Big data-driven water research towards metaverse  

作　　者：Minori Uchimiya 

机构地区：[1]USDA-ARS Southern Regional Research Center,1100 Allen Toussaint Boulevard,New Orleans,LA 70124,USA

出　　处：《Water Science and Engineering》2024年第2期101-107,共7页水科学与水工程（英文版）

摘　　要：Although big data is publicly available on water quality parameters,virtual simulation has not yet been adequately adapted in environmental chemistry research.Digital twin is different from conventional geospatial modeling approaches and is particularly useful when systematic laboratory/field experiment is not realistic(e.g.,climate impact and water-related environmental catastrophe)or difficult to design and monitor in a real time(e.g.,pollutant and nutrient cycles in estuaries,soils,and sediments).Data-driven water research could realize early warning and disaster readiness simulations for diverse environmental scenarios,including drinking water contamination.

关 键 词：Data mining OMICS Remote sensing SENSOR CHEMOINFORMATICS 

分 类 号：TV213.4[水利工程—水文学及水资源]