Articles | Volume 28, issue 3
https://doi.org/10.5194/hess-28-441-2024
© Author(s) 2024. 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-28-441-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An inter-comparison of approaches and frameworks to quantify irrigation from satellite data
Department of Hydrology, Geological Survey of Denmark and Greenland, 1350 Copenhagen, Denmark
Department of Geosciences and Natural Resource Management, University of Copenhagen, 1350 Copenhagen, Denmark
Jacopo Dari
Department of Civil and Environmental Engineering, University of Perugia, via G. Duranti 93, 06125 Perugia, Italy
National Research Council, Research Institute for Geo-Hydrological Protection, via Madonna Alta 126, 06128 Perugia, Italy
Sara Modanesi
National Research Council, Research Institute for Geo-Hydrological Protection, via Madonna Alta 126, 06128 Perugia, Italy
Christian Massari
National Research Council, Research Institute for Geo-Hydrological Protection, via Madonna Alta 126, 06128 Perugia, Italy
Luca Brocca
National Research Council, Research Institute for Geo-Hydrological Protection, via Madonna Alta 126, 06128 Perugia, Italy
Rasmus Fensholt
Department of Geosciences and Natural Resource Management, University of Copenhagen, 1350 Copenhagen, Denmark
Simon Stisen
Department of Hydrology, Geological Survey of Denmark and Greenland, 1350 Copenhagen, Denmark
Julian Koch
Department of Hydrology, Geological Survey of Denmark and Greenland, 1350 Copenhagen, Denmark
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Cited
8 citations as recorded by crossref.
- Evaluating Uncertainties in an SM-Based Inversion Algorithm for Irrigation Estimation in a Subtropical Humid Climate L. Almendra-Martín et al. 10.3390/w16172445
- Synthesizing regional irrigation data using machine learning – Towards global upscaling via metamodeling S. Kragh et al. 10.1016/j.agwat.2025.109404
- Runoff spatiotemporal variability driven by climate change and human activity for the Nianchu River Basin in Southwestern Tibet Z. Yuan et al. 10.1016/j.ejrh.2025.102301
- Identifying irrigated areas using land surface temperature and hydrological modelling: application to the Rhine basin D. Purnamasari et al. 10.5194/hess-29-1483-2025
- Evaluating the Performance of Irrigation Using Remote Sensing Data and the Budyko Hypothesis: A Case Study in Northwest China D. Zhou et al. 10.3390/rs17061085
- Agricultural water demand is taxing regional water supplies S. McDermid 10.1038/s44221-024-00215-8
- Toward field-scale groundwater pumping and improved groundwater management using remote sensing and climate data T. Ott et al. 10.1016/j.agwat.2024.109000
- PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts G. Paolini et al. 10.3390/rs16071116
8 citations as recorded by crossref.
- Evaluating Uncertainties in an SM-Based Inversion Algorithm for Irrigation Estimation in a Subtropical Humid Climate L. Almendra-Martín et al. 10.3390/w16172445
- Synthesizing regional irrigation data using machine learning – Towards global upscaling via metamodeling S. Kragh et al. 10.1016/j.agwat.2025.109404
- Runoff spatiotemporal variability driven by climate change and human activity for the Nianchu River Basin in Southwestern Tibet Z. Yuan et al. 10.1016/j.ejrh.2025.102301
- Identifying irrigated areas using land surface temperature and hydrological modelling: application to the Rhine basin D. Purnamasari et al. 10.5194/hess-29-1483-2025
- Evaluating the Performance of Irrigation Using Remote Sensing Data and the Budyko Hypothesis: A Case Study in Northwest China D. Zhou et al. 10.3390/rs17061085
- Agricultural water demand is taxing regional water supplies S. McDermid 10.1038/s44221-024-00215-8
- Toward field-scale groundwater pumping and improved groundwater management using remote sensing and climate data T. Ott et al. 10.1016/j.agwat.2024.109000
- PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts G. Paolini et al. 10.3390/rs16071116
Latest update: 05 Apr 2025
Executive editor
Freshwater is a precious commodity for mankind, and irrigation is one of the largest component of freshwater usage by mankind. Many uncertainties exist in determining the amount of freshwater usage for irrigation. This manuscript discusses various ways to quantify irrigation and application of remote sensing to assess irrigation fluxes. With future, high-resolution remote sensing platforms becoming available, this work will be helpful to develop application pertaining to irrigation quantification especially is drought affected and semi-arid regions of the world.
Freshwater is a precious commodity for mankind, and irrigation is one of the largest component...
Short summary
This study provides a comparison of methodologies to quantify irrigation to enhance regional irrigation estimates. To evaluate the methodologies, we compared various approaches to quantify irrigation using soil moisture, evapotranspiration, or both within a novel baseline framework, together with irrigation estimates from other studies. We show that the synergy from using two equally important components in a joint approach within a baseline framework yields better irrigation estimates.
This study provides a comparison of methodologies to quantify irrigation to enhance regional...
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