Development of a hydrological ensemble prediction system and a visualization approach for improved interpretation during typhoon events

Abstract. Typhoons are accompanied by heavy rainfall and cause loss of life and property. Hydrological ensemble prediction systems can provide decision makers with hydrological information, such as peak stage and peak time, with some lead time. This information assists decision makers in taking the necessary measures to prevent and mitigate disasters. This study proposes a hydrological ensemble prediction system that includes numerical weather models that perform rainfall forecasts and hydrologic models that produce assessments of surface runoff and the associated flooding. However, the spatiotemporal uncertainty associated with the numerical models and the difficulty in interpreting the model results hinder effective decision making during emergency response situations. Thus, this study also presents an extension of the ‘Peak-Box’ visualization methodology that assists in interpreting the forecast results for operational purposes. A small watershed with area of 100 km² and four typhoons that occurred from 2012 to 2015 were selected to evaluate the performance of these tools. The results showed that the modified visualization approach improved the intelligibility of forecasts of the peak stages and peak times compared to that of approaches previously described in the literature. The new approach includes all available forecasts to increase the sample size. The capture rate is greater than 50 %, which is considered practical for decision makers. The proposed system and the modified visualization approach have demonstrated their potential for both decreasing the uncertainty of numerical rainfall forecasts and improving the performance of flood forecasts.