Accuracy of daily estimation of grass reference evapotranspiration using ERA-Interim reanalysis products with assessment of alternative bias correction schemes
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DOI: 10.1016/j.agwat.2018.08.003
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- Pereira, L.S. & Paredes, P. & Jovanovic, N., 2020. "Soil water balance models for determining crop water and irrigation requirements and irrigation scheduling focusing on the FAO56 method and the dual Kc approach," Agricultural Water Management, Elsevier, vol. 241(C).
- Paredes, P. & Pereira, L.S., 2019. "Computing FAO56 reference grass evapotranspiration PM-ETo from temperature with focus on solar radiation," Agricultural Water Management, Elsevier, vol. 215(C), pages 86-102.
- Qiu, Rangjian & Li, Longan & Liu, Chunwei & Wang, Zhenchang & Zhang, Baozhong & Liu, Zhandong, 2022. "Evapotranspiration estimation using a modified crop coefficient model in a rotated rice-winter wheat system," Agricultural Water Management, Elsevier, vol. 264(C).
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- Paredes, P. & Pereira, L.S. & Almorox, J. & Darouich, H., 2020. "Reference grass evapotranspiration with reduced data sets: Parameterization of the FAO Penman-Monteith temperature approach and the Hargeaves-Samani equation using local climatic variables," Agricultural Water Management, Elsevier, vol. 240(C).
- Ferreira, Lucas Borges & da Cunha, Fernando França & Fernandes Filho, Elpídio Inácio, 2022. "Exploring machine learning and multi-task learning to estimate meteorological data and reference evapotranspiration across Brazil," Agricultural Water Management, Elsevier, vol. 259(C).
- Blankenau, Philip A. & Kilic, Ayse & Allen, Richard, 2020. "An evaluation of gridded weather data sets for the purpose of estimating reference evapotranspiration in the United States," Agricultural Water Management, Elsevier, vol. 242(C).
- Kayatz, Benjamin & Baroni, Gabriele & Hillier, Jon & Lüdtke, Stefan & Freese, Dirk & Wattenbach, Martin, 2024. "Supporting decision-making in agricultural water management under data scarcity using global datasets – chances, limits and potential improvements," Agricultural Water Management, Elsevier, vol. 296(C).
- Kang, Yan & Chen, Peiru & Cheng, Xiao & Zhang, Shuo & Song, Songbai, 2022. "Novel hybrid machine learning framework with decomposition–transformation and identification of key modes for estimating reference evapotranspiration," Agricultural Water Management, Elsevier, vol. 273(C).
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- Nouri, Milad & Homaee, Mehdi, 2022. "Reference crop evapotranspiration for data-sparse regions using reanalysis products," Agricultural Water Management, Elsevier, vol. 262(C).
- Allen, Richard G. & Dhungel, Ramesh & Dhungana, Bibha & Huntington, Justin & Kilic, Ayse & Morton, Charles, 2021. "Conditioning point and gridded weather data under aridity conditions for calculation of reference evapotranspiration," Agricultural Water Management, Elsevier, vol. 245(C).
- Pelosi, A. & Chirico, G.B., 2021. "Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data?," Agricultural Water Management, Elsevier, vol. 258(C).
- Pôças, I. & Calera, A. & Campos, I. & Cunha, M., 2020. "Remote sensing for estimating and mapping single and basal crop coefficientes: A review on spectral vegetation indices approaches," Agricultural Water Management, Elsevier, vol. 233(C).
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- Pelosi, A., 2023. "Performance of the Copernicus European Regional Reanalysis (CERRA) dataset as proxy of ground-based agrometeorological data," Agricultural Water Management, Elsevier, vol. 289(C).
- Jovanovic, N. & Pereira, L.S. & Paredes, P. & Pôças, I. & Cantore, V. & Todorovic, M., 2020. "A review of strategies, methods and technologies to reduce non-beneficial consumptive water use on farms considering the FAO56 methods," Agricultural Water Management, Elsevier, vol. 239(C).
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Keywords
Meteorological variables; FAO Penman-Monteith ETo; Accuracy indicators; Raw reanalysis data; Cross-validation; Bias correction methods;All these keywords.
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