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dc.contributor.authorYang, Sheng-Chien_US
dc.contributor.authorYang, Tsun-Huaen_US
dc.contributor.authorChang, Ya-Chien_US
dc.contributor.authorChen, Cheng-Hsinen_US
dc.contributor.authorLin, Mei-Yingen_US
dc.contributor.authorHo, Jui-Yien_US
dc.contributor.authorLee, Kwan Tunen_US
dc.date.accessioned2020-10-05T01:59:51Z-
dc.date.available2020-10-05T01:59:51Z-
dc.date.issued2020-05-01en_US
dc.identifier.urihttp://dx.doi.org/10.3390/su12104258en_US
dc.identifier.urihttp://hdl.handle.net/11536/154984-
dc.description.abstractHydrological 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.en_US
dc.language.isoen_USen_US
dc.subjecthydrological ensemble prediction systemen_US
dc.subjectnumerical weather modelen_US
dc.subjectflood forecasten_US
dc.subjectpeak flowen_US
dc.subjectvisualizationen_US
dc.titleDevelopment of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoonsen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/su12104258en_US
dc.identifier.journalSUSTAINABILITYen_US
dc.citation.volume12en_US
dc.citation.issue10en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.identifier.wosnumberWOS:000543421400316en_US
dc.citation.woscount0en_US
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