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通过利用CMIP6一般循环模型的数据驱动方法来评估德克萨斯州未来的水供应
Wenzhao Li1, Dongfeng Li2, Hesham El-Askary3
1Earth Systems Science and Data Solutions Lab, Chapman University, Orange, CA 92866, USA; Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA.
The Science of the total environment
|February 24, 2024
概括
气候变化影响德克萨斯州的水资源,新的数据驱动模型在预测中表现优于其他模型. 一些地区面临着日益严重的水资源压力,这凸显了适应性水资源管理战略的必要性.
科学领域:
- 气候科学 气候科学
- 水文学的水文学
- 环境科学 环境科学
背景情况:
- 由于气候变化,极端降水事件正在增加,影响水资源分配.
- 德克萨斯州面临着独特的供水挑战,因为它的快速增长和西-东降水梯度.
研究的目的:
- 改进对德克萨斯州未来水资源的预测,使用相结合模型对比项目第6阶段 (CMIP6) 的数据和数据驱动的方法.
- 分析德克萨斯州水资源规划地区实际蒸发转化 (AET) 和净水供应 (NWA) 的预测变化.
主要方法:
- 利用CMIP6数据和数据驱动的方法来增强用于水资源预测的多模型组合.
- 使用技能指标,将数据驱动模型的性能与CMIP5和CMIP6模型进行了比较.
- 分析了根据不同的共享社会经济途径 (SSP) 从2015年到2074年的NWA和水需求的预测变化.
主要成果:
- 与CMIP5和CMIP6模型相比,数据驱动模型在所有技能指标上表现出卓越的表现.
- 预计波动的水压力模式,德克萨斯州16个水资源规划区域中有9个面临着调和需求和供应的挑战.
- 在北德克萨斯州 (SSP2-4.5) 观察到降水,AET和NWA的增加趋势,但在南德克萨斯州 (SSP5-8.5) 观察到下降趋势.
结论:
- 数据驱动的方法为推动气候科学和改善水资源预测提供了巨大的潜力.
- 有效的水资源管理需要考虑水的供应和需求的空间和时间变化.
- 适应性水资源管理策略对于应对德克萨斯州不断变化的水资源供应情况至关重要.
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