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基于远程传感的GRDC排放时间序列的延伸 - 一个月产品与不确定性估计
Omid Elmi1, Mohammad J Tourian2, Peyman Saemian2
1Institute of Geodesy, University of Stuttgart, Stuttgart, Germany. omid.elmi@gis.uni-stuttgart.de.
Scientific data
|February 24, 2024
概括
基于远程传感的GRDC (RSEG) 数据集扩展使用卫星数据扩展河流排放记录,用于不活跃的仪表. 这项研究恢复了对全球83%的河流排放的关键水文监测.
科学领域:
- 水文学的水文学
- 遥感 遥感 遥感 遥感
- 环境科学 环境科学
背景情况:
- 自20世纪80年代以来,全球流水数据中心 (GRDC) 数据集已经历了活跃河流标尺的显著下降.
- 到2020年,只有14%的GRDC标尺保持活跃,限制了全球排放监测能力.
研究的目的:
- 开发一套新的数据集,即基于遥感的GRDC扩展 (RSEG),以扩展历史的河流排放记录.
- 通过将遗留数据与遥感观测数据相结合,重新建立不活跃的标尺站的水文监测.
主要方法:
- 使用一个随机非参数映射算法来扩展不活跃的GRDC站的月度放电时间序列.
- 该算法利用卫星图像和高度测量得出的河流宽度和水高度观测.
- 对估计的排放进行了广泛的质量评估,包括统计验证和视觉检查.
主要成果:
- 在6015个GRDC站中,RSEG数据集成功扩展了3377个GRDC站的排放记录.
- 平均排放量中等至大河流的排放估计显示质量令人满意 (KGE>0.5).
- RSEG数据集恢复了之前GRDC站测量的83%的河流排放总量监测能力,达到7895公里3/月.
结论:
- RSEG数据集有效地扩展了GRDC河流排放记录,大大提高了全球水文监测能力.
- 远程传感数据集成为因现场测量网络的衰退造成的数据缺口提供了可行的解决方案.
- 虽然性能因河流大小而有所不同,但RSEG数据集提供了宝贵的水文洞察力,特别是对于较大的河流系统.
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