Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons

Sheng-Chi Yang, Tsun-Hua Yang, Ya-Chi Chang, Cheng-Hsin Chen, Mei-Ying Lin, Jui-Yi Ho and Kwan Tun Lee
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Sheng-Chi Yang: National Applied Research Laboratories, Taipei 106, Taiwan
Tsun-Hua Yang: Department of Civil Engineering, National Chiao Tung University, Hsinchu 300, Taiwan
Ya-Chi Chang: Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, Hsinchu 310, Taiwan
Cheng-Hsin Chen: Department of Civil Engineering, National Chung Hsing University, Taichung 402, Taiwan
Mei-Ying Lin: National Science and Technology Center for Disaster Reduction, Taipei 231, Taiwan
Jui-Yi Ho: National Science and Technology Center for Disaster Reduction, Taipei 231, Taiwan
Kwan Tun Lee: Department of River and Harbor Engineering, National Taiwan Ocean University, Keelung 202, Taiwan

Sustainability, 2020, vol. 12, issue 10, 1-20

Abstract: Hydrological ensemble prediction systems (HEPSs) can provide decision makers with early warning information, such as peak stage and peak time, with enough lead time to take the necessary measures to mitigate disasters. This study develops a HEPS that integrates meteorological, hydrological, storm surge, and global tidal models. It is established to understand information about the uncertainty of numerical weather predictions and then to provide probabilistic flood forecasts instead of commonly adopted deterministic forecasts. The accuracy of flood forecasting is increased. However, the spatiotemporal uncertainty associated with these numerical models in the HEPS and the difficulty in interpreting the model results hinder effective decision-making during emergency response situations. As a result, the efficiency of decision-making is not always increased. Thus, this study also presents a visualization method to interpret the ensemble results to enhance the understanding of probabilistic runoff forecasts for operational purposes. A small watershed with area of 100 km 2 and four historical typhoon events were selected to evaluate the performance of the method. The results showed that the proposed HEPS along with the 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 capture rate is greater than 50%, which is considered practical for decision makers. The proposed HEPS with the visualization method has potential for both decreasing the uncertainty of numerical rainfall forecasts and improving the efficiency of decision-making for flood forecasts.

Keywords: hydrological ensemble prediction system; numerical weather model; flood forecast; peak flow; visualization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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