Author
Listed:
- 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
Center of Excellence for Ocean Engineering, National Taiwan Ocean University, Keelung 202, Taiwan)
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.
Suggested Citation
Sheng-Chi Yang & Tsun-Hua Yang & Ya-Chi Chang & Cheng-Hsin Chen & Mei-Ying Lin & Jui-Yi Ho & Kwan Tun Lee, 2020.
"Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons,"
Sustainability, MDPI, vol. 12(10), pages 1-20, May.
Handle:
RePEc:gam:jsusta:v:12:y:2020:i:10:p:4258-:d:361634
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Citations
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Cited by:
- Kamal Abdelrahim Mohamed Shuka & Ke Wang & Ghali Abdullahi Abubakar & Tianyue Xu, 2024.
"Impact of Structural and Non-Structural Measures on the Risk of Flash Floods in Arid and Semi-Arid Regions: A Case Study of the Gash River, Kassala, Eastern Sudan,"
Sustainability, MDPI, vol. 16(5), pages 1-23, February.
- Joško Trošelj & Han Soo Lee & Lena Hobohm, 2023.
"Enhancing a Real-Time Flash Flood Predictive Accuracy Approach for the Development of Early Warning Systems: Hydrological Ensemble Hindcasts and Parameterizations,"
Sustainability, MDPI, vol. 15(18), pages 1-33, September.
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