Is operational river flood forecasting scientific? Can a human mechanism be developed to accurately predict floods?

Operational river flood forecasting is a highly challenging activity for several reasons that go beyond strictly scientific aspects. Hydrometeorological forecasting requires extremely complex systems, where issues like communication of warning, accessibility of the results and administrative and/or institutional factors can be as important as monitoring and modelling activities (Pagano et al., 2014; Silvestro et al., 2017). Nevertheless, the cornerstone of such systems, and undoubtedly the most demanding part from a scientific point of view, still is the meteorological-hydrological modelling chain, supported by in-situ or remotely sensed measurements. Increasingly refined modelling chains have been developed in the recent years (e.g., UK Environmental Prediction Research, Canadian Great Lakes, U.S. Navy’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®)). Despite their complexity, these systems all have to deal with some inherent limitations of the meteorological and hydrological models. The main sources of errors in weather forecast are connected to both inaccuracy in defining the initial state, due to the lack of available measures or observation/assimilation errors, and approximations of the models, whose structure is not capable to represent properly the phenomena of interest (Allen et al., 2002; Buizza, 2018). These problems are exacerbated by the chaotic nature of the atmosphere. Even though hydrological models are much simpler than meteorological models in their structure (Liu et al., 2012; Pagano et al., 2014), they also have to struggle with different sources of uncertainty that, according to Renard et al. (2010), can be grouped in four categories: 1) input uncertainty; 2) output uncertainty (e.g., runoff estimates are not straightforward); 3) structural model uncertainty and; 4) parametric uncertainty. Furthermore, since very seldom catchments are perfect natural systems, some effects of human disturbances virtually cannot be modelled. The main link between atmospheric and hydrological compartments in a forecasting chain is precipitation forecast, which is an output variable for weather models and constitutes the main input for hydrological models. Quantitative Precipitation Forecast (QPF) is a major challenge for operational meteorology, because the reliability of precipitation forecasts crucially affects streamflow forecasts skill (for a review see Cuo et al., 2011; for recent applications, e.g., Davolio et al., 2015; Tao et al., 2016; Davolio et al., 2017; Li et al., 2017). Among the various strategies adopted for addressing this issue, in the recent years several studies focusing on coastal areas assessed the importance of Sea Surface Temperature (SST) initial and boundary conditions as relevant drivers of QPF, capable to influence, consequently, the streamflow forecast. This impact can be particularly strong in topographically complex coastal areas, characterized by several small catchments, such as in the Mediterranean Basin, for which several research cooperative efforts have been activated (e.g., the MEDiterranean Experiment, MEDEX, Jansa et al., 2014; the HYdrological cycle in the Mediterranean Experiment, HyMeX, Drobinski et al., 2014). Several studies focused recently on the effects of sea surface-atmosphere interactions over heavy precipitation at midlatitudes, particularly in the Mediterranean area (e.g., Manzato et al., 2015; Romaniello et al., 2015; Rainaud et al., 2016). Some of them showed that large variations of the average values of SST boundary conditions significantly affect location and intensity of high impact events (Lebeaupin et al., 2006; Miglietta et al., 2011; Senatore et al., 2014; Meredith et al., 2015; Pastor et al., 2015; Miglietta et al., 2018; Pytharoulis, 2018). Furthermore, using coupled atmosphere-ocean simulations, Berthou et al. (2014, 2015) highlighted the major effects of long-term SST changes in the representation of Mediterranean intense rain events, even though features at smaller time scales can also contribute significantly. Lebeaupin et al. (2006) found that higher resolution SST fields have poor effects on convection in the case study they analysed (southern atmosphere) and two-way (with feedback) manner. WRF-Hydro system dramatically evolved in last years (Salas et al., 2018; Lin et al., 2018: Lahmers et al., 2019), being operationally adopted into the NOAA National Water Model (NWM) across the continental U.S, besides being used for research applications (e.g., Yucel et al., 2015; Senatore et al., 2015; Arnault et al., 2016; Verri et al., 2017).. MATERIALS AND METHODS Study area and events description Location of Calabrian peninsula in the centre of the Mediterranean as well as its complex orography entails a very irregular precipitation distribution (average annual precipitation varies between 600 and 1500 mm; Federico et al., 2010) and amplifies the occurrence of extreme weather events, which have often caused deaths (about 200 in the period between 1980 and 2016; Petrucci et al., 2018). Among the relatively numerous recent events, this study focuses on two case studies occurred in 2015 and characterized by distinctive different features. The first high impact event (case study 1) was very localized in space and time and hit the north-eastern part of the region on the morning of 12 August 2015. The analysis at the synoptic scale (Figs. 1a-f) shows that in the early hours of 12 August 2015 a main low pressure system coming from the Atlantic moved over the French and Spanish coasts, while over the central Mediterranean a cut-off low occurred, giving rise to a new low pressure vortex with reduced dimensions that caused intense local rainfall. The observed precipitation patterns (Fig. 1g) involved only small areas in the mainland, specifically the territory of the Corigliano and Rossano municipalities. The data provided by the Italian National Radar Network (integrated in the same map of Fig. 1g), though underestimating ground observations, show that most of the precipitation occurred over the Ionian Sea. The Corigliano rain gauge measured high rainfall values (Fig. 1h). During the 48 hours from 00:00 UTC 11 August 2015 up to 00:00 UTC 13 August 2015, 255.2 mm of rain were recorded, with a maximum of 246.4 mm in 24 hours (from 6:00 pm 11 August to 6:00 pm 12 August), 223.2 mm in 12 hours (from 01:45 am 12 August to 01:45 pm 12 August), 167.4 mm in 6 hours, 107.2 mm in 3 hours and 51.4 mm in 1 hour. The hydrological impact concerned some small/very small coastal catchments, the most important of which is the Citrea Creek (11.4 km2 , catchment boundaries highlighted in Fig. 1i), which overflowed causing several tens of millions of euros of damage. 30 The second event (case study 2) involved a much larger area and developed over 4 days, from October to 2 November 2015. The synoptic analysis (Figs. 2a-c) shows another cut-off low, remaining stationary over Sicily for much of the period and attracting humid and warm air from the Ionian Sea to the southeast (a detailed synoptic description of the event is provided by Avolio et al., 2018). The orographic effect in this event turned out to be decisive, the Calabrian mountain ranges acting as a real barrier, therefore large part of the rainfall occurred in the Ionian (eastern) side of the region. While on 30 October 2015 only the northern part of the region was affected (Fig. 2d; about 200 mm in 24 hours in the Oriolo station), the highest precipitation during the entire event was recorded in the southern coast (Figs. 2e-g), with a maximum of about 740 mm (Chiaravalle Centrale station) and a daily maximum of about 370 mm (Sant’Agata del Bianco). In Figs. 2d-g, rain gauges observations overlap the precipitation fields detected by the weather radars, extending also over the sea. The hydrological impact of the event concerned the whole eastern side of the region. Two catchments are selected for this study, namely the Ancinale River closed at the Razzona gauging station (116 km2 , Fig. 2h) and the Bonamico Creek closed at the Casignana gauging station (138 km2 , Fig. 2i). Such catchments are chosen because they are two of the biggest with available observations of water levels (unfortunately no discharge data are available) and are located in the north and the south, respectively, of the rainiest area. Specifically, Chiaravalle Centrale station is located at the Ancinale River outlet.