe #telescope

💧🌏 Greg Cocks @[email protected] · 2026-06-16 · 03:41 UTC

🚨 FEMA’s Hazus v7.2 Is Here — A Major Upgrade For Disaster Risk Modeling
--
https://www.fema.gov/flood-maps/products-tools/hazus <-- shared link to FEMA HAZUS download, documentation, use case, etc
--
[I used to work some with Hazus back in the back, but my career changed path; I still appreciate its strength and unity of purpose (sic) #alldataisspatial]
H/T @Laban "L.J." Johnson | Founder, LJ Learn & Concordia Initiative | Crisis Support · Leadership Development · Community Resilience | Bridging worlds to help people rise
“FEMA’s Hazus GIS platform has been updated with a new ArcGIS Pro–based version, bringing faster, more powerful tools for estimating losses from floods, hurricanes, earthquakes, and other natural hazards.
Key updates in Hazus 7.2 include:
• Streamlined workflows for flood and hurricane modeling
• New Earthquake ShakeMap integration using USGS data
• Expanded and improved results exports and reporting (including geodatabase outputs)
• Stronger security with known vulnerabilities addressed
• Performance improvements and optimized installation process
• [Significantly enhanced and comprehensive summary reports for flood and earthquake are now available for download.]
• Full integration with ArcGIS Pro (3.4–3.6) for a modern GIS experience
This release represents a significant step forward in how hazard planners, emergency managers, and GIS professionals analyze and prepare for disaster impacts…”
--
“FEMA’s Hazus program provides software, data, methods, and guidance for estimating risk from natural hazards. Hazus can estimate building damages, economic losses, displaced households, casualties, debris generation and more resulting from a natural hazard event and can be used in all phases of emergency management…”
#HAZUS #fedservice #fedscience #oublicgood #publicsafety #emergencyresponse #software #spatialdata #GIS #spatial #mapping #risk #hazard #riskassessment #naturalhazard #humanimpacts #earthquake #wildfire #spatialanalysis #spatiotemporal #flood #flooding #cost #damage #economic #publicsafety #publichealth #emergencymanagement #opensource #opendata #tsunami #tornado #hurricane #ShakeMap #infrastructure #planning #policy #preparedness #impacts #geology #engineeringgeology #remotesensing #earthobservation
@FEMA

#alldataisspatial #hazus #fedservice #fedscience #oublicgood #publicsafety

💧🌏 Greg Cocks @[email protected] · 2026-06-13 · 05:44 UTC

Late Miocene Euphrates River Drained Into A Partially Desiccated Eastern Mediterranean
--
https://doi.org/10.1038/s41561-026-01962-x <-- shared paper
--
[the paleogeographic reconstruction is outstanding, including the strength and information conveyed so well in that figure, kudos!]
H/T @lina Jakaitė-Darkšė
“Although the Euphrates River - stretching ~3,000 km across Western Asia - has shaped the region’s geology for millions of years, the timing of its origin and the evolution of its course remain enigmatic. So far, two contrasting hypotheses have been proposed to explain the fluvial system’s Late Neogene path: termination in Anatolia at a palaeo-lake or the Mediterranean, or a southeastward continuation to Arabia. Here [they] use seismic-reflection and topographic data to show that two previously identified sedimentary accumulations - deposited during the terminal phase of the Late Miocene Messinian salinity crisis - resulted from dual riverine systems that drained into a partially desiccated eastern Mediterranean before avulsing toward the Persian Gulf and converging to form the modern Euphrates River. From probabilistic sediment-budget modelling, [they] show that although the latest Messinian drainage basins were an order of magnitude smaller than their present-day extents, the total palaeo-discharge exceeded that of the modern Tigris, Euphrates and Nile rivers combined, indicating intense palaeo-precipitation and high palaeo-relief. These results suggest that plate-margin deformation both controlled the fluvial avulsions that diverted the Euphrates River from the Anatolian–Eurasian Plate to the Arabian Plate, and established the conditions necessary for the development of the alluvial Fertile Crescent…”
#water #hydrology #hydrography #paleogeography #Euphrates #river #Miocene #reconstruction #spatialreconstruction #geology #change #erosion #MiddleEast #spatialanalysis #spatiotemporal #Neogene #Anatolia #paleolake #Mediterranean #Arabia #Messinian #remotesensing #model #modeling #topography #hydrogeomorphology #geomorphology #PersianGulf #sediment #paleodischarge #volume #Tigris #elevation #platetectonics #structuralgeology #platemargin #fluvial #avulsion #FertileCrescent

#water #hydrology #hydrography #paleogeography #euphrates #river

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

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