PL3

Increasing extreme precipitation intensity at short duration is reported in recent literature and related to the global warming. For improving risk management and adaptation to changing climate, it is important to estimate the changes in hourly extremes, because they cause numerous hydro-geological hazards. High resolution climate models (Convection-permitting models, CPMs) resolve the scales at which convective processes occur, and can provide higher confidence in the future estimates of hourly precipitation than coarser resolution models. However, since actual CPM runs are available for short time slices (10–20 years), estimation of extremes by using classical Extreme Value approaches is difficult. Novel methods based on the concept of ordinary event have shown the capacity of deriving reliable frequency analyses from short data records, and they can be successfully applied to CPMs.

Recent literature reported distinct orographic effects on precipitation extremes. In particular, decreasing intensity with elevation for hourly extremes is found (“reverse orographic effect”) as contrasted with the orographic enhancement of precipitation for long durations. The reverse orographic effect was tentatively associated to orography-induced turbulence. These processes could be sub-grid even for CPMs, so it is crucial to understand whether and how CPMs can represent the orographic effect before using the simulations to project future extremes in mountainous areas.

We focus our study on an orographically complex area in the Eastern Italian Alps. Precipitation data comes from: i) ~170 5-min resolution rain gauges (our benchmark), ii) CPM simulations from COSMO model, run at 2.2 km spatial resolution and 1h time-resolution. The model is driven with ERA Interim re-analyses for the period 2000-2009. A storm-based statistical method is applied to both observed and simulated time series, and we use a Weibull distribution for modelling the upper tail of ordinary events. We derive the distribution parameters and extreme return levels up to 20-year return period for durations between 1 and 24 h. We look at their dependence on elevation, and we quantify the bias between observations and CPM, the dependence of the biases with elevation.

Spatial patterns in the CPM biases on the annual maxima and the modelled return levels emerge for short durations, while a general better agreement between model and observation is found at the daily duration. For the 1h return levels, the bias depends on elevation, with increasing overestimation with elevation, which implies a weak representation of the reverse orographic effect.

This work shows that we can have reliable estimates of high return levels from short CPM runs by using proper statistical methods. The results can improve our understanding of the changes in the meteorological processes underlying the changes in the precipitation extremes, and could help us develop adjustment approaches accounting for the role of orography at multiple durations.

How to cite: Dallan, E., Marra, F., Fosser, G., Formetta, G., Marani, M., Schaer, C., and Borga, M.: How is the reverse orographic effect on hourly extreme precipitation reproduced by a high resolution climate model?, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-66, https://doi.org/10.5194/egusphere-plinius17-66, 2022.

The RESILIENCE project aims at developing  an integrated methodology for assessing the impact of climatic variations and changes on the intense precipitation and wind regimes, and on the consequent triggering of flash floods, debris-flows and wind-related forest damages. A significant increase of short and intense precipitation is expected in the next future due to global warming, with consequent impacts on flash floods and hydro-geomorphic hazards such as shallow landslides and debris flows. Despite their societal importance, only few studies have explored potential climate change effects on these hydrological and hydro-geological processes. In fact, no accepted estimates of such changes to be used in engineering practice or environmental management planning exist so far, nationally or regionally.

The RESILIENCE project tries to address this specific knowledge gap. Two recent scientific advances are at the basis of the development of RESILIENCE. The first advance is the advent of high-resolution climate models, also called Convection-Permitting Climate Models (CPM), which improve the representation of both precipitation and wind field at the sub-daily scales compared to the standard coarser resolution Regional Climate Models. However, due to their computational costs, simulations are currently available for only short (typically ten years) time slices and few emission scenarios. These time series are too short to provide reliable statistics of extremes if analyzed using the classical extreme value methods. A second recent advance in the field of extreme value theory, the Metastatistical Extreme Value Distribution (MEVD), allows to overcome this limitation: it provides reliable extreme event probability estimates even from short time series, as in the case of CPM outputs, since it is based on all “ordinary events'' in the series instead of just yearly maxima or a few “peak-over-threshold” values per year as in the traditional methods.

Given this background, and focusing on the Veneto region in Italy as a study area, the specific objectives of RESILIENCE are 1) to quantify near (2041-2050) and far (2090-2099) future changes in precipitation and wind extremes probability at sub-daily temporal scales with respect to the baseline (1996-2005) using the MEVD approach  and high-resolution COSMO-CLM simulations, 2) to quantify the associated future impacts on flash floods, debris flows and forest damages, 3) to provide data and hazard models to support flood and forest risk management plans in the Italian North-East accounting for future climate changes.

RESILIENCE brings together an interdisciplinary group of scientists, from hydrologists, to climate modelers, to statisticians, to forest science experts, and is based on the interaction with three key Project Stakeholders. The project results will be communicated and disseminated to a wide audience of residents in the Veneto region and beyond, through collaborations with Museums, Academies and Local Authorities.

How to cite: Dallan, E., Borga, M., Marra, F., Fosser, G., Martina, M., Marani, M., Gregoretti, C., Lingua, E., Canale, A., Massimiliano, M., Bernard, M., Costa, M., Cesarini, L., Dalmasso, G., Caruso, M. F., Zanaga, V., and Zaramella, M.: RESILIENCE Project - Extreme Storms in the Italian North-East: frequency, impacts and projected changes, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-84, https://doi.org/10.5194/egusphere-plinius17-84, 2022.

We investigate the spatial and temporal patterns of annual and seasonal biases in extreme precipitation simulated by a convection permitting climate model forced with reanalysis data (Era Interim driven COSMO-CLM model) across a 10-years period (2000-2009). Specifically, we aim at developing an adjustment procedure able to preserve extremes at different temporal and spatial scales, and which can be applied to future scenarios.

The biases are here defined as the ratio between simulated and observed rainfall at 130 rain gauges. The quantile-based analysis reveals a general overestimation for gauges located in foothill or mountain areas (elevation > 500 m asl), and a general underestimation over lowland sites. This behavior is recurrent for various investigated quantities, such as annual or seasonal biases, and their counterparts estimated upon Extreme precipitation Values (EV) or wet periods. We also observe a temporal heterogeneity of the biases estimated in different years or seasons. Dry years (e.g. 2003) are characterized by remarkably high biases, while those estimated upon springs and autumns data within the investigation period are generally overestimated and underestimated, respectively.

We explore two preliminary adjustment approaches: Quantile Mapping (QM) and Linear Scaling (LS) adjustments. QM corrects simulated rainfall series but can affect the rainfall temporal autocorrelation. Conversely, LS preserves the autocorrelation but fails in the correction of seasonal and annual biases. EV-related biases are not properly corrected, and further statistical methods need to be formulated to correct EV simulated rainfall while both respecting their ACF and taking into account orographic effects.

How to cite: Schiavo, M., Dallan, E., Fosser, G., Marra, F., and Borga, M.: Statistical methodologies for biases correction of precipitation for a convection-permitting climate model and their spatio-temporal patterns in North-Eastern Italy, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-88, https://doi.org/10.5194/egusphere-plinius17-88, 2022.

Liguria region is historically affected by severe hydro-meteorological events often resulting in dramatic death tolls and large socio-economic impacts. On 7-8 October 1970, Genoa, region capital city, was struck by the most catastrophic flood event of its history. On the evening of 7 October pre-frontal storms affected the western side of the city (Voltri, Prà and Pegli municipalities), while on 8 October 1970 an anticyclone block generated recurring convective systems that hit Genoa city and above all the Bisagno Valley. The heavy rainfall continued more than 24 h with highs at Bolzaneto rain gauge (Polcevera Valley, northwest of Genoa city center) where over 950 mm of rainfall in 24 hours was measured. Over the city center and the Bisagno Valley, 400 mm in 24 h was recorded. The Bisagno stream channels overflowed, submerging the city center. The 1970 event in Genoa City was also the most dramatic in terms of damage: 44 fatalities occurred and over 2000 individuals were evacuated.

This study hindcasts the meteorological evolution of this event at high spatial resolution (1.5 km) and temporal one (1 hour) using the Weather and Research Forecasting (WRF) model by downscaling the ERA5 climatology developed by European Center for Medium-Range Weather Forecast (ECMWF). The weather hindcast scenario is compared with available meteorological observations as well as with recorded geomorphological impacts on Genoa city center and municipalities.

How to cite: Parodi, A., Boni, G., Faccini, F., and Paliaga, G.: Hindcast high-resolution simulation of the most catastrophic rainfall event in Genoa City (7-8 October 1970): hydro-meteorological and geomorphological analysis, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-89, https://doi.org/10.5194/egusphere-plinius17-89, 2022.

Changes in slope stability can arise from hydro-mechanical processes driven by atmosphere-soil interaction, and these processes are affected by the temperature at which they occur. This is well studied in cold climates, but even at temperatures well above freezing, experiments show significant changes in soil parameters upon comparatively small variations in temperature. These effects are typically neglected in geomechanical models, as their formulations do not typically include temperature or, if they do, they relate it to soil hydrology and not soil mechanics. Therefore, by only focusing on extremes in hydrological forcing, we may be underestimating the role of climate change in landsliding in temperate regions. Within ongoing projects, we are exploring the relationship between temperature and slope stability with various approaches and at various scales. In the laboratory, we are conducting temperature-controlled oedometer tests and ring-shear tests on saturated soils, observing patterns of strengthening or weakening in relation to both the mineralogy and shear rate. We also are evaluating correlations between basic and mechanical properties on the basis of the soil’s response to heating and cooling. We are using such correlations in the field to obtain insights on slope stability, particularly of rock bodies. Focusing on soils, we are developing thermo-hydro-mechanical model formulations for slope stability under climate change. At the catchment scale, we are using statistical tools to find whether a temperature-related variable (such as the land surface temperature) can inform landslide susceptibility models. Insights from debris flow-yielding steep mountain catchments and gentle clay slopes with slow creep processes suggest the significance of temperature and its fluctuations in influencing/controlling gravitational processes also independently of its influence on vegetation and hydrological forcing.

How to cite: Scaringi, G., Loche, M., Tourchi, S., and Lombardo, L.: Temperature and slope stability in temperate climate, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-26, https://doi.org/10.5194/egusphere-plinius17-26, 2022.

Quantifying rainfall volumes at varying duration and frequencies (e.g. design rainfall) and their uncertainty is crucial for a reliable design of water related infrastructures, such as flood retention reservoirs, urban drainage systems, spillways, culverts. This is of particular relevance in orographically complex area where extreme rainfall could trigger hydro-geological hazards.

Estimate of the design rainfall and its uncertainty is usually done at-site, i.e. at the position where the rain gauge is located and regionalization methods are required to provide estimates in ungauged locations. 

In this work we exploit the potential of the Simplified Metastatistical Extreme Value (SMEV) statistical framework for the analysis of extreme rainfall based on ordinary events and not only the annual maxima and we evaluated the performances of two different regionalization methods (namely, regionalization of extreme rainfall quantiles and of the distribution function parameters). The performance of the two selected approaches is evaluated by leave one out cross-validation and traditional goodness of fit measures (i.e. percent bias, percent root mean square error, and Kling Gupta efficiency).

The study area is the Alto Adige Region located in the Italian Alps, where 57 rain gauges at sub-hourly and hourly time steps are analyzed.

Preliminary results show that accounting for elevation in the regionalization (Kriging) methods provides better performances and reduce the design rainfall uncertainty in ungauged locations.

How to cite: Formetta, G., Marra, F., Dallan, E., and Borga, M.: Extreme rainfall estimation in orographically complex ungauged locations, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-80, https://doi.org/10.5194/egusphere-plinius17-80, 2022.

This work analyses the spatial structure of some extra-ordinary extreme rainfall events (EEEs) in Liguria (NW of Italy). The EEEs affecting the region are often caused by Mediterranean Back-building MCS events which are usually characterized by a very small spatial extent. EEEs produce the annual maximums of precipitation for short durations, commonly used for the probabilistic analysis of rainfall and flood hazard.

The characteristic spatial scale of the EEE analyzed, represented by the cross-sectional dimension of the peak structures, compared with the average rain gauge density shows that the former is often less than or of the same order as the latter.

Rain gauge data are used to obtain statistics of extreme rainfall, usually expressed by rainfall depth-duration-frequency (DDF) curves. This statistical approach relies on the assumption that the maxima observed by the raingauges are matching with the local maxima of the actual event. The lower is the average rain gauge density compared to the characteristic spatial scale of EEEs, the less valid is the aforementioned hypothesis.

The spatial analysis of some recent EEEs in the region underlines that the mismatch between the characteristic spatial scale of the rainfall field and the average rain gauge density can be extremely significant.

This impacts the probability of observing the actual peak rainfall and can lead to an overestimation of the return period associated with the most intense events, which are of interest for the design of hydraulic structures and risk planning.

The dramatic underestimation of the rainfall depth at very high return periods due to the application of traditional statistical methods has been already highlighted as a criticality in the literature, focusing on daily rainfall. This work presents a first attempt to set up a framework to quantify the underestimation of the precipitation peak (or the overestimation of the return period) at sub daily scale as a function of the ratio between the raingauge density and the transversal dimension of the precipitation events.

How to cite: Boni, G., De Angeli, S., Lagasio, M., and Parodi, A.: How the spatial structure of extreme rainfall observed by meteo-radars can impact the estimation of the return period of extra-ordinary events?, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-95, https://doi.org/10.5194/egusphere-plinius17-95, 2022.

Italy is one of the countries most exposed to hydrogeological risk in Europe. From the hydrological point of view, alluvial phenomena and rainfall-induced landslides have a common origin, since both of them are caused by intense surface runoff causing slope instability or water overflow in the drainage network. In particular, the territory of central Italy has a complex orography, where heterogeneous basins with different areas co-exist. Vast basins such as that of the Tiber, are found in geographical areas contiguous to minor hydrographic basins, which are mainly located along the eastern slope of the Apennines. Due to this complexity of the landscape, the territorial response to precipitation can be different and alluvial phenomena can be the result of different processes, with the precipitation as a common denominator. Floods or flash floods, but also rainfall-triggered landslides represent the main effects at the ground, due to intense or persistent rains. In general, river floods are considered more predictable than flash floods, since the latter are linked to very localized rain events, concentrated over a short period of time. The predictability of landslides is associated with attentive monitoring, based on the definition of rainfall thresholds.In this work, the hydrological model developed by Cetemps (CHyM) is applied for the simulation and detection of areas subjected to hydrological stress of a large geographical domain, which includes all of Central Italy, during diverse severe weather event impacting Central Italy in the recent years. We propose the validation of three different stress indices on a geographical area of ​​about 65 500 km2, including basins of very different sizes and characterized by heterogeneous substrates. The main purpose is to present a unique tool for the forecast on a regional scale of hydrogeological stresses induced by precipitation. The identification of stress conditions is given through the use of indices, able to detect areas affected by floods, flash floods and landslides, also providing a key to discriminate and classify these three different phenomena.

How to cite: Lombardi, A., Colaiuda, V., Gallicchio, D., Boscaino, G., Raparelli, E., Tuccella, P., Lidori, R., Rossi, F. L., Liberatore, S., and Tomassetti, B.: User-oriented indices for rainfall-related hydrogeological hazards prediction at regional scale: validation in Central Italy, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-59, https://doi.org/10.5194/egusphere-plinius17-59, 2022.

The Italian peninsula has one of the highest hydrogeological risk levels in Europe, characterised by a geomorphologically varied and geologically complex territory. In particular, mountainous areas are characterized by fragile environments that are frequently affected by floods and instability.

The weather events that have struck our country in recent decades have often triggered/reactivated natural instability processes that have been particularly damaging in terms of structures and infrastructure. In mountainous and hilly areas, both muddy-debris flows and surface landslides are particularly widespread. The former is triggered within secondary basins, often fed by surface landslides, and are particularly evident on alluvial conoids, affecting population centers. There are many variables, both meteorological and territorial, that make forecasting these phenomena very difficult.

In view of the intensification of these severe weather events, it is important to set up an advanced hazard forecasting system in mountain locations that allows geological analyses to be integrated with atmospheric and hydrological modelling. In this context, the identification of areas susceptible to landslides cannot be performed using a conventional approach, since hydrological-hydraulic methods have a poor or poor calibration.

In response to the need of fast communication to make the Early Warning System more effective, allowing an immediate assessment of the risk and its spatial and temporal location, we propose the use of specially designed indices that, although deduced from the predicted physical fields, allow warning messages to be provided both on the basis of observed and predicted rainfall, and on the basis of the flow forecasts of the monitored rivers and their main tributaries.

We therefore propose a new approach, based on a forecasting chain that brings together geomorphological information, reliable high-resolution weather forecasts and hydrological models.

In this work, a pre-operational chain was set up, coupling off-line the high-resolution Weather Research and Forecasting (WRF) meteorological model and the Cetemps Hydrological Model (CHyM). Different stress indices were calculated useful to identify the debris flows of the Croso river and possible criticalities on the other river basins.

How to cite: Tomassetti, B., Ferrarese, S., Golzio, A., Colaiuda, V., Luciani, M., Tuccella, P., and Lombardi, A.: Early Warning System for hydrogeological risk forecasting in mountain environments: The Rio Croso case study., 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-62, https://doi.org/10.5194/egusphere-plinius17-62, 2022.

Water-age accounting, and its stable isotopic signature due to fractionation, is becoming a powerful tool in gaining further insights in several science questions related to watershed hydrologic response in extreme weather events and its sensitivity to land and climate changes. Experience is quite limited on fully distributed watershed models capable of explicitly tracking water age and stable isotopes variations along the modelled fluxes. Most of these models rely on a full-mixing simplifying hypothesis inside each model conceptual reservoir, e.g. a soil layer in a computational pixel or a river reach. This hypothesis is known to seriously affect the capability of matching model results with isotope data, especially at time scales much shorter than the seasonal one, hence preventing efficient data assimilation to improve model calibration ad state estimation. We propose here a water age-and-isotope tracking version of the fully distributed watershed model MOBIDIC, which in its standard operational version includes surface energy-mass balance, snowpack dynamics, hydraulic river and reservoir routing, surface-groundwater interactions. An augmented EnKF isotope and river discharge data assimilation framework is also presented based on such a model, aimed at both estimating key model parameters and improving the estimation of river water partitioning among different sources during floods. While input hydrometeorological data used in the experiments refer to real high-flow events on a mid-size mountain basin, synthetic data are generated (with an ideally ‘unknown’ set of model parameters) for river flows and isotopes in a first assimilation efficiency assessment presented here.

How to cite: Castelli, F. and Arrighi, C.: Water-Age Accounting, Fully Distributed Watershed Modeling for Flood Forecasting, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-75, https://doi.org/10.5194/egusphere-plinius17-75, 2022.

Maghreb countries are strongly impacted by floods, causing twice as many deaths as in southern European countries in recent decades. However, due to the lack of data accessibility, there are no studies to analyze whether the frequency or intensity of floods are changing at the regional scale. In this work, a recent database of daily river discharge data from 58 basins located in Algeria, Morocco and Tunisia with on average 32 years of complete records over the time period 1970-2017 is considered to analyze the evolution of floods. A peaks-over-threshold sampling of flood events is considered, to detect trends on the annual frequency and the magnitude of floods. The results illustrate the complexity of conducting trend detection in a context of high inter-annual variability, with spurious trends detected in several cases due to isolated extreme events. Overall, few statistically significant trends are detected on the intensity of floods but an increase in flood frequency is detected in one-third of the basins. The results are interpreted in relation to land-use change, river regulation by dams and reservoirs, and climatic change. Recommendations concerning the use of frequency analysis approaches on floods in this region are given.

How to cite: Tramblay, Y., El Khalki, E. M., Benaabidate, L., Boulmaiz, T., Boutaghane, H., Dakhlaoui, H., Hanich, L., Ludwig, W., Meddi, M., Sadaoui, M., El Mehdi Saidi, M., and Mahé, G.: Changes in flood hazards in North Africa and implications for flood frequency analysis, 17th Plinius Conference on Mediterranean Risks, Frascati, Rome, Italy, 18–21 Oct 2022, Plinius17-87, https://doi.org/10.5194/egusphere-plinius17-87, 2022.