Soil erosion estimation based on rainfall disaggregation

Jebari, Sihem; Berndtsson, Ronny; Olsson, Jonas; Bahri, Aki√ßa

doi:10.1016/j.jhydrol.2012.03.001

Cited by 41 publications

(30 citation statements)

References 30 publications

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“…The more clayey the B horizon, the more difficult the water infiltration and the more severe the erosion process. In an alluvial soil, which consists of complex units of mineral soils, Jebari et al (2012) recorded erodibility from 0.036 to 0.054 Mg ha h MJ -1 mm -1 . The topography factor (LS) ranged from 0 to 10.83 (Figure 1 b).…”

Section: Resultsmentioning

confidence: 99%

Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5

Carvalho

Durigon

Antunes

et al. 2014

Pesq. agropec. bras.

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-The objective of this work was to evaluate the seasonal variation of soil cover and rainfall erosivity, and their influences on the revised universal soil loss equation (Rusle), in order to estimate watershed soil losses in a temporal scale. Twenty-two TM Landsat 5 images from 1986 to 2009 were used to estimate soil use and management factor (C factor). A corresponding rainfall erosivity factor (R factor) was considered for each image, and the other factors were obtained using the standard Rusle method. Estimated soil losses were grouped into classes and ranged from 0. , respectively. Mean annual soil loss in the watershed was 109.5 Mg ha -1 , but the central area, with a loss of nearly 300.0 Mg ha -1 , was characterized as a site of high water-erosion risk. The use of C factor obtained from remote sensing data, associated to corresponding R factor, was fundamental to evaluate the soil erosion estimated by the Rusle in different seasons, unlike of other studies which keep these factors constant throughout time.Index terms: C factor, rainfall erosivity, remote sensing, soil loss, vegetation index. Predição da erosão do solo com uso da Rusle e séries temporais de NDVI do Landsat 5 TMResumo -O objetivo deste trabalho foi avaliar a variação estacional da cobertura do solo e da erosividade da chuva e suas influências na equação universal de perda de solo revisada (Rusle), para estimar as perdas de solo em uma microbacia, em escala temporal. , mas a área central da bacia, com perdas de aproximadamente 300,0 Mg ha -1 , foi considerada como de alto risco à erosão pela água. O uso do fator C obtido a partir da técnica de sensoriamento remoto, associado ao fator R correspondente, é fundamental para avaliar as perdas de solo estimadas pela Rusle em diferentes épocas do ano, diferentemente de outros estudos em que estes fatores são mantidos constantes ao longo do tempo.Termos para indexação: fator C, erosividade, sensoriamento remoto, perda de solo, índice de vegetação.

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Section: Resultsmentioning

confidence: 99%

Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5

Carvalho

Durigon

Antunes

et al. 2014

Pesq. agropec. bras.

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“…The cascade-based disaggregation model for continuous rainfall time series was suggested by (Olsson, 1995(Olsson, , 1998. The technique was later successfully implemented by (Güntner et al, 2001;Jebari et al, 2012;Rana et al, 2013) for temporal disaggregation of point rainfall and the development of IDF curves from shortduration rainfall extremes. Due to freezing weather conditions during winter, most of the TBRGs' are inoperative from early November to late April of the following year.…”

Section: Infilling Missing Amp Recordmentioning

confidence: 99%

Does nonstationarity in rainfall require nonstationary intensity–duration–frequency curves?

Ganguli

Coulibaly

2017

Hydrol. Earth Syst. Sci.

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Abstract. In Canada, risk of flooding due to heavy rainfall has risen in recent decades; the most notable recent examples include the July 2013 storm in the Greater Toronto region and the May 2017 flood of the Toronto Islands. We investigate nonstationarity and trends in the short-duration precipitation extremes in selected urbanized locations in Southern Ontario, Canada, and evaluate the potential of nonstationary intensity-duration-frequency (IDF) curves, which form an input to civil infrastructural design. Despite apparent signals of nonstationarity in precipitation extremes in all locations, the stationary vs. nonstationary models do not exhibit any significant differences in the design storm intensity, especially for short recurrence intervals (up to 10 years). The signatures of nonstationarity in rainfall extremes do not necessarily imply the use of nonstationary IDFs for design considerations. When comparing the proposed IDFs with current design standards, for return periods (10 years or less) typical for urban drainage design, current design standards require an update of up to 7 %, whereas for longer recurrence intervals (50-100 years), ideal for critical civil infrastructural design, updates ranging between ∼ 2 and 44 % are suggested. We further emphasize that the above findings need re-evaluation in the light of climate change projections since the intensity and frequency of extreme precipitation are expected to intensify due to global warming.

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“…Na obtenção da erosividade, Jebari et al (2012) em uma bacia agrícola na Tunísia, utilizaram a duração de 15 min, visto que as chuvas naquela localidade caracterizamse por serem convectivas em cerca de 70% dos casos com duração inferior a 1 h (JEBARI et al, 2007). Além disso, 12% dos eventos de chuva foram considerados erosivos para a duração de 15 min (JEBARI et al, 2008), causando grande impacto da gota da chuva, com início do processo de desprendimento de partículas do solo.…”

Section: Methodsunclassified

Erosividade sob duas durações de intensidades máximas da chuva em Pelotas - RS

Damé¹,

Teixeira²,

Gonçalves³

et al. 2012

AGRO@MBIENTE

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Palavras-chave -Chuvas intensas. Erosão. Registros pluviográficos. Abstract -In the Universal Equation ofSoil Loss (USLE), erosivity is the factor related to rain and express its potential to cause soil erosion, being necessary to know its kinetic energy and the maximum intensities of rain in duration of 30 min. Thus, the aim of this study was to verify and quantify the impact of the rain duration, considering 15 and 30 min, on the USLE erosivity factor. To achieve this, 863 rain gauge records were used, duiring the period of 1983 to 1998 in the city of Pelotas, RS, obtained from the Agrometeorological Station -Covenant EMBRAPA/UFPel, INMET (31 o 51´S; 52 o 21´O and altitude of 13,2 m). With the records, it was estimated the erosivity values from the maximum intensities of rain during the period evaluated. The average annual values of erosivity was 2551,3 MJ ha -1 h -1 ano -1 and 1406,1 MJ ha -1 h -1 ano -1 , for the average intensities of 6,40 mm h -1 and 3,74 mm h -1 , in durations of 15 and 30 min, respectively. The results of this study have shown that the percentage of erosive rainfalls in relation to the total precipitation was of 91.0%, and that the erosivity was influenced by the duration of the maximum intensity of rain.

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Soil erosion estimation based on rainfall disaggregation

Cited by 41 publications

References 30 publications

Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5

Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5

Does nonstationarity in rainfall require nonstationary intensity–duration–frequency curves?

Erosividade sob duas durações de intensidades máximas da chuva em Pelotas - RS

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