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Updated: Sep 16, 2025

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Watershed Planning within a Quantitative Scenario Analysis Framework
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在共享社会经济路径2020-2100下,印度河流域的网格人口结构数据集
Barira Haider1, Cheng Jing2, Buda Su3
1State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
Scientific data
|July 10, 2025
概括
这项研究为印度河流域提供了高分辨率的人口数据集,这对于了解资源分配和环境可持续性在人口快速增长的情况下至关重要. 这些数据有助于未来对可持续发展和气候变化影响的研究.
科学领域:
- 环境科学 环境科学
- 人口统计学 人口统计学
- 地理空间分析的研究.
背景情况:
- 印度河流域面临着严重的水争端和人口快速增长.
- 高分辨率的人口数据对于评估资源分配和环境可持续性至关重要.
研究的目的:
- 为印度河流域开发一个高分辨率的网格化人口数据集.
- 通过共享社会经济路径 (SSP1-5) 预测未来人口规模和结构变化 (2020-2100年).
主要方法:
- 利用阿富汗,中国,印度和巴基斯坦的历史人口数据和省级人口参数.
- 在2.5弧分钟 (~5公里) 的网格分辨率上预测人口变化.
- 与62,140个网格中观察到的网格化人口数据对数据集进行了验证.
主要成果:
- 创建了印度河流域详细的人口网格数据集.
- 预测涵盖不同社会经济情景下的人口规模和结构 (年龄,性别) 变化.
- 数据集通过对观察到的数据进行验证来证明其高准确性.
结论:
- 开发的数据集是资源管理和可持续发展研究的宝贵资源.
- 它支持对印度河流域气候变化影响的评估.
- 促进跨境水资源管理的知情决策.
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