five

Experimental delta evolution across a gradient of flooding intensities

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://zenodo.org/record/4928814
下载链接
链接失效反馈
官方服务:
资源简介:
Overbank flooding is a ubiquitous condition in natural rivers that modifies floodplain sediment dispersal and impacts channel mobility. While variable discharge is a critical component driving these processes, fluvial landscape evolution is typically modeled by simplifying the hydrograph to an equivalent steady discharge; namely, the channel-forming discharge. In this framework, changes in the hydrograph only affect landscape evolution if they modify the channel-forming discharge, but different formulations for the channel-forming discharge can generate a range of predictions from the same input hydrograph. Here, we investigate how hydrographs with different flood intensities affect channel mobility, sediment accumulation patterns, and alluvial morphology using a suite of physical experiments where a fan delta grew by dispersing a cohesive sediment mixture into a basin. Flood intensity (\(Q_v \)) was defined as the ratio of the maximum discharge to the minimum discharge, i.e. \(Q_v = Q_{max} / Q_{min}\). The experiments spanned three levels: no flooding, low-intensity flooding, and high-intensity flooding, while the time-averaged discharge was equivalent between all flooding regimes.   This dataset is an HDF5 dataset, which is a general format. The data largely consist of a set of 3D arrays that contain 2D topography and imagery data, where the third dimension is time. Each data object is paired with a 1D vector that links datasets across the time dimension, since data were collected at different intervals. The appropriate linking datasets are also included as CSVs.
创建时间:
2021-06-12
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作