Articles | Volume 19, issue 11
https://doi.org/10.5194/hess-19-4463-2015
© 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-19-4463-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes
S. V. Kumar
CORRESPONDING AUTHOR
Science Applications International Corporation, Beltsville, MD, USA
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
C. D. Peters-Lidard
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
J. A. Santanello
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
R. H. Reichle
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
C. S. Draper
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Universities Space Research Association, NASA Goddard Space Flight Center, Greenbelt, MD, USA
R. D. Koster
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
G. Nearing
Science Applications International Corporation, Beltsville, MD, USA
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
M. F. Jasinski
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
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128 citations as recorded by crossref.
- Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP S. Modanesi et al. 10.5194/hess-26-4685-2022
- On the Utility of High-Resolution Soil Moisture Data for Better Constraining Thermal-Based Energy Balance over Three Semi-Arid Agricultural Areas B. Ait Hssaine et al. 10.3390/rs13040727
- Dual state/rainfall correction via soil moisture assimilation for improved streamflow simulation: evaluation of a large-scale implementation with Soil Moisture Active Passive (SMAP) satellite data Y. Mao et al. 10.5194/hess-24-615-2020
- Assimilation of Satellite Soil Moisture Products for River Flow Prediction: An Extensive Experiment in Over 700 Catchments Throughout Europe D. De Santis et al. 10.1029/2021WR029643
- Detecting and mapping irrigated areas in a Mediterranean environment by using remote sensing soil moisture and a land surface model J. Dari et al. 10.1016/j.jhydrol.2021.126129
- Soil moisture background error covariance and data assimilation in a coupled land‐atmosphere model L. Lin et al. 10.1002/2015WR017548
- A triple collocation-based 2D soil moisture merging methodology considering spatial and temporal non-stationary errors J. Zhou et al. 10.1016/j.rse.2021.112509
- Machine learning-based detection of irrigation in Vojvodina (Serbia) using Sentinel-2 data M. Radulović et al. 10.1080/15481603.2023.2262010
- Assessment of anthropogenic and climate-driven water storage variations over water-stressed river basins of Ethiopia A. Yoshe 10.2166/nh.2024.169
- The Land surface Data Toolkit (LDT v7.2) – a data fusion environment for land data assimilation systems K. Arsenault et al. 10.5194/gmd-11-3605-2018
- Assimilation of Passive L-band Microwave Brightness Temperatures in the Canadian Land Data Assimilation System: Impacts on Short-Range Warm Season Numerical Weather Prediction M. Carrera et al. 10.1175/JHM-D-18-0133.1
- An inter-comparison of different PSO-optimized artificial intelligence algorithms for thermal-based soil moisture retrieval N. Behnia et al. 10.1007/s12145-021-00747-7
- Indicator of Flood-Irrigated Crops From SMOS and SMAP Soil Moisture Products in Southern India C. Pascal et al. 10.1109/LGRS.2023.3267825
- The Potential Utility of Satellite Soil Moisture Retrievals for Detecting Irrigation Patterns in China X. Zhang et al. 10.3390/w10111505
- Global scale error assessments of soil moisture estimates from microwave-based active and passive satellites and land surface models over forest and mixed irrigated/dryland agriculture regions H. Kim et al. 10.1016/j.rse.2020.112052
- Impact of Bias-Correction Methods on Effectiveness of Assimilating SMAP Soil Moisture Data into NCEP Global Forecast System Using the Ensemble Kalman Filter J. Yin & X. Zhan 10.1109/LGRS.2018.2806092
- Irrigation characterization improved by the direct use of SMAP soil moisture anomalies within a data assimilation system Y. Kwon et al. 10.1088/1748-9326/ac7f49
- Improved soil moisture estimation and detection of irrigation signal by incorporating SMAP soil moisture into the Indian Land Data Assimilation System (ILDAS) A. Chakraborty et al. 10.1016/j.jhydrol.2024.131581
- A New Method for Generating the SMOPS Blended Satellite Soil Moisture Data Product without Relying on a Model Climatology J. Yin et al. 10.3390/rs14071700
- Enhancing Noah Land Surface Model Prediction Skill over Indian Subcontinent by Assimilating SMOPS Blended Soil Moisture A. Nair & J. Indu 10.3390/rs8120976
- Modeling actual water use under different irrigation regimes at district scale: Application to the FAO-56 dual crop coefficient method L. Olivera-Guerra et al. 10.1016/j.agwat.2022.108119
- Remote Sensing, Geophysics, and Modeling to Support Precision Agriculture—Part 2: Irrigation Management A. Pradipta et al. 10.3390/w14071157
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