Slope Steepness Effects on Soil Loss from Disturbed Lands

Mclsaac, Gregory F.; Mitchell, James K.; Hirschi, M. C.

doi:10.13031/2013.30513

Cited by 24 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The slope factor from the USLE was modified by McCool et al [98,99] after extensive evaluation of the original database as in the following equations: S = 10.8sinθ + 0.03; sinθ < 0.09 (10) S = 16.8sinθ − 0.50; sinθ ≥ 0.09 (11) where θ is the slope angle, which is based on an evaluation of data from disturbed lands with slopes of up to 84%. McIssac et al [100] developed an equation similar to Equations ( 10) and (11) with exponents in the same range, and McCool et al [99] stated that Equations ( 10) and ( 11) can also be used for disturbed lands.…”

Section: Main Factorsmentioning

confidence: 99%

“…The erosion rate in disturbed and agricultural lands generally increased with an increase in the slope steepness and slope length [99][100][101][102][103]. However, in natural hillslopes, it was frequently found that soil erosion decreases with an increase in the slope steepness and slope length because of the increasing depression storage and roughness factor, infiltration, and subsurface flow [54,[104][105][106][107].…”

Section: Main Factorsmentioning

confidence: 99%

See 1 more Smart Citation

Risk Assessment of Soil Erosion Using a GIS-Based SEMMA in Post-Fire and Managed Watershed

2022

View full text Add to dashboard Cite

A large wildfire occurred due to strong winds and dry climates in the Gangwon province of South Korea. Thereafter, floods and sediment damage were caused by Typhoon Mitag in the burned areas. This study was an attempt to quantitatively evaluate the risk of soil erosion in wildfire areas using the Soil Erosion Model for Mountain Areas (SEMMA) based on GIS, which was developed in South Korea. The model required the integration of maps of the main factors involved, i.e., rainfall erosivity, vegetation index, soil erodibility, and slope length and steepness. According to the model simulation results, high erosion rates of over 100 t/ha were concentrated within the wildfire areas. Sediment yields from the study watershed, including the wildfire areas, were estimated to be 40.33 t/ha for the 30-year frequency of rainfall, which is similar to those of the typhoon. The high risk of erosion was predominantly observed in the upper mountains, which are characterized by steep slopes, silt loam, and shallow soil depths within the wildfire areas. Urgent and excessive logging of burned trees further increased the risk of erosion. However, various treatment strategies were implemented to control soil erosion and sediment transport from the post-fire watershed. This study confirmed that temporal and spatial BMPs should be selected and enforced to reduce sediment disasters in wildfire areas.

show abstract

Section: Main Factorsmentioning

confidence: 99%

Section: Main Factorsmentioning

confidence: 99%

Risk Assessment of Soil Erosion Using a GIS-Based SEMMA in Post-Fire and Managed Watershed

2022

View full text Add to dashboard Cite

show abstract

“…C, es el factor cultivo (vegetación o de uso del suelo) P, es el factor de prácticas de conservación de suelos agrícolas Las parcelas de erosión usadas para desarrollar las relaciones empíricas fueron suelos agrícolas, es decir, tierras de cultivo, de textura media, sobre pendientes que variaban de 0,5 % a 25 % y con longitudes de pendiente que iban de 11 m a 180 m . Se esperaban estimaciones confiables sobre la cantidad de erosión bajo condiciones estrechamente similares a partir de las cuáles las relaciones empíricas habían sido derivadas (Mclsaac et al, 1987). Debido a tales limitaciones, se estandarizaron todas las variables involucradas en el modelo y por consiguiente, se evaluaron las potenciales aplicaciones y limitaciones de la USLE .…”

Section: S C P (1)unclassified

“…La constante de proporcionalidad para la relación de Zingg, combinó los efectos de la precipitación, cosecha y manejo (Mclsaac et al, 1987). Zingg es "a menudo señalado como el diseñador de la primera ecuación de predicción de erosión" (Lane et al, 1988).…”

Section: Efecto Del Gradiente De Pendiente En La Pérdida De Suelounclassified

“…El modelo USLE no se aplica en longitudes más cortas que aproximadamente 4 m , porque para tales longitudes de pendiente, la pérdida del suelo puede atribuirse principalmente a la erosión en interregueros (el impacto de la gota de agua y donde la escorrentía simplemente descarga al final de la pendiente), siendo despreciable la erosión en regueros. Consecuentemente, las ecuaciones 10, 32 y 33 qué se desarrollaron de parcelas de erosión de 22,13 m de longitud (Mclsaac et al, 1987), no pueden aplicarse a cualquier gradiente de pendiente, si la longitud de pendiente es ≤ 4 m (McCool et al, 1987).…”

Section: Efecto De La Longitud De Pendiente En La Pérdida De Suelounclassified

See 1 more Smart Citation

Metodología de cálculo del factor topográfico, LS, integrado en los modelos Rusle y Usped. Aplicación al arroyo del lugar, Guadalajara (España).

Suárez¹

View full text Add to dashboard Cite

show abstract

Investigating reservoir sediment and watershed erosion using a geographical information system

Chang

Bayes²,

McKeever³

2003

Hydrological Processes

View full text Add to dashboard Cite

Abstract:Most economic developments may have been at the expense of soil conservation. Soil erosion results in impacts on reservoir sediment, crop yield, and water quality. This study introduces the procedure of using a geographical information system for investigating reservoir sediments and soil erosion of the corresponding watershed. First, the bathymetric surface of a reservoir is surveyed using two real-time kinematic global position systems and a sonar-based depth gauge. Using the on-board computer, receivers, and sonar, bathymetric readings are recorded three times a second to establish actual coordinates and depth measurements. Data are then converted using a digital terrain model to obtain the current image bathymetric surface. The image of original bathymetric surfaces when constructed can be obtained by digitizing the existing map. The subtraction of these two images is used to estimate the amount of sediment deposits. Next, parameters of rainfall-runoff erosivity factor, soil erodibility factor, slope length factor, slope steepness factor, cover-management factor, and support practice factor are evaluated for each grid of the corresponding watershed. The average annual soil loss from each grid is estimated by the revised universal soil loss equation to obtain the total amount of the soil loss for the watershed. Using the example of Charles Mill Lake, Ohio, USA, the estimated average amount of sediment deposits in the lake was about 2Ð44 ð 10 4 m 3 year 1 . On the other hand, the estimated soil erosion from the corresponding watershed was about 4Ð22 ð 10 8 kg year 1 or 1Ð56 ð 10 5 m 3 year 1 . Hence, it can be concluded that about 15Ð6% of the soils eroded from the watershed have been deposited in the lake.

show abstract

Slope Steepness Effects on Soil Loss from Disturbed Lands

Cited by 24 publications

References 0 publications

Risk Assessment of Soil Erosion Using a GIS-Based SEMMA in Post-Fire and Managed Watershed

Risk Assessment of Soil Erosion Using a GIS-Based SEMMA in Post-Fire and Managed Watershed

Metodología de cálculo del factor topográfico, LS, integrado en los modelos Rusle y Usped. Aplicación al arroyo del lugar, Guadalajara (España).

Investigating reservoir sediment and watershed erosion using a geographical information system

Contact Info

Product

Resources

About