Data underlying the publication: Integrating WRF forecasts at different scales for pluvial flood forecasting using a rainfall threshold approach and a real-time flood model
DOI: 10.4121/a98b55f5-548c-4f0f-ae29-da1552774b5f
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Dataset
Regional Numerical Weather Prediction (NWP) models increase the resolution and extend forecasts by several days when initialised with global models. These models produce forecasts at higher spatial and temporal resolutions but are computationally demanding and do not necessarily result in more accurate forecasts especially in data-scarce cities. This research evaluated how rainfall forecasting model scale dependencies satisfy high-resolution hazard forecasting requirements with two different flood forecasting approaches. Rainfall forecasts of different spatial resolutions, cumulus schemes and lead times from a high-resolution Weather Research and Forecasting (WRF) model were first evaluated and then used as input in a rainfall threshold and 1D MIKE urban drainage model for flood forecasting in the data-scarce city of Alexandria City, Egypt. This dataset includes the output of the downscaled Global Forecasting System which is freely accessible online, WRF preprocessing files and WRF namelist files used to configure the WRF model and the output files of the WRF model for three events: Oct 2015, Dec 2018 and Nov 2020. The WRF model is freely available open source software which be downloaded from the developer's official repository https://github.com/wrf-model
History
- 2025-11-07 first online, published, posted
Publisher
4TU.ResearchDataFormat
netcdf/.nc, Unix shell script/.shAssociated peer-reviewed publication
Integrating WRF forecasts at different scales for pluvial flood forecasting using a rainfall threshold approach and a real-time flood modelDerived from
Funding
- This work used the Dutch national e-infrastructure with the support of the SURF Cooperative (grant code EINF-3489.) Dutch Research Council (NWO)
Organizations
TU Delft, Faculty of Civil Engineering and Geosciences, Department of Hydraulic EngineeringIHE Delft Institute for Water Education, Department of Coastal and Urban Risk Resilience
DATA
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