Impact of Disdrometer Types on Rainfall Erosivity Estimation

Abstract

Soil erosion by water is affected by the rainfall erosivity, which controls the initial detachment and mobilization of soil particles. Rainfall erosivity is expressed through the rainfall intensity (I) and the rainfall kinetic energy (KE). KE–I relationships are an important tool for rainfall erosivity estimation, when direct measurement of KE is not possible. However, the rainfall erosivity estimation varies depending on the chosen KE–I relationship, as the development of KE–I relationships is affected by the measurement method, geographical rainfall patterns and data handling. This study investigated how the development of KE–I relationships and rainfall erosivity estimation is affected by the use of different disdrometer types. Rainfall data were collected in 1-min intervals from six optical disdrometers at three measurement sites in Austria, one site in Czech Republic and one site in New Zealand. The disdrometers included two disdrometers of each of the following types: the PWS100 Present Weather Sensor from Campbell Scientific, the Laser Precipitation Monitor from Thies Clima and the first generation Parsivel from OTT Hydromet. The fit of KE–I relationships from the literature varied among disdrometers and sites. Drop size and velocity distributions and developed KE–I relationships were device-specific and showed similarities for disdrometers of the same type across measurement sites. This hindered direct comparison of results from different types of disdrometers, even when placed at the same site. Thus, to discern spatial differences in rainfall characteristics the same type of measurement instrument should be used.

SfM‐MVS Photogrammetry for Splash Erosion Monitoring under Natural Rainfall

“…The same issue occurred due to missing disdrometers for a small number of rainfall events, and there were generally some differences between the disdrometer devices at each of the sites. However, these obstacles were resolved by comparing the instruments (Johannsen et al, 2020a) and deriving regression equations for converting the kinetic energy (Johannsen et al, 2020b).…”

“…However, disdrometers were not located at all sites all the time. In periods without disdrometer measurements, regression equations were derived for each location and for each device, by means of which these rainfall characteristics were calculated (Johannsen et al, 2020b). The general parameters of the sites and the measured data (total and maximum single event values) within the project period are presented in Table 2.…”

Rainfall Parameters Affecting Splash Erosion under Natural Conditions

“…When the raindrop size and velocity is not directly measured, the rainfall KE is estimated from the experimentally based equations between rainfall intensity and KE from other studies. Theoretically obtained rainfall KE could underestimate or overestimate the real KE [38][39][40]. Furthermore, DSD obtained from other studies can significantly vary depending on rain type and geographical location [41].…”

“…However, higher average monthly EI 30 and erosivity density compared to the Petzenkirchen site were caused by intensive storms recorded in June and August 2018 ( Figure 3). It should be noted that calculated mean drop diameter could be affected by differences in measured drop size distributions between the disdrometer types used in the study [40].…”

“…For the periods when the disdrometer data were not available due to disruptions or errors, the KE was calculated based on KE and intensity relationships developed for the three sites, according to the data investigated in Johannsen et al [40]. The KE is presented as the function of the intensity, which was available from the rain gauge.…”