• Karuppanan, Saravanan

Abstract

<jats:title>Abstract</jats:title><jats:p>The Increasing demand for food production with limited available water resources poses a threat to agricultural activities. Conventional optimization algorithm increases the processing stage and it performed with in the space, which is allocated from user. Therefore, the proposed work is utilized to design with better performance results. The conjunctive allocation of water resources maximizes the net benefit of farmers. In this study, a novel hybrid optimization model developed is first of its kind to resolve the sharing of water resources conflict among different reaches based on a genetic algorithm (GA), bacterial foraging optimization (BFO) and ant colony optimization (ACO) to maximize the net benefit of the water deficit Sathanur reservoir command. The GA-based optimization model considered crop-related physical and economic parameters to derive optimal cropping patterns for three different conjunctive use policies and further allocation of surface and groundwater for different crops are enhanced with the BFO. The allocation of surface and groundwater for the head, middle and tail reaches obtained from BFO is considered as an input to the ACO as a guiding mechanism to attain an optimal cropping pattern. Comparing the average productivity values, Policy 3 (3.665 Rs/m3) has better values relating to Policy 1 (3.662 Rs/m3) and Policy 2 (3.440 Rs/m3). Thus, developed novel hybrid optimization model (GA-BFO-ACO) is very promising for enhancing farmer's net income and can be replicated in other irrigated regions to overcome chronic water problems. The productivity value of policy 3 was 6.54% greater than that of policy 2, whereas that of policy 1 was 6.45% greater. Overall, the comparison shows the better performance analysis of various optimization is done successfully.</jats:p>

Topics

• impedance spectroscopy
• surface