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Climate change is increasingly influencing the water cycle, hindering the effective management of water resources in various sectors. Lazio, central Italy, exhibits a wide range of climatic conditions, stretching from the Tyrrhenian coast to the Apennines. This study assessed a crucial aspect of climate change, focusing specifically on reference evapotranspiration (ETo) and its associated hydrological variables. The seasonal Mann–Kendall (MK) test was used to assess trends in gridded data. The K-means algorithm was then applied to divide Lazio into four homogeneous regions (clusters), each characterized by distinct trends in hydrological variables. The analysis revealed statistically significant increasing trends (p ≤ 0.01) in temperature, solar radiation, and ETo, with more marked effects observed in the coastal and hilly clusters. In contrast, statistically significant decreasing trends (p ≤ 0.01) were observed for relative humidity, while no statistically significant trends (p > 0.01) were observed for precipitation. This study's methodology, combining trend analysis and clustering, provides a comprehensive view of ETo dynamics in Lazio, aiding in pattern recognition and identifying regions with similar trends. [ABSTRACT FROM AUTHOR]

Hazardous hydrological events cause soil erosion and it is essential to anticipate the potential environmental impacts of prevailing erosion processes that occur at different time-scales. Here, we present the modelling of net soil erosion rates for the Bradano River Basin (southern Italy), based on rainfall erosivity, surface overland flow and transport sub-models. A semi-empirical framework was developed, upscaling point rainfall values based on the Foster-Thornes approach in order to give an insight into monthly and annual soil losses over the period 1950–1958 and 1961 (calibration) and over a longer time-frame (1950–2020: reconstruction). In the 2765-km2 study area, ~ 68% of the sediment mobilized within the basin reached the basin outlet (mean value for 1950–2020: ~ 366 Mg km−2 yr−1). A moderate declining trend in net erosion rates was observed after the 1980s, concurrent with the contraction of cropland in favour of natural vegetation and river channelization. Our results suggest that the parsimonious principle used here seems sufficiently robust to be suitable for applications in other Mediterranean landscapes. [ABSTRACT FROM AUTHOR]

Hydrological disasters, such as floods, can have dire consequences for human societies. Historical information plays a key role in detecting whether particular types of hydrological disasters have increased in frequency and/or magnitude and, if so, they are more likely attributable to natural or human-induced climatic and other environmental changes. The identification of regions with similar flood conditions is essential for the analysis of regional flooding regimes. To this end, we here present the longest existing flood reconstruction for the Eastern Liguria Area (ELA) in northwestern Italy, covering 1582 to 2022 CE, which offers a case study representative of the central Mediterranean region. An Annual Flood Intensification Index was developed to transform the historical data into a continuous annual hydrological time-series contained by a homogeneous data structure for the study-area. We found two change-points (trend breaks) in the reconstructed time-series, in 1787 and 1967, with only occasional heavy floods comparable to present-day disasters occurring before the first change-point, and an increasing intensification of floods after the second change-point up to the present day. The recent intensification of flooding in the ELA, associated with changes in land use and land cover, also appears to coincide with phases in which hydrological hazards have become more changeable and extreme in disaster-affected areas. This is evidenced by river basin responses to human-induced disturbances. [ABSTRACT FROM AUTHOR]

Enhancing spatial data attributes is crucial for effective basin-scale environmental modelling and improving our understanding and management of precipitation patterns. In this study, we focused on reconstructing homogeneous areal precipitation data in the complex terrain of the Calore River Basin (CRB) in Southern Italy. Until 1869, weather observations in the region were inconsistent, unstandardised, and lacked coordination, but the establishment of meteorological observatories brought a more unified approach to weather monitoring. We relied on the rainfall data obtained from two of these historical observatories: Benevento (1869–present) and Montevergine (1884–present). We utilised a statistical regression framework that considered rainfall measurements and temporal properties from specific locations to reconstruct and visually analyse the evolution patterns of annual mean areal precipitation (MAP) in the CRB from 1869 to 2020. The analysis revealed that mean MAP decreased from 1153 mm yr−1 (1869–1951) to 998 mm yr−1 (1952–2020). This decrease was accompanied by a reduction in interannual variability (from 168 mm yr−1 to 147 mm yr−1 standard deviation), and the difference between the means was significant (p < 0.0001), suggesting a sudden shift in the time-series. These findings provide a basis for CRB water resource management and insights for modelling other complex Mediterranean basins. [ABSTRACT FROM AUTHOR]

Snow cover duration is a crucial climate change indicator. However, measurements of days with snow cover on the ground (DSG) are limited, especially in complex terrains, and existing measurements are fragmentary and cover only relatively short time periods. Here, we provide observational and modelling evidence that it is possible to produce reliable time-series of DSG for Italy based on instrumental measurements, and historical documentary data derived from various sources, from a limited set of stations and areas in the central-southern Apennines (CSA) of Italy. The adopted modelling approach reveals that DSG estimates in most settings in Italy can be driven by climate factors occurring in the CSA. Taking into account spatial scale-dependence, a parsimonious model was developed by incorporating elevation, winter and spring temperatures, a large-scale circulation index (the Atlantic Multidecadal Variability, AMV) and a snow-severity index, with in situ DSG data, based on a core snow cover dataset covering 97 years (88% coverage in the 1907–2018 period and the rest, discontinuously from 1683 to 1895, from historical data of the Benevento station). The model was validated on the basis of the identification of contemporary snow cover patterns and historical evidence of summer snow cover in high massifs. Beyond the CSA, validation obtained across terrains of varying complexity in both the northern and southern sectors of the peninsula indicate that the model holds potential for applications in a broad range of geographical settings and climatic situations of Italy. This article advances the study of past, present and future DSG changes in the central Mediterranean region. [ABSTRACT FROM AUTHOR]

Background: Rainfall and other climatic agents are the main triggers of soil erosion in the Mediterranean region, where they have the potential to increase discharge and sediment transport and cause long-term changes in the river system. For the Magra River Basin (MRB), located in the upper Tyrrhenian coast of Italy, we estimated changes in net erosion as a function of the geographical characteristics of the basin, the seasonal distribution of precipitation, and the vegetation cover. Methods and findings: Based on rainfall erosivity and surface flow and transport sub-models, we developed a simplified model to assess basin-wide sediment yields on a monthly basis by upscaling the point rainfall input. Our calibration dataset of monthly data (Mg km-2 month-1, available for the years 1961 and 1963–1969) revealed that our model satisfactorily reproduces the net soil erosion in the study area (R2 = 0.81). For the period 1950–2020, the reconstruction of an annually aggregated time-series of monthly net erosion data (297 Mg km-2 yr-1 on average) indicated a moderate decline in sediment yield after 1999. This is part of a long-term downward trend, which highlights the role played by land-use changes and reforestation of the mountainous areas of the basin. Conclusion: This study shows the environmental history and dynamics of the basin, and thus the varying sensitivity of hydrological processes and their perturbations. Relying on a few climatic variables as reported from a single representative basin location, it provides an interpretation of empirically determined factors that shape active erosional landscapes. In particular, we showed that the most recent extreme storms associated with sediment yield have been characterised by lower cumulative rainfall, indicating a greater propensity for the basin to produce sediment more discontinuously over time. [ABSTRACT FROM AUTHOR]

Rainfall erosivity drives damaging hydrological events with significant environmental and socio-economic impacts. This study presents the world's hitherto longest time-series of annual rainfall erosivity (725–2019 CE), one from the Tiber River Basin (TRB), a fluvial valley in central Italy in which the city of Rome is located. A historical perspective of erosive floods in the TRB is provided employing a rainfall erosivity model based on documentary data, calibrated against a sample (1923–1964) of actual measurement data. Estimates show a notable rainfall erosivity, and increasing variability, during the Little Ice Age (here, ~ 1250–1849), especially after c. 1495. During the sixteenth century, erosive forcing peaked at > 3500 MJ mm hm–2 h–1 yr–1 in 1590, with values > 2500 MJ mm hm–2 h–1 yr–1 in 1519 and 1566. Rainfall erosivity continued into the Current Warm Period (since ~ 1850), reaching a maximum of ~ 3000 MJ mm hm–2 h–1 yr–1 in the 1940s. More recently, erosive forcing has attenuated, though remains critically high (e.g., 2087 and 2008 MJ mm hm–2 h–1 yr–1 in 1992 and 2005, respectively). Comparison of the results with sediment production (1934–1973) confirms the model's ability to predict geomorphological effects in the TRB, and reflects the role of North Atlantic circulation dynamics in central Italian river basins. [ABSTRACT FROM AUTHOR]

Societies can be better prepared to face hydrological extremes (e.g. flash floods) by understanding the trends and variability of rainfall aggressiveness and its derivative, erosivity density (ED). Estimating extended time series of ED is, however, scientifically challenging because of the paucity of long-term high-resolution pluviometric observations. This research presents the longest ED time series reconstruction (1701–2019) in northwest Italy (Piedmont region) to date, which is analysed to identify damaging hydrological periods. With this aim, we developed a model consistent with a sample (1981–2015) of detailed novel Revised Universal Soil Loss Erosion-based high-resolution data and documentary hydrological extreme records. The modelled data show a noticeable rising trend in ED from 1897 onwards, together with an increase of extreme values for return periods of 10 and 50 years, consistent with the Clausius‐Clapeyron scaling of extreme rainfall. We also suggest the North Atlantic Oscillation and Atlantic Multidecadal Oscillation may be associated with rainfall extremes in Piedmont. [ABSTRACT FROM AUTHOR]

Snow events are not a rare episode in Mediterranean area, especially in northern and hilly areas of Italy. However, snowfall occurring quasi-simultaneously in the whole peninsula is extraordinary. This study collects, reconstructs, and analyzes the extraordinary snowfall episodes that occurred simultaneously in the whole Italian peninsula since 1709. This is the longest snowfall time series in the central Mediterranean area. The data, obtained by several documentary sources (from ancient archival to online databases), have been analyzed using different statistical tests, in order to explore normality, homogeneity, and stationarity. The results are characterized by a time-series stationarity with a quasi 60- and 100-year-dominant oscillation. No clear trend in the snowfall episode records is found. The 60-year cycle roughly matches with global-scale oscillations linked to natural forces, such as the Atlantic Multidecadal Oscillation and the winter North Atlantic Oscillation. Particular attention was directed to analyze the impact of snowfall on pre-industrial society, underlining the differences among northern and central regions, where snow was a more usual phenomenon, and its impact was mainly on transports of supplies or exceptionally on buildings, and southern regions, where it had a stronger impact also on orchards and cattle. [ABSTRACT FROM AUTHOR]

Periods characterized by heavy rain and storms can trigger Multiple Damaging Hydrological Events (MDHE), in turn developing flooding, erosion, downpours and other phenomena affecting human habitats and ecosystems. However, approaches and applications to model MDHE and weather warning under specific environmental conditions are still poor. Based on the interpretation of the rainstorm-MDHE relationship, it was reconsidered and extended to a model-based rainstorms hazard index (RHI) developed in a previous paper, where rainstorm-pulsing force and resistance state are combined. In this way, landscape response was achieved by individual formative rainfall events, while the specific sequence of events that can affect landscape was only assessed in a qualitative way. A retrospective evaluation of rainstorm hazard modelling, control runs, are also given for different precipitation durations (from 1 to 240 h), to be compared with MDHE at two test-sites of Southern Italy (Benevento, Campania region; Scilla, Calabria region). For these sites, the complete series of historical MDHE which occurred during a 10 year period (1997-2008) was gathered and used to validate the results of the rainfall model. The tool is relatively simple and potentially attractive to rapidly prediction of adverse consequences of rainstorms. Perspectives for real-time applications in emergency planning are ultimately given for an agenda in future research. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This work presents an attempt to reconstruct the Mediterranean Italy climate across one of the coldest interval (ad 1645-1715) of the 'Little Ice Age' (LIA), characterized by a prolonged episode of low solar acitivty known as 'Maunder minimum' (MM). LIA was characterized by marked climatic variability over this part of southern Europe, particularly during the MM. Using a model based on adding subregional details to regional-scale reconstruction, we estimated for this period a mean winter temperature of ∼1°C lower than in the baseline period 1961-1990 (∼8°C), and the anomaly further lowered down to about -4°C in the winter of 1683-1684. In addition, the interannual variability of extreme low temperatures makes the MM an outstanding climatic period. There is also some consistency of the empirical evidence with the modelling results that, for high-resolution wintertime seasonal reconstruction, central Mediterranean Sub-regional Area shows a colder climate than that represented by coarser simulation of European temperatures during the LIA period. [ABSTRACT FROM AUTHOR]

Evaluation of soil erodibility is an important task for Mediterranean lands, in which fertility and crop yield are significantly affected by soil erosion. The soil physicochemical parameters affecting soil erodibility are highly variable in space and, as for many other environmental variables, sample measurements are generally not enough for assessing its spatial variability with an acceptable level of uncertainty at the scales of practical interest. This study illustrates the procedure applied for estimating the pattern of soil erodibility across the Sele Basin (Southern Italy), where soil properties have been measured on a limited number of sparse samples. Sampled data were integrated with other sparse data estimated by local regression functions, which relate soil erodibility to auxiliary variables, such as terrain attributes and land system class memberships. Sampled and estimated data were merged in a composed data set to assess the spatial pattern of soil erodibility by ordinary kriging. The proposed approach offers effective spatial predictions, and it is exportable to regions where financial costs for soil sampling are not feasible. [ABSTRACT FROM AUTHOR]

A simplified regression model is here calibrated on the basis of rainfall data records of Sicily (southern Italy), in order to show the model reliability in assessing the R-factor of the Universal Soil Loss Equation and its revised version (RUSLE) and to provide an estimate of long-term rainfall erosivity at medium-regional scale. The proposed model is a rearrangement of a former simplified model, formulated for the Italian environment, grouping three easily available rainfall variables on various time scales, which has been shown to be more successful than others in reproducing the rainfall erosive power over different locations of Italy. A geostatistical interpolation procedure is then applied for generating the regional long-term erosivity map with associated standard error. Areas with severe erosive rainfalls (from 2,000 up to more than 6,000 MJ mm ha−1 h−1) are pointed out which will correspond to areas suffering from severe soil erosion. Solving the problem of calculating the R-factor value in the RUSLE equation by means of such a simplified model here formulated will allow to predict the related soil loss. Moreover, given the availability of long time-series of concerned rainfall data, it will be possible to analyse the variability of rainfall erosivity within the last 50 years, and to investigate the application of RUSLE or similar soil erosion models with forecasting purposes of soil erosion risk. [ABSTRACT FROM AUTHOR]

This work presents a modelling study where monthly-based climate data are used to estimate the Normalized Difference Vegetation Index (NDVI). The latter is a measure of vegetation greenness, usually derived from satellite-driven information. A model was developed to link NDVI data to rainfall and temperature measures. The test area was a 3 × 3 km grid centred to the top of Monte Pino hill (Southern Italy), for which multi-year (from 1996 to 2004) climate and satellite-derived NDVI data were available. The simulated NDVI data compared well with the remote-sensed measurements (e.g. modelling efficiency ∼0.80), thus showing a strong linking between vegetation greenness and climate patterns in spite of the many disturbances exerted from farming. The model was used to reconstruct an extended series of monthly NDVI values for a period antecedent 1996 (1972–1995). The analysis of long-term anomalies indicated a positive trend of NDVI over time, consistent with the air temperature increase registered in the same period. [ABSTRACT FROM AUTHOR]

This paper examines the drought patterns in Italy for the period from 1961 to 2006. The condition of drought was considered from an agricultural perspective, using the variability in the annual yield of maize as an indication of climate patterns. A procedure is presented where weather datasets, a drought stress index (MCDI: Mediterranean crop drought index) and geo-spatial analysis are used to assess the spatial distribution and the general evolution of drought. The regional perspective presented characterizes the general climatology of Italy and compares the climate to a severe drought that occurred in 2003. This study identifies some areas (such as major islands, the central Tyrrhenian coast and south-eastern zones) where agricultural drought is likely to be a problem. In general, the temporal patterns outlined in this study indicate an increase in drought over Italy. Considering the poor resolution of global output results for regional and sub-regional assessments, the analysis carried out provides background data and a methodology for climatologists, ecologists and others interested in developing bio-climate patterns within large geographical regions. [ABSTRACT FROM AUTHOR]

Changes in the spatial and temporal features of precipitation patterns may have important effects on the magnitude and timing of erosive rainfalls, which will in turn result in changes in soil degradation response. This study presents a secular timescale environmental hazard assessment to account for the impacts of climate erosive forcing on an agricultural landscape identified as potentially vulnerable, mainly to erosional soil degradation processes. An empirical probabilistic model for temporal characterisation of this impact, termed CHIEF (Climate Hazard Index Erosive Forcing), was developed to evaluate the annual balance between climate driving and climate resisting forces in the Po River Basin {northern Italy) during the period 1775 to 2003. In the CHIEF approach, an ecological system adapted to the natural hydro-climatic regime was assumed; fluctuations in this regime, especially those exceeding thresholds of rainfall energy intensity, may trigger erosional soil degradation processes. In this way, the time sensitivity of the CHIEF model reflects the magnitude of annual input nested within patterns of long-term environmental change occurring within a specific temporal window, in order to capture different modes of climatic variability and their hydro-geomorphological implications. [ABSTRACT FROM AUTHOR]

Land evaluation is sensitive to the effects of variability of ecologically complex phenomena. A probability map incorporating some of these phenomena is proposed to account for local uncertainty of areas affected by soil degradation in the Apennines of south Italy. To be useful, a method for assessing soil degradation should integrate several kinds of data. We present here an overview of the geostatistical approach to solving this problem: non-linear estimation. The following factors have been considered: the soil erosion by water (geomorphologic indicator), the station aridity (bioclimate indicator), and top-soil depth (pedologic indicator). We convert the continuous data values of each variable at each location using a binary variable indicator transform based on critical thresholds. The indicator transform values for individual variables are then integrated to form multiple variable indicator transform (MVIT) to evaluate the degree of soil degradation. Areas suited to soil degradation maps delineated by geographical information system (GIS), showed that the joint probabilities of meeting specific criteria indicator Kriging were influenced by the critical threshold values used to transform each individual variable and the method of integration. So, the understanding of soil vulnerability to degradation is increased to providing a way to classify degraded regions. On the basis of this information different land uses strategies could be identified to develop sustainable assessment models of soils. For example, many countries of these disadvantaged areas, should have agro-forestation programmes that increase the heterogeneity in vegetation cover contrasting hydrological properties, thus promoting a self-regulating system for runoff and erosional soil degradation control. [Copyright &y& Elsevier]

• Geostatistics and GIS connected topo-climatic factors and forest productivity. • Spatial patterns showed the environmental control on forest productivity. • Probability maps differentiated high and low wood productivity rates. The prediction of forest productivity is essential for sustainable forest management, particularly in countries, like Italy, where forest is an important part of many protected areas. A spatial predictive probability model for forest productivity rates in Italy was developed over the period 1961–1990, based on 135 annually-resolved records of site productivity and auxiliary variables measured at 219 stations. Our analysis shows that the probability of finding high (>7.3 m3 ha−1 yr−1) and low (<5.8 m3 ha−1 yr−1) productivity rates changes across different regions of Italy. The generated spatial patterns contribute to a better understanding of the factors structuring the distribution of forest productivity in Italy because they reflect the dependence of temperature and water availability conditions on the latitudinal and altitudinal location of the study areas. We observed that the temperature control dominates forest productivity at high elevations and latitudes, whereas low-elevation sites in central and southern Italy are more sensitive to water availability. The proposed spatial probability modelling should be further assessed for its possible incorporation into forest management plans. [ABSTRACT FROM AUTHOR]

In the low Mediterranean basin, late spring and autumn rainfall events have the potential to increase discharge and transport substantial amounts of sediment soil (that is, the net soil erosion from a watershed). For the Alento River Basin (ARB), located in the low Tyrrhenian coast of Italy, we estimated changes of net erosion as dependent on the seasonality of antecedent soil moisture and its control on rainfall-runoff and erosivity. Based on rainfall and runoff erosivity sub-models, we developed a simplified model to evaluate basin-wide sediment yields on a monthly basis by upscaling point rainfall input. For the period 1951–2018, the reconstruction of a time series of monthly net erosion data indicated a decreasing trend of the sediment yield after 1991. Revegetation and land abandonment that occurred in the last decades can explain such a decrease of net erosion, which occurred even when rainfall erosivity increased. This response, obtained at the basic scale, does not exclude that rapidly developing mesoscale convective systems, typically responsible for the heaviest and most destructive rainfall events in the ARB, can affect small catchments, which are the most vulnerable systems to storm-driven flash floods and soil erosion hazards during soil tilling in spring and at beginning of autumn. [ABSTRACT FROM AUTHOR]

On 22nd November 2011, after extreme rainfall (more than 350 mm fell in 10 h), thousands of shallow landslides evolving into debris flows occurred in several torrent catchments of Peloritani ridge, northeastern Sicily, carrying a large amount of wood. A rapid increase in torrent discharge occurred during the storm, inducing floods of the Longano and Mela torrents, also amplified by wood obstructions of bridges. A detailed reconstruction of the main geo-hydrological events has been done. Landslides have been mapped by satellite photos and checked by field surveys, and were found to be particularly concentrated in the Longano, Mela and Saponara catchments. The timing of landslide initiation has been estimated by technical report data, eyewitnesses, and by calibration of the Leaky Barrel Model [Wilson, Wiezoreck, Environ Eng Geosci 1(1):11-27, 1995]. The recorded amount of rainfall has been transformed into the torrent discharge by the HEC-HMS model, using a detailed digital elevation model (DEM) with resolution of 2 × 2 m, and the torrent hydrograph has been obtained corresponding to several river sections. In the urban area of Barcellona Pozzo di Gotto, the torrent discharge reached its peak before the arrival of the large trunks, indicating that the main cause of the inundation in the urban area was the bridge obstruction. The aim of this study is to provide a detailed case history of landslides inducing floods, and their relationship with the use of simple hydrological models, which could help in estimating the risk of inundation caused by a large amount of wood in unmonitored catchments. [ABSTRACT FROM AUTHOR]