Study on a Water-Level-Forecast Method Based on a Time Series Analysis of Urban River Basins—A Case Study of Shibuya River Basin in Tokyo

Abstract

In urban basins, localized torrential rain increases the water level of rivers in an extremely short time, thereby leading to flooding within an hour. Therefore, to achieve early evacuation, the water level should be accurately forecasted. The outflow process in urban areas employs the sewer system to discharge the water back to rivers. However, the data for the sewer system are not freely available, and it requires much work and time to design a physical model based on such data. Thus, a vector autoregressive model to develop a water level forecast system that uses observed rainfall and water level is being used. Additionally, this model was used to ensure information conducive to evacuation approximately 20 min in advance and to assess its forecast accuracy, despite the very limited data—water levels at one point and average rainfall at another—without the need to build a physical model such as that which is used in sewer pipe calculations. Compared to the observed water level, the calculated water level increased faster; and thus, the forecast leaned toward safety in evacuation. Furthermore, the data from past five torrential rainfall events to achieve a stable forecast; this method can be applied to basins with limited observation data. Therefore, these results indicate that this method can be applied as a water level forecast method for basins with an extremely fast flood arrival time.

Keywords

• urban floods
• forecast method
• water level
• vector auto regressive model
• time series analysis