%0 Dataset
%T There are 193 datasets of 8 influencing factors in some embankment sections such as the Yellow Vast Embankment of the Yangtze River and the main embankment of the Yangtze River in Anqing
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/552f4653-b5cd-41e0-a92a-59e074f43639
%W NCDC
%R 10.12072/ncdc.nhri.db6792.2025
%A Lu Minggui
%K Levee seepage;machine learning
%X This dataset includes 193 samples from multiple embankment sections, such as the Huangguang Embankment and the Anqing Main Embankment along the Yangtze River, encompassing eight key influencing factors: water level difference (m), cover layer thickness (m), permeability coefficient (cm/s), effective cohesion (kg/cm), effective internal friction angle (°), dry density (g/cm³), void ratio, and compression coefficient (MPa⁻¹). The dataset exhibits significant advantages in terms of data diversity among influencing factors, offering higher resolution and reliability. It is widely applicable for embankment safety assessment, flood control model development, and the training and validation of machine learning algorithms. This supports the scientific and meticulous management of flood prevention and disaster mitigation efforts, and advances research and application development in the field of hydraulic engineering.