#instrumentation — Public Fediverse posts on home.social

💧🌏 Greg Cocks @[email protected] · 2026-07-31 · 05:21 UTC

Anatomy Of A Seafloor Spreading Event Captured By In Situ Seismogeodesy
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https://doi.org/10.1038/s41586-026-10785-0 <-- shared paper
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https://www.smithsonianmag.com/smart-news/in-a-first-scientists-witness-the-seafloor-spread-in-real-time-giving-them-a-rare-glimpse-at-a-mysterious-geologic-process-180989123/ <-- shared technical media article
--
H/T @Seabed 2030
“🔍 For the first time, scientists have observed seafloor spreading in real time.
Seafloor spreading is the process by which new oceanic crust is formed at mid-ocean ridges - a geological process that has shaped entire ocean basins over millions of years.
During a research expedition in the Indian Ocean, scientists had just deployed a suite of instruments when a series of earthquakes triggered a seafloor spreading event, allowing them to observe the process as it unfolded.
The findings offer rare new insights into how new oceanic crust forms and how the seafloor continues to evolve…”
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“Earth’s outermost layer - the crust - is constantly renewing itself. It’s broken into giant chunks called tectonic plates that pull apart, push against or slide past one another, creating grand geologic features.
Underwater mountain ranges, or mid-ocean ridges, for instance, generally take shape where two tectonic plates are moving away from each other. Magma can then bubble up in between, solidifying and turning into new oceanic crust as part of a process called seafloor spreading. Although the phenomenon has created entire ocean basins, it remains quite mysterious because it happens so deep in the water.
Now, for the first time, scientists have observed this dynamic activity happening in real time. They describe their findings - and their stroke of luck - in a study [link above], shedding light on a mechanism that made roughly two-thirds of Earth’s crust…”
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#Seabed2030 #OceanMapping #Hydrospatial #remotesensing #seafloor #seafloorspreading #oceanic #crust #geology #structuralgeology #IndianOcean #earthquake #midoceanridge #instrumentation #marine #seabed #hydrography #model #modeling #mapping #GIS #spatial #tectonicplates #magma #fortuitous #survey #seismogeodetic #monitoring #submarine #rifting #observation #volcanism #seismicity #dyke #fault #faulting #midoceanridge #MOR

#seabed2030 #oceanmapping #hydrospatial #remotesensing #seafloor #seafloorspreading

💧🌏 Greg Cocks @[email protected] · 2026-07-23 · 04:30 UTC

Global Performance of #RemoteSensing Based and Reanalysis-Driven Models to Estimate Open Water Evaporation
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https://doi.org/10.1029/2025WR042363
--
“ABSTRACT: Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, [they] analyze[d] the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. [They] compare[d] three remote sensing-based models, one reanalysis-driven model and one ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. [Their] results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm/day, respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.
PLAIN LANGUAGE SUMMARY: Water loss through evaporation in lakes and reservoirs directly affects water availability, which highlights the need to monitor these losses. However, measuring evaporation in situ is challenging and expensive. An alternative is to estimate evaporation using remote-sensing models and compare these estimates with in-situ data to verify their accuracy. Here, [they] evaluated four models and their ensemble (the models' mean value) using measurements from 27 lakes and reservoirs worldwide. [They] found that the ensemble presented higher accuracy and consistency than any individual model because it benefits from the strengths of each model. This approach can guide future improvements in estimating open-water evaporation, which is essential for large-scale water-resource management…”
#global #mapping #earthobservation #GIS #spatial #spatialanalysis #spatiotemporal #model #modeling #water #hydrology #surfacewater #waterbody #lake #reservoir #evaporation #evapotranspiration #watercycle #weather #meteorology #usecase #waterresources #watermanagement #waterloss #regional #estimate #policy #planning #instrumentation #comparasion

#remotesensing #global #mapping #earthobservation #gis #spatial

💧🌏 Greg Cocks @[email protected] · 2026-07-23 · 04:30 UTC

Global Performance of #RemoteSensing Based and Reanalysis-Driven Models to Estimate Open Water Evaporation
--
https://doi.org/10.1029/2025WR042363
--
“ABSTRACT: Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, [they] analyze[d] the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. [They] compare[d] three remote sensing-based models, one reanalysis-driven model and one ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. [Their] results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm/day, respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.
PLAIN LANGUAGE SUMMARY: Water loss through evaporation in lakes and reservoirs directly affects water availability, which highlights the need to monitor these losses. However, measuring evaporation in situ is challenging and expensive. An alternative is to estimate evaporation using remote-sensing models and compare these estimates with in-situ data to verify their accuracy. Here, [they] evaluated four models and their ensemble (the models' mean value) using measurements from 27 lakes and reservoirs worldwide. [They] found that the ensemble presented higher accuracy and consistency than any individual model because it benefits from the strengths of each model. This approach can guide future improvements in estimating open-water evaporation, which is essential for large-scale water-resource management…”
#global #mapping #earthobservation #GIS #spatial #spatialanalysis #spatiotemporal #model #modeling #water #hydrology #surfacewater #waterbody #lake #reservoir #evaporation #evapotranspiration #watercycle #weather #meteorology #usecase #waterresources #watermanagement #waterloss #regional #estimate #policy #planning #instrumentation #comparasion

#remotesensing #global #mapping #earthobservation #gis #spatial

💧🌏 Greg Cocks @[email protected] · 2026-07-23 · 04:30 UTC

Global Performance of #RemoteSensing Based and Reanalysis-Driven Models to Estimate Open Water Evaporation
--
https://doi.org/10.1029/2025WR042363
--
“ABSTRACT: Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, [they] analyze[d] the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. [They] compare[d] three remote sensing-based models, one reanalysis-driven model and one ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. [Their] results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm/day, respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.
PLAIN LANGUAGE SUMMARY: Water loss through evaporation in lakes and reservoirs directly affects water availability, which highlights the need to monitor these losses. However, measuring evaporation in situ is challenging and expensive. An alternative is to estimate evaporation using remote-sensing models and compare these estimates with in-situ data to verify their accuracy. Here, [they] evaluated four models and their ensemble (the models' mean value) using measurements from 27 lakes and reservoirs worldwide. [They] found that the ensemble presented higher accuracy and consistency than any individual model because it benefits from the strengths of each model. This approach can guide future improvements in estimating open-water evaporation, which is essential for large-scale water-resource management…”
#global #mapping #earthobservation #GIS #spatial #spatialanalysis #spatiotemporal #model #modeling #water #hydrology #surfacewater #waterbody #lake #reservoir #evaporation #evapotranspiration #watercycle #weather #meteorology #usecase #waterresources #watermanagement #waterloss #regional #estimate #policy #planning #instrumentation #comparasion

#remotesensing #global #mapping #earthobservation #gis #spatial

💧🌏 Greg Cocks @[email protected] · 2026-07-23 · 04:30 UTC

Global Performance of #RemoteSensing Based and Reanalysis-Driven Models to Estimate Open Water Evaporation
--
https://doi.org/10.1029/2025WR042363
--
“ABSTRACT: Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, [they] analyze[d] the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. [They] compare[d] three remote sensing-based models, one reanalysis-driven model and one ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. [Their] results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm/day, respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.
PLAIN LANGUAGE SUMMARY: Water loss through evaporation in lakes and reservoirs directly affects water availability, which highlights the need to monitor these losses. However, measuring evaporation in situ is challenging and expensive. An alternative is to estimate evaporation using remote-sensing models and compare these estimates with in-situ data to verify their accuracy. Here, [they] evaluated four models and their ensemble (the models' mean value) using measurements from 27 lakes and reservoirs worldwide. [They] found that the ensemble presented higher accuracy and consistency than any individual model because it benefits from the strengths of each model. This approach can guide future improvements in estimating open-water evaporation, which is essential for large-scale water-resource management…”
#global #mapping #earthobservation #GIS #spatial #spatialanalysis #spatiotemporal #model #modeling #water #hydrology #surfacewater #waterbody #lake #reservoir #evaporation #evapotranspiration #watercycle #weather #meteorology #usecase #waterresources #watermanagement #waterloss #regional #estimate #policy #planning #instrumentation #comparasion

#comparasion #instrumentation #planning #policy #estimate #regional

💧🌏 Greg Cocks @GregCocks · 2026-07-23 · 04:30 UTC

Global Performance of #RemoteSensing Based and Reanalysis-Driven Models to Estimate Open Water Evaporation
--
https://doi.org/10.1029/2025WR042363
--
“ABSTRACT: Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, [they] analyze[d] the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. [They] compare[d] three remote sensing-based models, one reanalysis-driven model and one ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. [Their] results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm/day, respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.
PLAIN LANGUAGE SUMMARY: Water loss through evaporation in lakes and reservoirs directly affects water availability, which highlights the need to monitor these losses. However, measuring evaporation in situ is challenging and expensive. An alternative is to estimate evaporation using remote-sensing models and compare these estimates with in-situ data to verify their accuracy. Here, [they] evaluated four models and their ensemble (the models' mean value) using measurements from 27 lakes and reservoirs worldwide. [They] found that the ensemble presented higher accuracy and consistency than any individual model because it benefits from the strengths of each model. This approach can guide future improvements in estimating open-water evaporation, which is essential for large-scale water-resource management…”
#global #mapping #earthobservation #GIS #spatial #spatialanalysis #spatiotemporal #model #modeling #water #hydrology #surfacewater #waterbody #lake #reservoir #evaporation #evapotranspiration #watercycle #weather #meteorology #usecase #waterresources #watermanagement #waterloss #regional #estimate #policy #planning #instrumentation #comparasion

#remotesensing #global #mapping #earthobservation #gis #spatial

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

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

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

💧🌏 Greg Cocks @[email protected] · 2026-03-04 · 05:00 UTC

United States Tsunami Alerting Analysis, 2026 Report
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https://mil.wa.gov/asset/69a08a91462bf/United-States-Tsunami-Alerting-Analysis-2026-updated.pdf <-- shared report PDF
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#naturalhazard #earthquake #USA #alert #monitoring #tsunami #risk #hazard #humanimpacts #lossoflife #death #infrastructure #damage #cost #economics #coast #coastal #nationwide #hazardassessment #emergencymanagement #GIS #spatial #instrumentation #spatialanalysis #model #modeling #operations #geography geomorphometry demographics #geologichazard #alertsystems #warning #ocean #marine #wave #emergencyresponse #planning #messaging #response
@National Tsunami Hazard Mitigation Program

#naturalhazard #earthquake #usa #alert #monitoring #tsunami

💧🌏 Greg Cocks @[email protected] · 2026-03-04 · 05:00 UTC

United States Tsunami Alerting Analysis, 2026 Report
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https://mil.wa.gov/asset/69a08a91462bf/United-States-Tsunami-Alerting-Analysis-2026-updated.pdf <-- shared report PDF
--
#naturalhazard #earthquake #USA #alert #monitoring #tsunami #risk #hazard #humanimpacts #lossoflife #death #infrastructure #damage #cost #economics #coast #coastal #nationwide #hazardassessment #emergencymanagement #GIS #spatial #instrumentation #spatialanalysis #model #modeling #operations #geography geomorphometry demographics #geologichazard #alertsystems #warning #ocean #marine #wave #emergencyresponse #planning #messaging #response
@National Tsunami Hazard Mitigation Program

#naturalhazard #earthquake #usa #alert #monitoring #tsunami

💧🌏 Greg Cocks @[email protected] · 2026-03-04 · 05:00 UTC

United States Tsunami Alerting Analysis, 2026 Report
--
https://mil.wa.gov/asset/69a08a91462bf/United-States-Tsunami-Alerting-Analysis-2026-updated.pdf <-- shared report PDF
--
#naturalhazard #earthquake #USA #alert #monitoring #tsunami #risk #hazard #humanimpacts #lossoflife #death #infrastructure #damage #cost #economics #coast #coastal #nationwide #hazardassessment #emergencymanagement #GIS #spatial #instrumentation #spatialanalysis #model #modeling #operations #geography geomorphometry demographics #geologichazard #alertsystems #warning #ocean #marine #wave #emergencyresponse #planning #messaging #response
@National Tsunami Hazard Mitigation Program

#naturalhazard #earthquake #usa #alert #monitoring #tsunami

💧🌏 Greg Cocks @[email protected] · 2026-03-04 · 05:00 UTC

United States Tsunami Alerting Analysis, 2026 Report
--
https://mil.wa.gov/asset/69a08a91462bf/United-States-Tsunami-Alerting-Analysis-2026-updated.pdf <-- shared report PDF
--
#naturalhazard #earthquake #USA #alert #monitoring #tsunami #risk #hazard #humanimpacts #lossoflife #death #infrastructure #damage #cost #economics #coast #coastal #nationwide #hazardassessment #emergencymanagement #GIS #spatial #instrumentation #spatialanalysis #model #modeling #operations #geography geomorphometry demographics #geologichazard #alertsystems #warning #ocean #marine #wave #emergencyresponse #planning #messaging #response
@National Tsunami Hazard Mitigation Program

#response #messaging #planning #emergencyresponse #wave #marine

💧🌏 Greg Cocks @GregCocks · 2026-03-04 · 05:00 UTC

United States Tsunami Alerting Analysis, 2026 Report
--
https://mil.wa.gov/asset/69a08a91462bf/United-States-Tsunami-Alerting-Analysis-2026-updated.pdf <-- shared report PDF
--
#naturalhazard #earthquake #USA #alert #monitoring #tsunami #risk #hazard #humanimpacts #lossoflife #death #infrastructure #damage #cost #economics #coast #coastal #nationwide #hazardassessment #emergencymanagement #GIS #spatial #instrumentation #spatialanalysis #model #modeling #operations #geography geomorphometry demographics #geologichazard #alertsystems #warning #ocean #marine #wave #emergencyresponse #planning #messaging #response
@National Tsunami Hazard Mitigation Program

#naturalhazard #earthquake #usa #alert #monitoring #tsunami

Smidmart @[email protected] · 2026-02-03 · 10:00 UTC

🚀⚡ The future of space launches is built on one rule: measure everything before you commit.
know more:https://zurl.co/3VELF

#Smidmart #Instrumentation #DigitalVoltmeter #Ammeter #IgnitionSystem #HealthMonitoring #TestAndMeasurement #AerospaceEngineering #GroundSupport

#smidmart #instrumentation #digitalvoltmeter #ammeter #ignitionsystem #healthmonitoring

💧🌏 Greg Cocks @[email protected] · 2025-12-13 · 05:31 UTC

Ensemble Deep Learning Towards High-Resolution Soil-Moisture Mapping For Enhanced Water Management In California's Central Valley
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https://doi.org/10.1016/j.envsoft.2025.106824 <-- shared paper
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#agriculture #crops #groundwater #pumping #monitoring #agronomic #irrigation #planning #scheduling #wateruse #sustainability #wateruse #watersecurity #deeplearning #framework #soilmoisture #downscaling #watermanagement #california #centralvalley #ensemblemodeling #model #modeling #SMAP #satellite #rootzone #remotesensing #spatialanalysis #spatiotemporal #AI #sensitivityanalysis #fieldobservation #instrumentation #fieldchecking #seasonal #crop #crops #production #foodsecurity #NVDI #NDWI #ET #evapotranspiration #MODIS #pluvial

#agriculture #crops #groundwater #pumping #monitoring #agronomic

💧🌏 Greg Cocks @[email protected] · 2025-11-01 · 21:55 UTC

Have You Ever Wondered What A New Concrete Stilling Well [stream gauge] Looked Like?
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H/T Roy Socolow, USGS
"While doing research on the USGS stream gaging program for a local presentation, [he] found this beautiful image of a classic stilling well from the Kentucky archives. Intakes and valve stems in perfect condition, hand pump and flush tank ready to fill, no kerosene or funky well water smell, and the clock weights on the Stevens recorder have plenty of travel room. Makes them] think of the good old days climbing down well ladders to “muck out” wells. Many of these “tanks” of instrument shelters still exist with either working intakes or as converted bubble gages. Many others have been decommissioned due to safety issues (falling or confined space hazards). Thanks to the men of the #CCC and #WPA..."
#gage #streamflow #instrumentation #hydrology #measurement #history #waterresources #stillingwell #recording #USGS #fedscience #fedservice
@USGS