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10
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1.
Combined
assimilation
of streamflow and satellite soil moisture with the particle filter and geostatistical modeling
作者:
Hongxiang Yan
;
yan2@pdx.edu" class="auth_mail" title="E-mail the corresponding author
;
Hamid Moradkhani hamidm@pdx.edu" class="auth_mail" title="E-mail the corresponding author
关键词:
Data
assimilation
;
Particle filter
;
Markov chain
Monte
Carlo
;
Soil moisture
;
Geostatistical modeling
;
ASCAT
刊名:Advances in Water Resources
年:2016
2.
Comparison of Ensemble Kalman Filter groundwater-
data
assimilation
methods based on stochastic moment equations and
Monte
Carlo
simulation
作者:
M. Panzeria
;
marco.panzeri@polimi.it" class="auth_mail
;
M. Rivaa
;
b
;
A. Guadagninia
;
b
;
S.P. Neumanb
关键词:
Ensemble Kalman Filter
;
Random hydraulic conductivity field
;
Moment equations
;
Data
assimilation
;
Transient groundwater flow
;
Filter inbreeding
刊名:Advances in Water Resources
年:April, 2014
3.
Hydrologic
data
assimilation
using particle Markov chain
Monte
Carlo
simulation: Theory, concepts and applications
作者:
Jasper A. Vrugta
;
b
;
jasper@uci.edu
;
Cajo J.F. ter Braakc
;
Cees G.H. Diksd
;
Gerrit Schoupse
关键词:
Particle filtering
;
Bayes
;
Sequential
Monte
Carlo
;
Markov chain
Monte
Carlo
;
DREAM
;
Parameter and state estimation
刊名:Advances in Water Resources
年:2013
4.
Characterization of Non-Gaussian Geologic Facies Distribution Using Ensemble Kalman Filter with Probability Weighted Re-Sampling
作者:
Siavash Nejadi (1) Juliana Leung (1) Japan Trivedi (1) 1. School of Mining and Petroleum Engineering
;
University of Alberta
;
Markin/CNRL Natural Resources Engineering Facility
;
Edmonton
;
AB
;
T6G 2W2
;
Canada
关键词:
Non
;
Gaussian distributions
;
Facies characterization
;
Dynamic
data
integration
;
History matching
;
Ensemble methods
;
Re
;
sampling techniques
刊名:Mathematical Geosciences
出版者:Springer Berlin Heidelberg
年:2015
5.
Iterative ensemble smoothers in the annealed importance sampling framework
作者:
Andreas S. Stordal
;
a
;
Andreas.S.Stordal@iris.no" class="auth_mail" title="E-mail the corresponding author
;
Ahmed H. Elsheikhb
;
Ahmed.Elsheikh@pet.hw.ac.uk" class="auth_mail" title="E-mail the corresponding author
关键词:
Data
assimilation
;
Iterative ensemble methods
;
Annealed importance sampling
刊名:Advances in Water Resources
年:2015
6.
Ensemble Kalman filter versus particle filter for a physically-based coupled surface-subsurface model
作者:
Damiano Pasetto
;
Matteo Camporese
;
Mario Putti
关键词:
Surface/subsurface water interactions
;
CATHY Model
;
Bayesian uncertainty evaluation
;
Monte
Carlo
data
assimilation
;
SIR particle filter
;
Ensemble Kalman filter
刊名:Advances in Water Resources
年:2012
7.
To improve model soil moisture estimation in arid/semi-arid region using in situ and remote sensing information
作者:
Kuolin Hsu (1) kuolinh@uci.edu Jialun Li (1) Soroosh Sorooshian (1)
关键词:
Soil moisture –
;
Land surface model –
;
Data
assimilation
–
;
Sequential
Monte
Carlo
刊名:Paddy and Water Environment
年:2012
8.
Seasonal dynamics of CO2 balance and water consumption of C3 and C4-type cover crops compared to bare soil in a suitability study for their use in vineyards in Germany and Argentina
作者:
Ernesto M. Uliarte
;
Hans R. Schultz
;
Christian Frings
;
M¨¦lanie Pfister
;
Carlo
s A. Parera
;
Ra¨²l F. del
Monte
关键词:
Gas-exchange
;
C3 and C4-type cover crops
;
Water use efficiency
;
Tillage
;
Vineyard
刊名:Agricultural and Forest Meteorology
年:2013
9.
Data
assimilation
for transient flow in geologic formations via ensemble Kalman filter
作者:
Yan Chen and Dongxiao Zhang
关键词:
Data
assimilation
;
Ensemble Kalman filter
;
Hydraulic conductivity
;
Monte
Carlo
method
;
Uncertainty
刊名:Advances in Water Resources
年:2006
10.
Calibration framework for a Kalman filter applied to a groundwater model
作者:
Jean-Philippe Dré
;
court
;
Henrik Madsen and Dan Rosbjerg
关键词:
Groundwater
;
Automatic calibration
;
Ensemble Kalman filter
;
Uncertainty estimation
;
Bias
;
Latin hypercube sampling
刊名:Advances in Water Resources
年:2006
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