In a semi-arid area, how can global soil moisture products be used to estimate the antecedent soil moisture conditions for flood modeling?

Devastating floods in the Mediterranean region are caused by heavy rains. Flood forecasting systems are critically needed in Maghreb countries like Morocco to reduce their consequences. It is difficult to design such a system for ungauged areas. Even if there is a shortage of observable data, remote sensing products might compensate for this Soil moisture content may have a substantial impact on flood event magnitude and is therefore an essential part of flood modeling. ESA-CCI, SMOS, SMOS-IC, ASCAT and the ERA5 reanalysis are compared against in situ data and one continuous soil-moisture-accounting in this work. SMA model outputs and observed soil moisture are strongly linked to the SMOS-IC satellite product and the ERA5 reanalysis. For an event-based hydrological model, comparing soil moisture records permitted the calculation of the starting soil moisture status using the Soil Conservation Service Curve Number (SCS-CN). It is possible that daily in-situ soil moisture data may not be a true representation of catchment soil moisture conditions; yet, the ASCAT, SMOS-IC, and ERA5 products performed similarly well in validation to model floods. The daily time step may not accurately represent the saturation status just before a flood since soil moisture in these semi-arid locations is depleted more quickly following precipitation. For the hourly time step, the SCS-CN model's initial soil moisture conditions were shown to be more accurately represented by ERA5 and in situ data. Soil moisture data in semi-arid areas might be used to build effective flood forecasting and modeling systems.