EGU22-3905
https://doi.org/10.5194/egusphere-egu22-3905
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Selection of flash flood models in data-scarce regions like Jordan 

Clara Hohmann1, Christina Maus1, Dörte Ziegler1, Sameh Kantoush2, and Qasem Abdelal3
Clara Hohmann et al.
  • 1Civil Engineering, Koblenz University of Applied Sciences, Koblenz, Germany (hohmann@hs-koblenz.de)
  • 2Water Resources Research Center - Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan
  • 3Civil and Environmental Engineering, German Jordanian University, Amman, Jordan

Severe flash floods have hit Jordan in recent years, e.g., in 2018 and 2020, leading to fatalities and infrastructure damages. Moreover, even though Jordan is one of the water scarcest countries of the world, extreme rainfall events might occur more frequently under climate change (IPCC Sixth Assessment Report 2021), causing flash floods in wadi systems. Also, the population growth combined with construction and sealing in cities increases the risk of damages, and authorities are under pressure to provide solutions for disaster risk reduction. Few flash flood models have been adopted and developed for wadi systems. Here the scientific community might help by providing tools to understand better, assess, and predict such events to introduce possible adaptation strategies.

The BMBF funded German-Jordanian project “CapTain Rain” studies flash flood risks with a transdisciplinary approach, interacting with local stakeholders. Jordan receives annual precipitation of around 110 mm overall, and hydrological data is not abundant, discontinuous, and of differing quality. Hence, flash flood modelling approaches and available software for humid regions from northern hemisphere industrialized countries cannot be easily transferred. Therefore, we want to review the variety of model options for flash flood modelling in arid and humid areas and give an overview of the selection process.

The model selection is often based on different aspects like application of interest, data requirements and availability, model complexity, code availability and open-source option, user knowledge, and modeling group experience. On the one hand, Beven and Young (2013) strengthen that model selection should not be more complex as necessary and fit-for-purpose. On the other hand, Addor and Melsen (2019) saw a strong social component. They mention the hydrological model selection is stronger influenced by legacy aspects instead of adequacy aspects. Horton et al. (2021) reviewed the hydrological model application for Switzerland. They discuss that not all aspects of model selection are mentioned in the published articles, mainly social elements. In addition, their author survey shows that modeling group experience plays a crucial factor in model selection, and most models used have a strong basis in the country.

By focusing on Jordan or other dry and data-scarce regions worldwide, other aspects need to be considered. For example, modelling knowledge of users might be limited, validation and calibration data are scarce, and financial resources for software are restricted. Therefore, we see an urgent need to analyze the aspects of model selection for flash floods in Wadi systems in a scientific context and to give the stakeholders a fact-based overview about possible model options.  

 

Literature:

Addor, N.; Melsen, L.A. (2019): Legacy, Rather Than Adequacy, Drives the Selection of Hydrological Models. WRR. 55, 378–390

Beven, K.; Young, P. (2013): A guide to good practice in modeling semantics for authors and referees. WRR. 49, 5092–5098

Horton, P; Schaefli, B.; Kauzlaric, M. (2021): Why do we have so many different hydrological models? A review based on the case of Switzerland. Wiley Interdiscip.Rev.-Water, e1574

How to cite: Hohmann, C., Maus, C., Ziegler, D., Kantoush, S., and Abdelal, Q.: Selection of flash flood models in data-scarce regions like Jordan , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3905, https://doi.org/10.5194/egusphere-egu22-3905, 2022.

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