Articles | Volume 21, issue 1
https://doi.org/10.5194/hess-21-635-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-21-635-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Evaluation of snow data assimilation using the ensemble Kalman filter for seasonal streamflow prediction in the western United States
Chengcheng Huang
College of Global Change and Earth System Science, Beijing Normal
University, Beijing, China
National Center for Atmospheric Research, Boulder, CO 80301, USA
National Center for Atmospheric Research, Boulder, CO 80301, USA
Martyn P. Clark
National Center for Atmospheric Research, Boulder, CO 80301, USA
Andrew W. Wood
National Center for Atmospheric Research, Boulder, CO 80301, USA
Xiaogu Zheng
College of Global Change and Earth System Science, Beijing Normal
University, Beijing, China
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49 citations as recorded by crossref.
- Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios A. Gelfan et al. 10.5194/hess-22-2073-2018
- Interconnected hydrologic extreme drivers and impacts depicted by remote sensing data assimilation T. Lahmers et al. 10.1038/s41598-023-30484-4
- Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed D. Casson et al. 10.5194/hess-22-4685-2018
- Runoff response to the uncertainty from key water-budget variables in a seasonally snow-covered mountain basin G. Cui et al. 10.1016/j.ejrh.2023.101601
- The role of probabilistic precipitation forecasts in hydrologic predictability S. Seo & J. Sung 10.1007/s00704-020-03273-6
- The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset C. Alvarez-Garreton et al. 10.5194/hess-22-5817-2018
- Assimilating snow observations to snow interception process simulations Z. Lv & J. Pomeroy 10.1002/hyp.13720
- Assimilation of blended in situ-satellite snow water equivalent into the National Water Model for improving hydrologic simulation in two US river basins Y. Gan et al. 10.1016/j.scitotenv.2022.156567
- Implications of observation-enhanced energy-balance snowmelt simulations for runoff modeling of Alpine catchments N. Griessinger et al. 10.1016/j.advwatres.2019.103410
- Subseasonal to seasonal streamflow forecasting in a semiarid watershed P. Broxton et al. 10.1111/1752-1688.13147
- A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment G. Piazzi et al. 10.5194/tc-12-2287-2018
- Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF‐Hydro System T. Lahmers et al. 10.1029/2021WR029867
- GEE can prominently reduce uncertainties from input data and parameters of the remote sensing-driven distributed hydrological model Z. Pan et al. 10.1016/j.scitotenv.2023.161852
- A seasonal algorithm of the snow-covered area fraction for mountainous terrain N. Helbig et al. 10.5194/tc-15-4607-2021
- An extension of data assimilation into the short-term hydrologic forecast for improved prediction reliability J. Leach & P. Coulibaly 10.1016/j.advwatres.2019.103443
- Why does snowmelt-driven streamflow response to warming vary? A data-driven review and predictive framework B. Gordon et al. 10.1088/1748-9326/ac64b4
- Operational Seasonal Water Supply and Water Level Forecasting for the Laurentian Great Lakes L. Fry et al. 10.1061/(ASCE)WR.1943-5452.0001214
- Sequential and batch data assimilation approaches to cope with groundwater model error: An empirical evaluation K. Markovich et al. 10.1016/j.envsoft.2022.105498
- The Multiple Snow Data Assimilation System (MuSA v1.0) E. Alonso-González et al. 10.5194/gmd-15-9127-2022
- Exploratory studies into seasonal flow forecasting potential for large lakes K. Sene et al. 10.5194/hess-22-127-2018
- Development of a copula‐based particle filter (CopPF) approach for hydrologic data assimilation under consideration of parameter interdependence Y. Fan et al. 10.1002/2016WR020144
- A Snow Water Equivalent Retrieval Framework Coupling 1D Hydrology and Passive Microwave Radiative Transfer Models Y. Cao et al. 10.3390/rs16101732
- Application of Parameter Screening to Derive Optimal Initial State Adjustments for Streamflow Forecasting J. Mai et al. 10.1029/2020WR027960
- Role of forcing uncertainty and background model error characterization in snow data assimilation S. Kumar et al. 10.5194/hess-21-2637-2017
- An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space S. Kumar et al. 10.1029/2022MS003259
- Assessing the impact of distributed snow water equivalent calibration and assimilation of Copernicus snow water equivalent on modelled snow and streamflow performance A. Beaton et al. 10.1002/hyp.15075
- The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review D. Jiang & K. Wang 10.3390/w11081615
- An Enkf-Based Scheme for Snow Multivariable Data Assimilation at an Alpine Site G. Piazzi et al. 10.2478/johh-2018-0013
- Efficient treatment of climate data uncertainty in ensemble Kalman filter (EnKF) based on an existing historical climate ensemble dataset H. Liu et al. 10.1016/j.jhydrol.2018.11.047
- Improving monthly streamflow forecasts through assimilation of observed streamflow for rainfall-dominated basins across the CONUS A. Mazrooei & A. Sankarasubramanian 10.1016/j.jhydrol.2019.05.071
- Assimilation of Ground and Satellite Snow Observations in a Distributed Hydrologic Model for Water Supply Forecasting P. Micheletty et al. 10.1111/1752-1688.12975
- Assessing 32-Day Hydrological Ensemble Forecasts in the Lake Champlain–Richelieu River Watershed M. Abaza et al. 10.1061/(ASCE)HE.1943-5584.0001983
- Probabilistic Spatial Meteorological Estimates for Alaska and the Yukon A. Newman et al. 10.1029/2020JD032696
- Benchmarking an operational hydrological model for providing seasonal forecasts in Sweden M. Girons Lopez et al. 10.5194/hess-25-1189-2021
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- 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. 10.3390/geosciences13030089
- An intercomparison of approaches for improving operational seasonal streamflow forecasts P. Mendoza et al. 10.5194/hess-21-3915-2017
- Data Assimilation Improves Estimates of Climate-Sensitive Seasonal Snow M. Girotto et al. 10.1007/s40641-020-00159-7
- Review of Snow Data Assimilation Methods for Hydrological, Land Surface, Meteorological and Climate Models: Results from a COST HarmoSnow Survey J. Helmert et al. 10.3390/geosciences8120489
- Leveraging a novel hybrid ensemble and optimal interpolation approach for enhanced streamflow and flood prediction M. El Gharamti et al. 10.5194/hess-28-3133-2024
- An Enriched Prediction Intervals Construction Method with Hybrid Intelligent Optimization J. Lu et al. 10.1155/2018/4893617
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- Assimilation of near-real time data products into models of an urban basin J. Leach et al. 10.1016/j.jhydrol.2018.05.064
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- Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling D. Araya et al. 10.5194/hess-27-4385-2023
- Does the Complexity of Evapotranspiration and Hydrological Models Enhance Robustness? D. Birhanu et al. 10.3390/su10082837
Latest update: 19 Nov 2024
Short summary
This study examined the potential of snow water equivalent data assimilation to improve seasonal streamflow predictions. We examined aspects of the data assimilation system over basins with varying climates across the western US. We found that varying how the data assimilation system is implemented impacts forecast performance, and basins with good initial calibrations see less benefit. This implies that basin-specific configurations and benefits should be expected given this modeling system.
This study examined the potential of snow water equivalent data assimilation to improve seasonal...
Special issue