This study aims to investigate the occurrences of floods by analyzing the monthly precipitation time sequence utilizing ordinary Kalman filter (OKF) and adaptive Kalman Filter (AKF). OKF identifies the abnormal precipitation periods in the sequence by comparing the observed and average precipitation patterns. AKF detects the changes in the precipitation pattern by associating them with the abrupt changes in the parameters of the periodic model of the precipitation time sequence. The 92-year long precipitation record at Fukuoka City, Japan shows three types of abnormal precipitation periods, which exhibit different degrees of possibility of flood occurrence. In addition, it shows nine precipitation epochs with different precipitation patterns. The model parameters estimated by AKF in one epoch characterize its precipitation pattern and describe the occurrences of the abnormal precipitation periods, revealing whether the risk of flood occurrence is high or not in the epoch.
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- Analysis of Flood Occurrence through Characterization of Precipitation Patterns
R. R. Medina
- Springer Netherlands