Estimation of Soil Erosion and Sediment Yield Using GIS at Catchment Scale

Bhattarai, Rabin; Dutta, Dushmanta

doi:10.1007/s11269-006-9118-z

Cited by 163 publications

(82 citation statements)

References 27 publications

(27 reference statements)

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“…The slope-steepness factor (S) was evaluated according to equations 5 and 6 presented in McCool et al (1987) for slopes greater than 4 m, which were applied in several studies (BHATTARAI;DUTTA, 2007;CHORWDARY;MAL, 2007;DABRAL;BAITHURI;PANDEY, 2008;BESKOW et al, 2009): Spatial distribution of water erosion...…”

Section: Usle Parametersmentioning

confidence: 99%

“…Modeling is a tool to provide a quantitative and consistent approach to predict soil loss and the sediment delivery ratio under a wide range of conditions (BHATTARAI;DUTTA, 2007). In addition, it can be used to evaluate hypotheses and determine the appropriate soil management and land use for each site (TUCCI, 1998).…”

Section: Introductionmentioning

confidence: 99%

“…Simple empirical methods, such as the Universal Soil Loss Equation (USLE) (WISCHMEIER;SMITH, 1978), have been used for the assessment of soil erosion at the watershed scale (BHATTARAI; DUTTA, 2007;CHOWDARY;MAL, 2007;DABRAL;BAITHURI;PANDY, 2008;BESKOW et al, 2009). The USLE is the simplest and most widely used model for erosion prediction, which estimates the long-term annual average rate of erosion with generally acceptable accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Spatial distribution of water erosion risk in a watershed with eucalyptus and Atlantic Forest

et al. 2013

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The process of water erosion occurs in watersheds throughout the world and it is strongly affected by anthropogenic influences. Thus, the knowledge of these processes is extremely necessary for planning of conservation efforts. This study was performed in an experimental forested watershed in order to predict the average potential annual soil loss by water erosion using the Universal Soil Loss Equation (USLE) and a Geographic Information System (GIS), and then compared with soil loss tolerance. All the USLE factors were generated in a distributed approach employing a GIS tool. The layers were multiplied in the GIS framework in order to predict soil erosion rates. Results showed that the average soil loss was 6.2 Mg ha -1 yr -1 . Relative to soil loss tolerance, 83% of the area had an erosion rate lesser than the tolerable value. According to soil loss classes, 49% of the watershed had erosion less than 2.5 Mg ha -1 yr -1 . However, about 8.7% of the watershed had erosion rates greater than 15 Mg ha -1 yr -1 , being mainly related to Plinthosol soil class and roads, thus requiring special attention for the improvement of sustainable management practices for such areas. Eucalyptus cultivation was found to have soil loss greater than Atlantic Forest. Thus, an effort should be made to bring the erosion rates closer to the native forest. Implementation of the USLE model in a GIS framework was found to be a simple and useful tool for predicting the spatial variation of soil erosion risk and identifying critical areas for conservation efforts.Index terms: Forest systems, soil losses, USLE, GIS, coastal plain. RESUMOO processo de erosão hídrica ocorre em todo mundo sendo fortemente afetado por influências antrópicas. Assim, o conhecimento desses processos é extremamente necessário para o planejamento de práticas de conservação do solo. O estudo foi conduzido em uma bacia hidrográfica experimental florestada com o objetivo de estimar o potencial médio de perdas de solo anuais por erosão hídrica, utilizando a Equação Universal de Perdas de Solo (EUPS) inserida no Sistema de Informação Geográfica (SIG), e comparar com a tolerância de perdas de solo. Todos os fatores da EUPS foram gerados de forma distribuída utilizando a plataforma SIG. Os mapas foram multiplicados no ambiente SIG para estimar as taxas de erosão do solo. Os resultados mostraram que a perda de solo média foi de 6,2 Mg ha -1 ano -1 . Em relação à tolerância de perdas de solo, 83% apresentaram taxas de erosão menores que o valor de tolerância permitido. Com relação às classes de perdas de solo, 49% da bacia tiveram perdas de solo menores que 2,5 Mg ha -1 ano -1 . Entretanto, cerca de 8,7% da área da bacia apontaram taxas de erosão maiores que 15 Mg ha -1 ano -1 , estando, principalmente, relacionada à classe de solo Plintossolo e as estradas, exigindo uma atenção especial para conduzir um manejo sustentável nessas áreas. O cultivo de eucalipto mostrou perdas de solo maiores que a Mata Atlântica. Desse modo, um esforço deve ser realizado a fim de aprox...

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Section: Usle Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spatial distribution of water erosion risk in a watershed with eucalyptus and Atlantic Forest

et al. 2013

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“…Thus, water erosion modeling is an important and consistent tool to defining areas more susceptible to soil loss, which considers spatial and temporal variability of characteristics that interfere in the eroding process (Bhattarai;Dutta, 2007).…”

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confidence: 99%

Spatial and Temporal Modeling of Water Erosion in Dystrophic Red Latosol (Oxisol) Used for Farming and Cattle Raising Activities in a Sub-Basin in the South of Minas Gerais

et al. 2015

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Water erosion is one of the most important soil degradation processes and it can be intensified by land use and vegetal covering changes. Thus, water erosion modeling studies associated to multi temporal analyses of land use are effective in assessing how changes in land cover affects sediment yield. Therefore, considering the modifications in the land use from 1986 to 2011, the aim of this study ranged to estimate water erosion rates and compare them to the soil loss tolerance (SLT) limit in the Latosols (Oxisols) at Ribeirão Caçús sub-basin, in the South of Minas Gerais State, Southeast Brazil, by means of the Revised Universal Soil Loss Equation (RUSLE) in association with the geographic information system (GIS), and geostatistical techniques. So, for each year mapped, soil loss averages were compared by t test at 5% significance to assess the soil degradation stage. The results indicated that, in the period, the soil loss average rate was from 2.4 to 2.6 Mg ha -1 year -1 and the areas with soil loss above the limit of SLT were around 8.0%. The t test demonstrated there was no considerable difference among the soil loss averages (p = 0.18). In consequence, the area of degraded soils did not increase. Thus, the RUSLE model in GIS is a simple and useful tool to estimate the soil loss and help define soil conservation and recovery measures.

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“…Tais dados derivaram do MDE Topodata, filtrado pela função PIT do TauDEM 5.0, que remove os pixels com valores anômalos. O MDE Topodata apresenta acurácia na obtenção desses dados pela resolução de 30 m, similar à parcela empírica padrão da USLE de 22,13 m (Bhattarai & Dutta 2007). Assim, a equação para estimativa do fator LS foi: LS = (a * resolution/ 22,13) 0,4 * (sen θ/ 0,0896), em que LS é o fator topográfico da teoria da potência do escoamento; a é a área de contribuição hidrológica derivada do algoritmo D∞ e da extensão TauDEM 5.0; e θ é a declividade em graus.…”

Section: Atributos Solosunclassified