23 citations as recorded by crossref.

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2. 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
3. A Decentralized Framework for Parameter and State Estimation of Infiltration Processes S. Bo & J. Liu 10.3390/math8050681
4. 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
5. Unscented weighted ensemble Kalman filter for soil moisture assimilation X. Fu et al. 10.1016/j.jhydrol.2019.124352
6. Simultaneous estimation of surface soil moisture and soil properties with a dual ensemble Kalman smoother N. Chu et al. 10.1007/s11430-015-5175-6
7. Application of hybrid Kalman filter for improving water level forecast X. Wang & V. Babovic 10.2166/hydro.2016.085
8. A gaussian process-based iterative Ensemble Kalman Filter for parameter estimation of unsaturated flow K. Liu et al. 10.1016/j.jhydrol.2020.125210
9. Adaptive Kalman Filtering for Postprocessing Ensemble Numerical Weather Predictions A. Pelosi et al. 10.1175/MWR-D-17-0084.1
10. Inverse Physics-Informed Neural Networks for transport models in porous materials M. Berardi et al. 10.1016/j.cma.2024.117628
11. Development and evaluation of an efficient soil-atmosphere model (FHAVeT) based on the Ross fast solution of the Richards equation for bare soil conditions A. Tinet et al. 10.5194/hess-19-969-2015
12. 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
13. 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
14. 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
15. A dynamic data-driven method for dealing with model structural error in soil moisture data assimilation Q. Zhang et al. 10.1016/j.advwatres.2019.103407
16. Integrating Sentinel-2 Imagery with AquaCrop for Dynamic Assessment of Tomato Water Requirements in Southern Italy A. Dalla Marta et al. 10.3390/agronomy9070404
17. Estimation of hydraulic parameters in a heterogeneous low‐lying farmland near Venice E. Zancanaro et al. 10.1002/hyp.14791
18. On the uncertainty of initial condition and initialization approaches in variably saturated flow modeling D. Yu et al. 10.5194/hess-23-2897-2019
19. 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
20. ReLU surrogates in mixed-integer MPC for irrigation scheduling B. Agyeman et al. 10.1016/j.cherd.2024.10.005
21. Soil moisture map construction by sequential data assimilation using an extended Kalman filter B. Agyeman et al. 10.1016/j.jhydrol.2021.126425
22. Parameter and State Estimation of One-Dimensional Infiltration Processes: A Simultaneous Approach S. Bo et al. 10.3390/math8010134
23. 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