scholarly journals Application of the WRF model rainfall product for the localized flood hazard modeling in a data-scarce environment

2022 ◽  
Author(s):  
Y. Umer ◽  
V. Jetten ◽  
J. Ettema ◽  
L. Lombardo

AbstractUrban flood hazard model needs rainfall with high spatial and temporal resolutions for flood hazard analysis to better simulate flood dynamics in complex urban environments. However, in many developing countries, such high-quality data are scarce. Data that exist are also spatially biased toward airports and urban areas in general, where these locations may not represent flood-prone areas. One way to gain insight into the rainfall data and its spatial patterns is through numerical weather prediction models. As their performance improves, these might serve as alternative rainfall data sources for producing optimal design storms required for flood hazard modeling in data-scarce areas. To gain such insight, we developed Weather Research and Forecasting (WRF) design storms based on the spatial distribution of high-intensity rainfall events simulated at high spatial and temporal resolutions. Firstly, three known storm events (i.e., 25 June 2012, 13 April 2016, and 16 April 2016) that caused the flood hazard in the study area are simulated using the WRF model. Secondly, the potential gridcell events that are able to trigger the localized flood hazard in the catchment are selected and translated to the WRF design storm form using a quantile expression. Finally, three different WRF design storms per event are constructed: Lower, median, and upper quantiles. The results are compared with the design storms of 2- and 10-year return periods constructed based on the alternating-block method to evaluate differences from a flood hazard assessment point of view. The method is tested in the case of Kampala city, Uganda. The comparison of the design storms indicates that the WRF model design storms properties are in good agreement with the alternating-block design storms. Mainly, the differences between the produced flood characteristics (e.g., hydrographs and the number of flood gird cells) when using WRF lower quantiles (WRFLs) versus 2-year and WRF upper quantiles (WRFUs) versus 10-year alternating-block storms are very minimal. The calculated aggregated performance statistics (F scores) for the simulated flood extent of WRF design storms benchmarked with the alternating-block storms also produced a higher score of 0.9 for both WRF lower quantiles versus 2-year and WRF upper quantile versus 10-year alternating-block storm. The result suggested that the WRF design storms can be considered an added value for flood hazard assessment as they are closer to real systems causing rainfall. However, more research is needed on which area can be considered as a representative area in the catchment. The result has practical application for flood risk assessment, which is the core of integrated flood management.

2021 ◽  
Author(s):  
Yakob M Umer ◽  
Victor G Jetten ◽  
Janneke Ettema ◽  
Luigi Lombardo

Abstract Urban flood hazard model needs rainfall with high spatial and temporal resolutions for flood hazard analysis to accurately simulate flood dynamics in complex urban environments. However, in many developing countries, such high-quality data is scarce. Data that exist are also spatially biased towards airports and urban areas in general, where these locations may not represent flood-prone areas. One way to gain insight into the rainfall data and its spatial patterns is through numerical weather prediction models. As their performance improves, these might serve as alternative rainfall data sources for producing optimal design storms required for flood hazard modelling in data-scarce areas. To gain such insight, we developed WRF design storms based on the spatial distribution of high-intensity rainfall events simulated at high spatial and temporal resolutions. Firstly, three known events (i.e., 25 June 2012, 13 April 2016, and 16 April 2016) that caused the flood hazard in the study area are simulated using the WRF model. Secondly, the potential gridcell-events that are able to trigger the localized flood hazard in the catchment are selected and translated to the WRF design storm form using a quantile expression. Finally, three different WRF design storms per event are constructed: Lower, median, and upper quantiles. The results are compared with the design storms of 2 and 10-year return periods constructed based on the alternating-block method to evaluate differences from a flood hazard assessment point of view. The method is tested in the case of Kampala city, Uganda. The comparison of the design storms indicates that WRF design storms properties are in good agreement with the alternating block design storms. Mainly, the differences between the produced flood characteristics (e.g., hydrographs and the number of flood gird cells) when using WRFLs versus 2-year and WRFUs versus 10-year alternating block storms are very minimal. The calculated aggregated performance statistics (F scores) for the simulated flood extent of WRF design storms benchmarked with the alternating block storms also produced a higher score of 0.9 for both WRF lower quantiles versus 2-year and WRF upper quantile versus 10-year alternating block storm. The result suggested that the WRF design storms can be considered an added value for flood hazard assessment as they are closer to real systems causing rainfall. However, more research is needed on which area can be considered as a representative area in the catchment.


2021 ◽  
Vol 193 (4) ◽  
Author(s):  
Guido Borzi ◽  
Alejandro Roig ◽  
Carolina Tanjal ◽  
Lucía Santucci ◽  
Macarena Tejada Tejada ◽  
...  

2021 ◽  
Vol 656 (1) ◽  
pp. 012010
Author(s):  
M Zeleňáková ◽  
M Šugareková ◽  
P Purcz ◽  
S Gałaś ◽  
M M Portela ◽  
...  

2019 ◽  
Author(s):  
Attilio Castellarin ◽  
Caterina Samela ◽  
Simone Persiano ◽  
Stefano Bagli ◽  
Valerio Luzzi ◽  
...  

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 873
Author(s):  
Yakob Umer ◽  
Janneke Ettema ◽  
Victor Jetten ◽  
Gert-Jan Steeneveld ◽  
Reinder Ronda

Simulating high-intensity rainfall events that trigger local floods using a Numerical Weather Prediction model is challenging as rain-bearing systems are highly complex and localized. In this study, we analyze the performance of the Weather Research and Forecasting (WRF) model’s capability in simulating a high-intensity rainfall event using a variety of parameterization combinations over the Kampala catchment, Uganda. The study uses the high-intensity rainfall event that caused the local flood hazard on 25 June 2012 as a case study. The model capability to simulate the high-intensity rainfall event is performed for 24 simulations with a different combination of eight microphysics (MP), four cumulus (CP), and three planetary boundary layer (PBL) schemes. The model results are evaluated in terms of the total 24-h rainfall amount and its temporal and spatial distributions over the Kampala catchment using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis. Rainfall observations from two gauging stations and the CHIRPS satellite product served as benchmark. Based on the TOPSIS analysis, we find that the most successful combination consists of complex microphysics such as the Morrison 2-moment scheme combined with Grell-Freitas (GF) and ACM2 PBL with a good TOPSIS score. However, the WRF performance to simulate a high-intensity rainfall event that has triggered the local flood in parts of the catchment seems weak (i.e., 0.5, where the ideal score is 1). Although there is high spatial variability of the event with the high-intensity rainfall event triggering the localized floods simulated only in a few pockets of the catchment, it is remarkable to see that WRF is capable of producing this kind of event in the neighborhood of Kampala. This study confirms that the capability of the WRF model in producing high-intensity tropical rain events depends on the proper choice of parametrization combinations.


2017 ◽  
Vol 114 (37) ◽  
pp. 9785-9790 ◽  
Author(s):  
Hamed R. Moftakhari ◽  
Gianfausto Salvadori ◽  
Amir AghaKouchak ◽  
Brett F. Sanders ◽  
Richard A. Matthew

Sea level rise (SLR), a well-documented and urgent aspect of anthropogenic global warming, threatens population and assets located in low-lying coastal regions all around the world. Common flood hazard assessment practices typically account for one driver at a time (e.g., either fluvial flooding only or ocean flooding only), whereas coastal cities vulnerable to SLR are at risk for flooding from multiple drivers (e.g., extreme coastal high tide, storm surge, and river flow). Here, we propose a bivariate flood hazard assessment approach that accounts for compound flooding from river flow and coastal water level, and we show that a univariate approach may not appropriately characterize the flood hazard if there are compounding effects. Using copulas and bivariate dependence analysis, we also quantify the increases in failure probabilities for 2030 and 2050 caused by SLR under representative concentration pathways 4.5 and 8.5. Additionally, the increase in failure probability is shown to be strongly affected by compounding effects. The proposed failure probability method offers an innovative tool for assessing compounding flood hazards in a warming climate.


2020 ◽  
Author(s):  
Michelle Bensi ◽  
Somayeh Mohammadi ◽  
Shih-Chieh Kao ◽  
Scott T. DeNeale

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