Modeling of optimal design and management of micro-irrigation system [electronic resource].

By: Contributor(s): Language: English Summary language: Arabic Description: p.805-830Other title:
  • نمذجة التصميم والإدارة الأمثلين لنظم الرى المصغرة [Added title page title]
Uniform titles:
  • Misr journal of agricultural engineering, 2013 v.30 (3) [electronic resource].
Subject(s): Online resources: In: Misr Journal of Agricultural Engineering 2013.v.30(3)Summary: A nonlinear optimization model for design and management of microirrigation system is proposed. The model divides the field into subunits. The decision variables are pipes lengths and diameters (lateral, riser, manifold. auxilimy, submain and main}, the total number of subunits, number of sets or shifts operating simultaneously, irrigation time per set, system average operating pressure, pressure at the control head (pump), pump power, emitter average flow rate and total capital cost. The Microsoft Excel Solver tool that applies the Generalized Reduced Gradient (GRG2) nonlinear optimization code was used to solve the optimization problem. The objective function is minimizing the system total cost. Results showed that the cost per unit area increased by increasing the total irrigated area: Meanwhile the total costs increased by increasing the total area in case of irrigating the whole area at once (one shift). The rate of increasing cost depends on the number of shifts, number of sets and number of subunit per set that operate simultaneously. The total costs were affected by the emission uniformity. Results indicated that total cost increased at higher uniformity. This effect increased by decreasing number of shifts.
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A nonlinear optimization model for design and management of microirrigation system is proposed. The model divides the field into subunits. The decision variables are pipes lengths and diameters (lateral, riser, manifold. auxilimy, submain and main}, the total number of subunits, number of sets or shifts operating simultaneously, irrigation time per set, system average operating pressure, pressure at the control head (pump), pump power, emitter average flow rate and total capital cost. The Microsoft Excel Solver tool that applies the Generalized Reduced Gradient (GRG2) nonlinear optimization code was used to solve the optimization problem. The objective function is minimizing the system total cost. Results showed that the cost per unit area increased by increasing the total irrigated area: Meanwhile the total costs increased by increasing the total area in case of irrigating the whole area at once (one shift). The rate of increasing cost depends on the number of shifts, number of sets and number of subunit per set that operate simultaneously. The total costs were affected by the emission uniformity. Results indicated that total cost increased at higher uniformity. This effect increased by decreasing number of shifts.

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