Articles | Volume 18, issue 7
https://doi.org/10.5194/hess-18-2503-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-2503-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Kalman filters for assimilating near-surface observations into the Richards equation – Part 1: Retrieving state profiles with linear and nonlinear numerical schemes
G. B. Chirico
Department of Agricultural Engineering, University of Naples Federico II, Naples, Italy
H. Medina
Department of Basic Sciences, Agrarian University of Havana, Havana, Cuba
N. Romano
Department of Agricultural Engineering, University of Naples Federico II, Naples, Italy
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- Inflation method based on confidence intervals for data assimilation in soil hydrology using the ensemble Kalman filter A. Jamal & R. Linker 10.1002/vzj2.20000
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- Soil moisture map construction by sequential data assimilation using an extended Kalman filter B. Agyeman et al. 10.1016/j.jhydrol.2021.126425
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19 citations as recorded by crossref.
- Effects of Soil Hydraulic Properties on Soil Moisture Estimation X. Fu et al. 10.1007/s13351-023-2049-2
- Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review Y. Li et al. 10.3390/rs8060456
- Obtaining soil hydraulic parameters from soil water content data assimilation under different climatic/soil conditions J. Valdes-Abellan et al. 10.1016/j.catena.2017.12.022
- Kalman filters for assimilating near-surface observations into the Richards equation – Part 3: Retrieving states and parameters from laboratory evaporation experiments H. Medina et al. 10.5194/hess-18-2543-2014
- How Critical Is the Assimilation Frequency of Water Content Measurements for Obtaining Soil Hydraulic Parameters with Data Assimilation? J. Valdes-Abellan et al. 10.2136/vzj2018.07.0142
- Recursively updating the error forecasting scheme of a complementary modelling framework for improved reservoir inflow forecasts A. Gragne et al. 10.1016/j.jhydrol.2015.05.039
- Integrating Sentinel-2 Imagery with AquaCrop for Dynamic Assessment of Tomato Water Requirements in Southern Italy A. Dalla Marta et al. 10.3390/agronomy9070404
- Adaptive Kalman Filtering for Postprocessing Ensemble Numerical Weather Predictions A. Pelosi et al. 10.1175/MWR-D-17-0084.1
- Comparison of ensemble-based state and parameter estimation methods for soil moisture data assimilation W. Chen et al. 10.1016/j.advwatres.2015.08.003
- Inflation method based on confidence intervals for data assimilation in soil hydrology using the ensemble Kalman filter A. Jamal & R. Linker 10.1002/vzj2.20000
- Geophysical and hydrological data assimilation to monitor water content dynamics in the rocky unsaturated zone L. De Carlo et al. 10.1007/s10661-018-6671-x
- Soil moisture map construction by sequential data assimilation using an extended Kalman filter B. Agyeman et al. 10.1016/j.jhydrol.2021.126425
- Kalman filters for assimilating near-surface observations into the Richards equation – Part 2: A dual filter approach for simultaneous retrieval of states and parameters H. Medina et al. 10.5194/hess-18-2521-2014
- The numerical solution of Richards’ equation by means of method of lines and ensemble Kalman filter M. Berardi & M. Vurro 10.1016/j.matcom.2015.08.019
- Forecasting potential evapotranspiration by combining numerical weather predictions and visible and near-infrared satellite images: an application in southern Italy G. Chirico et al. 10.1017/S0021859618000084
- Soil Moisture Estimation by Assimilating In‐Situ and SMAP Surface Soil Moisture Using Unscented Weighted Ensemble Kalman Filter X. Fu et al. 10.1029/2023WR034506
- Unscented weighted ensemble Kalman filter for soil moisture assimilation X. Fu et al. 10.1016/j.jhydrol.2019.124352
- Understanding the key factors that influence soil moisture estimation using the unscented weighted ensemble Kalman filter X. Fu et al. 10.1016/j.agrformet.2021.108745
- On the uncertainty of initial condition and initialization approaches in variably saturated flow modeling D. Yu et al. 10.5194/hess-23-2897-2019
1 citations as recorded by crossref.
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