Day 4

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Paper title Exploitation of satellite soil surface moisture data (ESA-CCI) for modelling rainfall-runoff in semi-arid catchment (High Atlas of Morocco).
  1. Myriam Benkirane Cadi Ayyad Universty Speaker
  2. Nour-Eddine Laftouhi GeoSciences Laboratory, Geology Department, Faculty of Sciences Semlalia, Cadi Ayyad University
  3. Saïd Khabba LMFE, Faculté des Sciences Semlalia, Université Cadi Ayyad, 40000 Marrakech, Maroc. / Center for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University (UM6P), 43150 Benguerir, Morocco.
Form of presentation Poster
  • A7. Hydrology and Water Cycle
    • A7.01 Inland Water Storage and Runoff: Modeling, In Situ Data and Remote Sensing
Abstract text The Mediterranean regions are characterized by intense rainfall events strongly affected by violent rainfall events causing floods. The vulnerability to flooding in the Moroccan High Atlas, especially in the Tensift basin, has been increasing over the last decades. Rainfall-runoff models can be very useful for flash flood forecasting. However, event-based models require a reduction of their uncertainties related to the estimation of initial moisture conditions before a flood event. Soil moisture may strongly modulate the magnitude of floods and is thus a critical parameter to be considered in flood modeling.
The aim of this study is to compare daily soil moisture measurements obtained by time domain reflectometry (TDR) at Sidi Rahal station with satellite soil moisture products (European Space Agency Climate Change Initiative, ESA-CCI), in order to estimate the initial soil moisture conditions for each event. A modeling approach based on rainfall-runoff observations of 30 sample flood events from (2011 to 2018), in the Ghdat basin, were extracted and modeled by an event-based rainfall-runoff model (HEC-HMS) which is based on the Soil Conservation Service (SCS-CN), loss model, and a Clark unit hydrograph was developed for simulation and calibration of the 10-minute rainfall runoff.
These data were used in the validation process of the event modeling part and indicate that soil moisture could help to improve the initial conditions of event-based models in small basins to improve the quality of flood forecasting. The rationale is that a better representation of the catchment states leads to a better streamflow estimation. By exploiting the strong physical connection between the soil moisture dynamic and rainfall, this methodology is very satisfactory for reproducing rainfall-runoff events in this small Mediterranean mountainous watershed, since Nash coefficients of validation are ranging from (0.76 to 0.89), the same approach could be implemented in other watersheds in this region. The results of this study indicate that the remote sensing data are theoretically useful for estimating soil moisture conditions in data-sparse watersheds in arid Mediterranean regions.
Keywords: Soil moisture; Floods; Remote sensing; Hydrological modeling, CN method, Mediterranean basin.