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Cairo University (2013)

Modeling Subsurface Drip Irrigation Systems Considering Root Uptake

Ahmed M. Tawfik Abdelraouf

Titre : Modeling Subsurface Drip Irrigation Systems Considering Root Uptake

نمذجة أنظمة الري بالتنقيط تحت السطحي مع أخذ امتصاص الجذور في الاعتبار

Auteur : Ahmed M. Tawfik Abdelraouf

Université de soutenance : Cairo University

Grade : Doctor of Philosophy (PhD) 2013

Résumé
Subsurface drip irrigation (SDI) should spread, which has high irrigation efficiency. Experimental field data from Adlia Farm was analyzed to compare between traditional surface drip and SDI for different crops and different soil treatments. Moreover, Hydrus was used to evaluate the soil wetting patterns, irrigation efficiency, and relative transpiration for different pipe installation depths, and different root distribution shapes. Hydrus was also used to show the effect of soil conditioners mixing ratios and the geometry of treated zone on irrigation efficiency and relative transpiration. Moreover, neural networks were used to predict irrigation efficiency and relative transpiration knowing the pipe installation depth, irrigation depth relative to transpiration depth, and irrigation rate. The network was then used to search for the optimum design that maximizes the irrigation efficiency keeping the relative transpiration above a threshold value. The results showed that properly designed SDI can save irrigation water and produce higher quality products

Mots clés : Modeling, Hydrus, Subsurface drip irrigation, Root uptake, Neural networks

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Page publiée le 23 octobre 2018, mise à jour le 3 mars 2019