Author(s): Chiaki Yoshida; Makoto Nakatsugawa; Shun Kudo
Linked Author(s):
Keywords: Rainfall forecast; Water level forecast; Nearest-Neighbor Method; Climate changes; Sea Surface Temperature
Abstract: The purpose of this study is water level forecasts for the Kahayan River in Indonesia. In recent years, peatland in that basin has been drying as a result of the development of agricultural, and such drying has caused more frequent largescale wildfires there. Also due to effects of a slight rainfall, large amounts of greenhouse gases have been emitted from peat fire in the subject area of this study. The purpose of this study is to forecast rainfall and river water levels and to provide the forecast information to mitigate peat fires. Specifically, rainfall prediction was done first by using the rainfall values from ground rain gauges, the dataset provided by the Global Precipitation Climatology Project (GPCP) and the Nearest-Neighbor Method (NNM) is one of the pattern matching method. Then, water level prediction was done by inputting the predicted rainfall values into the hydrological model. In forecasting the water level, climate changes such as those related to El Niño were taken into consideration by incorporating the Sea Surface Temperature (SST) at the Pacific Ocean off the coast of Peru into the forecast factors. The accuracy of water level forecasts times of low water in the dry season with scant rainfall was improved by using the lower limit value of predicted rainfall based on the error evaluation. It was demonstrated that long-term water level forecasts with 1-to 3-month lead times were able to be done with reasonable accuracy. The results will be useful for basin management that better prevents the wildfires of the peatland.
Year: 2015