Synthesizing regional irrigation data using machine learning – Towards global upscaling via metamodeling
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DOI: 10.1016/j.agwat.2025.109404
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- Brombacher, Joost & Silva, Isadora Rezende de Oliveira & Degen, Jelle & Pelgrum, Henk, 2022. "A novel evapotranspiration based irrigation quantification method using the hydrological similar pixels algorithm," Agricultural Water Management, Elsevier, vol. 267(C).
- Hanna Meyer & Edzer Pebesma, 2022. "Machine learning-based global maps of ecological variables and the challenge of assessing them," Nature Communications, Nature, vol. 13(1), pages 1-4, December.
- Simons, G.W.H. & Bastiaanssen, W.G.M. & Cheema, M.J.M. & Ahmad, B. & Immerzeel, W.W., 2020. "A novel method to quantify consumed fractions and non-consumptive use of irrigation water: Application to the Indus Basin Irrigation System of Pakistan," Agricultural Water Management, Elsevier, vol. 236(C).
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