دورية أكاديمية

High-Resolution Urban Flood Forecasting by Using a Coupled Atmospheric and Hydrodynamic Flood Models

التفاصيل البيبلوغرافية
العنوان: High-Resolution Urban Flood Forecasting by Using a Coupled Atmospheric and Hydrodynamic Flood Models
المؤلفون: Guangzhao Chen, Jingming Hou, Nie Zhou, Shaoxiong Yang, Yu Tong, Feng Su, Lei Huang, Xu Bi
المصدر: Frontiers in Earth Science, Vol 8 (2020)
بيانات النشر: Frontiers Media S.A., 2020.
سنة النشر: 2020
المجموعة: LCC:Science
مصطلحات موضوعية: urban flood forecasting, hydrodynamic model, atmospheric model, inundation, graphic processing unit high-performance computation, Science
الوصف: Flood forecasting is one of the most significant tools for reducing flood risk and avoiding the loss of life To solve the problem of low resolution and the short lead time of the traditional urban flood forecasting method, this work develops a novel high-accuracy and long lead time model through coupling the atmospheric and hydrodynamic models. The GRAPE_MESO model is applied as an atmospheric model for predicting rainstorms. To improve reliability, a reconstructed method is put forward to correct predicted rainstorm data. The reconstructed predicted rainstorm is then used as input data for the hydrodynamic flood model. Finally, the urban flood inundation process was forecasted by the coupled atmospheric and flood model. Though applying the coupled model at Fengxi New Town (China), the performance is evaluated for realistic urban flood forecasting. The results show that the coupled modeling system can predict the urban flood inundation process with high-resolution and a long lead time.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2296-6463
Relation: https://www.frontiersin.org/articles/10.3389/feart.2020.545612/full; https://doaj.org/toc/2296-6463
DOI: 10.3389/feart.2020.545612
URL الوصول: https://doaj.org/article/25d021afb2b04a10905a094584cc4230
رقم الأكسشن: edsdoj.25d021afb2b04a10905a094584cc4230
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:22966463
DOI:10.3389/feart.2020.545612