Using data assimilation method to calibrate a heterogeneous conductivity field and improve solute transport prediction with an unknown contamination source

Stochastic Environmental Research and Risk Assessment

Volumn 23, Issue 8, 2009, Pages 1155-1167

  Huang, Chunlin ^a   Hu, Bill X ^b   Li, Xin ^a   Ye, Ming ^b  

^a Chinese Academy of Sciences   (China)

^b FLORIDA STATE UNIVERSITY   (United States)

Author keywords

Data assimilation; Ensemble Kalman filter; Hydraulic conductivity; Solute transport; Steady state flow

Indexed keywords

CONTAMINATION SOURCES; CONTINUOUS MEASUREMENTS; DATA ASSIMILATION; DATA ASSIMILATION METHODS; ENSEMBLE KALMAN FILTER; GROUNDWATER CONTAMINATION; HETEROGENEOUS MEDIA; HETEROGENEOUS MEDIUM; HYDRAULIC HEADS; INITIAL CONDITIONS; MEASUREMENT POINTS; MODEL PARAMETERS; NUMERICAL EXPERIMENTS; SOLUTE CONCENTRATIONS; SOURCE CONDITIONS; SPATIAL DISTRIBUTION; STATE VARIABLES; STEADY-STATE FLOWS;

CONTROL THEORY; DATA PROCESSING; GROUNDWATER; GROUNDWATER POLLUTION; HYDRAULIC CONDUCTIVITY; HYDROGEOLOGY; KALMAN FILTERS; RIVER POLLUTION;

SOLUTE TRANSPORT;

CALIBRATION; DATA ASSIMILATION; GROUNDWATER FLOW; GROUNDWATER POLLUTION; HETEROGENEITY; HETEROGENEOUS MEDIUM; HYDRAULIC CONDUCTIVITY; HYDRAULIC HEAD; KALMAN FILTER; POINT SOURCE POLLUTION; POLLUTANT TRANSPORT; PREDICTION; SOLUTE TRANSPORT; SPATIAL DISTRIBUTION; STEADY FLOW; TWO-DIMENSIONAL MODELING; UNCERTAINTY ANALYSIS;

EID: 71149113996     PISSN: 14363240     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00477-008-0289-4     Document Type: Article

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