MétaCan
Menu
Retour à la cohorte
Enregistrement W4220795376 · doi:10.5194/egusphere-egu22-10542

From Coarse Resolution to Realistic Resolution: GRACE as a Science Communication and Policymaking Tool for Sustainable Groundwater Management

2022· preprint· en· W4220795376 sur OpenAlexaff
Li Xu, J. S. Famiglietti, D. M. Ferris, Xander Huggins, Chinchu Mohan, Sara Sadri, Palash Sanyal, Jefferson S. Wong

Notice bibliographique

Revuenon disponible
Typepreprint
Langueen
DomaineEarth and Planetary Sciences
ThématiqueGeophysics and Gravity Measurements
Établissements canadiensUniversity of VictoriaUniversity of SaskatchewanGlobal Institute for Water Security
Organismes subventionnairesnon disponible
Mots-clésGroundwaterOperationalizationSustainabilityDelphi methodEnvironmental resource managementSustainable managementEnvironmental planningEnvironmental scienceComputer scienceEngineeringEcology

Résumé

récupéré en direct d'OpenAlex

<p>Managing groundwater resources is challenging because they are difficult to monitor. The application of remote sensing methods has improved our capacity to monitor variability in groundwater storage, as is the case for the Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow-On (GRACE-FO) missions. While GRACE-based groundwater studies to date have covered many places across the globe, perspectives that link scientific studies to policymaking and practices are still limited. Challenges to applying GRACE data into practice result from their coarse resolution, which limits their utility at the smaller scales at which water management decisions are made. Another reason is that the data and related studies can be difficult to use and understand by policymakers and end-users. However, these challenges offer the GRACE scientific community opportunities to communicate with stakeholders, policymakers, and the public in raising awareness around groundwater sustainability issues. This paper addresses three questions: which GRACE data and GRACE-derived products can be useful for groundwater practices and management; how GRACE-derived groundwater messages can be better communicated with practitioners; and how to better operationalize GRACE-derived products for groundwater practice and management. This paper also aims to provide an agenda for the continued use of GRACE and GRACE-FO for the purpose of sustainable groundwater management. To gain insight into these questions, a policy Delphi survey was conducted to collect opinions of both the scientific and non-scientific communities. We made use of target search and snowballing techniques to identify suitable participants who are experienced groundwater researchers or practitioners, and who are familiar with GRACE. A total of 25 participants from around the world were surveyed (14 scientific and 11 non-scientific), and they provided thoughtful responses. We found that both communities acknowledged the potential of GRACE data and GRACE-derived products for groundwater management, and would be willing to collaborate to develop projects for practical applications. Better communication between researchers and practitioners was recommended as a key for the application of GRACE-derived products into practice. Practitioners noted their high demand for reliable data for their management responsibilities, but are more favorable towards locally observed data. The reliability of GRACE at small scales was an issue, even though some robust downscaling methods have been demonstrated down to local scales. The survey showed a desire for more comparison of GRACE-derived products to local measurements to determine whether GRACE products, e.g. downscaled data, can be useful for informing local decisions. Based on the survey, we proposed an agenda that helps to improve the usefulness of GRACE-derived products for practices. This agenda includes scientific recommendations that help to resolve the resolution and technical barriers for local applications, and professional perspectives that bridge the connection between science and policy, and facilitate communication for groundwater management.</p>

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,289
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,037
Tête enseignante GPT0,286
Écart entre enseignants0,249 · 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 tête enseignante, pas un consensus.

Devis d'étudeThéorique ou conceptuel
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

Explorer davantage

Même sujetGeophysics and Gravity MeasurementsTravaux en français237 207