CFDID: a China Flood Disaster Impact Database from 1994 to 2023

China is one of the countries most severely affected by flood disasters. Long-term and systematic flood impact data are essential for flood risk assessment, flood impact model calibration, disaster prevention and reduction. However, an open, long-term, China-focused event-scale database with detailed flood disaster impact indicators remains lacking. Here we present the China Flood Disaster Impact Database (CFDID), which contains 1716 flood disaster event records from 1994 to 2023, including 1391 parent-event (L1) records. CFDID is compiled from 66 official documents and covers five flood-related disaster categories: rainstorm flood, typhoon, snowmelt flood, ice-jam flood, and dam-break flood. Each record includes date, location, disaster category, data source and available values for eight impact indicators: deaths and missing persons, affected population, affected cropland area, damaged cropland area, failed cropland area, collapsed dwellings, damaged dwellings, and direct economic losses. The database was constructed using a workflow that combines optical character recognition (OCR), large language model (LLM)-based information extraction, and manual verification, thereby improving the efficiency of converting unstructured text information into structured event records while ensuring data quality. Relative to the corresponding official national totals during 1994–2023, the impacts reported in L1 records in CFDID account for 68.49 % of deaths and missing persons, 72.24 % of affected population, 60.70 % of affected cropland area, 65.67 % of collapsed dwellings, and 74.86 % of direct economic losses. Compared with commonly used international flood impact databases, CFDID contains more detailed event records and accounts for higher percentages of the corresponding official totals for most impact indicators. CFDID also includes agricultural impact indicators, which are rarely available in international hazard impact databases. CFDID is available at https://doi.org/10.5281/zenodo.22918521 (Cui et al., 2026) and will be continuously updated by year.