Harrie-Jan Hendricks Franssen spends much of his time researching Data assimilation, Hydrology, Soil water, Evapotranspiration and Precipitation. The concepts of his Data assimilation study are interwoven with issues in Estimation theory, Management science and Ensemble Kalman filter. Harrie-Jan Hendricks Franssen interconnects Hydraulic conductivity, Groundwater flow, Aquifer and Hydraulic head in the investigation of issues within Ensemble Kalman filter.
His study in Soil water is interdisciplinary in nature, drawing from both Ecosystem, Hydrology, Environmental resource management and Water content. In his research on the topic of Evapotranspiration, Hydrological modelling and Groundwater recharge is strongly related with Downscaling. His Topsoil study, which is part of a larger body of work in Soil science, is frequently linked to Context, bridging the gap between disciplines.
Harrie-Jan Hendricks Franssen mainly focuses on Data assimilation, Hydrology, Water content, Groundwater and Ensemble Kalman filter. His Data assimilation study necessitates a more in-depth grasp of Meteorology. Many of his research projects under Hydrology are closely connected to Variable with Variable, tying the diverse disciplines of science together.
His study on Water content also encompasses disciplines like
Harrie-Jan Hendricks Franssen mainly investigates Data assimilation, Water content, Atmospheric sciences, Ensemble Kalman filter and Soil science. In most of his Data assimilation studies, his work intersects topics such as Climatology. His Water content study is concerned with Hydrology in general.
His Hydrology research integrates issues from Sampling and Lysimeter. His Ensemble Kalman filter research is multidisciplinary, incorporating elements of Estimation theory, Algorithm, Normal score, Mean squared error and Remote sensing. His Soil science research incorporates elements of Evaporation and Aquifer.
The scientist’s investigation covers issues in Water content, Ensemble Kalman filter, Data assimilation, Meteorology and Water balance. His work in Water content covers topics such as Soil water which are related to areas like Spatial variability. The various areas that Harrie-Jan Hendricks Franssen examines in his Ensemble Kalman filter study include Algorithm, Flood myth, Remote sensing and Normal score.
His Data assimilation study frequently involves adjacent topics like Atmospheric sciences. His work carried out in the field of Meteorology brings together such families of science as Cosmic ray, Carbon flux, Forcing, Plant functional type and Drip irrigation. The study incorporates disciplines such as Mean squared error and Water resources in addition to Water balance.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Modeling Soil Processes: Review, Key Challenges, and New Perspectives
H. Vereecken;A. Schnepf;J. W. Hopmans;M. Javaux.
Vadose Zone Journal (2016)
Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities
Yuqiong Liu;Yuqiong Liu;A. Weerts;M. Clark;H.-J Hendricks Franssen.
Hydrology and Earth System Sciences (2012)
Real-time groundwater flow modeling with the Ensemble Kalman Filter: Joint estimation of states and parameters and the filter inbreeding problem
H. J. Hendricks Franssen;W. Kinzelbach.
Water Resources Research (2008)
Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter
Carsten Montzka;Hamid Moradkhani;Lutz Weihermüller;Harrie-Jan Hendricks Franssen.
Journal of Hydrology (2011)
Energy balance closure of eddy-covariance data: a multisite analysis for European FLUXNET stations.
H.J. Hendricks Franssen;H.J. Hendricks Franssen;R. Stöckli;I. Lehner;E. Rotenberg.
Agricultural and Forest Meteorology (2010)
Parameter estimation by ensemble Kalman filters with transformed data: Approach and application to hydraulic tomography
A. Schöniger;W. Nowak;H.-J. Hendricks Franssen.
Water Resources Research (2012)
SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin, Australia
H. Lievens;S.K. Tomer;A. Al Bitar;G.J.M. De Lannoy.
Remote Sensing of Environment (2015)
Accuracy of the cosmic-ray soil water content probe in humid forest ecosystems: The worst case scenario
H. R. Bogena;J. A. Huisman;R. Baatz;H.-J. Hendricks Franssen.
Water Resources Research (2013)
How can remote sensing contribute in groundwater modeling
P. Brunner;H.-J.Hendricks Franssen;L. Kgotlhang;Peter Bauer-Gottwein.
Hydrogeology Journal (2007)
Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket
S. Gebler;H.-J. Hendricks Franssen;T. Pütz;H. Post.
Hydrology and Earth System Sciences (2015)
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