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The identification of thresholds of simple and practical determination capable of operating a separation between non-erosive and erosive rains has considerable importance from both a practical and scientific point of view. It allows reducing the work necessary to manage and process erosive events and provides useful information to determine the triggering of erosion processes of different entities and nature and consequently to understand their dynamics better.In previous work, Todisco et al. (2019) analyzed 528 rainfall events from 2008 to 2017 at the Masse experimental station (central Italy) to define and evaluate several thresholds of rainfall characteristics able to classify non-erosive and erosive events. Each threshold value was obtained by imposing that the long-term erosivity of the events above the threshold is equal to the long-term erosivity of all erosive events observed. The evaluation criteria of the thresholds were mainly based on the percentage of correct selections, CSI (number of erosive events selected to the total number of erosive events) and the percentage of wrong selection, WSI (number of non-erosive events to the total number of events selected). The analysis was performed on the basis of a 5-min rainfall dataset.This work aims to evaluate the influence of the rainfall data acquisition time on the thresholds (both in terms of value and accuracy). For this purpose, the Masse experimental station's rainfall dataset was aggregated at a 30-min time interval and then subjected to the same analysis carried out in the previous study. The 30-min time interval has a practical interest since it represents the typical time interval of the Regional Hydrographic Service data.The results indicate that some of the best thresholds identified on the basis of the 5-min database are the best also working on the 30-minute data, with small performance variations (CSI ranging between 55 to 75% and WSI between 15 to 30%). Among the best thresholds can be mentioned: the total event rainfall, Pe (14.4 and 15.2mm for the 5-min and 30-min database, respectively), the kinetic energy of the event, E (2.4 and 2.7MJ ha−1), the rainfall duration above a pre-determined intensity, Drun (0.3 and 0.5h), and the Maximum rainfall amount in a rain shower, P_max_burst (7.6 and 10.2mm). It is evident that the threshold value tends to slightly increase, passing from a 5-min to a 30-min rainfall dataset. Moreover, some thresholds considered effective working on the 5-min dataset, obtained very poor performance on the 30-min database. This happened for some rainfall variables related to the number of runs or showers during the event, such as the Maximum rainfall depth cumulated from the start of the rainfall event to the rain shower, Max_P_pre_burst. This poor performance depends on the fact that in the 30-min dataset, the internal structure of the event hyetograph is smoothed and not able to provide relevant information as in the 5-min dataset.The best thresholds identified from the 30-min rainfall dataset will be used in a regional analysis aimed to map the spatial variability of the return periods of erosive events. |
