Advances in uncertainty quantification for water resources applications

Autor:	Daniel M. Tartakovsky, Valentina Ciriello, Jonghyun Lee
Přispěvatelé:	Valentina Ciriello, Jonghyun Lee, Daniel M. Tartakovsky
Rok vydání:	2021
Předmět:	Water resources Environmental Engineering uncertainty quantification Computer science Environmental Chemistry Computational intelligence Biochemical engineering Uncertainty quantification water resources Safety Risk Reliability and Quality General Environmental Science Water Science and Technology
Zdroj:	Stochastic Environmental Research and Risk Assessment. 35:955-957
ISSN:	1436-3259 1436-3240
DOI:	10.1007/s00477-021-01998-y
Popis:	Engineering and physical sciences often rely on mathematical approximations of reality (aka models) that are parameterized with indirect and noisy observations. Consequently, characterization and quantification of uncertainty is a primary challenge in modern science-based predictions (National Research Council 2012). When applied to water resources, uncertainty quantification (UQ) plays a central role in assessing the reliability and accuracy of hydrological models and making optimal water management decisions based on such models (Tartakovsky 2013). Environmental policy and regulations around the world increasingly require UQ as a basis for the planning of measures able to meet the prescribed objectives and minimize possible hazards for human health and the environment (e.g., EP 2000).
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::468c50cb1b197c32c4fe3567f73121f2 https://doi.org/10.1007/s00477-021-01998-y Zobrazit plný text záznamu Full text from SpringerLink