| Autor: |
Yihong Zhou, Zening Wu, Hongshi Xu, Huiliang Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Journal of Hydrology: Regional Studies, Vol 44, Iss , Pp 101248- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2214-5818 |
| DOI: |
10.1016/j.ejrh.2022.101248 |
| Popis: |
Study region: Built-up area of Zhengzhou, China. Study focus: An urban flood forecasting model based on multi-model integrated forecasting is proposed. Based on the data of rainfall process and inundation process, a multi-model ensemble prediction model was established for 27 typical waterlogging points in Zhengzhou by using BMA (Bayesian Model Average) coupling different data-driven methods. Combined with the rainfall forecast data, the BMA was driven to predict and warn the inundation process of urban flood. New hydrological insights for the region: Using the BMA to predict urban flood can improve the accuracy and stability of using single model to predict urban flood. The results indicate that the prediction accuracy of BMA model is 36–46% higher than that of single model, which demonstrate that BMA makes effective use of the advantages of each model and can provide higher accuracy in prediction and early warning. Additionally, BMA significantly reduces the uncertainty of single model prediction in the prediction of inundation process. The analysis of early warning in two different urban flood events indicates that BMA is more suitable for the prediction of severe waterlogging and illustrates the great potential and prospects of BMA in urban flood early warning. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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