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Evaluation of pedotransfer functions in predicting the soil water contents at field capacity and wilting point

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  • Givi, J.
  • Prasher, S.O.
  • Patel, R.M.

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  • Givi, J. & Prasher, S.O. & Patel, R.M., 2004. "Evaluation of pedotransfer functions in predicting the soil water contents at field capacity and wilting point," Agricultural Water Management, Elsevier, vol. 70(2), pages 83-96, November.
    • Handle: RePEc:eee:agiwat:v:70:y:2004:i:2:p:83-96
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    Cited by:

    1. 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).
    2. 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.
    3. Abdullah, Araz S. & Aziz, Moyassar Mohammed & Siddique, K.H.M. & Flower, K.C., 2015. "Film antitranspirants increase yield in drought stressed wheat plants by maintaining high grain number," Agricultural Water Management, Elsevier, vol. 159(C), pages 11-18.
    4. Łukasz Borek & Andrzej Bogdał & Tomasz Kowalik, 2021. "Use of Pedotransfer Functions in the Rosetta Model to Determine Saturated Hydraulic Conductivity (Ks) of Arable Soils: A Case Study," Land, MDPI, vol. 10(9), pages 1-22, September.
    5. Liao, Kaihua & Lai, Xiaoming & Zhou, Zhiwen & Liu, Ya & Zhu, Qing, 2020. "Uncertainty analysis and ensemble bias-correction method for predicting nitrate leaching in tea garden soils," Agricultural Water Management, Elsevier, vol. 237(C).

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