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Optimal integrated management of groundwater resources and irrigated agriculture in arid coastal regions

机译:干旱沿海地区地下水资源与灌溉农业的优化综合管理

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Groundwater systems in arid coastal regions are particularly at risk due to limited potential for groundwater replenishment and increasing water demand, caused by a continuously growing population. For ensuring a sustainable management of those regions, we developed a new simulation-based integrated water management system. The management system unites process modelling with artificial intelligence tools and evolutionary optimisation techniques for managing both water quality and water quantity of a strongly coupled groundwater-agriculture system. Due to the large number of decision variables, a decomposition approach is applied to separate the original large optimisation problem into smaller, independent optimisation problems which finally allow for faster and more reliable solutions. It consists of an analytical inner optimisation loop to achieve a most profitable agricultural production for a given amount of water and an outer simulation-based optimisation loop to find the optimal groundwater abstraction pattern. Thereby, the behaviour of farms is described by crop-water-production functions and the aquifer response, including the seawater interface, is simulated by an artificial neural network. The methodology is applied exemplarily for the south Batinah region/Oman, which is affected by saltwater intrusion into a coastal aquifer system due to excessive groundwater withdrawal for irrigated agriculture. Due to contradicting objectives like profit-oriented agriculture vs aquifer sustainability, a multi-objective optimisation is performed which can provide sustainable solutions for water and agricultural management over long-term periods at farm and regional scales in respect of water resources, environment, and socio-economic development.
机译:干旱沿海地区的地下水系统尤其受到威胁,这是由于人口不断增长所导致的补充地下水的潜力有限和需水量增加。为了确保对这些地区的可持续管理,我们开发了一种基于模拟的新综合水资源管理系统。该管理系统将过程建模与人工智能工具和进化优化技术相结合,用于管理强耦合地下水农业系统的水质和水量。由于决策变量数量众多,因此采用了一种分解方法将原始的大型优化问题分为较小的独立优化问题,最终可以实现更快,更可靠的解决方案。它由一个分析内部优化循环(用于在给定量的水量下实现最有利的农业生产)和一个基于外部仿真的优化循环(用于查找最佳的地下水提取模式)组成。因此,通过作物水生产函数来描述农场的行为,并通过人工神经网络来模拟包括海水界面在内的含水层响应。该方法被示例性地应用于南部的Batinah地区/阿曼,该地区由于灌溉农业抽取过多的地下水而受到海水入侵沿海含水层系统的影响。由于利益导向型农业与含水层可持续性等相互矛盾的目标,因此进行了多目标优化,可以在水资源和水资源,环境和社会方面在农场和区域范围内长期提供可持续的水和农业管理解决方案。 -经济发展。

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