Prediction of Soybean Yield and Water Productivity under Defi cit Irrigation Using Yield-Stress Model

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Authors

  • Samiha Abou El-Fetouh OUDA
  • Rashad Abou ELENIN
  • Mouhamed Abedel Kader SHREIF
  • Bogachan BENLI
  • Manzour QADIR

Keywords:

Readily available water depletion, consumptive water use, irrigation rescheduling.

Abstract

Five fi eld trials (1997-2001) were conducted at Beni Sweif governorate, Egypt to study the effect of two irrigation treatments, i.e. required amounts (the amount of soil moisture that is removed by the plants from the soil profi le, plus 20% to satisfy the leaching requirement) and farmer amount (excessive) on wheat yield and water consumptive use. Furthermore, to use Yield-Stress model to simulate the depletion of readily available water from the root zone and reschedule irrigation to save irrigation water. The model predictions showed good agreement between measured and predicted values of soybean yield and water consumptive use. Results showed that rescheduling required irrigation without reducing the applied amount could increase soybean yield by an average of
1.5% over all the growing seasons. Rescheduling farmer irrigation could save an average of 17.54% of the applied amounts and could increase soybean yield by an average of 11.93% over all the growing seasons. Deducting 10 and 20% of rescheduled farmer irrigation amounts could reduced soybean yield by an average of 1.03 and 3.79%, respectively over all the growing seasons, and could save 25.79 and 34.04% of farmer irrigation water amounts, respectively. Water productivity was the highest under deducting 20% of rescheduled farmer irrigations. Therefore, to save irrigation water and to maintain low yield losses it could be recommended to irrigate soybean with the amount of rescheduled farmer irrigation less 20%.

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Published

2019-07-14

How to Cite

OUDA, S. A. E.-F., ELENIN, R. A., SHREIF, M. A. K., BENLI, B., & QADIR, M. (2019). Prediction of Soybean Yield and Water Productivity under Defi cit Irrigation Using Yield-Stress Model. International Journal of Natural and Engineering Sciences, 2(2), 05–12. Retrieved from https://ijnes.org/index.php/ijnes/article/view/414

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