Spatial and temporal variations of rainfall-runoff erosivity (R) factor in Kakheti, Georgia

Tsitsagi, Mariam; Berdzenishvili, Ana; Gugeshashvili, M.

doi:10.1016/j.aasci.2018.03.010

Cited by 20 publications

(12 citation statements)

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“…Farming, habitation, terracing, deforestation, and overgrazing are some of the activities which lead to increased soil erosion rates. Soil erosion process has three distinct phases: detachability, transportability, and deposition [27][28][29]. Soil erosion process begins with detachment, where breakdown of soil particles occurs due to raindrop impact, shearing, and/or the drag force possessed by wind or even through forces that result from tillage activities [24,[30][31][32].…”

Section: Soil Erosion Processmentioning

confidence: 99%

“…Waterborne erosion is more pronounced when the two rainfall attributes are on the higher side [86]. Rainfall erosivity factor (R) quantifies the erosive power possessed by rainfall, and it much depends on the rainfall's intensity and amount [29,60,86]. e R factor is expressed as the sum of EI-values for each particular storm for a year and averaged for over long periods of time (more than 20 years) so as to accommodate discernible recurring rainfall patterns [29].…”

Section: Rainfall Erosivity Factor (R)mentioning

confidence: 99%

“…e storm erosivity index reflects the amalgamated effect of soil particle dislodgement and runoff transportability to cause net erosion [29]. e mean of the annual sums for the period under consideration gives the rainfall erosivity factor (R factor).…”

Section: Rainfall Erosivity Factor (R)mentioning

confidence: 99%

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Soil Loss Assessment Using the Revised Universal Soil Loss Equation (RUSLE) Model

Luvai

Obiero

Omuto

2022

Applied and Environmental Soil Science

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Many catchment areas have suffered from exhaustive changes because of various land use activities over the recent past. These land use changes are associated with intensified environmental degradation witnessed in catchment areas. Such environmental problems include extreme soil erosion. Soil erosion is one of the most critical problems responsible for the degradation of land worldwide. This phenomenon occurs as a result of the complex interactions that exist between natural and human-induced factors. Most factors experience spatiotemporal variations, hence complicating the soil erosion phenomenon. This complexity in the erosion process makes it difficult to quantify soil loss. Without proper information on soil loss, it becomes quite hard for decision-makers and managers to manage catchment areas. However, the availability of soil erosion models has made it easy to estimate soil loss. Many models have been developed to consider these complexities in soil erosion studies. Empirical models such as RUSLE provide a simple and broad methodology through which soil erosion is assessed. The RUSLE model integrates well geographic information system (GIS) and above all remote sensing. This paper presents an overview of the developmental milestones in estimating soil loss using the RUSLE model. The parameterization of the RUSLE model has been adequately reviewed with much emphasis on challenges and successes in derivation of each individual factor. From the review, it was established that different equations have been developed by researchers for modeling the five factors for the RUSLE model. The development of such equations was found to take into account the different variations that depict the soil erosion process.

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Section: Soil Erosion Processmentioning

confidence: 99%

Section: Rainfall Erosivity Factor (R)mentioning

confidence: 99%

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Soil Loss Assessment Using the Revised Universal Soil Loss Equation (RUSLE) Model

Luvai

Obiero

Omuto

2022

Applied and Environmental Soil Science

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“…Vega e Flebes (2007) ressaltam que a agressividade das chuvas está relacionada com a energia cinética, que embora pouco discutido em meteorologia e climatologia, é fundamental na agricultura e silvicultura devido à sua contribuição substancial para a erosão e degradação dos solos. Tsitsagi et al (2018) afirmam que vários eventos de chuvas muito intensas são responsáveis pela maior proporção de erosão do solo.…”

Section: Introductionunclassified

Index of rain aggressiveness and erosivity in different climate types in Brazil

Galatto

Souza

Back

2023

CLIUM

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Heavy rains are responsible for triggering erosion processes and landslides. Knowledge of the spatial variation of rainfall aggressiveness makes it possible to plan land use and propose prevention and mitigation measures. This work aims to evaluate the rainfall aggressiveness indices and relate them to the climatic types in Brazil. Estimated monthly precipitation data were used for each Brazilian municipality and the Fournier (IF), Modified Fournier (IFM) and Total Erosivity Index (TEI) indexes were calculated. The data were geoprocessed and correlated with the climate types in Brazil, according to the Köppen classification. The IF ranged from 7.3 to 110.5 with 47.5% of the territory classified as “Moderate erosivity”. The IFM ranged from 48 to 388 with 76% in the “Very High” erosivity class and 16.0% “High”. The climate types Af, Am Cfb, Cwa and Cwb are classified as “Moderate erosivity” or higher. The TSI ranged from 444 to 4977 and 54.3% had “High” erosivity and 31.5% “Moderate”. The climate type Am presented the highest mean TSI followed by Aw, Af, As, CWa and Cwb, with TSI above 2000. The lowest TSI values were observed in the Cfa and Cfb climates, followed by the BSh climate.

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“…Under the background of global climate change, the soil erosion rate varies due to various reasons, among which the most direct reason is the changes in rainfall erosivity (Tsitsagi et al 2018). The general soil loss equation (USLE) put forward by Wischmeier and Smith (1978) and the revised USLE (Renard et al 1991) are most commonly used to calculate soil erosion rate.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal evolutionary analysis of rainfall erosivity during 1901–2017 in Beijing, China

Liu

Zhang

et al. 2021

Environ Sci Pollut Res

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Rainfall erosivity is regarded as one of the main factors affected soil erosion. Based on the 117 a monthly precipitation data of Beijing from 1901 to 2017, the temporal and spatial variation characteristics of rainfall erosivity in Beijing were analyzed by using Theil-Sen median analysis (Sen) and the Mann-Kendall (MK) trend test, R/S analysis method, cumulative anomaly method , MK mutation test method, Pettitt test, and wavelet analysis. The results showed that the average annual rainfall erosivity in Beijing ranged from 1080.6 to 6432.78 MJ • mm / (hm 2 • h • a), with an average value of 3465.06 MJ • mm / (hm 2 • h • a), showing a gradual decrease from southeast to northwest. In the seasonal distribution, 86% of rainfall erosivity was mainly concentrated in summer. In the past 117 years, the annual rainfall erosivity in most areas of Beijing had shown a downward trend, but its future trend also showed an increasing trend, indicating that Beijing, especially the northern part, was facing greater potential pressure of soil erosion. Through the cross validation of various methods, the abrupt change interval of rainfall erosivity in Beijing from 1901 to 2017 was from 1994 to 1997. The change of rainfall erosivity in Beijing has strong oscillation in 32 years and small periodic change in 15 and 7 years. The results will provide decision-making basis for soil erosion control and water/soil conservation planning.Additionally, they will be benefited to ensure the national agricultural and food security.

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Spatial and temporal variations of rainfall-runoff erosivity (R) factor in Kakheti, Georgia

Cited by 20 publications

References 12 publications

Soil Loss Assessment Using the Revised Universal Soil Loss Equation (RUSLE) Model

Soil Loss Assessment Using the Revised Universal Soil Loss Equation (RUSLE) Model

Index of rain aggressiveness and erosivity in different climate types in Brazil

Spatiotemporal evolutionary analysis of rainfall erosivity during 1901–2017 in Beijing, China

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