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contributor authorVarade Smita;Patel Jayantilal N.
date accessioned2019-02-26T07:50:27Z
date available2019-02-26T07:50:27Z
date issued2018
identifier other%28ASCE%29HE.1943-5584.0001655.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4249758
description abstractThe quantity and various sources of water for irrigation are important controlling factors in the agricultural development of any area. The aim of this work is to determine an optimal cropping pattern to maximize the net annual returns, to conserve groundwater resources, and to use optimal land under cultivation for a region that has a scarcity of surface water resource and uncertain rainfall. Hence, mathematical models are developed based on data collected from government agencies, interviews of farmers in the region, and a practical survey of the region. An optimization problem is formulated based on the developed mathematical models. For this purpose, an optimization problem is formulated. Sinnar Taluka of Maharashtra state in India is the study area, in which groundwater is the only source for irrigation in this region. Hence, the Minor Irrigation Department (MID) of Nasik has planned an artificial recharge for the study area. The existing cropping pattern is studied extensively, and a new cropping pattern is suggested by solving the optimization problem using advanced optimization algorithms such as Jaya and particle swarm optimization (PSO). The PSO algorithm is widely used in water management. The Jaya algorithm is new in the area of water management and has significantly shown its competitiveness in this study. It has allocated land and water optimally in less computational time and provided higher net annual returns than PSO.
publisherAmerican Society of Civil Engineers
titleDetermination of Optimum Cropping Pattern Using Advanced Optimization Algorithms
typeJournal Paper
journal volume23
journal issue6
journal titleJournal of Hydrologic Engineering
identifier doi10.1061/(ASCE)HE.1943-5584.0001655
page5018010
treeJournal of Hydrologic Engineering:;2018:;Volume ( 023 ):;issue: 006
contenttypeFulltext


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