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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]

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]

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]

Future climate change is expected to significantly alter the growth of vegetation in grassland systems, in terms of length of the growing season, forage production, and climate-altering gas emissions. The main objective of this work was, therefore, to simulate the future impacts of foreseen climate change in the context of two pastoral systems in the central Italian Apennines and test different adaptation strategies to cope with these changes. The PaSim simulation model was, therefore, used for this purpose. After calibration by comparison with observed data of aboveground biomass (AGB) and leaf area index (LAI), simulations were able to produce various future outputs, such as length of growing season, AGB, and greenhouse gas (GHG) emissions, for two time windows (i.e., 2011–2040 and 2041–2070) using 14 global climate models (GCMs) for the generation of future climate data, according to RCP (Representative Concentration Pathways) 4.5 and 8.5 scenarios under business-as-usual management (BaU). As a result of increasing temperatures, the fertilizing effect of CO2, and a similar trend in water content between present and future, simulations showed a lengthening of the season (i.e., mean increase: +8.5 and 14 days under RCP4.5 and RCP8.5, respectively, for the period 2011–2040, +19 and 31.5 days under RCP4.5 and RCP8.5, respectively, for the period 2041–2070) and a rise in forage production (i.e., mean biomass peak increase of the two test sites under BaU: +53.7% and 62.75% for RCP4.5. and RCP8.5, respectively, in the 2011–2040 period, +115.3% and 176.9% in RCP4.5 and RCP8.5 in 2041–2070, respectively,). Subsequently, three different alternative management strategies were tested: a 20% rise in animal stocking rate (+20 GI), a 15% increase in grazing length (+15 GL), and a combination of these two management factors (+20 GI × 15 GL). Simulation results on alternative management strategies suggest that the favorable conditions for forage production could support the increase in animal stocking rate and grazing length of alternative management strategies (i.e., +20 GI, +15 GL, +20 GI × 15 GL). Under future projections, net ecosystem exchange (NEE) and nitrogen oxide (N2O) emissions decreased, whereas methane (CH4) rose. The simulated GHG future changes varied in magnitude according to the different adaptation strategies tested. The development and assessment of adaptation strategies for extensive pastures of the Central Apennines provide a basis for appropriate agricultural policy and optimal land management in response to the ongoing climate change. [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]

Highlights • We assessed the grassland model CoSMo whit data from different plant mixtures. • The model was able to reproduce time trends of species composition and yield. • Simulations were performed to analyse climate change impact on grassland dynamics. Abstract Plant diversity supports the high aptitude of grassland covers to provide fodder production for animal feeding and contribute to the storage of carbon, while also granting pollination and aesthetics of landscapes. This ability depends on the management intensity of the grassland system, physical constraints and climatic characteristics. Most of current grassland models simulating the impact of weather conditions, soil fertility and the intensity of use of grassland systems (by grazing and/or mowing) on fodder production and carbon-nitrogen fluxes inherit eco-physiological and biophysical details from crop models without considering explicitly temporal changes in taxonomic and functional composition. The dynamic grassland model CoSMo (COmmunity Simulation MOdel) includes a set of rules to simulate explicitly seasonal changes in species composition of managed grasslands under various soil, climate and management drivers, and it is consistent with the degree of complexity of the most generic crop simulators. The incorporation of CoSMo functionalities into the standalone crop simulators CropSyst and WOFOST is proposed as a way to: (i) reduce the uncertainty in estimations of harvested aboveground biomass (AGB) and (ii) simulate dynamically the relative abundance of species (for respectively the whole community and individual species). Considering three mixtures of grassland species (with increasing complexity from Mix 1 to Mix 3) in a mown hay meadow in central Italy (Massa Marittima, 43° 03′ N, 10° 53′ E, 380 m a.s.l.), we show that CoSMo overall improved the model ability to reproduce observed AGB in Mix 1 and 2 (e.g. with CropSyst in Mix 2 relative root mean square error [ RRMSE ] lowered from 35.01 to 25.27%) while the model performance for Mix 3 appeared as not unambiguously linked to considering plant diversity. An assessment of the relative abundance estimates for the whole community indicates 30%< RRMSE <40% with both CoSMo-coupled CropSyst and WOFOST in Mix 1 and Mix 2, while it increases up to ∼60% in Mix 3. The consequences of explicitly accounting for plant diversity for simulated grassland outputs depend on the conditions evaluated, which require further studies. However, our results suggest that grassland modelling omitting plant diversity dynamics are likely over- or underestimating harvested biomass of the plant community, thus biasing projections of future fodder production and estimates of animal feed supplies. This work proves for the first time that CoSMo can support the simulation of grassland systems beyond its theoretical framework. [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]

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]

• 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]

Abstract: Temperature and photoperiod can be used to simulate post-emergent hemp (Cannabis sativa L.) phenology. With reference to hemp in Italy, our main objective was to model field crops grown under a range of temperature and day length regimes. Dates of emergence and 50% of flowering were collected at Cadriano (Bologna) from serially sown field experiments (1996–1999, 2003–2005) on five cultivars: Carmagnola (late maturity), Felina 34 (medium maturity), Fibranova (late maturity), Futura (medium-late maturity), and Tiborszallasi (medium-late maturity). The database of phenological records was segregated into calibration and validation subsets. A phenology model was developed which utilises the beta function for response to hourly air temperature, and a switch-off function for response to day length. The life cycle of hemp from emergence to 50% of flowering was defined in terms of physiological development days (chronological days at the optimum photoperiod and temperature) and considered in three phases: juvenile phase (BVP), photo-sensitive phase (PIP), flower development phase (FDP). Critical temperatures (T b, base; T o, optimum, T c, ceiling), which did not vary widely across phases and cultivars, were estimated as common values: T b =1.9°C for BVP and 11.3°C for the other phases, T o =26.4°C and T c =40.0°C for all phases. Other parameters, i.e. day length of half-maximum development rate at PIP, and physiological development days for FDP, were also estimated as common values for all cultivars. Different genotypes were mainly characterised for the sensitivity to photoperiod (shape parameter n) and BVP length. With n ∼50, Felina 34 and Futura are regarded as low sensitive cultivars. Tiborszallasi was estimated as the highest sensitive cultivar (n close to 70), whereas Carmagnola and Fibranova showed an intermediate sensitivity (n ∼62). Felina 34 also differentiated for its relatively short BVP length at optimum conditions, i.e. ∼13 days; duration of about 20 days was the estimate for the other cultivars. Model performance against calibration dataset was good (percent relative root mean square in the range ∼6–20%), and comparison against independent data also confirmed the general applicability of this model. Owing to the importance of flowering date in hemp management techniques, these results can be used in decision support for hemp production though further evaluation of the model under a variety of latitudes is required. [Copyright &y& Elsevier]

• Available rainfall data are characterized by different time resolution, "ta" • A database involving metadata from many geographic areas is presented. • The "ta" history of rainfall data in a variety of rain gauges is reconstructed. • The registration methods of the rainfall data changed over the years. • Currently about 50% of rain gauge stations provide data with any "ta" Collected rainfall records by gauges lead to key forcings in most hydrological studies. Depending on sensor type and recording systems, such data are characterized by different time-resolutions (or temporal aggregations), t a. We present an historical analysis of the time-evolution of t a based on a large database of rain gauge networks operative in many study areas. Globally, t a data were collected for 25,423 rain gauge stations across 32 geographic areas, with larger contributions from Australia, USA, Italy and Spain. For very old networks early recordings were manual with coarse time-resolution, typically daily or sometimes monthly. With a few exceptions, mechanical recordings on paper rolls began in the first half of the 20th century, typically with t a of 1 h or 30 min. Digital registrations started only during the last three decades of the 20th century. This short period limits investigations that require long time-series of sub-daily rainfall data, e.g, analyses of the effects of climate change on short-duration (sub-hourly) heavy rainfall. In addition, in the areas with rainfall data characterized for many years by coarse time-resolutions, annual maximum rainfall depths of short duration can be potentially underestimated and their use would produce errors in the results of successive applications. Currently, only 50% of the stations provide useful data at any time-resolution, that practically means t a = 1 min. However, a significant reduction of these issues can be obtained through the information content of the present database. Finally, we suggest an integration of the database by including additional rain gauge networks to enhance its usefulness particularly in a comparative analysis of the effects of climate change on extreme rainfalls of short duration available in different locations. [ABSTRACT FROM AUTHOR]