Articles | Volume 26, issue 18
https://doi.org/10.5194/hess-26-4685-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-4685-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Sep 2022
Research article |
| 26 Sep 2022
| 26 Sep 2022
Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP
Sara Modanesi
Research Institute for Geo-hydrological Protection, National Research Council, Via della Madonna Alta 126, 06128 Perugia, Italy
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
DICEA Dept. of Civil and Environmental Engineering, University of
Florence, Via di S. Marta 3, 50139 Firenze, Italy
Christian Massari
CORRESPONDING AUTHOR
Research Institute for Geo-hydrological Protection, National Research Council, Via della Madonna Alta 126, 06128 Perugia, Italy
Michel Bechtold
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
Hans Lievens
Department of Environment, Ghent University, Coupure links 653, 9000 Ghent, Belgium
Angelica Tarpanelli
Research Institute for Geo-hydrological Protection, National Research Council, Via della Madonna Alta 126, 06128 Perugia, Italy
Luca Brocca
Research Institute for Geo-hydrological Protection, National Research Council, Via della Madonna Alta 126, 06128 Perugia, Italy
Luca Zappa
Department of Geodesy and Geoinformation, Technische Universität Wien (TU Wien), Wiedner Hauptstraße 8–10, 1040 Vienna, Austria
Gabriëlle J. M. De Lannoy
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, Belgium
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Cited
17 citations as recorded by crossref.
- Comprehensive quality assessment of satellite- and model-based soil moisture products against the COSMOS network in Germany T. Schmidt et al. 10.1016/j.rse.2023.113930
- Irrigation in the Earth system S. McDermid et al. 10.1038/s43017-023-00438-5
- Comparison of Google Earth Engine Machine Learning Algorithms for Mapping Smallholder Irrigated Areas in a Mountainous Watershed, Upper Blue Nile Basin, Ethiopia Y. Mekonnen et al. 10.1007/s12524-024-01846-w
- Optimisation of AquaCrop backscatter simulations using Sentinel-1 observations S. de Roos et al. 10.1016/j.rse.2023.113621
- An inter-comparison of approaches and frameworks to quantify irrigation from satellite data S. Kragh et al. 10.5194/hess-28-441-2024
- PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts G. Paolini et al. 10.3390/rs16071116
- Retrieving the irrigation actually applied at district scale: Assimilating high-resolution Sentinel-1-derived soil moisture data into a FAO-56-based model P. Laluet et al. 10.1016/j.agwat.2024.108704
- Regional data sets of high-resolution (1 and 6 km) irrigation estimates from space J. Dari et al. 10.5194/essd-15-1555-2023
- Retrieving Soil Moisture from Sentinel-1: Limitations over Certain Crops and Sensitivity to the First Soil Thin Layer H. Bazzi et al. 10.3390/w16010040
- A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations L. Brocca et al. 10.3389/fsci.2023.1190191
- Estimating multi-scale irrigation amounts using multi-resolution soil moisture data: A data-driven approach using PrISM G. Paolini et al. 10.1016/j.agwat.2023.108594
- Evaluation of soil moisture estimation techniques based on Sentinel-1 observations over wheat fields M. Arias et al. 10.1016/j.agwat.2023.108422
- Soil Moisture Monitoring at Kilometer Scale: Assimilation of Sentinel-1 Products in ISBA O. Rojas-Munoz et al. 10.3390/rs15174329
- Assimilating ASCAT normalized backscatter and slope into the land surface model ISBA-A-gs using a Deep Neural Network as the observation operator: Case studies at ISMN stations in western Europe X. Shan et al. 10.1016/j.rse.2024.114167
- Benefits and pitfalls of irrigation timing and water amounts derived from satellite soil moisture L. Zappa et al. 10.1016/j.agwat.2024.108773
- Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication G. De Lannoy et al. 10.3389/frwa.2022.981745
- Is It Possible to Quantify Irrigation Water‐Use by Assimilating a High‐Resolution Satellite Soil Moisture Product? E. Jalilvand et al. 10.1029/2022WR033342
15 citations as recorded by crossref.
- Comprehensive quality assessment of satellite- and model-based soil moisture products against the COSMOS network in Germany T. Schmidt et al. 10.1016/j.rse.2023.113930
- Irrigation in the Earth system S. McDermid et al. 10.1038/s43017-023-00438-5
- Comparison of Google Earth Engine Machine Learning Algorithms for Mapping Smallholder Irrigated Areas in a Mountainous Watershed, Upper Blue Nile Basin, Ethiopia Y. Mekonnen et al. 10.1007/s12524-024-01846-w
- Optimisation of AquaCrop backscatter simulations using Sentinel-1 observations S. de Roos et al. 10.1016/j.rse.2023.113621
- An inter-comparison of approaches and frameworks to quantify irrigation from satellite data S. Kragh et al. 10.5194/hess-28-441-2024
- PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts G. Paolini et al. 10.3390/rs16071116
- Retrieving the irrigation actually applied at district scale: Assimilating high-resolution Sentinel-1-derived soil moisture data into a FAO-56-based model P. Laluet et al. 10.1016/j.agwat.2024.108704
- Regional data sets of high-resolution (1 and 6 km) irrigation estimates from space J. Dari et al. 10.5194/essd-15-1555-2023
- Retrieving Soil Moisture from Sentinel-1: Limitations over Certain Crops and Sensitivity to the First Soil Thin Layer H. Bazzi et al. 10.3390/w16010040
- A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations L. Brocca et al. 10.3389/fsci.2023.1190191
- Estimating multi-scale irrigation amounts using multi-resolution soil moisture data: A data-driven approach using PrISM G. Paolini et al. 10.1016/j.agwat.2023.108594
- Evaluation of soil moisture estimation techniques based on Sentinel-1 observations over wheat fields M. Arias et al. 10.1016/j.agwat.2023.108422
- Soil Moisture Monitoring at Kilometer Scale: Assimilation of Sentinel-1 Products in ISBA O. Rojas-Munoz et al. 10.3390/rs15174329
- Assimilating ASCAT normalized backscatter and slope into the land surface model ISBA-A-gs using a Deep Neural Network as the observation operator: Case studies at ISMN stations in western Europe X. Shan et al. 10.1016/j.rse.2024.114167
- Benefits and pitfalls of irrigation timing and water amounts derived from satellite soil moisture L. Zappa et al. 10.1016/j.agwat.2024.108773
2 citations as recorded by crossref.
- Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication G. De Lannoy et al. 10.3389/frwa.2022.981745
- Is It Possible to Quantify Irrigation Water‐Use by Assimilating a High‐Resolution Satellite Soil Moisture Product? E. Jalilvand et al. 10.1029/2022WR033342
Latest update: 29 Jun 2024
Short summary
Given the crucial impact of irrigation practices on the water cycle, this study aims at estimating irrigation through the development of an innovative data assimilation system able to ingest high-resolution Sentinel-1 radar observations into the Noah-MP land surface model. The developed methodology has important implications for global water resource management and the comprehension of human impacts on the water cycle and identifies main challenges and outlooks for future research.
Given the crucial impact of irrigation practices on the water cycle, this study aims at...
