Storminess and Environmental Change

A brief survey on the extreme rainfalls in the Mediterranean area has been carried out beginning from the key thermal and pluviometric features of the Mediterranean macroclimate (wet and mild winters – warm and dry summers), passing through the main air masses that influence the basin and coming arriving to the main circulation patterns favourable to extreme rainfall (Atlantic troughs, Mediterranean cyclones, blocking systems). In the final part of the work a statistical climatology of daily extreme rainfall events on the Mediterranean area has been carried out analysing for the period 1973–2010 the extreme events in the whole Mediterranean basin and in the Western and Eastern sub-basins. On the basis of the results, it has been possible to state that the temporal behavior of the relative weight of selected precipitation classes is generally steady on average. Exploring each rainfall class, it has been evidenced only a significant increase of “moderate” events (whole basin) and a meanwhile decrease of “strong” events (West). On the other hand, the observed positive trends of classes “moderate” and “strong” for the East part of the basin should be confirmed by a richer dataset referred to this specific area. Such analysis has highlighted the weaknesses of the historical series currently available in the freely accessible International datasets, pointing up the need of more reliable data sources in terms of time continuity and spatial coverage.

Changes in the spatial and temporal features of rainfall patterns may have important effects on the magnitude and timing of erosive storms, which will in turn result in changes in landscape response. Mediterranean Europe regions are characterized by strong climatic variability, where dry periods are interrupted by pulsing rainstorms throughout the year. Examples of these types are illustrated in this chapter by heavy showers or thunderstorms commonly localised, causing surface erosion by overland flow in the form of rill and gully erosion with remarkable mass movements on the torrential landscape. However, erosive storms forcing is not only related to water erosion, but it is also involved in multiple damaging hydrological events, such as flash-flooding, mudflow and non-point-source pollution. These phenomena generally agree with the seasonality pattern as flash flood-generating rainfall over the various Mediterranean regions. The chapter also maintaining a focus on the analysis on as extreme events are linked to the storm erosivity.

Precipitation variability and extremes have always been part of the Earth’s climate system, though they can manifest in many ways, both spatially and temporally. The chapter explores quantitative concepts of rainfall (storm) erosivity useful for soil erosion monitoring as well as for hydrological extreme events assessment. In this way, a review of the storms erosivity models was done in order to account indicators of climatic changes on both spatial and temporal domains. Most models here summarized were run to estimate erosivity for specific time aggregation levels (from event to multidecadal). For erosion modelling, it would be also preferable to be able to calculate an estimated erosivity value for a particular site. However, different parameterisation options were given in the chapter for accounting of the geographical location effects. The purpose of this chapter was to synthesize and stimulate new research on important issues in climatology, geomorphology, and agricultural engineering, and to provide an intensive and comprehensive review of current modelling and practice.

This work analyses the prominent characteristics of extreme storms and flash-flood regimes in two main areas of the Mediterranean region: the North-Western (comprising Spain, France and Italy) and South-Eastern region (Israel). The two areas are chosen to represent the two end members of variation in flash-flood regimes in the Mediterranean basin. Data from 99 events collected in the two areas (69 from the North-Western region and 30 from the South-Eastern region), for which occurrence date, catchment area and flood peak are available, were used to provide a detailed description the flash-flood seasonality patterns, the synoptic and mesoscale atmospheric controls, and flood envelope relationship. Results show that the flood envelope curve for the South-Eastern region exhibits a more pronounced decreasing with catchment size with respect to the curve of the North-Western region. The differences between the two relationships reflect variations in the fractional storm coverage of the basin and hydrological characteristics between the two regions. Seasonality analysis shows that the events in the North-Western region tend to occur between August and November, whereas those in the South-Eastern area tend to occur in the period between October and May, reflecting the relevant patterns in the synoptic conditions controlling the generation of intense precipitation events.

In contrast to the moderate amounts of yearly average rainfall, the recurrence of heavy rainstorm can be considered a critical hydro-climatological feature for land-and-soil conservation-and-planning of the river basins. This work illustrates a spatial modelling study of rainstorm aggressiveness to assess downscaling in the erosive rainfall climatic classification across Euro-Mediterranean regions. Rainfall erosivity was estimated by the R–climatic factor of the RUSLE approach at 102 raingauges across Europe. For this purpose, an issue model of kriging, termed as lognormal probability cokriging (LPCK), is emphasized to a soft description of the erosive hazard in terms of probability, which is consistent to mitigate the uncertainty of the rainfall erosivity spatial classification. For improving spatial prediction, multivariate geostatistical modelling uses the rainfall 95th percentile at about a 1,000,000 of grid-points as auxiliary information, when the erosivity information is transferred from point to landscape. The estimate of uncertainty at unsampled raingauge via LPCK, was used to explain the probability of exceeding the thresholds of 1,000 and 1,500 MJ mm ha⁻¹ h⁻¹ year⁻¹ as critical values classes of the erosivity at a spatial resolution around to 25 km. In this way, about the 50 % of the area has a probability higher of the 70 % subjected to a rate exceeding to 1,000 MJ mm ha⁻¹ h⁻¹ year⁻¹. The area hit by storm erosivity with a rate higher of 1,500 MJ mm ha⁻¹ h⁻¹ year⁻¹, drops to around 10 %, although, with a probability of 50 %, the surface remains still large (about 40 % of the area).

This work illustrates a modelling study of the erosive power of rainstorms, in integration with GIS techniques, to assess long-term storm erosive hazard in the Mediterranean region. From long-term average erosivity values, it was observed that large erosive rainfalls tend to occur especially in late summer, confined to continental areas, and autumn, along the Mediterranean coasts and near-to-coast reliefs. Rainfall intensity anomalies registered in the September and December months of different years were further investigated, because rain rate was observed to increase in these periods, especially affecting the month of September. An increased erosive hazard was signaled to have occurred in a recent decade (1991–2010) in comparison to the baseline climatology (1961–1990), and some time-series were detected for some sites during the period (1950–2010). Possible consequences on soil erosion were discussed. Remarks were also made concerning the bearing of the findings on a wider interpretation of erosive hazards on soil conservation and the need for future studies.

Based on a parsimonious interpretation of rainstorm processes, the SISEM model – comparable with the Revised Universal Soil Loss Equation – was developed in this work to generate erosivity mean values at different time-aggregation scales (monthly, seasonal and yearly). Following this idea, erosive rainfalls are eligible to be grouped in some vulnerable periods of the year (e.g., cropping months or seasons), or for some particularly stormy interdecadal periods. The test area was conducted for the Campania Region and surrounding Italian areas, where 110 digital stations with sufficient data derived from Department of Civil Protection of Campania Region. The model was evaluated against (R)USLE estimates both on calibration and validation datasets using a range of R modules–based performance statistics. Results show that highly hazardous rainfall erosivity is expected in autumn season, with a more random occurrence in other periods of the year. Taking SISEM model very few and easy retrievable data into account, it is desirable to extend its use of sites without any pluviograph data for time and spatial interpolation purposes over peninsular Central and Southern Italy.

This chapter presents and assesses the Decadal Rainfall Erosive Multiscale Model-France (DREMM-F), in which extreme precipitation data (to the right of the 95th percentile) are used to estimate decadal-scale rainfall–runoff erosivity values compatible with the Universal Soil Loss Equation and its revision – (R)USLE. The model meets the need of estimating rainfall-runoff erosivity when sub-daily extremes rainfall data are missing. The test region is mainland France (and surrounding areas), in which 26 weather stations (ranging from about 27–1,300 m a.s.l.) with rain and (R)USLE rainfall-runoff erosivity data were available over multiple decades. The construction of the model is simplified to a location-explicit term and to the understanding that the most erosive rainfalls are those recorded during the summertime and the beginning of autumn (May–October) as known from the European climatology. In addition, the inclusion of a site-specific elevation term allowed to account for the specific features of mainland France. Once parameterized to capture decadal rainfall–runoff erosivity variability over the test area, the DREMM-F was run to produce the temporal pattern of rainfall-runoff erosivity in the Rhône river basin, and compared to the sequence of flash-floods events over 1951–2010. It was also tested in comparison with previous models at selected sites. Implications for rainfall-runoff erosivity modelling were also discussed concluding that a limited number of parameters may be sufficient to represent decadal rainfall-runoff erosivity in a region positioned at the crossing of a zone of contrasting precipitation patterns.

Climate and weather variability induces considerable switch in storm-erosivity, which is the power of rainfall involved in many damaging hydro-meteorological events worldwide. The present paper proposes advances in our understanding of the hydroclimatological processes and their associated modelling requirements that can be useful in both climate simulation and extremes reconstruction. The novel model CREM (Complexity-reduced Storm Erosivity Model) was developed to test a parsimonious approach in order to perform historical reconstructions of annual rainfall-runoff erosivity when high-resolution precipitation records (e.g., hourly or sub-hourly) are missing. The test-area is located in the Western Swiss Plateau (around Bern), where erosive rainstorm can occur with different modes as seasonal meteorological patterns evolve. The CREM incorporates monthly precipitation and the daily maximum rainfall in a year for estimating storm erosivity compatible with the climatic factor of the RUSLE. Despite its simplicity, the CREM has estimated the storm erosivity with sufficient accuracy, explaining about 90 % of the interannual variability for the validation period (1989–2010). This model calibration offered the possibility of using the model to reconstruct the annual erosivity for the study-area since 1864. Analysis of the reconstructed time series identified two breakpoints (end of nineteenth century, 1970s) that could be related to distinct climate periods. It also indicated a moderate temporal dependence structure. In general, the CREM model produced reliable results and is thus proposed as a useful tool for climatic reconstructions.

This work illustrates an articulated approach for predicting storm erosivity at multiple spatial and time scales over Sicily, the major island of the Mediterranean Central Area (MCA). Starting from the long-term mean erosivity spatial pattern, a downscaling approach to estimate design-storm erosivity was exploited with the aim to map the climate hazard over Sicily referred to 5- and 20-years return periods during the nominal period 1950–1998. The spatial distribution of a Design Erosive Storm Hazard Index (DESHI) was considered as a random field, where the spatial structure varies with duration and recurrence interval of the erosive storms climatic forcing. The expansion of DESHI soft information from points to the whole island landscape was achieved using records from 106 raingauges. Lacking geospatial information was then derived by means of the indicator kriging interpolation via probability maps for practical questions involving communication uncertainty in detecting erosive-prone areas. This approach provides a first exploration of critical areas and helps identify where future infill sampling should be focused in supporting a more precise characterization and conservation planning.

This chapter presents an assessment of annual cumulative erosive storms driving Multiple Damaging Hydrological Events (MDHE) such as floods, landslides and accelerated slope erosion events. This was done in a Mediterranean area where difficulties arise in the reconstruction of the relation between storm erosivity, due to the lack of long detailed and homogeneous recorded time series. This gap has been filled in by merging historical precipitation data from European datasets (Pauling A, Luterbacher J, Casty C, Wanner H, Climate Dynam 26:387–405, 2006) with written proxy documents in which damaging hydrological events were recorded. The research was focused on the Bonea river basin, located in Southern Italy, where a large number of hydrological disasters has occurred (and documented) during the period 1700–2000. For this purpose, a parsimonious approach was used to develop a model named CESAM (Cumulative Erosive Storm Anomalies per Annum) from a previous erosivity anomalies equation and evaluated against erosivity data compatible with the RUSLE scheme. The historical climatology of the Bonea basin has shown pronounced interannual and interdecadal variations dependent on multi-decadal scale erosivity, reflecting the mixed population of thermo-convective and cyclonic rainstorms with large positive-and-high anomalies.

On the 10th November 2010, a debris avalanche occurred in the San Mango sul Calore municipality (Southern Italy). The event was triggered from the North facing side of Mount Tuoro after a rainstorm, involving pyroclastic and colluvial materials that covered part of the hill-slope. The landslide destroyed and occupied houses and damaged several service lines. Field surveys showed that it affected only the deforested part of the slope and its source area was located downslope a man-made cut. We analyzed rainfall data of the climatic station located about 1 km far from the debris avalanche at about 600 m above the sea level. The landslide was triggered after about 63 h of rainfall. The cumulative rain recorded during the storm was about 235 mm. In the three days of rain, the alert threshold of a rainstorm hazard index used as a reference has been exceeded. In order to obtain information about landslide motion we performed a dynamic analysis using the model DAN3D to simulate the landslide mass. The rheological parameters used to simulate the event have been obtained from laboratory tests and through trial and error site-specific calibration.

The erosion and transport of solid and dissolved sediment are largely a function of human activities, climate and geology (reflecting both topography and lithology). Modelling of organic sedimentation is important to understand climate-driven changes in past carbon storage and explore scenarios of future evolution. The main difficulty is to separate the effects of climate change, human activity and the high natural variability of river basins, and to consider the non-stationary sediment records. Basins of mountainous lakes are less affected by human actions and represent a good indicator of how climate variability drives the sediment delivery and carbon accumulation. Alpine basins, in particular, are interesting cases for evaluating simplified approaches to the modelling of annual sediment yields. The model developed in this study (TOCCLIM) extracts percentiles and runoff from the seasonal rainfall data to estimate how changes in the rainfall pattern can influence the fluxes of total organic carbon (TOC). The TOCCLIM was evaluated in the Lake Thun (Switzerland) and used to reconstruct the hydroclimatic forcing of the TOC back to 1600. Land-use changes were taken into account only through feedbacks on the precipitation regimes. We show that some predictive skill can be obtained for inter-to-multidecadal analysis.

Climate variability induces considerable interannual fluctuations in particulate/suspended fraction and dissolved fraction (DOC), especially in mountain areas, where river-streams are continuously recharged naturally by rain and snow melt. However, long-term experiment and modelling have received little attention in the context of climate changes. Better understanding of DOC mechanisms and related time scales are needed for better carbon management. This study presents a novel model namely DOCCLIM (Dissolved Organic Carbon Climatological Model), which was developed to test a complexity-reduced approach in order to perform historical reconstruction in the lack of physical assumptions. The test-site is located in North Italy (Lake Maggiore). DOCCLIM incorporated monthly precipitation and temperature data only, plus some climate indicators. Despite its simplicity, DOCCLIM has been able to estimate DOC yearly fluctuations, explaining about 80 % of the interannual variability at the calibration stage. DOCCLIM can be easily used for estimating DOC in historical times, when not all of the hydrobiological sampling data are available for the purpose.

Precipitation, together with temperature, is the most important variable in defining the climate of a region. Then, the right understanding of rainfall variability, which occurs over a wide range of temporal scales, has relevance for a large variety of problems linked to meteorology and climate, both in theoretical and practical frameworks. The double aspect, continuous and point process, of rainfall sequences manifests itself depending on the scale of aggregation of the rainfall events and on the intensity thresholds associated to storminess risk. This requires the use of different characteristic variables, different reference models as well as different analysis techniques for obtaining a comprehensive characterization of the observational time series and assessing risk. This Chapter provides a quick overview of the many aspects of the reconstruction of the time scale properties based on the investigation of historical data. Storminess observed for several decades at two Italian sites (Genoa and Palermo), which exhibit different climatic features, were analysed both with tools typical of point processes and more standard analysis techniques to provide a coherent picture of the basic properties of rainfalls that can be extracted from daily data about weather, seasonal, and climatic scales. Both analogous and complementary cycles appear when we approach the problem from the two different perspectives separately; additional behaviours are detected when we integrate them. This comprehensive picture of historical data represents the background for understanding precipitation regimes and identifying possible climatic changes or human pressure effects that could increase storminess risk.

In this chapter, based on the data available in a regional database, some severe damaging hydrogeological events (DHEs) occurred in the last century in Calabria (Italy) have been described in terms of both triggering rain and damaging effects. Among the analyzed cases, there are only three long standing events (1951, 1953 and 1972), while the others are shorter. As far as the triggering rain, the 1951 and 1953 events are still not surpassed, and fortunately it is the same for the number of victims. If we consider the event occurred on 2000 as an exception caused by the negligence of the municipality that allowed a campsite so close to the river, the number of victims per event shows a decreasing trend. This can be a normal evolution which occurs in developed countries, where, because of an improving event management, damage to people tend do decrease and damage to goods to increase. The seasonality is clear: the majority of the events occurred between September and November, which in Calabria are the rainiest months. In terms of damaging phenomena, landslides were always the most frequent type. Greatest damage, especially in terms of victims, was caused by floods, the effects of which were often amplified by sea storms. The interrelations between the different phenomena, as the relationship between floods and landslides carrying debris into the river network and the connection between floods and sea storms, confirm that DHEs have to be studied with a general approach and taking into consideration all the phenomena and their interrelation which can amplify damage and cause cascading effects.

The objective of this study is to investigate the simulation skill of extreme rainfalls in Naples (Italy). The coasts of Italian peninsula have been affected by frequent damaging hydrological events in the last decade, driven by intense rainfall and deluges. The internal mechanisms for rainfall variability that generate these hydrological events in the Mediterranean are still unknown. In the present study, an annual series of daily maximum rainfall spanning the period 1866–2010 was used to skill projection at intradecadal scale. A procedure was developed where a predictable structure was first provided by reducing noise via low-pass band Gaussian filter, and successively elaborated by an exponential smoothing approach for the purposes of simulation – in testing period – and forecast – in projection time. The analysis was based on a set of online tools that are suitable to discover the manifestation of a possible trajectory of projected extreme rainfall changes. Hindcast experiments by model runs were tested, and pattern simulated with horizon placed in the year 2050. Projections discover a clear rising of extreme rainfall with cyclical pattern similar to the past. The oscillation of simulated extreme rainfalls was coupled with variations attributed to internal climate variability, such as the Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation. This suggests that a correlation exists between the occurrence of extreme rainfalls at Naples and large-scale climatic phenomena.