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Updated: May 12, 2025

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气候变化下的可持续水分配:深度学习方法可以预测饮用水短缺

Hamid Kardan Moghaddam¹, Zahra Rahimzadeh Kivi², Ebrahim Abtahizadeh³

¹Department of Water Resources Study, Water Research Institute, Tehran, Iran.

Journal of environmental management

|May 9, 2025

概括

德黑兰因过度依赖地下水和气候变化而面临严重的水危机. 先进的机器学习模型预测供水量大幅下降,迫切需要可持续的管理策略.

科学领域:

环境科学环境科学
水文学的水文学
城市规划城市规划

背景情况:

干旱地区的大都市面临着城市化和气候变化加剧的关键供水挑战.
德黑兰的水资源紧张正在加剧,地下水供应超过51%的需求,水层每年耗尽32厘米.
不可持续的水需求是由人口增长,移民,城市规划不良和环境管理不足所驱动的.

研究的目的:

开发和应用先进的机器学习模型,在气候变化和城市压力下预测德黑兰的水资源.
评估城市集中,土地利用管理不善和气候变化的对水资源供应的影响.
为可持续的水资源管理和在水库和含水层之间分配提供路线图.

主要方法:

混合模拟模型结合了循环神经网络 (RNN) 和长短期记忆 (LSTM) 与优化算法 (火优化器,鱼优化算法,马优化算法).
在三个排放路径 (SSP1.26,SSP2.45,SSP5.85) 下,利用了三种最先进的气候模型 (MRI-ESM2,CNRM-CM6-1,BCC-CSM2) 进行2021-2050年预测.
通过整合地表和地下水资源,开发了一种用于减轻水资源短缺的概念模型.

主要成果:

RNN-FHO模型在预测水流入方面表现出色;RNN-WOA模型在预测地下水表波动方面表现出色.
预计到2050年,大的入水量将从8% (乐观) 降至11% (最坏的情况下).
到2030年,水需求将超过2.2亿公,由于过度提取 (100-300亿公),可能导致46-171厘米的含水层抽取.

结论:

德黑兰的水资源受到严重威胁,需要在水资源管理方面进行范式转变.
紧急实施包括减少人均消耗,回收水,处理废水使用和优化分配在内的战略至关重要.
该研究为全球缺水的城市环境提供了变革性的解决方案.

关键词:

适应战略适应战略水层的补充是水层的补充.气候变化气候变化气候变化气候模型的气候模型.水资源分配水资源的分配水资源不平衡造成的不平衡

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