Rainfall Erosivity in Soil Erosion Processes

Bellocchi, Gianni; Diodato, Nazzareno

doi:10.3390/w12030722

Cited by 6 publications

(2 citation statements)

References 15 publications

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“…It depends on the physical attributes of precipitation, such as the size, dispersion, kinetic energy, and velocity of the raindrops (Ahmed Mohamed Abd Elbasit, 2013). Since sediment and nutrient losses are mostly caused by rainfall erosivity, farmers may be at risk of crop failures, and landscape equilibrium states may become unstable (Panagos, et al, 2015).An important component regulating water erosion in terrestrial ecosystems and other harmful hydrological phenomena, such as oods and ash oods, is the exposure of the Earth's surface to intense rainfall (Gianni Bellocchi and Nazzareno Diodato, 2020).A measurement of the erosive force of rainfall is called rainfall erosivity. Erosivity is determined by rainfall kinetic energy, which in turn strongly depends on rainfall intensity (Anton Vrielinga.…”

Section: Introductionmentioning

confidence: 99%

Geospatial Assessment of Aridity and Erosivi̇ty Indices in Northwest Somalia Usi̇ng the Corine Model

Ahmed,

Nur,

MOHAMED

et al. 2024

Preprint

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The degree of soil erosion depends on the erodibility of the soil and the erosive agents. The primary energy source for soil detachment and transport in water erosion processes is rain and runoff. In the northwest region of Somalia, we thoroughly evaluated the aridity and erosivity indices. This study, aridity and erosivity indices and arid periods of Woqoyi Galbeed were assessed. In the CORINE methodology, four parameters are used to evaluate the potential and actual soil erosion risks: Soil erodibility, erosivity, topography (slope), and land cover. Fournier Precipitation Index and Bagnouls-Gaussen Drought Index were calculated using rainfall data that were measured from 2011–2019 in the region and temperature data that were taken from 50 meteorological stations. The study illustrates that most of the study area is under moderate erosion risk. Although a small portion of the Southern parts of the study areas have high erosion risk, these areas have low erosion risk due to the very steep slope. The Erosivity Index quantifies the effect of rainfall impact and also reflects the amount and rate of runoff likely to be associated with precipitation events. Evaluating the result of MFI and BGI overlaid shows that there is low erosivity risk in the northern part of the country. It includes the Bossaso, Aburin, Dararweyne, Burco, Xudun and Iskushuban weather stations. It is covering the area of 204978, 65km2, which represents 32.14% of the study area. This indicates that Northern part of the country, annual rainfall is low, whereas some areas like Erigabo and gebiley are relatively moderate in the MFI.

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Section: Introductionmentioning

confidence: 99%

Geospatial Assessment of Aridity and Erosivi̇ty Indices in Northwest Somalia Usi̇ng the Corine Model

Ahmed,

Nur,

MOHAMED

et al. 2024

Preprint

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“…Thus, it is important to use more than one image for the characterization of land uses from classification techniques. Several researchers have analyzed the temporal distribution of soil losses to identify the periods of the year that are the most prone to erosive processes (Bellocchi and Diodato, 2020;Rutebuka et al, 2020;Zhu et al, 2021). Understanding the temporal variations in land use helps in making decisions regarding the monitoring and management of watersheds.…”

Section: Introductionmentioning

confidence: 99%

Soil loss estimated by means of the RUSLE model in a subtropical climate watershed

Zanchin¹,

Moura²,

Nunes³

et al. 2021

Revista Brasileira De Ciência Do Solo

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Erosion process occurs naturally, shaping the Earth's surface. Soil loss can cause harmful effects to the environment when intensive anthropic activities occur. Mathematical models have been used as effective and less costly alternatives for identifying sites highly prone to soil loss, especially at the watershed scale. In Brazil, the Revised Universal Soil Loss Equation (RUSLE) is one of the most commonly used soil loss prediction models. The RUSLE requires information on soil erodibility, rainfall erosivity, topography, land use and cover (C), and conservation practices (P) to estimate average annual soil losses. Images derived from remote sensing techniques are generally used to quantify the spatialization of C factor; however, the variation in land use throughout the year is not usually considered. This study aimed to estimate soil losses in an important subwatershed of Candiota river watershed (CRWsub) by using RUSLE, considering land use and rainfall erosivity in different periods of the year. The periods considered were P1 (January, February and March), P2 (April, May and June), P3 (July, August and September) and P4 (October, November and December). Based on the results, the lowest soil losses occurred in P1. Probably, the high vegetation cover in the soil increases its protection against rainfall erosivity. In P3, the heavy rainfall events are predominantly frontal, occurring in the same months as those when the preparation of the soil for later planting takes place; that is, there is no vegetation cover in this period, thus making the soil more prone to erosion. The use of different images to classify and identify land uses is the best way to understand soil losses throughout the year in the study area. It was possible to observe that agricultural areas are generally associated with greater soil losses in the subwatershed. In addition, the land uses were considered to vary quarterly, thereby making it possible to identify the periods most prone to erosion processes throughout the year. Finally, the erosion percentages in the subwatershed can be linked to the tolerance index for different land-uses, soil classes, and slope categories.

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Soil Erosion Catastrophe in Iraq-Preview, Causes and Study Cases

Eltaif

Gharaibeh

2022

Earth and Environmental Sciences Library

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Rainfall Erosivity in Soil Erosion Processes

Cited by 6 publications

References 15 publications

Geospatial Assessment of Aridity and Erosivi̇ty Indices in Northwest Somalia Usi̇ng the Corine Model

Geospatial Assessment of Aridity and Erosivi̇ty Indices in Northwest Somalia Usi̇ng the Corine Model

Soil loss estimated by means of the RUSLE model in a subtropical climate watershed

Soil Erosion Catastrophe in Iraq-Preview, Causes and Study Cases

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