Articles | Volume 16, issue 1
https://doi.org/10.5194/hess-16-105-2012
© Author(s) 2012. 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-16-105-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Improving estimated soil moisture fields through assimilation of AMSR-E soil moisture retrievals with an ensemble Kalman filter and a mass conservation constraint
B. Li
Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, and Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
D. Toll
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
X. Zhan
NOAA NESDIS Center for Satellite Applications and Research, Camp Springs, MD, USA
B. Cosgrove
NOAA/NWS Office of Hydrologic Development, Silver Spring, MD, USA
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34 citations as recorded by crossref.
- Constraining the ensemble Kalman filter for improved streamflow forecasting D. Maxwell et al. 10.1016/j.jhydrol.2018.03.015
- Development of a daily soil moisture product for the period of 2002–2011 in Chinese mainland K. Yang et al. 10.1007/s11430-019-9588-5
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- On the uncertainty of initial condition and initialization approaches in variably saturated flow modeling D. Yu et al. 10.5194/hess-23-2897-2019
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- Evaluating uncertainties in multi-layer soil moisture estimation with support vector machines and ensemble Kalman filtering D. Liu et al. 10.1016/j.jhydrol.2016.04.021
- Assimilation of Satellite-Derived Soil Moisture and Brightness Temperature in Land Surface Models: A Review R. Khandan et al. 10.3390/rs14030770
- Estimating surface turbulent heat fluxes from land surface temperature and soil moisture observations using the particle batch smoother Y. Lu et al. 10.1002/2016WR018943
- Evolution of ensemble data assimilation for uncertainty quantification using the particle filter‐Markov chain Monte Carlo method H. Moradkhani et al. 10.1029/2012WR012144
- Assimilation of SMOS Soil Moisture for Quantifying Drought Impacts on Crop Yield in Agricultural Regions S. Chakrabarti et al. 10.1109/JSTARS.2014.2315999
- Assimilation of GRACE terrestrial water storage into a land surface model: Evaluation and potential value for drought monitoring in western and central Europe B. Li et al. 10.1016/j.jhydrol.2012.04.035
- Assimilating shallow soil moisture observations into land models with a water budget constraint B. Dan et al. 10.5194/hess-24-5187-2020
- Satellite soil moisture data assimilation for improved operational continental water balance prediction S. Tian et al. 10.5194/hess-25-4567-2021
- Quantifying Precipitation Uncertainty for Land Data Assimilation Applications S. Alemohammad et al. 10.1175/MWR-D-14-00337.1
- An Intercomparison of Noah Model Skills With Benefits of Assimilating SMOPS Blended and Individual Soil Moisture Retrievals J. Yin et al. 10.1029/2018WR024326
- Spatial variability and its scale dependency of observed and modeled soil moisture over different climate regions B. Li & M. Rodell 10.5194/hess-17-1177-2013
- Sensitivity of Near-Surface Temperature Forecasts to Soil Properties over a Sparsely Vegetated Dryland Region J. Massey et al. 10.1175/JAMC-D-13-0362.1
- Three Decades of Groundwater Drought Research: Evolution and Trends I. El Bouazzaoui et al. 10.3390/w16050743
- Soil moisture background error covariance and data assimilation in a coupled land‐atmosphere model L. Lin et al. 10.1002/2015WR017548
- Support vector machine and data assimilation framework for Groundwater Level Forecasting using GRACE satellite data D. Liu et al. 10.1016/j.jhydrol.2021.126929
- Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale R. Rosolem et al. 10.5194/hess-18-4363-2014
- A land data assimilation system for simultaneous simulation of soil moisture and vegetation dynamics Y. Sawada et al. 10.1002/2014JD022895
- Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model P. Laiolo et al. 10.1016/j.jag.2015.06.002
- Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities Y. Liu et al. 10.5194/hess-16-3863-2012
- Simultaneous assimilation of in situ soil moisture and streamflow in the SWAT model using the Extended Kalman Filter L. Sun et al. 10.1016/j.jhydrol.2016.10.040
- Monitoring and Predicting Agricultural Droughts for a Water-Limited Subcontinental Region by Integrating a Land Surface Model and Microwave Remote Sensing Y. Sawada et al. 10.1109/TGRS.2019.2927342
- Comparison of X-Band and L-Band Soil Moisture Retrievals for Land Data Assimilation X. Xu et al. 10.1109/JSTARS.2017.2703988
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