English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Erosive storms constitute a major natural hazard. They are frequently a source of erosional processes impacting the natural landscape with considerable economic consequences. Understanding the aggressiveness of storms (or rainfall erosivity) is essential for the awareness of environmental hazards as well as for knowledge of how to potentially control them. Reconstructing historical changes in rainfall erosivity is challenging as it requires continuous time-series of short-term rainfall events. Here, we present the first homogeneous environmental (1500–2019 CE) record, with the annual resolution, of storm aggressiveness for the Po River region, northern Italy, which is to date also the longest such time-series of erosivity in the world. To generate the annual erosivity time-series, we developed a model consistent with a sample (for 1981–2015 CE) of detailed Revised Universal Soil Loss Erosion-based data obtained for the study region. The modelled data show a noticeable descending trend in rainfall erosivity together with a limited inter-annual variability until ~1708, followed by a slowly increasing erosivity trend. This trend has continued until the present day, along with a larger inter-annual variability, likely associated with an increased occurrence of short-term, cyclone-related, extreme rainfall events. These findings call for the need of strengthening the environmental support capacity of the Po River landscape and beyond in the face of predicted future changing erosive storm patterns.

Historical predictability of rainfall erosivity: a reconstruction for monitoring extremes over Northern Italy (1500–2019)