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Preprints
https://doi.org/10.5194/nhess-2020-119
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-119
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 12 May 2020

Submitted as: research article | 12 May 2020

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This preprint is currently under review for the journal NHESS.

Challenges in flood modelling over data scarce regions: how to exploit globally available soil moisture products to estimate antecedent soil wetness conditions in Morocco

El Mahdi El Khalki1, Yves Tramblay2, Christian Massari3, Luca Brocca3, and Mohamed El Mehdi Saidi1 El Mahdi El Khalki et al.
  • 1Geosciences and Environment Laboratory, Cadi Ayyad University, Marrakesh, 40000, Morocco
  • 2HydroSciences Montpellier (Univ. Montpellier, CNRS, IRD), Montpellier, 34000, France
  • 3Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, 06100, Italy

Abstract. The Mediterranean region is characterized by intense rainfall events giving rise to devastating floods. In Maghreb countries such as Morocco, there is a strong need for forecasting systems to reduce the impacts of floods. The development of such a system in the case of ungauged catchments is complicated but remote sensing products could overcome the lack of in-situ measurements. The soil moisture content can strongly modulate the magnitude of flood events and consequently is a crucial parameter to take into account for flood modeling. In this study, different soil moisture products (ESA-CCI, SMOS, SMOS-IC, ASCAT satellite products and ERA5 reanalysis) are compared to in-situ measurements and one continuous soil moisture accounting (SMA) model for basins located in the High-Atlas Mountains, upstream of the city of Marrakech. The results show that the SMOS-IC satellite product and the ERA5 reanalysis are best correlated with observed soil moisture and with the SMA model outputs. The different soil moisture datasets were also compared to estimate the initial soil moisture condition for an event-based hydrological model based on the Soil Conservation Service Curve Number (SCS-CN). The ASCAT, SMOS-IC and ERA5 products performed equally well in validation to simulate floods, outperforming daily in situ soil moisture measurements that may not be representative of the whole catchment soil moisture conditions. The results also indicated that the daily time step may not fully represent the saturation state before a flood event, due to the rapid decay of soil moisture after rainfall in these semi-arid environments. Indeed, at the hourly time step, ERA5 and in-situ measurements were found to better represent the initial soil moisture conditions of the SCS-CN model by comparison with the daily time step. The results of this work could be used to implement efficient flood modelling and forecasting systems in semi-arid regions where soil moisture measurements are lacking.

El Mahdi El Khalki et al.

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Short summary
In North Africa, the vulnerability to floods is high and there is a need to improve the flood forecasting systems. Remote sensing and reanalysis data can palliate the lack of in-situ measurements, in particular for soil moisture that is a crucial parameter to consider when modelling floods. In this study we provide an evaluation of recent globally available soil moisture products for flood modelling in Morocco.
In North Africa, the vulnerability to floods is high and there is a need to improve the flood...
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