Abstract
The ever-increasing availability of new remote sensing and land surface model datasets opens new opportunities for hydrologists to improve flood forecasting systems. The current study investigates the performance of two operational soil moisture (SM) products provided by the “EUMETSATSatellite Application Facility in Support of Operational Hydrology and Water Management” (H-SAF, http://hsaf.meteoam.it/) within a recently-developed hydrological model called the “simplified continuous rainfall-runoff model” (SCRRM) and the possibility of using such a model at an operational level. The model uses SM datasets derived from external sources (i.e., remote sensing and land surface models) as input for calculating the initial wetness conditions of the catchment prior to the flood event. Hydro-meteorological data from 35 Italian catchments ranging from 800 to 7400 km2 were used for the analysis for a total of 593 flood events. The results show that H-SAF operational products used within SCRRM satisfactorily reproduce the selected flood events, providing a median Nash–Sutcliffe efficiency index equal to 0.64 (SM-OBS-1) and 0.60 (SM-DAS-2), respectively. Given the results obtained along with the parsimony, the simplicity and independence of the model from continuously-recorded rainfall and evapotranspiration data, the study suggests that: (i) SM-OBS-1 and SM-DAS-2 contain useful information for flood modelling, which can be exploited in flood forecasting; and (ii) SCRRM is expected to be beneficial as a component of real-time flood forecasting systems in regions characterized by low data availability, where a continuous modelling approach can be problematic.
Highlights
Flooding has become one of the events producing the most fatalities annually [1]
We show the performances obtained by simplified continuous rainfall-runoff model” (SCRRM) using soil moisture (SM)-OBS-1 and SM-DAS-2 compared with the results obtained by MISDc
A simplified continuous rainfall-runoff model using SM from external sources for initialization has been used for testing the performance of two operational products (SM-OBS-1 and SM-DAS-2) of the “EUMETSAT Satellite Application Facility in Support of Operational Hydrology and
Summary
Flooding has become one of the events producing the most fatalities annually [1]. Whereas much progress has been made in meteo-forecasts and warnings and in public preparedness, a comparable system for “quantitatively” predicting floods has experienced less progress, especially in floods occurring in medium–small catchment sizes (100–1000 km2 ), as demonstrated by recent events occurring in Italy (i.e., Liguria, Tuscany and Sicily at the end of 2011, Umbria in 2012 and Sardinia in 2014).the anticipation of the magnitude of an event is crucial for performing the correct actions within civil protection activities, but this is not a simple task. Flooding has become one of the events producing the most fatalities annually [1]. The amount of precipitation that transforms an otherwise ordinary rainfall event into an extraordinary one is led by complex interactions between meteorology and hydrology, such as, among other important factors, the soil moisture (SM). Conditions prior to the flood event [2,3,4,5]. Predicting a flood event is a matter of being able to correctly describe such factors, but it is strongly related to the capability of the early warning system in terms of the data and tools upon which it can rely. That is: (i) an appropriate rainfall-runoff (RR) hydrological model able to infer, with a certain degree of accuracy, the discharge hydrograph; and (ii) a dense network of sensors able to provide good quality observations in near real time
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