Department of Civil &Environmental Engineering, University of Connecticut, Storrs, Connecticut 06269-3037, USA.
Advanced Radar Research Center, National Weather Center, University of Oklahoma, Norman, Oklahoma 73072, USA.
Sci Data. 2017 Jan 5;4:160124. doi: 10.1038/sdata.2016.124.
Basin morphometry is vital information for relating storms to hydrologic hazards, such as landslides and floods. In this paper we present the first comprehensive global dataset of distributed basin morphometry at 30 arc seconds resolution. The dataset includes nine prime morphometric variables; in addition we present formulas for generating twenty-one additional morphometric variables based on combination of the prime variables. The dataset can aid different applications including studies of land-atmosphere interaction, and modelling of floods and droughts for sustainable water management. The validity of the dataset has been consolidated by successfully repeating the Hack's law.
流域形态计量学是将风暴与水文灾害（如滑坡和洪水）联系起来的重要信息。在本文中，我们提出了第一个具有 30 弧秒分辨率的分布式流域形态计量学的全球综合数据集。该数据集包括九个主要形态计量变量；此外，我们还提出了基于主要变量组合生成二十一个附加形态计量变量的公式。该数据集可辅助不同的应用，包括土地-大气相互作用的研究，以及洪水和干旱模型，以实现可持续水资源管理。该数据集的有效性已通过成功重复哈克定律得到巩固。
