Patterns, Trends, and Climate Change Impacts in Southern Italy
Extreme rainfall events represent one of the most critical hydrological hazards, with direct consequences for floods, landslides, urban drainage systems, and water resources management. In recent decades, growing scientific evidence has highlighted significant changes in rainfall extremes, particularly at short time scales, driven by climate variability and ongoing climate change.
This page provides an overview of recent research on sub-daily rainfall extremes, with a specific focus on Southern Italy and the Mediterranean region, drawing on the results of Avino et al. (2021, 2022, 2024).
Why Study Rainfall Extremes?
Rainfall extremes are characterized by high intensity and short duration precipitation events that can overwhelm natural and artificial drainage systems. Unlike mean rainfall, extreme precipitation shows strong spatial and temporal variability, making it difficult to identify clear trends at the regional scale.
Recent international studies indicate that intense rainfall events are increasing globally, especially for short durations. However, these changes are not uniform and require local and regional analyses to be properly understood.
Data Challenges and Methodological Advances
One of the main limitations in the analysis of rainfall extremes is the fragmentation of sub-daily rainfall records, caused by changes in monitoring networks, sensor relocation, and missing observations. To overcome these issues, recent research has focused on the development of robust data reconstruction methods.
A key methodological advance is the Spatially Constrained Ordinary Kriging (SC-OK) technique, introduced and validated by Avino et al., which combines geostatistical interpolation with physically meaningful spatial constraints. This approach allows:
- Reconstruction of missing sub-daily rainfall annual maxima
- Improvement of time series completeness
- Preservation of statistical consistency with observed data
These advances enable more reliable trend detection and reduce uncertainty in extreme rainfall analyses.
Evidence from Southern Italy
Sub-daily Rainfall Trends (1970–2018 / 1970–2020)
Recent studies focusing on Southern Italy highlight several robust findings:
- Most rainfall stations show no statistically significant trend across all durations.
- When trends are detected, they are predominantly positive for short durations (1–3 hours).
- For longer durations (12–24 hours), trends tend to weaken or disappear, and in some areas negative tendencies emerge.
- Rainfall extremes exhibit strong spatial heterogeneity, with localized clusters of increasing short-duration intensity.
These results are consistent across different statistical techniques, including Mann–Kendall trend test, Regional Kendall test, record-breaking analysis, and change-point detection (Pettitt test).
Change Points and Non-Stationarity
Beyond monotonic trends, recent analyses have identified change points in rainfall extreme time series, indicating abrupt shifts in rainfall regimes rather than gradual changes. These changes often cluster around the late 1990s and early 2000s and are consistent across multiple durations.
The identification of change points is particularly important for flood risk assessment, design storm estimation, and non-stationary hydrological modeling.
Implications for Hydrology and Risk Management
The observed increase in short-duration rainfall extremes has critical implications for urban drainage and stormwater infrastructure, flash flood hazard in small catchments, landslide susceptibility, and climate-adaptive hydraulic design. Traditional assumptions of stationarity may lead to underestimation of design rainfall and hydraulic risk, especially for short-duration events.
References
- Jahanshahi, A., A. Avino, F. D. Pacia, L. Furnari, A. Senatore, P. Perrini, R. Zhuang, U. Terracciano, A. N. Sarwar, L. Viscido, L. Gianni, G. Mendicino, L. V. Noto and S. Manfreda, Near-future shifts in hydrological extremes and drought-to-flood transitions in Mediterranean catchments of southern Italy., 2026.
- Manfreda, S., The space-time representation of extraordinary rainfall events., Ecohydrology, 2024. [pdf] [doi]
- Avino, A., L. Cimorelli, P. Furcolo, V. Noto, A. Pelosi, D. Pianese, P. Villani and S. Manfreda, Are rainfall extremes intensifying in Southern Italy?., Journal of Hydrology, 2024. [pdf] [doi]
- Avino, A., S. Manfreda, L. Cimorelli and D. Pianese, Trend of annual maximum rainfall in Campania Region (Southern Italy)., Hydrological Processes, 2021. [doi]
- Manfreda, S., D. Miglino and C. Albertini, Impact of detention dams on the probability distribution of floods., Hydrology and Earth System Sciences, 2021. [doi]
- Manfreda, S., V. Iacobellis, A. Gioia, M. Fiorentino and K. Kochanek, Impact of climate on hydrological extremes., Water, 2018. [doi]
- Gioia, A., S. Manfreda, V. Iacobellis and M. Fiorentino, Comparison of different methods describing the peak runoff contributing areas during floods., Hydrological Processes, 2017. [pdf] [doi]
- Gioia, A., V. Iacobellis, S. Manfreda and M. Fiorentino, Influence of infiltration and soil storage capacity on the skewness of the annual maximum flood peaks in a theoretically derived distribution., Hydrology and Earth System Sciences, 2012. [doi]
- Iacobellis, V., A. Gioia, S. Manfreda and M. Fiorentino, Flood quantiles estimation based on theoretically derived distributions: regional analysis in Southern Italy., Natural Hazards and Earth System Sciences, 2011. [doi]
- Fiorentino, M., A. Gioia, V. Iacobellis and S. Manfreda, Regional analysis of runoff thresholds behaviour in Southern Italy based on theoretically derived distributions., Advances in Geosciences, 2011. [pdf] [doi]
- Iacobellis, V., M. Fiorentino, A. Gioia and S. Manfreda, Best Fit and Selection of Theoretical Flood Frequency Distributions Based on Different Runoff Generation Mechanisms., Water, 2010. [pdf] [doi]
- Gioia, A., V. Iacobellis, S. Manfreda and M. Fiorentino, Runoff thresholds in derived flood frequency distributions., Hydrology and Earth System Sciences, 2008. [doi]
- Fiorentino, M., S. Manfreda and V. Iacobellis, Peak Runoff Contributing Area as Hydrological Signature of the Probability Distribution of Floods., Advances in Water Resources, 2007. [doi]
- Fiorentino, M., A. Gioia, V. Iacobellis and S. Manfreda, Analysis on flood generation processes by means of a continuous simulation model., Advances in Geosciences, 2006. [pdf] [doi]
Rainfall Database
This page is part of the Hydrological Modelling research line of HydroLAB. See also: Flood Processes · Stochastic Modeling and Flood Dynamics · Ecohydrology · DREAM Model · Nature-Based Solutions.