Articles | Volume 17, issue 11
https://doi.org/10.5194/hess-17-4577-2013
© Author(s) 2013. 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-17-4577-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| Highlight paper
| 
19 Nov 2013
Research article | Highlight paper |
| 19 Nov 2013
Inverse streamflow routing
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
E. F. Wood
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
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Cited
29 citations as recorded by crossref.
- Spatio‐Temporal Model Variance‐Covariance Approach to Assimilating Streamflow Observations Into a Distributed Landscape Water Balance Model S. Tian et al. https://doi.org/10.1029/2021WR031649
- Combined assimilation of streamflow and satellite soil moisture with the particle filter and geostatistical modeling H. Yan & H. Moradkhani https://doi.org/10.1016/j.advwatres.2016.06.002
- Coherent Satellite Monitoring of the Water Cycle Over the Amazon. Part 2: Total Water Storage Change and River Discharge Estimation v. Pellet et al. https://doi.org/10.1029/2020WR028648
- Global patterns in river water storage dependent on residence time E. Collins et al. https://doi.org/10.1038/s41561-024-01421-5
- Enhancing SWOT discharge assimilation through spatiotemporal correlations Y. Yang et al. https://doi.org/10.1016/j.rse.2019.111450
- Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model W. Rudisill et al. https://doi.org/10.5194/gmd-16-6531-2023
- An experimental seasonal hydrological forecasting system over the Yellow River basin – Part 2: The added value from climate forecast models X. Yuan https://doi.org/10.5194/hess-20-2453-2016
- Spatiotemporal assimilation–interpolation of discharge records through inverse streamflow routing C. Fisher et al. https://doi.org/10.5194/hess-24-293-2020
- A digital twin model for contaminant fate and transport in urban and natural drainage networks with online state estimation M. Kim & M. Bartos https://doi.org/10.1016/j.envsoft.2023.105868
- River discharge estimation at daily resolution from satellite altimetry over an entire river basin M. Tourian et al. https://doi.org/10.1016/j.jhydrol.2017.01.009
- How Do Modeling Decisions Affect the Spread Among Hydrologic Climate Change Projections? Exploring a Large Ensemble of Simulations Across a Diversity of Hydroclimates O. Chegwidden et al. https://doi.org/10.1029/2018EF001047
- Operational aspects of asynchronous filtering for flood forecasting O. Rakovec et al. https://doi.org/10.5194/hess-19-2911-2015
- A First Look at River Discharge Estimation From SWOT Satellite Observations K. Andreadis et al. https://doi.org/10.1029/2024GL114185
- Improving River Routing Using a Differentiable Muskingum‐Cunge Model and Physics‐Informed Machine Learning T. Bindas et al. https://doi.org/10.1029/2023WR035337
- Underlying Fundamentals of Kalman Filtering for River Network Modeling C. Emery et al. https://doi.org/10.1175/JHM-D-19-0084.1
- A first continuous and distributed satellite-based mapping of river discharge over the Amazon V. Pellet et al. https://doi.org/10.1016/j.jhydrol.2022.128481
- Statistical Mapping of Freshwater Origin and Fate Signatures as Land/Ocean “Regions of Influence” in the Gulf of Mexico S. Fournier et al. https://doi.org/10.1029/2018JC014784
- Flow Duration Curve from Satellite: Potential of a Lifetime SWOT Mission A. Domeneghetti et al. https://doi.org/10.3390/rs10071107
- The National Hydrological Modeling System: Structure, Test Results, and Applications A. Gelfan et al. https://doi.org/10.3103/S1068373925090043
- A distributed simple dynamical systems approach (dS2 v1.0) for computationally efficient hydrological modelling at high spatio-temporal resolution J. Buitink et al. https://doi.org/10.5194/gmd-13-6093-2020
- Method of Discharge Data Assimilation into the ECOMAG Model Based on the Inverse Stream Routing Approach A. Bugaets et al. https://doi.org/10.1134/S0097807824607088
- Flood and drought hydrologic monitoring: the role of model parameter uncertainty N. Chaney et al. https://doi.org/10.5194/hess-19-3239-2015
- Comparative hydro-climatic datasets for catchment-wise linked water fluxes and storage changes across South America M. Zarei & G. Destouni https://doi.org/10.3389/fenvs.2026.1764771
- An inverse method for watershed change detection using hybrid conceptual and artificial intelligence approaches V. Nourani et al. https://doi.org/10.1016/j.jhydrol.2018.05.018
- Improving streamflow predictions at ungauged locations with real-time updating: application of an EnKF-based state-parameter estimation strategy X. Xie et al. https://doi.org/10.5194/hess-18-3923-2014
- Steeper temporal distribution of rain intensity at higher temperatures within Australian storms C. Wasko & A. Sharma https://doi.org/10.1038/ngeo2456
- In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics Y. Yang et al. https://doi.org/10.1029/2018WR024178
- The Event-specific Geomorphological Instantaneous Unit Hydrograph (E-GIUH): The basin hydrological response characteristic of a flood event H. Andrieu et al. https://doi.org/10.1016/j.jhydrol.2021.127158
- Estimating River Depth from SWOT-Type Observables Obtained by Satellite Altimetry and Imagery M. Tourian et al. https://doi.org/10.3390/w9100753
29 citations as recorded by crossref.
- Spatio‐Temporal Model Variance‐Covariance Approach to Assimilating Streamflow Observations Into a Distributed Landscape Water Balance Model S. Tian et al. https://doi.org/10.1029/2021WR031649
- Combined assimilation of streamflow and satellite soil moisture with the particle filter and geostatistical modeling H. Yan & H. Moradkhani https://doi.org/10.1016/j.advwatres.2016.06.002
- Coherent Satellite Monitoring of the Water Cycle Over the Amazon. Part 2: Total Water Storage Change and River Discharge Estimation v. Pellet et al. https://doi.org/10.1029/2020WR028648
- Global patterns in river water storage dependent on residence time E. Collins et al. https://doi.org/10.1038/s41561-024-01421-5
- Enhancing SWOT discharge assimilation through spatiotemporal correlations Y. Yang et al. https://doi.org/10.1016/j.rse.2019.111450
- Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model W. Rudisill et al. https://doi.org/10.5194/gmd-16-6531-2023
- An experimental seasonal hydrological forecasting system over the Yellow River basin – Part 2: The added value from climate forecast models X. Yuan https://doi.org/10.5194/hess-20-2453-2016
- Spatiotemporal assimilation–interpolation of discharge records through inverse streamflow routing C. Fisher et al. https://doi.org/10.5194/hess-24-293-2020
- A digital twin model for contaminant fate and transport in urban and natural drainage networks with online state estimation M. Kim & M. Bartos https://doi.org/10.1016/j.envsoft.2023.105868
- River discharge estimation at daily resolution from satellite altimetry over an entire river basin M. Tourian et al. https://doi.org/10.1016/j.jhydrol.2017.01.009
- How Do Modeling Decisions Affect the Spread Among Hydrologic Climate Change Projections? Exploring a Large Ensemble of Simulations Across a Diversity of Hydroclimates O. Chegwidden et al. https://doi.org/10.1029/2018EF001047
- Operational aspects of asynchronous filtering for flood forecasting O. Rakovec et al. https://doi.org/10.5194/hess-19-2911-2015
- A First Look at River Discharge Estimation From SWOT Satellite Observations K. Andreadis et al. https://doi.org/10.1029/2024GL114185
- Improving River Routing Using a Differentiable Muskingum‐Cunge Model and Physics‐Informed Machine Learning T. Bindas et al. https://doi.org/10.1029/2023WR035337
- Underlying Fundamentals of Kalman Filtering for River Network Modeling C. Emery et al. https://doi.org/10.1175/JHM-D-19-0084.1
- A first continuous and distributed satellite-based mapping of river discharge over the Amazon V. Pellet et al. https://doi.org/10.1016/j.jhydrol.2022.128481
- Statistical Mapping of Freshwater Origin and Fate Signatures as Land/Ocean “Regions of Influence” in the Gulf of Mexico S. Fournier et al. https://doi.org/10.1029/2018JC014784
- Flow Duration Curve from Satellite: Potential of a Lifetime SWOT Mission A. Domeneghetti et al. https://doi.org/10.3390/rs10071107
- The National Hydrological Modeling System: Structure, Test Results, and Applications A. Gelfan et al. https://doi.org/10.3103/S1068373925090043
- A distributed simple dynamical systems approach (dS2 v1.0) for computationally efficient hydrological modelling at high spatio-temporal resolution J. Buitink et al. https://doi.org/10.5194/gmd-13-6093-2020
- Method of Discharge Data Assimilation into the ECOMAG Model Based on the Inverse Stream Routing Approach A. Bugaets et al. https://doi.org/10.1134/S0097807824607088
- Flood and drought hydrologic monitoring: the role of model parameter uncertainty N. Chaney et al. https://doi.org/10.5194/hess-19-3239-2015
- Comparative hydro-climatic datasets for catchment-wise linked water fluxes and storage changes across South America M. Zarei & G. Destouni https://doi.org/10.3389/fenvs.2026.1764771
- An inverse method for watershed change detection using hybrid conceptual and artificial intelligence approaches V. Nourani et al. https://doi.org/10.1016/j.jhydrol.2018.05.018
- Improving streamflow predictions at ungauged locations with real-time updating: application of an EnKF-based state-parameter estimation strategy X. Xie et al. https://doi.org/10.5194/hess-18-3923-2014
- Steeper temporal distribution of rain intensity at higher temperatures within Australian storms C. Wasko & A. Sharma https://doi.org/10.1038/ngeo2456
- In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics Y. Yang et al. https://doi.org/10.1029/2018WR024178
- The Event-specific Geomorphological Instantaneous Unit Hydrograph (E-GIUH): The basin hydrological response characteristic of a flood event H. Andrieu et al. https://doi.org/10.1016/j.jhydrol.2021.127158
- Estimating River Depth from SWOT-Type Observables Obtained by Satellite Altimetry and Imagery M. Tourian et al. https://doi.org/10.3390/w9100753
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