A multi-layer soil moisture data assimilation using support vector machines and ensemble particle filter

Journal of Hydrology

Volumn 475, Issue , 2012, Pages 53-64

  Yu, Zhongbo ^a,b   Liu, Di ^a   Lü, Haishen ^a   Fu, Xiaolei ^a   Xiang, Long ^a   Zhu, Yonghua ^a  

^a HOHAI UNIVERSITY   (China)

^b UNIVERSITY OF NEVADA   (United States)

Author keywords

Data assimilation; Ensemble kalman filter; Ensemble particle filter; Particle filter; Support vector machines

Indexed keywords

AIR TEMPERATURE; DATA ASSIMILATION; DATA ASSIMILATION METHODS; DATA ASSIMILATION TECHNIQUES; ENSEMBLE KALMAN FILTER; ENSEMBLE MEMBERS; HYDROLOGY AND WATER RESOURCE; METEOROLOGICAL PARAMETERS; MOISTURE DATA; PARTICLE FILTER; RESAMPLING; ROBUST MODELS; ROOT ZONE; SOIL TEMPERATURE; STUDY AREAS; SVM MODEL; TRAINING DATA; TRAINING PHASE;

COMPUTER SIMULATION; DATA PROCESSING; FORECASTING; KALMAN FILTERS; MONTE CARLO METHODS; PERSONNEL TRAINING; SOIL MOISTURE; SOIL SURVEYS; SUN; WATER RESOURCES;

SUPPORT VECTOR MACHINES;

AIR TEMPERATURE; DATA ASSIMILATION; FILTER; KALMAN FILTER; METEOROLOGY; NUMERICAL MODEL; PARTICLE SIZE; RELATIVE HUMIDITY; RHIZOSPHERE; SOIL MOISTURE; SOIL TEMPERATURE; SOLAR RADIATION; WATER RESOURCE; WATERSHED;

CHINA; JIANGSU; YIXING;

EID: 84870251764     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2012.08.034     Document Type: Article

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