Articles | Volume 19, issue 10
https://doi.org/10.5194/hess-19-4275-2015
© Author(s) 2015. 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-19-4275-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
22 Oct 2015
Research article |
| 22 Oct 2015
Correction of real-time satellite precipitation with satellite soil moisture observations
W. Zhan
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
N. Wanders
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
Department of Physical Geography, Utrecht University, Utrecht, the Netherlands
E. F. Wood
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
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33 citations as recorded by crossref.
- Flood forecasting using quantitative precipitation forecasts and hydrological modeling in the Sebeya catchment, Rwanda M. Assoumpta & D. Aja 10.2166/h2oj.2021.094
- Soil Moisture Data Assimilation to Estimate Irrigation Water Use R. Abolafia‐Rosenzweig et al. 10.1029/2019MS001797
- Effects of Different Spatial Precipitation Input Data on Crop Model Outputs under a Central European Climate S. Thaler et al. 10.3390/atmos9080290
- Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia L. Brocca et al. 10.1002/2016JD025382
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- Daily precipitation estimation through different microwave sensors: Verification study over Italy L. Ciabatta et al. 10.1016/j.jhydrol.2016.12.057
- Assessment of the effects of winter wheat scattering on SAR backscatter for soil moisture estimation based on a radiative transfer model M. Abassi et al. 10.1080/22797254.2024.2394780
- Earth Observation Data Synergy for the Enhanced Monitoring of Ephemeral Water Bodies to Anticipate Karst-Related Flooding E. Papageorgiou et al. 10.3390/geohazards4020012
- Exploiting a constellation of satellite soil moisture sensors for accurate rainfall estimation A. Tarpanelli et al. 10.1016/j.advwatres.2017.08.010
- SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture L. Ciabatta et al. 10.5194/essd-10-267-2018
- Evaluation of Backscattering Models and Support Vector Machine for the Retrieval of Bare Soil Moisture from Sentinel-1 Data J. Ezzahar et al. 10.3390/rs12010072
- Dual assimilation of satellite soil moisture to improve streamflow prediction in data‐scarce catchments C. Alvarez‐Garreton et al. 10.1002/2015WR018429
- Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons L. Karthikeyan et al. 10.1016/j.advwatres.2017.09.010
- Applicability of TRMM Precipitation for Hydrologic Modeling in a Basin in the Northeast Brazilian Agreste M. Soares Cruz et al. 10.1590/0102-7786331013
- SGD-SM 2.0: an improved seamless global daily soil moisture long-term dataset from 2002 to 2022 Q. Zhang et al. 10.5194/essd-14-4473-2022
- Application of Satellite Rainfall Products for Flood Inundation Modelling in Kelantan River Basin, Malaysia T. Tam et al. 10.3390/hydrology6040095
- Reliability of SM2RAIN precipitation datasets in comparison to gauge observations and hydrological modelling over arid regions F. Satgé et al. 10.1002/joc.6704
- A Review of Satellite-Derived Soil Moisture and Its Usage for Flood Estimation S. Kim et al. 10.1007/s41976-019-00025-7
- Respective Advantages of “Top‐Down” Based GPM IMERG and “Bottom‐Up” Based SM2RAIN‐ASCAT Precipitation Products Over the Tibetan Plateau Y. Fan et al. 10.1029/2020JD033946
- Analysis of an extreme weather event in a hyper-arid region using WRF-Hydro coupling, station, and satellite data Y. Wehbe et al. 10.5194/nhess-19-1129-2019
- Four decades of microwave satellite soil moisture observations: Part 1. A review of retrieval algorithms L. Karthikeyan et al. 10.1016/j.advwatres.2017.09.006
- Complementing near-real time satellite rainfall products with satellite soil moisture-derived rainfall through a Bayesian Inversion approach C. Massari et al. 10.1016/j.jhydrol.2019.03.038
- A Novel Real-Time Error Adjustment Method With Considering Four Factors for Correcting Hourly Multi-Satellite Precipitation Estimates H. Chen et al. 10.1109/TGRS.2021.3131238
- From SMOS Soil Moisture to 3-hour Precipitation Estimates at 0.1° Resolution in Africa T. Pellarin et al. 10.3390/rs14030746
- Comparison of the Performance of IMERG Products and Interpolation-Based Precipitation Estimates in the Middle Reaches of Yellow River Basin J. Shi et al. 10.3390/w14091503
- Correcting Satellite Precipitation Data and Assimilating Satellite-Derived Soil Moisture Data to Generate Ensemble Hydrological Forecasts within the HBV Rainfall-Runoff Model M. Ciupak et al. 10.3390/w11102138
- Bias correction framework for satellite precipitation products using a rain/no rain discriminative model S. Xiao et al. 10.1016/j.scitotenv.2021.151679
- A global near-real-time soil moisture index monitor for food security using integrated SMOS and SMAP S. Sadri et al. 10.1016/j.rse.2020.111864
- A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products C. Massari et al. 10.5194/hess-24-2687-2020
- Spatial downscaling of precipitation using adaptable random forests X. He et al. 10.1002/2016WR019034
- Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS H. Beck et al. 10.5194/hess-23-207-2019
- Evaluating drought monitoring utility of the top-down and bottom-up satellite precipitation products over mainland China from a three-dimensional perspective Y. Zhang et al. 10.1016/j.jhydrol.2023.130153
- Precipitation estimation using L‐band and C‐band soil moisture retrievals R. Koster et al. 10.1002/2016WR019024
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