Extreme precipitation with a continuous high frequency may trigger disasters such as floods. In an effort to minimize losses caused by flooding, a statistical model can be used to predict extreme precipitation by taking into account several factors that influence it. One model that can be used is Quantile Regression. Based on the results of quantile regression analysis involving temperature, humidity, sun exposure, wind speed and air pressure, it can be concluded that in the 75th, 90th and 95th quantiles, the variables that affect extreme precipitation are temperature and duration of sun exposure. The visualization of extreme precipitation predictions in the 75th, 90th and 95th quantiles have the same pattern as the actual data. The results of prediction of extreme precipitation are beneficial for flood mitigation as part of flood early warning system.
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