Abstract
The purpose of this study is to forecast rainfall and river water levels for the Kahayan River in Indonesia and to provide the forecast information to mitigate peat fires. First, rainfall was predicted by using the rainfall dataset provided by the Global Precipitation Climatology Project (GPCP) and the Nearest-Neighbor Method (NNM). Then, water level prediction was conducted by inputting the predicted rainfall values into a hydrological model. We incorporated Sea Surface Temperature (SST) into the NNM to treat El Niño event and the Indian Ocean Dipole mode (IOD) as major factors influencing rainfall in Indonesia. As a result, the forecast accuracy of water level reductions that can lead to large-scale peat fires was improved. It was demonstrated that long-term water level forecasts with 1 to 3 month lead times were able to be done with reasonable accuracy.
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Schedule a callMore From: Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering)
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