scholarly journals Hybrid optimization model for conjunctive use of surface and groundwater resources in water deficit irrigation system

2021 ◽  
Author(s):  
Karthikeyan Moothampalayam Sampathkumar ◽  
Saravanan Ramasamy ◽  
Balamurugan Ramasubbu ◽  
Saravanan Karuppanan ◽  
Balaji Lakshminarayanan
Keyword(s):  
Water Resources ◽  
Water Deficit ◽  
Optimization Model ◽  
Conjunctive Use ◽  
Hybrid Optimization ◽  
Cropping Pattern ◽  
Net Benefit ◽  
Hybrid Optimization Model ◽  
Optimal Cropping ◽  
Surface And Groundwater

Abstract 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.

scholarly journals Hybrid Optimization Model for Conjunctive Use of Surface and Groundwater Resources in Water Deficit Irrigation System

2021 ◽  
Author(s):  
Karthikeyan MoothampalayamSampathkumar ◽  
Saravanan Ramasamy ◽  
Balamurugan Ramasubbu ◽  
Hamid Reza Pourghasemi ◽  
Saravanan Karuppanan ◽  
...  
Keyword(s):  
Water Resources ◽  
Water Deficit ◽  
Optimization Model ◽  
Conjunctive Use ◽  
Hybrid Optimization ◽  
Cropping Pattern ◽  
Net Benefit ◽  
Hybrid Optimization Model ◽  
Optimal Cropping ◽  
Surface And Groundwater

Increasing demand for food production with limited available water resources pose the threat to agricultural activities. The conjunctive allocation of water resources maximizes the net benefit of farmers efficiently. In this study, a novel hybrid optimization model was developed based on a genetic algorithm (GA), bacterial foraging optimization (BFO) and ant colony optimization (ACO) to maximize the net benefit of water deficit Sathanur reservoir command. The GA-based opti-mization model considered crop-related physical and economical 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 reach obtained from BFO is considered as input to ACO as a guiding mechanism to attain an optimal cropping pattern. Comparing the average produc-tivity 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, the developed novel hybrid optimization model (GA-BFO-ACO) is very promising to enhance the farmer's net income as well as for the command area water conservation and can be replicated in other irrigated regions of the globe to overcome chronic land and water problems.

scholarly journals Multi Crop Optimization Using Linear Programming Model for Maximum Net Benefit

2018 ◽  
Vol 7 (3.12) ◽  
pp. 797
Author(s):  
Shreedhar R
Keyword(s):  
Linear Programming ◽  
Water Resources ◽  
Water Availability ◽  
Programming Model ◽  
Optimization Techniques ◽  
Cropping Pattern ◽  
Economic Returns ◽  
Net Benefit ◽  
Use Of Resources ◽  
Optimal Cropping

The water used for agriculture is 70% globally. This has resulted in new methods of saving water. Hence water saving techniques has to be practiced.  In water resources planning and management, optimization techniques is used for limited use of resources such as such as water, land, production cost, manpower, fertilizers, seeds, and pesticides. For cultivating each crop, the land area needs to be planned properly. Hence the crop pattern has to be decided optimally depending on available water resources and on economic basis. Therefore farmer needs to be educated to adopt optimum cropping pattern which maximises the economic returns. Hence the study is taken up to optimize the allocation of land areas to crops. The objective function for multi crop model were formulated using linear programming for maximizing the net benefits. The study resulted in optimal cropping pattern for different water availabilities ranging from 2000 Ha-m to 5500 Ha-m. The maximum net benefit for the study area varied from Rs. 53.2 Crores for 2000 Ha-m water availability to Rs.78 Crores at 5000 Ha-m water availability.  

Optimization of groundwater resource for balanced cropping pattern

Water Policy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 643-657
Author(s):  
Smita Varade ◽  
Jayantilal N. Patel
Keyword(s):  
Water Resources ◽  
Optimization Model ◽  
Pso Algorithm ◽  
Cropping Pattern ◽  
Groundwater Levels ◽  
Net Returns ◽  
Tlbo Algorithm ◽  
Net Benefits ◽  
Optimal Cropping ◽  
Teaching Learning

Abstract In this paper, an optimization model is formulated and optimal cropping pattern is suggested. Conjunctive use of water is not feasible for the study area as groundwater is the only source to fulfil irrigation demand. Water resources for the study area are limited. Best utilization of available water resources for increased net benefits is always advisable. Sinnar Taluka of Nasik district of Maharashtra state in India is considered as a study area. An existing cropping pattern is studied extensively and a new cropping pattern is suggested. Teaching–learning-based algorithm (TLBO) and particle swarm optimization (PSO) algorithm are applied to solve the optimization model. TLBO algorithm provides higher net returns as compared to PSO algorithm. TLBO and PSO saves up to 16.52% of water and benefits are increased by 35.81%. The study area is overexploited, this is fact. The new cropping pattern is suggested by considering minimum rainfall, i.e., 400 mm, so that in years when rainfall is above minimum rainfall the groundwater levels will be raised. In the proposed cropping pattern a few crop areas are majorly increased and a few crop areas are majorly reduced. The remaining crop areas are minorly increased or reduced and net benefits are increased and water demand decreased.

scholarly journals Self-adaptive multi-population-based Jaya algorithm to optimize the cropping pattern under a constraint environment

2019 ◽  
Vol 22 (2) ◽  
pp. 368-384
Author(s):  
Vijendra Kumar ◽  
S. M. Yadav
Keyword(s):  
Population Based ◽  
Cropping Pattern ◽  
Jaya Algorithm ◽  
Net Benefit ◽  
Invasive Weed ◽  
Cropping Patterns ◽  
Net Benefits ◽  
Optimal Cropping ◽  
Teaching Learning ◽  
Self Adaptive

Abstract Increasing population around the world, especially in India and China, has resulted in a drastic increase in water intake in both domestic and agricultural sectors. This, therefore, requires that water resources be planned and controlled wisely and effectively. With this consideration, the aim of the study is to achieve an optimal cropping pattern under a constrained environment. The objective is to maximize the net benefits with an optimum use of water. For optimization, a self-adaptive multi-population Jaya algorithm (SAMP-JA) has been used. For the Karjan reservoir in Gujarat State, India, two different models, i.e. maximum and average cropping patterns, were formulated based on the 75 per cent dependable inflow criteria. These two model scenarios are developed in such a way that either model can be selected by the farmer based on the crop area and its respective net benefits. Invasive weed optimization (IWO), particle swarm optimization (PSO), differential evolution (DE) and the firefly algorithm (FA) were compared to the results. The results show that the SAMP-JA obtained the maximum net benefit for both the models. The findings of the research are also compared with the actual cropping pattern. A significant increase has been noted in the cultivation of sugarcane, groundnut, wheat, millet, banana and castor. SAMP-JA has been noted to converge faster and outperforms PSO, DE, IWO, FA, teaching–learning-based optimization (TLBO), the Jaya algorithm (JA), elitist-JA and elitist-TLBO.

A hybrid optimization model based on multi-metrics for registration using free-form

2007 ◽  
Author(s):  
Jiasi Song ◽  
Lixu Gu ◽  
Pengfei Huang ◽  
Wei Li ◽  
Jianrong Xu
Keyword(s):  
Optimization Model ◽  
Hybrid Optimization ◽  
Free Form ◽  
Model Based ◽  
Hybrid Optimization Model
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