Global rainfall erosivity projections for 2050 and 2070

Panagos, Panos; Borrelli, Pasquale; Matthews, Francis; Liakos, Leonidas; Bezak, Nejc; Diodato, Nazzareno; Ballabio, Cristiano

doi:10.1016/j.jhydrol.2022.127865

Cited by 80 publications

(45 citation statements)

References 58 publications

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“…We thus offer these results as a springboard to support policy-makers, local authorities and civil protection in planning medium- and long-term actions to reduce hydrological disasters [ 105 – 106 ]. As rainfall erosivity is projected to increase by at least 35% globally by 2070 [ 107 ], the probability of hydrological hazards will also show similar trends.…”

Section: Discussionmentioning

confidence: 99%

Global assessment of storm disaster-prone areas

Diodato¹,

Borrelli

Panagos

et al. 2022

PLoS ONE

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Background Advances in climate change research contribute to improved forecasts of hydrological extremes with potentially severe impacts on human societies and natural landscapes. Rainfall erosivity density (RED), i.e. rainfall erosivity (MJ mm hm-2 h-1 yr-1) per rainfall unit (mm), is a measure of rainstorm aggressiveness and a proxy indicator of damaging hydrological events. Methods and findings Here, using downscaled RED data from 3,625 raingauges worldwide and log-normal ordinary kriging with probability mapping, we identify damaging hydrological hazard-prone areas that exceed warning and alert thresholds (1.5 and 3.0 MJ hm-2 h-1, respectively). Applying exceedance probabilities in a geographical information system shows that, under current climate conditions, hazard-prone areas exceeding a 50% probability cover ~31% and ~19% of the world’s land at warning and alert states, respectively. Conclusion RED is identified as a key driver behind the spatial growth of environmental disruption worldwide (with tropical Latin America, South Africa, India and the Indian Archipelago most affected).

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Section: Discussionmentioning

confidence: 99%

Global assessment of storm disaster-prone areas

Diodato¹,

Borrelli

Panagos

et al. 2022

PLoS ONE

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“…Many studies reported that satellite-based products tend to underestimate the extreme rainfall, which can have an important effect on the estimation of rainfall erosivity based on satellite-based products (Jiang et al, 2019;Palharini et al, 2020;Rahmawati and Lubczynski., 2018). For example, Bezak et al (2022) showed CMORPH estimates had a marked tendency to underestimate rainfall erosivity of high erosive areas when compared to the GloREDa estimates. In addition, underestimation of extreme rainfall from climate models will cause conservative projections of erosivity in high erosive areas 70 in the future (Panagos et al, 2022).…”

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confidence: 99%

“…For example, Bezak et al (2022) showed CMORPH estimates had a marked tendency to underestimate rainfall erosivity of high erosive areas when compared to the GloREDa estimates. In addition, underestimation of extreme rainfall from climate models will cause conservative projections of erosivity in high erosive areas 70 in the future (Panagos et al, 2022). Therefore, it is of great interest to examine the magnitude and frequency of occurrence of rainfall and rainfall erosivity of extreme storm events.…”

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confidence: 99%

“…Since soil erosion is difficult to measure at large scales, soil erosion models are often used for estimating soil loss by water erosion at regional, national and global scales. Rainfall erosivity maps can provide rainfall 40 erosivity values with rainfall observations and without observations and the generation of erosivity maps is one of necessary procedures for estimation of soil loss using most empirical soil erosion models (Bezak et al 2021(Bezak et al , 2022McGehee et al, 2022;Yue et al, 2022). Rainfall erosivity maps were usually generated by the interpolation of rainfall erosivity values from at-site rainfall observations by geostatistics techniques, such as the inverse distance weighting, ordinal Kriging and so on (Panagos et al, 2015;Sadeghi et al, 2017;Yin et al, 2019).…”

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confidence: 99%

“…Temporal variations in rainfall erosivity are important for understanding changes in soil erosion and assessing the future climate change impact on the land degradation. At present, research on the temporal change of rainfall erosivity mainly focuses on past changes (Cao et al, 2018;Qin et al2016;Wang 50 et al, 2022;Yang, 2015;Zhang et al, 2010) and future projections (Kilic et al 2021;Panagos et al, 2022).…”

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The most extreme rainfall erosivity ever recorded in China: The "7.20" rainstorm in Henan Province

Xiao

Yin

et al. 2022

Preprint

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Abstract. Severe water erosion occurs during extreme storm events. Such an extreme storm occurred in Zhengzhou in central China on 20 July 2021 (the “7.20” rainstorm). The magnitude and frequency of occurrence of this storm event were examined in terms of its erosivity values. To contextualize this extreme event, hourly rainfall data from 2420 automatic meteorological stations in China from 1951 to 2021 were analyzed to: (1) characterize the spatial and temporal distribution of rainfall and rainfall erosivity of the “7.20” rainstorm, (2) evaluate the average recurrence interval of the maximum daily and event rainfall erosivity, and (3) establish the geographical distribution of the maximum daily and event rainfall erosivity in China. The center of the “7.20” rainstorm moved from southeast to northwest in Henan province, and the most intense period of rainfall occurred in the middle and late stages of the storm. Zhengzhou meteorological station happened to be aligned with the center of the storm, with a maximum daily rainfall of 552.5 mm and a maximum hourly rainfall intensity of 201.9 mm"∙" h-1. The average recurrence interval of the maximum daily rainfall erosivity (43,354 MJ·mm·ha-1· h-1) and the maximum event rainfall erosivity (58 874 MJ·mm·ha-1·h-1) was estimated to be 109 079 and 154 154 years, respectively, assuming the generalized extreme value distribution, and these were the maximum rainfall erosivity ever recorded among 2420 meteorological stations in mainland China. The “7.20” rainstorm suggests that the most erosive of storms does not necessarily occur in the wettest places in southern China, and it can occur in mid-latitude around 35 °N with a moderate mean annual precipitation of 549.2 mm in Zhengzhou meteorological station.

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Effects of rock outcrops on runoff and erosion from karst slopes under simulated rainfall

Zhang,

Ma,

Qihua

et al. 2023

Land Degrad Dev

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Rock outcrops play a crucial role in affecting hydrological and erosion processes on karst hillslopes. However, due to various difficulties in constructing runoff plots on field rocky slopes, previous studies used small metal flumes to simulate outcropped slopes, which greatly differed from the natural rock outcropped slopes. In this study, the effects of rock outcrops on runoff and erosion were studied on karst slopes with natural soil–rock conditions at a larger plot scale (10 m in length × 2.2 m in width, 25° in gradient). Simulated rainfall experiments were conducted on the four runoff plots with different rock outcrop coverages (0%, 5%, 13%, and 42%) under five rainfall intensities (30, 60, 90, 120, and 150 mm·h−1). The study indicated that the rock outcrops complexed the water erosion processes by playing multiple and opposite roles simultaneously. It positively influences water erosion by serving as impermeable surfaces, providing preferential flow paths, and offering flow barriers to hillslopes. Conversely, it can exacerbate erosion by causing increased runoff, concentrating flow paths, and thus intensifying erosion in specific areas. Besides, the effects of these roles varied with the coverage of rock outcrops and rainfall intensity. The main results showed that (i) limited rock outcrop coverage (5% and 13%) increased runoff and erosion, but the opposite was observed on the severe rocky slope (42%). Both “infiltration‐excess” and “saturation‐excess” mechanisms coexisted by turns on karst slopes during rainfall; the break of “saturation balance” tended to occur on the severe rock outcrop slope with abundant soil–rock interface and underground fissures. (ii) Rock outcrops greatly increased the spatial variability and uncertainty of hydrological and erosion processes on karst slopes. The rock outcrops resulted in a larger range of variation in flow velocity and a greater difference among the three slope positions; it also brought more spatial heterogeneity in the development of rill erosion. (iii) Rock outcrops tended to increase flow velocity, and intensify flow turbulence, stream power, and flow energy. The severe rock outcrops significantly reduced the soil erosion induced by the limited soil detachment. This study contributes to a deeper understanding of the mechanisms behind how rock outcrops influence runoff and erosion and provides insights for improving soil erosion prediction in karst regions.

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Global rainfall erosivity projections for 2050 and 2070

Cited by 80 publications

References 58 publications

Global assessment of storm disaster-prone areas

Global assessment of storm disaster-prone areas

The most extreme rainfall erosivity ever recorded in China: The "7.20" rainstorm in Henan Province

Effects of rock outcrops on runoff and erosion from karst slopes under simulated rainfall

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