Flood4castRTF: A Real-Time Urban Flood Forecasting Model
Worldwide, climate change increases the frequency and intensity of heavy rainstorms. The increasing severity of consequent floods has major socio-economic impacts, especially in urban environments. Urban flood modelling supports the assessment of these impacts, both in current climate conditions and...
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doaj-cb39464210a74e888bdd3344731e02ba2021-06-01T00:22:56ZengMDPI AGSustainability2071-10502021-05-01135651565110.3390/su13105651Flood4castRTF: A Real-Time Urban Flood Forecasting ModelMichel Craninx0Koen Hilgersom1Jef Dams2Guido Vaes3Thomas Danckaert4Jan Bronders5Environmental Modelling Unit, Flemish Institute for Technological Research (VITO), 2400 Mol, BelgiumHydroscan NV, 3010 Leuven, BelgiumEnvironmental Modelling Unit, Flemish Institute for Technological Research (VITO), 2400 Mol, BelgiumHydroscan NV, 3010 Leuven, BelgiumEnvironmental Modelling Unit, Flemish Institute for Technological Research (VITO), 2400 Mol, BelgiumEnvironmental Modelling Unit, Flemish Institute for Technological Research (VITO), 2400 Mol, BelgiumWorldwide, climate change increases the frequency and intensity of heavy rainstorms. The increasing severity of consequent floods has major socio-economic impacts, especially in urban environments. Urban flood modelling supports the assessment of these impacts, both in current climate conditions and for forecasted climate change scenarios. Over the past decade, model frameworks that allow flood modelling in real-time have been gaining widespread popularity. Flood4castRTF is a novel urban flood model that applies a grid-based approach at a modelling scale coarser than most recent detailed physically based models. Automatic model set-up based on commonly available GIS data facilitates quick model building in contrast with detailed physically based models. The coarser grid scale applied in Flood4castRTF pursues a better agreement with the resolution of the forcing rainfall data and allows speeding up of the calculations. The modelling approach conceptualises cell-to-cell interactions while at the same time maintaining relevant and interpretable physical descriptions of flow drivers and resistances. A case study comparison of Flood4castRTF results with flood results from two detailed models shows that detailed models do not necessarily outperform the accuracy of Flood4castRTF with flooded areas in-between the two detailed models. A successful model application for a high climate change scenario is demonstrated. The reduced data need, consisting mainly of widely available data, makes the presented modelling approach applicable in data scarce regions with no terrain inventories. Moreover, the method is cost effective for applications which do not require detailed physically based modelling.https://www.mdpi.com/2071-1050/13/10/5651flood modellingurban floodingclimate changefast model set-upgrid modellingdata scarcity |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Michel Craninx Koen Hilgersom Jef Dams Guido Vaes Thomas Danckaert Jan Bronders |
spellingShingle |
Michel Craninx Koen Hilgersom Jef Dams Guido Vaes Thomas Danckaert Jan Bronders Flood4castRTF: A Real-Time Urban Flood Forecasting Model Sustainability flood modelling urban flooding climate change fast model set-up grid modelling data scarcity |
author_facet |
Michel Craninx Koen Hilgersom Jef Dams Guido Vaes Thomas Danckaert Jan Bronders |
author_sort |
Michel Craninx |
title |
Flood4castRTF: A Real-Time Urban Flood Forecasting Model |
title_short |
Flood4castRTF: A Real-Time Urban Flood Forecasting Model |
title_full |
Flood4castRTF: A Real-Time Urban Flood Forecasting Model |
title_fullStr |
Flood4castRTF: A Real-Time Urban Flood Forecasting Model |
title_full_unstemmed |
Flood4castRTF: A Real-Time Urban Flood Forecasting Model |
title_sort |
flood4castrtf: a real-time urban flood forecasting model |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2021-05-01 |
description |
Worldwide, climate change increases the frequency and intensity of heavy rainstorms. The increasing severity of consequent floods has major socio-economic impacts, especially in urban environments. Urban flood modelling supports the assessment of these impacts, both in current climate conditions and for forecasted climate change scenarios. Over the past decade, model frameworks that allow flood modelling in real-time have been gaining widespread popularity. Flood4castRTF is a novel urban flood model that applies a grid-based approach at a modelling scale coarser than most recent detailed physically based models. Automatic model set-up based on commonly available GIS data facilitates quick model building in contrast with detailed physically based models. The coarser grid scale applied in Flood4castRTF pursues a better agreement with the resolution of the forcing rainfall data and allows speeding up of the calculations. The modelling approach conceptualises cell-to-cell interactions while at the same time maintaining relevant and interpretable physical descriptions of flow drivers and resistances. A case study comparison of Flood4castRTF results with flood results from two detailed models shows that detailed models do not necessarily outperform the accuracy of Flood4castRTF with flooded areas in-between the two detailed models. A successful model application for a high climate change scenario is demonstrated. The reduced data need, consisting mainly of widely available data, makes the presented modelling approach applicable in data scarce regions with no terrain inventories. Moreover, the method is cost effective for applications which do not require detailed physically based modelling. |
topic |
flood modelling urban flooding climate change fast model set-up grid modelling data scarcity |
url |
https://www.mdpi.com/2071-1050/13/10/5651 |
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