Assessment of groundwater well vulnerability to contamination through physics-informed machine learning
Soriano M, Siegel H, Johnson N, Gutchess K, Xiong B, Li Y, Clark C, Plata D, Deziel N, Saiers J. Assessment of groundwater well vulnerability to contamination through physics-informed machine learning. Environmental Research Letters 2021, 16: 084013. DOI: 10.1088/1748-9326/ac10e0.Peer-Reviewed Original ResearchWell vulnerabilityLarge-scale problemsPhysics-informed machineGroundwater risk assessmentGroundwater contamination riskMetamodel predictionsShallow aquiferGroundwater resourcesChemical signaturesScale problemsAnthropogenic activitiesContaminant releaseContaminant sourcesQuality recordsNatural gas productionMarcellus ShaleHigh spatial resolutionUnconventional oilHousehold wellsNortheastern PennsylvaniaFuture impactGas developmentGeographic information systemNecessary numberPB model