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Tottori University (2018)

New scheme to optimize irrigation depths using a numerical model of crop response to irrigation and quantitative weather forecast

HASSAN MOHAMED FAHMY ABD EL BAKI

Titre : New scheme to optimize irrigation depths using a numerical model of crop response to irrigation and quantitative weather forecast

Auteur : HASSAN MOHAMED FAHMY ABD EL BAKI

Université de soutenance : Tottori University

Grade : Doctor of Philosoph 2018

Sommaire partiel
With increasing scarcity and growing competition for water, irrigation managers should adopt new approaches for irrigation scheduling to sustain crop production, and thereby maximize net income. About two thirds of irrigated farms are located in developing countries which are the main source of food production. With advances in computer technology and theory in soil physics, the use of numerical models can be an important tool to simulate crop water behavior under different conditions of water supply. It can also simulate water flow in the root zone and crop growth and is useful tool for extrapolating findings from field studies to conditions not tested yet, allowing projection for irrigation scheduling. In this study, new numerical scheme was verified through three field experiments to determine irrigation depths which maximize net incomes at each irrigation interval. Quantitative weather forecasts which are freely available on the internet were used as inputs data. This scheme was incorporated in a numerical model, WASH 2D, which simulates two dimensional water, solute, heat movement in soil with finite difference method. Net income was calculated as a function of cumulative transpiration over the irrigation interval. By predicting transpiration rates, the irrigation depths can be optimized to maximize net income. Parameter values of stress response function for both drought and salinity stresses were considered. Water pricing is also considered in this scheme to give farmers incentive to save water. To evaluate the economic benefits of this scheme, three field experiments were carried out in the sand field of Arid Land Research Center, Tottori University, Japan. This scheme was compared with automated irrigation system (AIS) as it efficiently meets plant requirements by setting appropriate trigger value of soil water content or soil suction. On the other hand, the AIM requires high initial investment and fails to adjust irrigation interval to weather forecasts, especially the traditional methods. The objective of this study was to verify the new scheme to optimize irrigation depth which gives maximal net income.

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Page publiée le 26 avril 2020