Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, H A; Naderi, Mehdi; Demattê, José A. M.; Kerry, Ruth

doi:10.1016/j.geomorph.2016.08.003

Cited by 82 publications

(45 citation statements)

References 31 publications

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“…Hence, predicting the T ‐value using pedotransfer functions (PTFs) could be a good alternative. PTFs are predictive functions that use easily measureable soil properties to predict certain soil properties (Ostovari et al, ). Multiple linear regression (MLR) is one the most common techniques for developing PTFs (Ostovari et al, ).…”

Section: Introductionmentioning

confidence: 99%

Soil loss tolerance in calcareous soils of a semiarid region: evaluation, prediction, and influential parameters

2020

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Predicting soil loss tolerance (T‐value) as a first and crucial step in assessing soil erosion using pedotransfer functions (PTFs) could save time and cost. Therefore, this study aimed to evaluate T‐value and its influential parameters for calcareous soils of the Dorudzan Watershed, Fars Province, Iran, and to develop PTFs for its prediction using easily measureable soil properties. T‐value was determined in 60 soil profiles based on the soil thickness method. Various basic soil properties were used to develop five PTFs using stepwise multiple linear regression. T‐value varied from 3.5 to 22.5 with a mean value of 10.4 t ha−1 yr−1, which is approximately equal to the proposed value by US Department of Agriculture (11 t ha−1 yr−1). T‐value in Inceptisols located in the dam shore and agricultural lands was significantly higher than that of Entisols located in the forest and rangelands. Organic matter (OM) with a correlation coefficient of .77 with T‐value was the most influential variable in prediction of T‐value. The PTF 5, which used OM, soil aggregate stability, and permeability, with the highest R2 (0.72 and 0.79), the lowest mean error (−0.44 and 1.75 t ha−1 yr−1), the lowest root mean square error (2.98 and 2.75 t ha−1 yr−1) and the minimum Akaike information criterion (51.1 and 17.2) provided the best predictions for T‐value. However, when considering the acceptable indices and easier measureable soil properties (OM, soil erodibility, and pH) in PTF 3, we concluded that it was the best model to predict T‐value. Generally, the application of thickness method is recommended to determine T‐value in semiarid regions.

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Section: Introductionmentioning

confidence: 99%

Soil loss tolerance in calcareous soils of a semiarid region: evaluation, prediction, and influential parameters

2020

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“…In the RUSLE model, the k factor is used to compute the average annual erosion (Renard et al, ), which depends on the soil physical properties (Angima et al, ). The accuracy of the k data determines the efficiency of the RUSLE model (Ostovari et al, ). The k can be evaluated in terms of its relationships with intrinsic soil properties and exogenic erosive forces.…”

Section: Introductionmentioning

confidence: 99%

Factors Affecting the Spatial and Temporal Variations in Soil Erodibility of China

et al. 2019

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Soil erosion occurs extensively across China, leading to severe degradation of the land and ecosystem services. However, the spatial and temporal variations in soil erodibility (k) and the distribution of soil erosion across land use types and slopes remain unclear. We synthesized the results from 325 sites published in 152 literatures to analyze the factors affecting the k, such as land use type, climate, topography, soil, and vegetation restoration age. The results showed that areas with slopes >25° had a larger k factor (k = 0.1047) than did those with slope <6° (k = 0.0637) or 6–25° (k = 0.0832). The k from 2006 to 2011 (k = 0.0725) was higher than that from 1999 to 2005 (k = 0.058) and that from 2012 to 2016 (k = 0.0631). The k value initially increased with vegetation restoration age and then gradually decreased. Land use also had an impact on the k factor, with the k factor of cropland (k = 0.0697) being higher than that of grassland (k = 0.0663) but lower than that of forest (k = 0.0967). Across China, North Shaanxi, Heilongjiang, and South Guizhou, which are located in the Loess Plateau in Northwest China, the Black Soil region of Northeast China, and the Karst areas in Southwest China, respectively, were the three most severely eroded regions due to hydraulic erosion, frost‐thaw erosion, and high‐intensity erosion, respectively. Overall, the most important factors affecting the k were soil characteristics, followed by topography and climate. Among them, soil nitrogen and precipitation were the two most critical factors influencing the k.

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“…However this method is time and labour consuming. Therefore since field measurements are expensive, difficult and sometimes hard to be conducted in the large scale, researchers have developed pedo-transfer functions which indicate a relationship between certain soil property and readily available soil properties to predict soil erodibility (Panagos et al, 2012;Ostovari et al, 2015;Ostovari et al, 2016). The soil erodibility factor k for a series of benchmark soils was obtained by direct soil loss measurement from fallow plot located in many U.S States (Swab et al, 1993).…”

Section: Estimation (Determination) Of Usle K-factormentioning

confidence: 99%

“…Because of the high cost of field installations and time involved, direct measurements of erodibility have been made on some bench-mark soils in USA (Schwab et al, 1993). Since field measurements are expensive, difficult and sometimes hard to be conducted in the large scale, researchers have developed pedotransfer functions which indicate a relationship between certain soil property and readily available soil properties to predict soil erodibility (Panagos et al, 2012;Ostovari et al, 2015;Ostovari et al, 2016). Wishmeier and Mannering (1969) proposed an erodibility equation, utilizing fifteen (15) soil properties and their interactions.…”

Section: Introductionmentioning

confidence: 99%

Estimating Erodibility Factor in Soils of Uyo, South-South Nigeria

Udoumoh¹,

Manuel²,

Precious³

et al. 2018

Int.J.Curr.Res.Aca.Rev.

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Soil erosion is a result of many factors such as rainfall intensity steepness of slope, length of slope, vegetative cover, soil erodibility factor as well as anthropogenic influences. Among these factors, soil erodibility is considered an essential parameter since it governs the ease with which soil particles are detached and transported by water. At the centre of this study is the determination of the erodibility factor (otherwise known as K factor) in the Wischmeier Universal Soil Loss Equation (USLE). The erodibility was determined by measuring four basic parameters closely related with the soil physical status: soil texture, soil structure, soil permeability, and organic matter content of the soil. Twenty four samples of surface and subsurface soils were collected from three gully erosion sites in Uyo watershed which were used to measure the above mentioned parameters in order to determine the K-factor. Using the model developed by Wichmeier and Smith (1978), the K factor was calculated for each soil sample when appropriate data are entered in a proper sequence. The permeability class as well as soil structure codes were determined using the United States Department of Agriculture (USDA) document published in 1983. The Wischmeier equation, among many erosion models, seems obviously to be the most realistic one, because it considers all the possible soil factors affecting soil erodibility. The K factor values obtained were found to be between 0.269Mg.h.MJ-1 mm-1 to 0.325Mg.h.MJ-1 mm-1 , which means that there is a slight variation in Uyo soils with respect to their behaviour towards erodibility or consequently towards erosion. It was discovered that the most significant variable or parameter on soil erodibility was silt and coarse sand whereas the less significant variable was clay. This study reveals the proneness and susceptibility of soils with high silt content to structural breakdown and consequently erosion.

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Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

Cited by 82 publications

References 31 publications

Soil loss tolerance in calcareous soils of a semiarid region: evaluation, prediction, and influential parameters

Soil loss tolerance in calcareous soils of a semiarid region: evaluation, prediction, and influential parameters

Factors Affecting the Spatial and Temporal Variations in Soil Erodibility of China

Estimating Erodibility Factor in Soils of Uyo, South-South Nigeria

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