Jointly mapping hydraulic conductivity and porosity by assimilating concentration data via ensemble Kalman filter

Journal of Hydrology

Volumn 428-429, Issue , 2012, Pages 152-169

  Li, Liangping ^a   Zhou, Haiyan ^a   Gómez Hernández, J Jaime ^a   Hendricks Franssen, Harrie Jan ^b  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

^b FORSCHUNGSZENTRUM JÜLICH   (Germany)

Author keywords

Data assimilation; Ensemble Kalman filter; Heterogeneity; Hydraulic conductivity and porosity; Multiple concentration data; Stochastic transport

Indexed keywords

DATA ASSIMILATION; ENSEMBLE KALMAN FILTER; HETEROGENEITY; MULTIPLE CONCENTRATION DATA; STOCHASTIC TRANSPORT;

AQUIFERS; CHARACTERIZATION; COMPUTER SIMULATION; DATA PROCESSING; GROUNDWATER FLOW; GROUNDWATER POLLUTION; GROUNDWATER RESOURCES; HYDRAULIC CONDUCTIVITY; KALMAN FILTERS; SENSORS;

POROSITY;

DATA ASSIMILATION; DATA SET; GROUNDWATER FLOW; HETEROGENEITY; HYDRAULIC CONDUCTIVITY; HYDROLOGICAL MODELING; KALMAN FILTER; MAPPING; NUMERICAL MODEL; PIEZOMETER; POLLUTANT TRANSPORT; POROSITY; PREDATION; REAL TIME; SENSOR; STOCHASTICITY; UNCERTAINTY ANALYSIS;

EID: 84862777821     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2012.01.037     Document Type: Article

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