43 citations as recorded by crossref.

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6. Assimilation of Images via Dictionary Learning-Based Sparsity Regularization Strategy: An Application for Retrieving Fluid Flows L. Li et al.
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15. Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models M. Mazzoleni et al.
16. ISANet: Deep Neural Network Approximating Image Sequence Assimilation for Tracking Fluid Flows L. Li & J. Ma
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19. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities Y. Liu et al.
20. Sensitivity‐Based Soil Moisture Assimilation for Improved Streamflow Forecast Using a Novel Forward Sensitivity Method (FSM) Approach R. Visweshwaran et al.
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22. Unified Hydrological Flow Routing for Variational Data Assimilation and Model Predictive Control R. Montero et al.
23. High-resolution modeling and prediction of urban floods using WRF-Hydro and data assimilation S. Kim et al.
24. Comparison of Deterministic and Probabilistic Variational Data Assimilation Methods Using Snow and Streamflow Data Coupled in HBV Model for Upper Euphrates Basin G. Uysal et al.
25. Multi-parametric variational data assimilation for hydrological forecasting R. Alvarado-Montero et al.
26. Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model R. Montero et al.
27. An integrated error parameter estimation and lag-aware data assimilation scheme for real-time flood forecasting Y. Li et al.
28. Improvement of operational flood forecasting through the assimilation of satellite observations and multiple river flow data F. Castelli & G. Ercolani
29. Improving flood forecasting using conditional bias-aware assimilation of streamflow observations and dynamic assessment of flow-dependent information content H. Shen et al.
30. Variational assimilation of remotely sensed flood extents using a 2-D flood model X. Lai et al.
31. Improving flood forecasting using conditional bias-penalized ensemble Kalman filter H. Lee et al.
32. State updating in a distributed hydrological model by ensemble Kalman filtering with error estimation J. Gong et al.
33. Hybrid forecasting model for non-stationary daily runoff series: A case study in the Han River Basin, China T. Xie et al.
34. A weakly-constrained data assimilation approach to address rainfall-runoff model structural inadequacy in streamflow prediction H. Lee et al.
35. Assimilation of hydrologic and hydrometeorological data into distributed hydrologic model: Effect of adjusting mean field bias in radar-based precipitation estimates H. Lee & D. Seo
36. Variational assimilation of streamflow data in distributed flood forecasting G. Ercolani & F. Castelli
37. Flood modelling using synthesised citizen science urban streamflow observations M. Fava et al.
38. Assimilating in situ and radar altimetry data into a large-scale hydrologic-hydrodynamic model for streamflow forecast in the Amazon R. Paiva et al.
39. SWAT‐Based Hydrological Data Assimilation System (SWAT‐HDAS): Description and Case Application to River Basin‐Scale Hydrological Predictions Y. Zhang et al.
40. Utilizing satellite precipitation estimates for streamflow forecasting via adjustment of mean field bias in precipitation data and assimilation of streamflow observations H. Lee et al.
41. A data-assimilated SEAS5 forecasting framework for seasonal hydropower inflows in a snow-dominated basin G. Uysal et al.
42. Toward Discharge Estimation for Water Resources Management with a Semidistributed Model and Local Ensemble Kalman Filter Data Assimilation S. Wongchuig et al.
43. Spatio‐Temporal Model Variance‐Covariance Approach to Assimilating Streamflow Observations Into a Distributed Landscape Water Balance Model S. Tian et al.