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Basin-scale multi-objective simulation-optimization modeling for conjunctive use of surface water and groundwater in northwest China

机译:中国西北地下水和地下水联合用途的盆地规模多目标仿真优化建模

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In the arid inland basins of China, the long-term unregulated agricultural irrigation from surface water diversion and groundwater abstraction has caused the unsustainability of water resources and the degradation of ecosystems. This requires the integrated management of surface water?(SW) and groundwater?(GW) at basin scale to achieve scientific decisions which support sustainable water resource allocation in China. This study developed a novel multi-objective simulation-optimization?(S-O) modeling framework. The optimization framework integrated a new epsilon multi-objective memetic algorithm?(ε-MOMA) with a MODFLOW-NWT model to implement real-world decision-making for water resource management while pondering the complicated groundwater–lake–river interaction in an arid inland basin. Then the optimization technique was validated through the SW–GW management in Yanqi Basin?(YB), a typical arid region with intensive agricultural irrigation in northwest China. The management model, involving the maximization of total water supply rate, groundwater storage, surface runoff inflow to the terminal lake, and the minimization of water delivery cost, was proposed to explore the trade-offs between socioeconomic and environmental factors. It is shown that the trade-off surface can be achieved in the four-dimensional objective space by optimizing spatial groundwater abstraction in the irrigation districts and surface water diversion in the river. The Pareto-optimal solutions avoid the prevalence of decision bias caused by the low-dimensional optimization formulation. Decision-makers are then able to identify their desired water management schemes with preferred objectives and achieve maximal socioeconomic and ecological benefits simultaneously. Moreover, three representative runoff scenarios in relation to climate change were specified to quantify the effect of decreasing river runoff on the water management in?YB. Results show that runoff depletion would have a great negative impact on the management objectives. Therefore, the integrated SW?and GW?management is of critical importance for the fragile ecosystem in?YB under changing climatic conditions.
机译:在中国干旱的内陆盆地中,从地表分流和地下水抽取的长期不受管制的农业灌溉引起了水资源的不可持续性和生态系统的退化。这需要地表水的综合管理?(SW)和地下水?(GW)处于盆地规模,以实现支持中国可持续水资源配置的科学决策。本研究开发了一种新的多目标仿真优化?(S-O)建模框架。优化框架集成了一种新的epsilon多目标麦克算法?(ε-moma),具有模型模型,以实现水资源管理的真实决策,同时在思考在内陆的干旱地区复杂的地下水 - 湖河互动盆地。然后通过延奇盆地的SW-GW管理验证了优化技术?(YB),这是一个典型的干旱地区,在中国西北部强化农业灌溉。提出了管理模式,涉及总供水率,地下水,地表径流流入到终端湖泊的地下水,以及最小化供水费用,探讨社会经济与环境因素之间的权衡。结果表明,通过优化灌溉区中的空间地下水抽象和河流的地表用水分流,可以在四维目标空间中实现折衷表面。 Pareto-Optimal解决方案避免了由低维优化制剂引起的决策偏差的普及。然后,决策者能够以首选目标识别其所需的水管理计划,并同时实现最大的社会经济和生态效益。此外,有关气候变化的三种代表性径流情景,规定了量化河流径流降低对水管理的影响?YB。结果表明,径流消耗将对管理目标产生巨大的负面影响。因此,集成的SW?和GW?管理对脆弱的生态系统在变化的气候条件下的脆弱生态系统中至关重要。

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