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Comparison of artificial neural network models and empirical and semi-empirical equations for daily reference evapotranspiration estimation in the Basque Country (Northern Spain)

Citations

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Cited by:

  1. Hossein Tabari, 2010. "Evaluation of Reference Crop Evapotranspiration Equations in Various Climates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(10), pages 2311-2337, August.
  2. Seydou Traore & Yufeng Luo & Guy Fipps, 2017. "Gene-Expression Programming for Short-Term Forecasting of Daily Reference Evapotranspiration Using Public Weather Forecast Information," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4891-4908, December.
  3. Shih-Lun Fang & Yi-Shan Lin & Sheng-Chih Chang & Yi-Lung Chang & Bing-Yun Tsai & Bo-Jein Kuo, 2024. "Using Artificial Intelligence Algorithms to Estimate and Short-Term Forecast the Daily Reference Evapotranspiration with Limited Meteorological Variables," Agriculture, MDPI, vol. 14(4), pages 1-20, March.
  4. Mattar, Mohamed A., 2018. "Using gene expression programming in monthly reference evapotranspiration modeling: A case study in Egypt," Agricultural Water Management, Elsevier, vol. 198(C), pages 28-38.
  5. Ali Rahimikhoob & Mahmood Behbahani & Javad Fakheri, 2012. "An Evaluation of Four Reference Evapotranspiration Models in a Subtropical Climate," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(10), pages 2867-2881, August.
  6. Shiri, Jalal, 2017. "Evaluation of FAO56-PM, empirical, semi-empirical and gene expression programming approaches for estimating daily reference evapotranspiration in hyper-arid regions of Iran," Agricultural Water Management, Elsevier, vol. 188(C), pages 101-114.
  7. Yassin, Mohamed A. & Alazba, A.A. & Mattar, Mohamed A., 2016. "Artificial neural networks versus gene expression programming for estimating reference evapotranspiration in arid climate," Agricultural Water Management, Elsevier, vol. 163(C), pages 110-124.
  8. Zou, Ping & Yang, Jingsong & Fu, Jianrong & Liu, Guangming & Li, Dongshun, 2010. "Artificial neural network and time series models for predicting soil salt and water content," Agricultural Water Management, Elsevier, vol. 97(12), pages 2009-2019, November.
  9. Roy, Dilip Kumar & Lal, Alvin & Sarker, Khokan Kumer & Saha, Kowshik Kumar & Datta, Bithin, 2021. "Optimization algorithms as training approaches for prediction of reference evapotranspiration using adaptive neuro fuzzy inference system," Agricultural Water Management, Elsevier, vol. 255(C).
  10. Behrooz Keshtegar & Ozgur Kisi & Hamed Ghohani Arab & Mohammad Zounemat-Kermani, 2018. "Subset Modeling Basis ANFIS for Prediction of the Reference Evapotranspiration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(3), pages 1101-1116, February.
  11. Bellido-Jiménez, Juan Antonio & Estévez, Javier & García-Marín, Amanda Penélope, 2021. "New machine learning approaches to improve reference evapotranspiration estimates using intra-daily temperature-based variables in a semi-arid region of Spain," Agricultural Water Management, Elsevier, vol. 245(C).
  12. Feng, Yu & Cui, Ningbo & Gong, Daozhi & Zhang, Qingwen & Zhao, Lu, 2017. "Evaluation of random forests and generalized regression neural networks for daily reference evapotranspiration modelling," Agricultural Water Management, Elsevier, vol. 193(C), pages 163-173.
  13. Vásquez, Cristina & Célleri, Rolando & Córdova, Mario & Carrillo-Rojas, Galo, 2022. "Improving reference evapotranspiration (ETo) calculation under limited data conditions in the high Tropical Andes," Agricultural Water Management, Elsevier, vol. 262(C).
  14. Fan, Junliang & Ma, Xin & Wu, Lifeng & Zhang, Fucang & Yu, Xiang & Zeng, Wenzhi, 2019. "Light Gradient Boosting Machine: An efficient soft computing model for estimating daily reference evapotranspiration with local and external meteorological data," Agricultural Water Management, Elsevier, vol. 225(C).
  15. Gafurov, Zafar & Eltazarov, S. & Akramov, Bekzod & Yuldashev, Tulkun & Djumaboev, Kakhramon & Anarbekov, Oyture, 2018. "Modifying Hargreaves-Samani equation for estimating reference evapotranspiration in dryland regions of Amudarya River Basin," Papers published in Journals (Open Access), International Water Management Institute, pages 9(10):1354-.
  16. Lu, Yingjie & Li, Tao & Hu, Hui & Zeng, Xuemei, 2023. "Short-term prediction of reference crop evapotranspiration based on machine learning with different decomposition methods in arid areas of China," Agricultural Water Management, Elsevier, vol. 279(C).
  17. Junzeng Xu & Junmei Wang & Qi Wei & Yanhua Wang, 2016. "Symbolic Regression Equations for Calculating Daily Reference Evapotranspiration with the Same Input to Hargreaves-Samani in Arid China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(6), pages 2055-2073, April.
  18. Traore, Seydou & Luo, Yufeng & Fipps, Guy, 2016. "Deployment of artificial neural network for short-term forecasting of evapotranspiration using public weather forecast restricted messages," Agricultural Water Management, Elsevier, vol. 163(C), pages 363-379.
  19. Mattar, M.A. & Alazba, A.A. & Zin El-Abedin, T.K., 2015. "Forecasting furrow irrigation infiltration using artificial neural networks," Agricultural Water Management, Elsevier, vol. 148(C), pages 63-71.
  20. Milan Gocić & Mohammad Arab Amiri, 2021. "Reference Evapotranspiration Prediction Using Neural Networks and Optimum Time Lags," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(6), pages 1913-1926, April.
  21. Shih-Lun Fang & Ting-Jung Chang & Yuan-Kai Tu & Han-Wei Chen & Min-Hwi Yao & Bo-Jein Kuo, 2022. "Plant-Response-Based Control Strategy for Irrigation and Environmental Controls for Greenhouse Tomato Seedling Cultivation," Agriculture, MDPI, vol. 12(5), pages 1-17, April.
  22. Cruz-Blanco, M. & Lorite, I.J. & Santos, C., 2014. "An innovative remote sensing based reference evapotranspiration method to support irrigation water management under semi-arid conditions," Agricultural Water Management, Elsevier, vol. 131(C), pages 135-145.
  23. Feng, Yu & Jia, Yue & Cui, Ningbo & Zhao, Lu & Li, Chen & Gong, Daozhi, 2017. "Calibration of Hargreaves model for reference evapotranspiration estimation in Sichuan basin of southwest China," Agricultural Water Management, Elsevier, vol. 181(C), pages 1-9.
  24. Yang, Yang & Luo, Yufeng & Wu, Conglin & Zheng, Hezhen & Zhang, Lei & Cui, Yuanlai & Sun, Ningning & Wang, Li, 2019. "Evaluation of six equations for daily reference evapotranspiration estimating using public weather forecast message for different climate regions across China," Agricultural Water Management, Elsevier, vol. 222(C), pages 386-399.
  25. Yamaç, Sevim Seda & Şeker, Cevdet & Negiş, Hamza, 2020. "Evaluation of machine learning methods to predict soil moisture constants with different combinations of soil input data for calcareous soils in a semi arid area," Agricultural Water Management, Elsevier, vol. 234(C).
  26. Tianao Wu & Wei Zhang & Xiyun Jiao & Weihua Guo & Yousef Alhaj Hamoud, 2020. "Comparison of five Boosting-based models for estimating daily reference evapotranspiration with limited meteorological variables," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-28, June.
  27. Traore, Seydou & Wang, Yu-Min & Kerh, Tienfuan, 2010. "Artificial neural network for modeling reference evapotranspiration complex process in Sudano-Sahelian zone," Agricultural Water Management, Elsevier, vol. 97(5), pages 707-714, May.
  28. Matin Ahooghalandari & Mehdi Khiadani & Mina Esmi Jahromi, 2016. "Developing Equations for Estimating Reference Evapotranspiration in Australia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(11), pages 3815-3828, September.
  29. Martí, Pau & Gasque, María, 2010. "Ancillary data supply strategies for improvement of temperature-based ETo ANN models," Agricultural Water Management, Elsevier, vol. 97(7), pages 939-955, July.
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