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 reducing 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 related to the reduced parameterization oppose to the need of a correct initialization of the model, especially in areas characterized by strong climate seasonality. In this case, the use of continuous models could be desirable but it is very problematic in poorly gauged areas where continuous rainfall and temperature data are not available. This paper introduces a Simplified Continuous Rainfall-Runoff model (SCRRM), 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 three parameters. For soil moisture, besides in situ data, satellite products from the Advanced SCATterometer (ASCAT) and the Advanced Microwave Scanning Radiometer for Earth observation (AMSR-E) sensors were employed. Additionally, the ERA-Land reanalysis soil moisture product of the European Centre for Medium-Range Weather Forecasting (ECMWF) was used.SCRRM was tested in the small catchment of the Rafina River, 109 km 2 , located in the eastern Attica region, Greece. Specifically, sixteen recorded rainfall-runoff events were simulated by considering the different indicators for the estimation of the initial soil moisture conditions from in situ, satellite and reanalysis data. By comparing the performance of the different soil moisture products, we conclude that: (i) all global indicators allow for a fairly good reproduction of the selected flood events, providing much better results than those obtained from setting constant initial conditions; (ii) the use of all the indicators yields similar results when compared with a standard continuous simulation approach that, however, is more data demanding; (iii) SCRRM is robust since it shows good performances in validation for a significant flood event that occurred on February 2013 (after calibrating the model for small to medium flood events). Due to the wide diffusion of globally available soil moisture retrievals and the limited number of parameters used, the proposed modelling approach is very suitable for runoff prediction in poorly gauged areas.
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
A web-based Decision Support System, named FLIRE DSS, for combined forest fire control and planning as well as flood risk management, has been developed and is presented in this paper. State of the art tools and models have been used in order to enable Civil Protection agencies and local stakeholders to take advantage of the web based DSS without the need of local installation of complex software and their maintenance. Civil protection agencies can predict the behavior of a fire event using real time data and in such a way plan its efficient elimination. Also, during dry periods, agencies can implement "what-if " scenarios for areas that are prone to fire and thus have available plans for forest fire management in case such scenarios occur. Flood services include flood maps and flood-related warnings and become available to relevant authorities for visualization and further analysis on a daily basis. When flood warnings are issued, relevant authorities may proceed to efficient evacuation planning for the areas that are likely to flood and thus save human lives. Real-time weather data from ground stations provide the necessary inputs for the calculation of the fire model in real-time, and a high resolution weather forecast grid supports flood modeling as well as the development of "what-if " scenarios for the fire modeling. All these can be accessed by various computer sources including PC, laptop, Smartphone and tablet either by normal network connection or by using 3G and 4G cellular network. The latter is important for the accessibility of the FLIRE DSS during firefighting or rescue operations during flood events. All these methods and tools provide the end users with the necessary information to design an operational plan for the elimination of the fire events and the efficient management of the flood events in almost real time. Concluding, the FLIRE DSS can be easily transferred to other areas with similar characteristics due to its robust architecture and its flexibility.
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