Influence of short-term rainfall forecast error on flood forecast operation: A risk assessment based on Bayesian theory

Abstract

To study rainfall forecast error’s influence on flood operation, short-term (24 hours ahead) rainfall forecast accuracy in Qian river basin were analyzed, probabilities of event on flood operation risk were estimated based on Bayesian theory, and the dynamic control scheme was discussed. Results show that, accuracy rate and missing report rate decreased while vacancy rate increased with the increase of rainfall forecast magnitude. For flood operation based on current rainfall forecast information of different magnitudes, level I (“no rain”) error nearly has no impact on it, level II (“light rain”) error has a little impact on small flood operation, and level III (“no less than moderate rain”) error has a great impact on large flood. For the dynamic control scheme in flood season, it is not necessary to discharge flood ahead of schedule so that limited water level can be kept at the upper boundary to provide higher potential energy for power generation when forecasting rainfall shows “no rain” or “light rain”, while it should be discharged ahead of schedule so that limited water level can be kept at a lower value to ensure an adequate flood storage capacity when forecasting rainfall shows “no less than moderate rain”.

Keywords:

• Rainfall information
• forecast error
• risk assessment
• Bayesian theory

Conflict of interest

The authors declared no conflict of interest.

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities, CHD (300102290105), Fundamental “111” Project (B08039), and special Fund for Basic Scientific Research of Central Colleges (300102299206).