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Enregistrement W4311012972 · doi:10.5281/zenodo.7421671

Water mission to measure Alaskan rivers on cutting edges of environmental change

2022· article· en· W4311012972 sur OpenAlexaboutno aff
Jason Jason

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueHermeneutics and Narrative Identity
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMeasure (data warehouse)Environmental scienceEnvironmental changeHydrology (agriculture)GeologyOceanographyClimate changeComputer scienceGeotechnical engineeringData mining

Résumé

récupéré en direct d'OpenAlex

The impending Surface Water and Sea Geography mission will give a store of information on Earth's water resources, even in distant locations. Alaska serves as a case study.\n\nWhile Alaska straddles the Cold Circle and is covered by vast expanses of frozen land, the state also has a ton of fluid water. Alaska holds around 40% of U.S, as a matter of fact. surface water resources. This includes in excess of 12,000 rivers, thousands additional streams and creeks, and hundreds of thousands of lakes.\n\nSo when the Surface Water and Sea Geology (SWOT) satellite launches this month from California's Vandenberg Space Power Base, it's just normal that Alaska will be among the first beneficiaries of this mission drove by NASA and the French space organization Center Public d'études Spatiales (CNES), with contributions from the Canadian Space Office and the UK Space Organization.\n\nSWOT will measure the level of practically all water on Earth's surface, from huge rivers to lakes and reservoirs to the sea. It will fill in gaps in remote places like Alaska and in numerous countries where surface water information is sparse or nonexistent. These measurements will be significant to water the executives and disaster preparedness agencies, universities, structural engineers, and others who need to follow water in their neighborhoods.\n\nAlaska's sheer size, tough territory, and restricted transportation infrastructure make customary stream measuring cost restrictive. While streamflows in most of the US are continuously observed by a U.S. Geographical Survey (USGS) organization of in excess of 8,500 stations, there are at present just 113 gauges in Alaska, and numerous huge rivers aren't observed. How much water moving through such rivers affects everything from the wellbeing and biodiversity of fish species to transportation and drinking water accessibility.\n\nThis lack of Alaskan stream data settled on USGS a coherent decision to serve as a SWOT early adopter. SWOT information will supplement a system at present being developed to screen those rivers, using radar altimetry information from the U.S.- European Jason-2 and - 3 and European Space Organization Sentinel satellites (created with regards to the European Copernicus program drove by the European Commission), and visible symbolism from the NASA-USGS Landsat satellites. The undertaking, in its third year, involves using space-borne instruments to measure the rise and stream of rivers. USGS partners incorporate the Alaska Division of Transportation and Public Facilities, Public Weather conditions Service's Alaska-Pacific Stream Forecast Center, U.S. Fish and Natural life Service, and Alaska Branch of Fish and Game.\n\n"Alaska is a spot that could especially profit from distant observation for streamflow estimates," said USGS hydrologist Robert Dudley. Dudley said Alaska is an extraordinary test case for scientists and water managers to work with new space-based tools like SWOT and put them to quick use.\n\nUSGS is ordering a historical record of estimated stream discharges, expanding on over two decades of NASA research to measure water surface levels in lakes and rivers. The information will permit scientists and water managers to understand how frequently streams experience low-and high-stream conditions and to foster a reference highlight assess ebb and flow conditions.\n\nThe SWOT advantage\n\nDudley says SWOT has numerous advantages over flow satellite-based waterway measurement techniques. Altimeters like those on the Jason series of satellites can measure how water levels differ in some enormous rivers, and Landsat can measure how stream widths shift. Be that as it may, neither one of the datas source without anyone else provides all the data expected to work out a reasonable estimate of how much water is moving through a stream without doing troublesome and costly on-the-ground adjustment. SWOT changes that by measuring both water levels and width simultaneously.\n\nFor instance, in the event that a stream has steep banks, it will not necessarily seem more extensive or smaller as its discharge rate changes. Conversely, even a minuscule change in water rise in a shallow-banked stream can mean significantly more water is moving through it.\n\nhttps://zenodo.org/record/7395648\n\nhttps://zenodo.org/record/7395650\n\nhttps://zenodo.org/record/7395654\n\nhttps://zenodo.org/record/7395664\n\nhttps://zenodo.org/record/7395670\n\nhttps://zenodo.org/record/7395705\n\nhttps://zenodo.org/record/7395710\n\nhttps://zenodo.org/record/7395712\n\nhttps://zenodo.org/record/7395716\n\nhttps://zenodo.org/record/7395722\n\nSWOT will also measure a stream's slope, which provides scientists a means to estimate how fast water is running off the landscape. Taking everything into account, steeper the slope, the faster the water.\n\nWhat's more, SWOT will gather the information expected to estimate stream flows at the same time, each time it flies over a waterway, which in Alaska will be about once like clockwork. SWOT's radar also can see through clouds, wiping out information gaps caused by clouds in Landsat and other visible-light symbolism.\n\nEnvironmental change is causing numerous hydrological changes in Alaska that SWOT will help study, said Jack Eggleston, head of the USGS Hydrologic Remote Sensing Branch. "Quickly increasing temperatures are causing streamflows to increase on the North Slope, where permafrost is softening," he said. "This is also changing the seasonality of streamflow, with high flows caused by snow liquefy happening prior in the year."\n\n"SWOT will permit us to see what's happening in Alaska hydrologically in ways that we haven't previously," said Tamlin Pavelsky, NASA's SWOT freshwater science lead, based at the University of North Carolina, Church Slope. "That is significant, because Alaska, being in the Icy, is also the spot in the US encountering the most environmental change at the present time. To know why that matters, ponder the number of resources we that get from Alaska."

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,075
Score d'incertitude au seuil0,150

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0080,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,080
Tête enseignante GPT0,229
Écart entre enseignants0,149 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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