EXAMINATION OF WATER LEVEL PREDICTION METHODS TO SUPPORT THE OPERATION OF CHECK GATES IN LOW-LYING SMALL STREAM

Abstract

 We studied the effectiveness of a water level prediction methods to support the operation of check gates in low-lying small stream, where both flood control and water utilization are required. From interview surveys with facility managers and on-site water level observations, it was found that the current decision to remove the gate weirs depends on managers' forecasts and visual observations of water level, and that water level predictions based on remote monitoring data are useful for facility management. In one rainfall event, it was estimated that the peak water level was kept from rising approximately 1 m by removing the weirs of the check gate. This indicates the importance of gate operation by the facility managers. The Nearest-Neighbor (NN) method, one of the pattern recognition methods that are easy to construct models, was applied to the study area as a water level prediction method. It was found that water levels could be predicted with an RMSE of 0.056 m to 0.13 m when the lead time was 4 h.