Detailed Analysis of Spatial–Temporal Variability of Rainfall Erosivity and Erosivity Density in the Central and Southern Pannonian Basin

Abstract

Estimation of rainfall erosivity (RE) and erosivity density (ED) is essential for understanding the complex relationships between hydrological and soil erosion processes. The main objective of this study is to assess the spatial–temporal trends and variability of the RE and ED in the central and southern Pannonian Basin by using station observations and gridded datasets. To assess RE and ED, precipitation data for 14 meteorological stations, 225 grid points. and an erosion model consisting of daily, monthly, seasonal, and annual rainfall for the period of 1961–2014 were used. Annual RE and ED based on station data match spatially variable patterns of precipitation, with higher values in the southwest (2100 MJ·mm·ha−1·h−1) and southeast (1650 MJ·mm·ha−1·h−1) of the study area, but minimal values in the northern part (700 MJ·mm·ha−1·h−1). On the other hand, gridded datasets display more detailed RE and ED spatial–temporal variability, with the values ranging from 250 to 2800 MJ·mm·ha−1·h−1. The identified trends are showing increasing values of RE (ranging between 0.20 and 21.17 MJ·mm·ha−1·h−1) and ED (ranging between 0.01 and 0.03 MJ·ha−1·h−1) at the annual level. This tendency is also observed for autumn RE (from 5.55 to 0.37 MJ·mm·ha−1·h−1) and ED (from 0.05 to 0.01 MJ·ha−1·h−1), as for spring RE (from 1.00 to 0.01 MJ·mm·ha−1·h−1) and ED (from 0.04 to 0.01 MJ·ha−1·h−1), due to the influence of the large-scale processes of climate variability, with North Atlantic Oscillation (NAO) being the most prominent. These increases may cause a transition to a higher erosive class in the future, thus raising concerns about this type of hydro-meteorological hazard in this part of the Pannonian Basin. The present analysis identifies seasons and places of greatest erosion risk, which is the starting point for implementing suitable mitigation measures at local to regional scales.

Estimation of potential soil erosion reduction using GIS-based RUSLE under different land cover management models: A case study of Pale Municipality, B&H

“…Similar studies have also been conducted in surrounding countries (Diodato, 2006;Mikoš et al, 2010;Simic Belnovic et al, 2013;Valjarević et al, 2014;Blinkov, 2015;Zdruli et al, 2016;Traykova-Pavlova et al, 2017;Bon Gregorič et al, 2018;Micić Ponjiger et al, 2021;Milentijević et al, 2021;Pandey et al, 2021). The RUSLE method in combination with GIS has been used in numerous modern works and research studies (Kouli et al, 2008;Prasannakumar et al, 2012;Tošić et al, 2013;Blackey et al, 2015;Efthimiou, 2016;Nasir and Selvakumar, 2018;Lanorte et al, 2019;Nolė et al, 2020;Polykretis et al, 2020;Milentijević et al, 2021;Sánchez Sánchez et al, 2021), which led to very satisfactory results.…”

Global assessment of storm disaster-prone areas

“…As such, RED reflects not only the component of climate forcing reproduced in the aggressiveness of the storm (rainfall erosivity), but also the damaging hazard and its associated hydrological risk [ 18 ]. In particular, RED values > 3.0 MJ ha -1 h -1 indicate an increased risk of erosive rainstorms, soil erosion and flooding [ 57 ]. This critical threshold value was popularised in storm geomorphology by Dabney et al [ 58 ] as the runoff increases when RED exceeds 3 MJ hm -2 h -1 , thus leading to an increasing erosive hazard as storm erosivity represents a large proportion of the rainfall amount in an intense event.…”

“…For instance, major tropical forest regions like Amazon and African regions are less vulnerable to hydrological hazards than Southeast Asia [ 64 ]. When RED values are > 1 MJ ha -1 h -1 , only a certain amount of precipitation can cause relatively high erosivity [ 57 ]. Therefore, we adopted two threshold values as follows: RED exceeds the threshold of 1.5 MJ hm -2 h -1 in the warning state and exceeds 3.0 MJ hm -2 h -1 in the alert state.…”

“…For instance, major tropical forest regions like Amazon and African regions are less vulnerable to hydrological hazards than Southeast Asia [64]. When RED values are > 1 MJ ha -1 h -1 , only a certain amount of precipitation can cause relatively high erosivity [57]. Therefore,…”

Integrating forest windthrow assessment data in the process of windscape reconstruction: Case of the extratropical storms downscaled for the Gutai Mountains (Romania)

“…Understanding the behavior of air flow in high wind situations over complex topographic surfaces, covered by forest vegetation, is essential in various practical domains, from forest and road infrastructure management to tourism (Gardiner et al, 2017). The evolution of storms and their impact on human society explain the great interest to study their frequency, intensity, trajectory, etc., objectifying the need to compute and display large datasets in a fast and accurate way (Gardiner et al, 2010(Gardiner et al, , 2013Schindler et al, 2012;Suvanto et al, 2016;Szwagrzyk et al, 2018;Lukić et al, 2021;Ponjiger et al, 2021). These efforts intensified especially after the storms Lothar and Martin (December 26 and 27, 1999 respectively), some of the most catastrophic events of the last century in Europe.…”