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

arXiv: https://arxiv.org/abs/2012.11154 · HTML: https://mlsanity.com/paper/2012.11154/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Dec 2020.

## Built on by (most cited first, 7 of 7)

- [Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook](https://mlsanity.com/paper/2310.10196/) (2023)
- [SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking](https://mlsanity.com/paper/2109.10399/) (2021)
- [IowaRain: A Statewide Rain Event Dataset Based on Weather Radars and Quantitative Precipitation Estimation](https://mlsanity.com/paper/2107.03432/) (2021)
- [HierarchicalForecast: A Reference Framework for Hierarchical Forecasting in Python](https://mlsanity.com/paper/2207.03517/) (2022)
- [ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method](https://mlsanity.com/paper/2504.07394/) (2025)
- [A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Series](https://mlsanity.com/paper/2412.00772/) (2024)
- [KnowIt: Deep Time Series Modeling and Interpretation](https://mlsanity.com/paper/2507.06009/) (2025)

## Abstract (arXiv)

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.