...
首页> 外文期刊>Water Resources Management >Agricultural Water Allocation by Integration of Hydro-Economic Modeling with Bayesian Networks and Random Forest Approaches
【24h】

Agricultural Water Allocation by Integration of Hydro-Economic Modeling with Bayesian Networks and Random Forest Approaches

机译:用贝叶斯网络与随机森林方法集成水力经济建模的农业水分配

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Sustainable utilization of water resources requires preventive measures that must be taken to promote optimal use of water resources together with consideration of stakeholder interests and the economic value of water. The main objective of this study is to present an integrated hydro-economic model for allocating agricultural water based on its economic value. The study region covered six irrigation networks downstream of the Zayandeh Rood Dam in Iran. In fact, this study addresses questions of how to allocate scarce water to different consumers, in order to achieve the highest efficiency and economic benefits. To gain this goal, the existing agricultural activities in each irrigation network were simulated by applying the Positive Mathematical Programming (PMP) economic model and then by coupling the economic model with a water allocation planning model of the basin (MODSIM), the hydro-economic framework was generated. These tools helped to allocate water based on its economic value, maximize net profit by determining the optimal cultivating area and analyze the effects of various allocation scenarios on employment, economic productivity, and reliability indicators. Moreover, Bayesian Networks and Random Forest algorithms were developed as an automated substitute to simplify the process and reduce computational complexity. The results showed that the Nekoabad Network enjoys top priority followed by the Barkhar, Mahyar, Sonati, Abshar, and Rodasht Networks. After implementing the Bayesian Network, the four criteria of MAE, MAPE, R-2, and the Nash-Sutcliffe index for the irrigation networks were 9 MCM, 24%, 0.738, and 0.644 respectively, which indicated the model has good accuracy. Random Forest method was also employed as a novel technique in automated allocation, and the values obtained for the four mentioned criteria were 7 MCM, 15%, 0.861, and 0.80, which showed it is more accurate. The results indicated the capability of the presented hydro-economic model as well as the intelligent models substituting it in allocating agricultural water.
机译:水资源可持续利用需要采取预防措施,以促进利益攸关方利益和水的经济价值促进水资源的最佳利用。本研究的主要目标是提出基于其经济价值分配农业水的综合水电模型。该研究区域在伊朗Zayandeh Rood Dam下游覆盖了六个灌溉网络。事实上,这项研究解决了如何将稀缺水分配给不同消费者的问题,以实现最高效率和经济效益。为了获得这一目标,通过应用积极的数学规划(PMP)经济模式,通过将经济模型与盆地(MODSIM)的水分配规划模型耦合,对每个灌溉网络中的现有农业活动进行模拟。框架是生成的。这些工具有助于根据其经济价值分配水,通过确定最佳培养面积并分析各种分配方案对就业,经济生产力和可靠性指标的影响来最大化净利润。此外,贝叶斯网络和随机森林算法被开发为自动替代,以简化过程并降低计算复杂性。结果表明,Nekoabad网络享有顶级优先权,然后是Barkhar,Mahyar,Sonati,Abshar和Rodasht网络。在实施贝叶斯网络之后,灌溉网络的MAE,MAPE,R-2和NASH-SUTCLIFFE指数的四个标准分别为9 mcm,24%,0.738和0.644,表明该模型具有良好的准确性。随机森林方法也被用作自动分配中的新技术,并且为四个上述标准获得的值为7mcm,15%,0.861和0.80,显示它更准确。结果表明,呈现的水力 - 经济模型以及智能模型,智能模型在分配农用水中。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号