Using globally available soil moisture indicators for flood modelling in Mediterranean catchments

Abstract

Abstract. Floods are one of the most dangerous natural hazards in Mediterranean regions. Flood forecasting tools and early warning systems can be very beneficial to reduce flood risk. Event-based rainfall runoff models are frequently employed for operational flood forecasting purposes because of their simplicity and the reduced number of parameters involved with respect to continuous models. However, the advantages that are related with the reduced parameterization face against the need for a correct initialization of the model, especially in areas affected by strong climate seasonality. On the other hand, the use of continuous models may be very problematic in poorly gauged areas. This paper introduces a simplified continuous rainfall-runoff model, which uses globally available soil moisture retrievals to identify the initial wetness condition of the catchment, and, only event rainfall data to simulate discharge hydrographs. The model calibration involves only 3 parameters. For soil moisture, beside in situ and modelled data, satellite products from the Advanced SCATterometer (ASCAT) and the Advanced Microwave Scanning Radiometer for Earth observation (AMSR-E) sensors are employed. Additionally, the ERA-LAND reanalysis soil moisture product of the European Centre for Medium Range Weather Forecasting (ECMWF) is used. The model was tested in the small catchment of Rafina, 109 km2 located in the Eastern Attica region, Greece. Specifically, fifteen rainfall-runoff events were modelled by considering different configurations for the initial soil moisture conditions. Comparing the performance of the different soil moisture products, it was found that all global indicators allow reproducing fairly well the selected flood events providing much better results than the situation where a constant initial condition is provided. ERA-LAND slightly outperforms the satellite soil moisture products and in general, all the indicators give the same performance obtained by ground and continuously simulated soil moisture data. Due to the wide diffusion of globally available soil moisture retrievals and the small amount of parameters used, the proposed modelling approach is very suitable for runoff prediction in poorly gauged areas.