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Optimization of Irrigation Water Allocation Framework Based on Genetic Algorithm Approach

机译:基于遗传算法方法的灌溉水分配框架优化

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摘要

In a world where excessive use and degradation of water resources are threatening the sustainability of livelihoods dependent on water and agriculture, increased food production will have to be done in the face of a changing climate and climate variability. There is a need to make optimal use of the available water resource to maximize productivity. Climate-smart irrigation is aimed at increasing per unit production and income from irrigated cropping systems without having negative impacts on the environment or other water users and uses. This paper developed a water allocation model using Genetic Algorithm to equitably allocation available water to the various sectors in Kano River Irrigation Scheme yielding an optimal as well as equitable water release with a 96.44% demand met. An average relative supply of 0.94 was obtained indicating the there was even supply of water to all the sectors. The model is robust and relatively easy to apply and can be employed by farm managers to achieve equity and optimal use of the available water resource.
机译:在一个过度使用和降低水资源的世界威胁到依赖水和农业的生计的可持续性的世界中,面对不断变化的气候和气候变化,必须采取增加的粮食生产。需要最佳使用可用的水资源来最大限度地提高生产率。气候智能灌溉旨在从灌溉种植系统的每单位生产和收入增加,而不会对环境或其他水用户和用途产生负面影响。本文开发了一种利用遗传算法的水分配模型,将可用水分配给Kano河灌溉方案中的各个部门,产生最佳的和公平的水释放,需求96.44%。获得了0.94的平均相对电源,表明甚至对所有部门提供了水。该模型具有稳健且相对容易申请,可以由农场管理人员雇用,实现公平和最佳使用可用的水资源。

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