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 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 km2, 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.
Highlights
In the context of climate change, in which runoff production mechanisms appear to be exacerbated by the modification of climatic variables, the flood frequency regime is altered and an increasing frequency of extreme events is to be expected
The results suggest that Simplified Continuous RR Model (SCRRM) can be advantageous for operational purposes, especially in poorly gauged areas, where there is a lack of continuous meteorological data sets and a need to reduce the model parameterization, as well as to simplify the model structure in order to facilitate the model setup by end users (Montaldo et al, 2005; Coccia et al, 2009; Todini, 2009)
We first describe the study area (Rafina River basin, 109 km[2], Greece), the meteorological data sets and the selected soil moisture (SM) indicators to be used within SCRRM, besides the other models used we describe the structure of SCRRM
Summary
In the context of climate change, in which runoff production mechanisms appear to be exacerbated by the modification of climatic variables, the flood frequency regime is altered and an increasing frequency of extreme events is to be expected. In the framework of the implementation of EUMETSAT’s H-SAF project (Satellite Application Facility on Support to Operational Hydrology and Water Management), an ASCAT root zone SM profile product has been developed based on ASCAT surface SM data assimilation into the ECMWF Land Surface Data Assimilation System (De Rosnay et al, 2013) All these SM data sets, which are globally available, might be potentially used for the initialization of event-based RR models in different catchments and regions worldwide, even for poorly gauged areas. A Simplified Continuous RR Model (SCRRM) is proposed by exploiting SM provided by ground, satellite and reanalysis data This new approach offers the advantages of continuous models, with the difference that the temporal evolution of SM over a long-term period is assessed by using SM directly from external sources, avoiding simulating processes such as evapotranspiration, evaporation and groundwater flow. We present both the comparison between in situ and the selected SM indicators used and the performance obtained from SCRRM compared to those obtained from the other models used in this study
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