Suppr超能文献

印度东部库沙布哈德拉-巴尔加维河三角洲联合水资源管理与作物优化规划的仿真优化。

Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India.

机构信息

Agricultural & Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur-721 302, India.

Civil and Environmental Engineering, Utah State University, Logan, UT 84322-4110, USA.

出版信息

Int J Environ Res Public Health. 2020 May 18;17(10):3521. doi: 10.3390/ijerph17103521.

Abstract

Water resources sustainability is a worldwide concern because of climate variability, growing population, and excessive groundwater exploitation in order to meet freshwater demand. Addressing these conflicting challenges sometimes can be aided by using both simulation and mathematical optimization tools. This study combines a groundwater-flow simulation model and two optimization models to develop optimal reconnaissance-level water management strategies. For a given set of hydrologic and management constraints, both of the optimization models are applied to part of the Mahanadi River basin groundwater system, which is an important source of water supply in Odisha State, India. The first optimization model employs a calibrated groundwater simulation model (MODFLOW-2005, the U.S. Geological Survey modular ground-water model) within the Simulation-Optimization MOdeling System (SOMOS) module number 1 (SOMO1) to estimate maximum permissible groundwater extraction, subject to suitable constraints that protect the aquifer from seawater intrusion. The second optimization model uses linear programming optimization to: (a) optimize conjunctive allocation of surface water and groundwater and (b) to determine a cropping pattern that maximizes net annual returns from crop yields, without causing seawater intrusion. Together, the optimization models consider the weather seasons, and the suitability and variability of existing cultivable land, crops, and the hydrogeologic system better than the models that do not employ the distributed maximum groundwater pumping rates that will not induce seawater intrusion. The optimization outcomes suggest that minimizing agricultural rice cultivation (especially during the non-monsoon season) and increasing crop diversification would improve farmers' livelihoods and aid sustainable use of water resources.

摘要

水资源可持续性是一个全球性的关注点,这是由于气候变化、人口增长以及为满足淡水需求而过度开采地下水等因素所致。解决这些相互矛盾的挑战有时可以借助模拟和数学优化工具来实现。本研究结合地下水流动模拟模型和两种优化模型,制定了最优的勘查级水资源管理策略。对于给定的水文和管理约束条件,两种优化模型都被应用于印度奥里萨邦马哈纳迪河流域地下水系统的一部分,该系统是该地区供水的重要水源。第一种优化模型采用经过校准的地下水模拟模型(美国地质调查局模块化地下水模型 MODFLOW-2005),并在 Simulation-Optimization MOdeling System (SOMOS) 模块 1(SOMO1)中运行,以估算在适当保护含水层免受海水入侵的约束条件下,最大允许的地下水开采量。第二种优化模型采用线性规划优化来:(a) 优化地表水和地下水的联合配置,以及 (b) 确定一种种植模式,使作物产量的净年收益最大化,同时又不会引起海水入侵。总的来说,优化模型比不采用分布式最大地下水抽提率的模型更好地考虑了气象季节、现有可耕种土地的适宜性和变异性、作物和水文地质系统,这些模型不会引起海水入侵。优化结果表明,减少农业水稻种植(特别是在非季风季节)和增加作物多样化将改善农民的生计,并有助于水资源的可持续利用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0d6/7277523/a5ccaea0c585/ijerph-17-03521-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验