Abstract
Flash floods are common in small Mediterranean watersheds and the alerts provided by real-time monitoring systems provide too short anticipation times to warn the population. In this context, there is a strong need to develop flood forecasting systems in particular for developing countries such as Morocco where floods have severe socio-economic impacts. In this study, the AROME (Application of Research to Operations at Mesoscale), ALADIN (Aire Limited Dynamic Adaptation International Development) and WRF (Weather Research and Forecasting) meteorological models are evaluated to forecast flood events in the Rheraya and Ourika basin located in the High-Atlas Mountains of Morocco. The model evaluation is performed by comparing for a set of flood events the observed and simulated probabilities of exceedances for different precipitation thresholds. In addition, two different flood forecasting approaches are compared: the first one relies on the coupling of meteorological forecasts with a hydrological model and the second one is a based on a linear relationship between event rainfall, antecedent soil moisture and runoff. Three different soil moisture products (in-situ measurements, European Space Agency’s Climate Change Initiative ESA-CCI remote sensing data and ERA5 reanalysis) are compared to estimate the initial soil moisture conditions before flood events for both methods. Results showed that the WRF and AROME models better simulate precipitation amounts compared to ALADIN, indicating the added value of convection-permitting models. The regression-based flood forecasting method outperforms the hydrological model-based approach, and the maximum discharge is better reproduced when using the WRF forecasts in combination with ERA5. These results provide insights to implement robust flood forecasting approaches in the context of data scarcity that could be valuable for developing countries such as Morocco and other North African countries.
Highlights
Flash floods mainly affect small watersheds where the response time to a rainfall event is very short, from a few minutes to a few hours [1,2,3]
The WRF and AROME models overestimate the cumulative precipitation over the Rheraya with an average of +113% and +62.5% respectively
In the Ourika, the WRF model shows an underestimation of −2.6% and an overestimation using the AROME model of +24%
Summary
Flash floods mainly affect small watersheds where the response time to a rainfall event is very short, from a few minutes to a few hours [1,2,3]. Water 2020, 12, 437 small- to medium-sized basins before flash floods are very short, as well as it is the time available to alert and warn the population of their impacts. These short flash-flood response times become especially challenging for civil protection authorities so as to issue dependable alerts and warning to the population [6]. The development of flood forecasting systems increases the lead time and preparedness to potentially high-impact flood events [7,8]. Any increase in lead time by using quantitative precipitation forecasts (QPFs) is important to reduce the impacts of flood events
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