edu.ucar.opensky::articles:26276 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T19:35:33.229493 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d75b06ff https://doi.org/10.5067/ASB0EQO2LYJV https Related Dataset #1 SMAP/Sentinel-1 L2 Radiometer/Radar 30-Second Scene 3 km EASE-Grid Soil Moisture, Version 3 https://doi.org/10.5067/MODIS/MCD15A2H.006 https Related Dataset #2 MCD15A2H MODIS/Terra+Aqua Leaf Area Index/FPAR 8-day L4 Global 500m SIN Grid V006 https://doi.org/10.5067/MODIS/MCD43A3.006 https Related Dataset #3 MCD43A3 MODIS/Terra+Aqua BRDF/Albedo Daily L3 Global - 500m V006 https://doi.org/10.5067/MODIS/MYD13A1.006 https Related Dataset #4 MYD13A1 MODIS/Aqua Vegetation Indices 16-day L3 Global 500m SIN Grid V006 https://doi.org/10.5281/zenodo.7341841 https Related Dataset #5 A 1km experimental dataset for the Mediterranean terrestrial region of Soil Moisture, Land Surface Temperature and Vegetation Optical Depth from passive microwave data Is it possible to quantify irrigation water-use by assimilating a high-resolution satellite soil moisture product? 2023-04-01T00:00:00Z publication https://n2t.org/ark:/85065/d75b06ff https://doi.org/10.1029/2022WR033342 Jalilvand, E. author Abolafia-Rosenzweig, Ronnie author Tajrishy, M. author Kumar, S. V. author Mohammadi, M. R. author Das, N. N. author UCAR/NCAR - Library publisher Irrigation is the largest human intervention in the water cycle that can modulate climate extremes, yet irrigation water use (IWU) remains largely unknown in most regions. Microwave remote sensing offers a practical way to quantify IWU by monitoring changes in soil moisture caused by irrigation. However, high-resolution satellite soil moisture data is typically infrequent (e.g., 6-12 days) and thus may miss irrigation events. This study evaluates the ability to quantify IWU by assimilating high-resolution (1 km) SMAP-Sentinel 1 remotely sensed soil moisture with a physically based land surface model (LSM) using a particle batch smoother (PBS). A suite of synthetic experiments is devised to evaluate different error sources. Results from the synthetic experiments show that unbiased simulations with known irrigation timing can produce an accurate irrigation estimate with a mean annual bias of 0.45% and a mean R-2 of 0.97, relative to observed IWU. Unknown irrigation timing can significantly deteriorate the model performance, resulting in an increased mean annual bias to 23% and decreased mean R-2 to 0.36. Adding random noise to synthetic observations does not significantly decrease model performance except for the experiments with low observation frequency (>12 days). In real-world experiments, the PBS data assimilation approach underestimates observed IWU by 18.6% when the timing of IWU is known. IWU estimates are consistently significantly higher over irrigated pixels compared to the non-irrigated pixels, indicating data assimilation skillfully conveys irrigation signals to the LSM. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright 2023 American Geophysical Union. None eng geoscientificInformation