- Ahmadi, S. H., & Javanbakht, Z. (2020). Assessing the physical and empirical reference evapotranspiration (ETo) models and time series analyses of the influencing weather variables on ETo in a semi-arid area. Journal of Environmental Management, 276, 111278.
- Akhavan, S., Kanani, E., & Dehghanisanij, H. (2019). Assessment of different reference evapotranspiration models to estimate the actual evapotranspiration of corn (Zea mays ) in a semiarid region (case study, Karaj, Iran). Theoretical and Applied Climatology, 137, 1403-1419.
- Allen, R.G., Pereira, L.S., Raes, D., & Smith, M. (1998). Crop Evapotranspiration. Guidelines for Computing Crop Water Requirements. Irrigation and Drainage Paper No. 56, FAO, Rome, Italy, 300 pp.
- Baier, W., & Robertson, G. W. (1965). Estimation of latent evaporation from simple weather observations. Canadian Journal of Plant Science, 45, 276-284.
- Berti, A., Tardivo, G., Chiaudani, A., Rech, F., & Borin, M. (2014). Assessing reference evapotranspiration by the Hargreaves method in north-eastern Italy. Agricultural Water Management. 140, 20–25.
- Blaney, H.F., & Criddle, W.D. (1950). Determining water requirements in irrigated areas from climatological and irrigation data. Soil conservation service technical paper 96; Soil conservation service. US Department of Agriculture, Washington.
- Boser, B.E., Guyon, I.M., & Vapnik, V.N. (1992). A training algorithm for optimal margin classifiers. In Haussler, editor, 5th Annual ACM Workshop on COLT, pages 144-152, Pittsburgh, PA.
- Braga, P., Crusiol, L. G. T., Nanni, M. R., Caranhato, A. L. H., Fuhrmann, M. B., Nepomuceno, A. L., Neumaier, N., Farias, J.R.B., Koltun, A., Goncalves, L.S.A., & Mertz Henning, L. M. (2021). Vegetation indices and NIR-SWIR spectral bands as a phenotyping tool for water status determination in soybean. Precision Agriculture, 22, 249-266.
- Breiman, L., Friedman, J., Olshen, R., & Stone, C. (1984). Classification and regression trees. Monterey, CA: Wadsworth & Brooks. In: Cole Advanced Books and Software.
- Didari, S., & Ahmadi, S.H. (2019). Calibration and evaluation of the FAO56-PenmanMonteith, FAO24-radiation, and Priestly-Taylor reference evapotranspiration models using the spatially measured solar radiation across a large arid and semi-arid area in southern Iran. Theoretical and Applied Climatology, 136 (1-2), 441-455.
- Droogers, P., & Allen, R.G. (2002). Estimating reference evapotranspiration under inaccurate data conditions. Irrigation and Drainage Systems, 16, 33-45.
- Eshaghi, A., Motamedvaziri, B., & Feiznia, S. (2010). Landslides Hazard Zonation Using Logistic Regression Method (Case Study: Safaroud Watershed). Territory, 24(6), 67-77.
- Friedman, J. H. (2001). Greedy function approximation: a gradient boosting machine. Annals of statistics, 29(5), 1189-1232.
- Gao, B.C. (1996). NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens. Environment, 58, 257-266.
- Gates, D.M., Keegan, H. J., Schleter, J. C., & Weidner, V. R. (1965). Spectral properties of plants. Applied optics. 4(1), 11 20
- Ge, J., Zhao, L., Yu, Z., Liu, H., Zhang, L., Gong, X., & Sun, H. (2022). Prediction of greenhouse tomato crop evapotranspiration using XGBoost machine learning model. Plants, 11(15), 1923.
- Granata, F. (2019). Evapotranspiration evaluation models based on machine learning algorithms-A comparative study. Agricultural Water Management, 217, 303-315.
- Hargreaves, G.H., & Samani, Z.A. (1985). Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture, 1, 96-99.
- Huete, A., Justice, C., & Liu, H. (1994). Development of vegetation and soil indices for MODIS-EOS. Remote Sensing. Environment, 49, 224-234.
- Huete, A.R. (2012). Vegetation Indices, Remote Sensing and Forest Monitoring. Geography Compass, 6, 513-532.
- Ivanov, N. N. (1954). About potential evapotranspiration estimation. Izv VGO, 86, 189-196.
- Jensen, M.E. (1968). In: In: Kozlowski, T.T. (Ed.), Water Consumption by Agricultural Plants. Water Deficits and Plant Growth, vol. 2. Academic Press, New York, pp. 1-22.
- Kharrufa, N. (1985). Simplified equation for evapotranspiration in arid regions. Beiträge Hydrol, 5, 39-47.
- Liu, Y., Yue, Q., Wang, Q., Yu, J., Zheng, Y., Yao, X., & Xu, S. (2021). A Framework for Actual Evapotranspiration Assessment and Projection Based on Meteorological, Vegetation and Hydrological Remote Sensing Products. Remote Sensing, 13(18), 3643.
- Mosre, J., & Suárez, F. (2021). Actual evapotranspiration estimates in arid cold regions using machine learning algorithms with in situ and remote sensing data. Water, 13(6), 870.
- Nouraki, A., Akhavan, S., Rezaei, Y., & Fuentes, S. (2021). Assessment of sunflower water stress using infrared thermometry and computer vision analysis. Water Supply, 21(3), 1228-1242.
- Nouraki, A., Golabi, M., Albaji, M., Naseri, A., & Homayouni, S. (2023). Spatial-temporal modeling of soil moisture using optical and thermal remote sensing data and machine learning algorithms. Iranian Journal of Soil and Water Research, 54(4), 637-653. (In Persian).
- Ravazzani, G., Corbari, C., Morella, S., Gianoli, P., & Mancini, M. (2012). Modified Hargreaves-Samani equation for the assessment of reference evapotranspiration in Alpine River Basins. Journal of Irrigation and Drainage Engineering, ASCE 138 (7), 592-599.
- Rodrigues, G. C., & Braga, R. P. (2021). Estimation of reference evapotranspiration during the irrigation season using nine temperature-based methods in a hot-summer Mediterranean climate. Agriculture, 11(2), 124.
- Schendel, U. (1967).Vegetationswasserverbrauch und-wasserbedarf. Habilitation; Kiel, p 137.
- Schneider, P., Roberts, D.A., & Kyriakidis, P.C. (2008). A VARI-based relative greenness from MODIS data for computing the Fire Potential Index. Remote Sensing of Environment, 112, 1151-1167.
- Shao, G., Han, W., Zhang, H., Liu, S., Wang, Y., Zhang, L., & Cui, X. (2021). Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices. Agricultural Water Management, 252, 106906.
- Thornthwaite, C.W. (1948). An approach toward a rational classification of climate. Geographical review, 38, 55-94.
- Trajkovic, S. (2007). Hargreaves versus penman–Monteith under humid conditions. Journal of Irrigation and Drainage Engineering, ASCE 133(1), 38-42.
- Yamaç, S. S., & Todorovic, M. (2020). Estimation of daily potato crop evapotranspiration using three different machine learning algorithms and four scenarios of available meteorological data. Agricultural Water Management, 228, 105875.
- Yang, W., Kobayashi, H., Wang, C., Shen, M., Chen, J., Matsushita, B., Tang, Y., Kim, Y., Bret-Harte, M.S., Zona, D.; Oechel, W., & Kondoh, A. (2019). A Semi-Analytical Snow-Free Vegetation Index for Improving Estimation of Plant Phenology in Tundra and Grassland Ecosystems. Remote Sensing of Environment, 228, 31–44.
- Yebra, M., Van Dijk, A., Leuning, R., Huete, A., & Guerschman, J.P. (2013). Evaluation of Optical Remote Sensing to Estimate Actual Evapotranspiration and Canopy Conductance. Remote Sensing of Environment, 129, 250-261.
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