The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
How much water is used for irrigation? A new approach exploiting coarse resolution satellite soil moisture products
Open accessAbstract
Abstract Knowledge of irrigation is essential for ensuring food and water security, and to cope with the scarcity of water resources, which is expected to exacerbate under the pressure of climate change and population increase. Even though irrigation is likely the most important direct human intervention in the hydrological cycle, we have only partial knowledge on the areas of our planet in which irrigation takes place, and almost no information on the amount of water that is applied for irrigation. In this study, we developed a new approach exploiting satellite soil moisture observations for quantifying the amount of water applied for irrigation. Through the inversion of the soil water balance equation, and by using satellite soil moisture products as input, the amount of water entering into the soil, and hence irrigation, is determined. Through synthetic experiments, we first assessed the impact of soil moisture measurement uncertainty and temporal resolution, also as a function of climate, on the accuracy of the method. Second, we applied the proposed approach to currently available coarse resolution satellite soil moisture products retrieved from the Soil Moisture Active and Passive mission (SMAP), the Soil Moisture and Ocean Salinity (SMOS) mission, the Advanced SCATterometer (ASCAT), and the Advanced Microwave Scanning Radiometer 2 (AMSR-2). Nine pilot sites in Europe, USA, Australia and Africa were used as case study to test the method in a real-world application. The synthetic experiment showed that the method is able to quantify irrigation, with satisfactory performance from satellite data with retrieval errors lower than ∼0.04 m³/m³ and revisit times shorter than 3 days. In the case studies based on real satellite data, qualitative assessments (due to missing in situ irrigation observations) showed that over regions in which satellite soil moisture products perform well, and which are characterized by prolonged periods without rainfall, the method shows good results in quantifying irrigation. However, at sites in which rainfall is sustained throughout the year, the proposed method fails in obtaining reliable performances. Similarly, low performances are obtained in areas where satellite products uncertainties are too large, or their spatial resolution is too coarse with respect to the size of the irrigated fields.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The NCEP/NCAR 40-Year Reanalysis Project
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., et al. (1996) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(1996)077<0437:tnyrp>2.0.co;2 · Cited by 28,360
Solutions for a cultivated planet
Foley, J. A., Ramankutty, N., Brauman, K. A., Cassidy, E. S., Gerber, J. S., Johnston, M., Mueller, N. D., O’Connell, C., Ray, D. K., West, P. C., et al. (2011) · Nature · doi:10.1038/nature10452 · Cited by 8,476
Global Water Resources: Vulnerability from Climate Change and Population Growth
Vörösmarty, C. J., Green, P., Salisbury, J., & Lammers, R. B. (2000) · Science · doi:10.1126/science.289.5477.284 · Cited by 5,036
The Soil Moisture Active Passive (SMAP) Mission
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow, W. T., Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., Johnson, J., et al. (2010) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2043918 · Cited by 3,754
A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation
Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., & Holtslag, A. A. M. (1998) · Journal of Hydrology · doi:10.1016/s0022-1694(98)00253-4 · Cited by 3,118
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D., & New, M. (2008) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2008jd010201 · Cited by 2,437
Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission
Kerr, Y. H., Waldteufel, P., Wigneron, J.-P., Martinuzzi, J., Font, J., & Berger, M. (2001) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/36.942551 · Cited by 1,697
High-quality spatial climate data-sets for Australia
Jones, D. A., Wang, W., & Fawcett, R. (2009) · Australian Meteorological and Oceanographic Journal · doi:10.1071/es09032 · Cited by 1,316
A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data
Wagner, W., Lemoine, G., & Rott, H. (1999) · Remote Sensing of Environment · doi:10.1016/s0034-4257(99)00036-x · Cited by 1,254
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., & de Roo, A. (2017) · Hydrology and Earth System Sciences · doi:10.5194/hess-21-589-2017 · Cited by 1,108
Metadata
- Authors
- Brocca, L., Tarpanelli, A., Filippucci, P., Dorigo, W., Zaussinger, F., Gruber, A., & Fernández-Prieto, D.
- Venue
- International Journal of Applied Earth Observation and Geoinformation
- Publisher
- Elsevier BV
- Published
- 2018-12
- Volume
- 73
- Pages
- 752-766
- ISSN
- 0303-2434 (ISSN-L)
- 1569-8432
- OpenAlex
- W2890649118
- Cited by
- 264
- References
- 46
- FWCI
- 9.50
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: How much water is used for irrigation? A new approach exploiting coarse resolution satellite soil moisture products. https://app.cochat.ai/papers/10.1016/j.jag.2018.08.023
- The paper
- Brocca, L., Tarpanelli, A., Filippucci, P., Dorigo, W., Zaussinger, F., Gruber, A., & Fernández-Prieto, D. (2018). How much water is used for irrigation? A new approach exploiting coarse resolution satellite soil moisture products. International Journal of Applied Earth Observation and Geoinformation. https://doi.org/10.1016/j.jag.2018.08.023
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.