4.7 Article

Global Reach-Level 3-Hourly River Flood Reanalysis (1980-2019)

期刊

BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
卷 102, 期 11, 页码 E2086-E2105

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/BAMS-D-20-0057.1

关键词

Rivers; Flood events; Hydrology; Hydrologic models; Risk assessment

资金

  1. National Natural Science Foundation of China [7146101701]
  2. Jet Propulsion Laboratory, California Institute of Technology
  3. U.S. National Aeronautics and Space Administration (NASA)

向作者/读者索取更多资源

Given recent advances in global runoff hydrology, river modeling, high-resolution hydrography, and climate reanalysis, a global 3-hourly river discharge record for 2.94 million river reaches has been developed for the period of 1980-2019. The modeling chain shows good performance in reconstructing flood events and highlights the importance of subdaily modeling.
Better understanding and quantification of river floods for very local and flashy events calls for modeling capability at fine spatial and temporal scales. However, long-term discharge records with a global coverage suitable for extreme events analysis are still lacking. Here, grounded on recent breakthroughs in global runoff hydrology, river modeling, high-resolution hydrography, and climate reanalysis, we developed a 3-hourly river discharge record globally for 2.94 million river reaches during the 40-yr period of 1980-2019. The underlying modeling chain consists of the VIC land surface model (0.05 degrees, 3-hourly) that is well calibrated and bias corrected and the RAPID routing model (2.94 million river and catchment vectors), with precipitation input from MSWEP and other meteorological fields downscaled from ERA5. Flood events (above 2-yr return) and their characteristics (number, spatial distribution, and seasonality) were extracted and studied. Validations against 3-hourly flow records from 6,000+ gauges in CONUS and daily records from 14,000+ gauges globally show good modeling performance across all flow ranges, good skills in reconstructing flood events (high extremes), and the benefit of (and need for) subdaily modeling.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据