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Updated: Sep 16, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

中国未来的水资源紧张:社会经济和气候变化情景下的预测

Danyang Gao¹, Guangtao Fu¹, Xi Wan²

¹Centre for Water Systems, University of Exeter, Exeter, EX4 4QF, UK.

Journal of environmental management

|July 8, 2025

概括

中国未来的水资源紧张局势将因地区而异,一些地区因气候变化和需求增加而面临更大的压力. 有针对性的水资源管理战略对于可持续的资源分配和利用至关重要.

科学领域:

环境科学环境科学
气候建模气候建模
水资源管理水资源的管理.

背景情况:

准确估计未来的水资源压力对于在气候和社会经济变化中可持续管理至关重要.
之前在中国的研究往往缺乏特定区域的校准或使用不一致的场景.
需要一个新的建模框架来解决这些局限性.

研究的目的:

开发和应用一个集成的机器学习和土地表面模型框架.
评估中国的水压力指数 (WSI),考虑水需求和资源.
在不同的气候社会经济情景下预测未来的WSI.

主要方法:

机器学习与土地表面模型的整合.
对建模框架的校准和验证.
使用SSP2-RCP4.5和SSP5-RCP8.5场景预测未来的WSI.

主要成果:

该框架准确地模拟了地表水资源 (R2 = 0.96) 和部门水需求 (平均R2 = 0.96).
在全国范围内,WSI预计从2022年到2100年将在0.20和0.31之间波动.
预计在西北部和中部地区,特别是SSP5-RCP8.5下,严重的水压力将增加,而一些北部/东北部地区可能会出现压力下降.

结论:

区域特定的水资源管理策略至关重要.
政策应该解决需求管理和压力地区的水分配问题.
对于需求日益增加的地区,建议优先考虑水利用效率和节约技术.
时间趋势为对长期挑战的阶段性政策响应提供了路线图.

关键词:

朱尔斯模型模型机器学习是机器学习.在SSP-RCP中使用SSP.水的稀缺水的稀缺水-能源-食品水

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