A comprehensive dataset of riverine levee overtopping events for advancing risk assessment

Earthen levees are the primary flood protection infrastructure worldwide, with overtopping recognized as the most prevalent mode of their failure. Despite its significance, detailed field data on overtopping events are often limited and fragmented. Here we present the Levee Loading and Incident Dataset - Overtopping (LLID-OT) version 1.0, a curated dataset of 487 overtopping events in U.S. riverine levees compiled over the past 15 years. Data were collected from diverse sources, including U.S. Army Corps of Engineers reports, aerial imagery, hydrologic data repositories, and eyewitness accounts, and include detailed information on hydraulic loading, soil and foundation classifications, construction/maintenance characteristics, geometry, and breach dimensions. Quality control included cross-referencing sources and verifying key parameters to ensure dataset consistency and reliability. Analysis reveals consistent relationships between breach characteristics and variables such as soil type, overtopping depth and duration, and levee geometry. The LLID-OT supports the development and calibration of data-driven and physics-based models, advancing levee risk assessment, design, and flood management.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2025-12-19
DOI
https://doi.org/10.1038/s41597-025-06349-y
Citations
1
Primary Topic
Dam Engineering and Safety
Type
article
Field-Weighted Citation Impact
0.95

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A comprehensive dataset of riverine levee overtopping events for advancing risk assessment

David M. Schaaf, Stefan Flynn, Farshid Vahedifard
1 citations
Scientific Data
Dam Engineering and Safety
0.95
article

A comprehensive dataset of riverine levee overtopping events for advancing risk assessment

David M. Schaaf, Stefan Flynn, Farshid Vahedifard
article en
1 citations

Abstract

Earthen levees are the primary flood protection infrastructure worldwide, with overtopping recognized as the most prevalent mode of their failure. Despite its significance, detailed field data on overtopping events are often limited and fragmented. Here we present the Levee Loading and Incident Dataset - Overtopping (LLID-OT) version 1.0, a curated dataset of 487 overtopping events in U.S. riverine levees compiled over the past 15 years. Data were collected from diverse sources, including U.S. Army Corps of Engineers reports, aerial imagery, hydrologic data repositories, and eyewitness accounts, and include detailed information on hydraulic loading, soil and foundation classifications, construction/maintenance characteristics, geometry, and breach dimensions. Quality control included cross-referencing sources and verifying key parameters to ensure dataset consistency and reliability. Analysis reveals consistent relationships between breach characteristics and variables such as soil type, overtopping depth and duration, and levee geometry. The LLID-OT supports the development and calibration of data-driven and physics-based models, advancing levee risk assessment, design, and flood management.

Scientific DataVol. 13(1)
Tufts University (US), United States Army Corps of Engineers (US), United Nations University Institute for Water, Environment, and Health (CA)
U.S. Army Corps of Engineers
Openalex Percentile: Top 19%
Dam Engineering and Safety
0.95
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.