在MERIT-Plus数据集中对5分钟和15分钟升级的河流网络的内流排水盆地进行划分
Alexander A Prusevich1, Richard B Lammers2, Stanley J Glidden2
1Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, 03824, USA. alex.proussevitch@unh.edu.
Scientific data
|January 10, 2024
概括
新的方法将关键的endorheic和exorheic盆地属性赋予数字河流网络,改善水文建模. 这提高了对水平衡和陆地地表水储量的理解.
科学领域:
- 水文学的水文学
- 地质科学 地质科学
- 环境科学 环境科学
背景情况:
- 数字河流网络,就像那些被Iterative Hydrography Upscaling (IHU) 算法处理的数字河流网络一样,往往缺乏必要的 endorheic 和 exorheic 盆地属性.
- 内陆排水盆地对于全球/区域水平衡的精确水文建模,陆地地表水储量以及理解重力异常和海平面上升等现象至关重要.
研究的目的:
- 开发和实施可靠的方法,为数字河流网络赋予 endorheic 和 exorheic 属性,包括由 IHU 处理的.
- 提高数字河流网络数据的准确性和实用性,用于各种水文和环境研究.
主要方法:
- 开发了一种两步方法,在不改变流动方向网格的情况下分配盆地属性.
- 步骤1:根据海洋连接性创建明确的盆地属性,标记 endorheic 和 exorheic 流域.
- 步骤2:实施合并算法来划定内流域,将小内陆流域整合到相邻的大流域中.
主要成果:
- 成功地将endorheic和exorheic属性分配给数字河流网络.
- 合并算法显著减少了划分的内陆盆地数量,同时保持了整体的内陆盆地拓和土地面积.
- 使用水平衡模型的验证证实了通过将低谷体积与内陆湖泊的水积累模型进行比较的准确性.
结论:
- 开发的方法通过结合重要的水文属性,有效地增强了数字河流网络数据集.
- 这些改进的数据集对于推进水文建模,水资源管理和地球水循环研究至关重要.
- 该方法提供了一种适用于各种数字河流网络数据集的多功能解决方案,超出了IHU处理的数据.
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