FlowDB a large scale precipitation, river, and flash flood dataset

TL;DR

FlowDB introduces a comprehensive large-scale dataset combining hourly precipitation and river flow data, along with flash flood event information, enabling new benchmarks for flood prediction and damage estimation.

Contribution

The paper presents a novel, publicly available dataset for precipitation, river flow, and flash flood damage, along with benchmarks and tools for flood prediction research.

Findings

Created a large-scale, multi-faceted flood dataset

Established benchmarks for stream flow forecasting and damage estimation

Laid groundwork for future dataset enhancements with additional environmental data

Abstract

Flooding results in 8 billion dollars of damage annually in the US and causes the most deaths of any weather related event. Due to climate change scientists expect more heavy precipitation events in the future. However, no current datasets exist that contain both hourly precipitation and river flow data. We introduce a novel hourly river flow and precipitation dataset and a second subset of flash flood events with damage estimates and injury counts. Using these datasets we create two challenges (1) general stream flow forecasting and (2) flash flood damage estimation. We have created several publicly available benchmarks and an easy to use package. Additionally, in the future we aim to augment our dataset with snow pack data and soil index moisture data to improve predictions.