Abstract
Abstract. A framework for a comprehensive synthetic rainfall-runoff database was developed to study catchment response to a variety of rainfall events. The framework supports effective flood risk assessment and management and implements simple approaches. It consists of three flexible components, a rainfall generator, a continuous rainfall-runoff model, and a database management system. The system was developed and tested at two gauged river sections along the upper Tiber River (central Italy). One of the main questions was to investigate how simple such approaches can be applied without impairing the quality of the results. The rainfall-runoff model was used to simulate runoff on the basis of a large number of rainfall events. The resulting rainfall-runoff database stores pre-simulated events classified on the basis of the rainfall amount, initial wetness conditions and initial discharge. The real-time operational forecasts follow an analogue method that does not need new model simulations. However, the forecasts are based on the simulation results available in the rainfall-runoff database (for the specific class to which the forecast belongs). Therefore, the database can be used as an effective tool to assess possible streamflow scenarios assuming different rainfall volumes for the following days. The application to the study site shows that magnitudes of real flood events were appropriately captured by the database. Further work should be dedicated to introduce a component for taking account of the actual temporal distribution of rainfall events into the stochastic rainfall generator and to the use of different rainfall-runoff models to enhance the usability of the proposed procedure.
Highlights
The increasing number and intensity of floods and flash flood events has caused environmental problems, taking a high human and economic toll (Smith and Ward, 1998; Villarini et al, 2010)
This paper proposes a comprehensive rainfall-runoff database (RR-DB) to be used as an integrated tool of an FFS which takes the discharge forecast uncertainty into account
The operational system of the RR-DB consists of three main model components: (1) a weather generator, (2) a continuous rainfall-runoff model, and (3) a relational database management system (RDBMS) used to store and manage simulation data
Summary
The increasing number and intensity of floods and flash flood events has caused environmental problems, taking a high human and economic toll (Smith and Ward, 1998; Villarini et al, 2010). With the growing evidence of flooding, decision makers need to take actions for addressing the disaster risk management through a reliable flood forecasting system (FFS hereafter) to respond to weather-induced catastrophic events In this context, it should be aimed at a right equilibrium between the need to achieve an accurate forecast and to develop a correct analysis of the rainfall spatial distribution, runoff formation and flood routing. Quantifying uncertainty within the flood forecasting would enable the authorities to set riskbased criteria for flood warning, furnish information for making rational decisions and offer potential for additional economic benefits of forecasts to every rational decision maker (Krzysztofowicz, 2001) In this context, this paper proposes a comprehensive rainfall-runoff database (RR-DB) to be used as an integrated tool of an FFS which takes the discharge forecast uncertainty into account.
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