An improved method for calculating slope length (λ) and the LS parameters of the Revised Universal Soil Loss Equation for large watersheds

Zhang, Hongming; Wei, Jicheng; Yang, Qinke; Baartman, Jantiene; Gai, Lingtong; Yang, Xiaomei; Li, Shu Qin; Yu, Jinxin; Ritsema, C.J.; Geissen, Violette

doi:10.1016/j.geoderma.2017.08.006

Cited by 93 publications

(40 citation statements)

References 30 publications

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“…This is especially problematic for computing the slope-length factor L, which is the most difficult factor to calculate among the six factors of the USLE. To approximate the shape of the hillslopes and compute the slope length λ in Equation 2, different methods have been proposed, such as Hickey [31] and Sextante [32], the unit contributing area [33,34], and a combination of the unit contributing area and LS-TOOL [35]. In addition, Foster and Wischmeier [36] propose dividing a slope into segments.…”

Section: Grid Cells and Slope Unitsmentioning

confidence: 99%

Soil Erosion Modeling and Comparison Using Slope Units and Grid Cells in Shihmen Reservoir Watershed in Northern Taiwan

Liu

Chen

et al. 2018

Water

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Soil erosion is a global problem that will become worse as a result of climate change. While many parts of the world are speculating about the effect of increased rainfall intensity and frequency on soil erosion, Taiwan’s mountainous areas are already facing the power of rainfall erosivity more than six times the global average. To improve the modeling ability of extreme rainfall conditions on highly rugged terrains, we use two analysis units to simulate soil erosion at the Shihmen reservoir watershed in northern Taiwan. The first one is the grid cell method, which divides the study area into 10 m by 10 m grid cells. The second one is the slope unit method, which divides the study area using natural breaks in landform. We compared the modeling results with field measurements of erosion pins. To our surprise, the grid cell method is much more accurate in predicting soil erosion than the slope unit method, although the slope unit method resembles the real terrains much better than the grid cell method. The average erosion pin measurement is 6.5 mm in the Shihmen reservoir watershed, which is equivalent to 90.6 t ha−1 yr−1 of soil erosion.

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Section: Grid Cells and Slope Unitsmentioning

confidence: 99%

Soil Erosion Modeling and Comparison Using Slope Units and Grid Cells in Shihmen Reservoir Watershed in Northern Taiwan

Liu

Chen

et al. 2018

Water

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“…In the upstream Minjiang watershed, many mountainous areas are with >20° slopes [24,28]. Therefore, the slopes cannot be quantified by the slope factor formula of the U.S. general soil erosion equation (applicable for an area with a maximum slope of 15 degrees) [6,30]. Instead, the empirical formula developed in the Fujian area is used for the calculation [28,31]: …where λ is the slope length (m) and θ is the slope angle (°).…”

Section: Calculation and Results Of Each Factormentioning

confidence: 99%

Quantitative Evaluation of Soil Erosion in the Upper Minjiang River Basin of China Based on Integration of Geospatial Technologies Using RUSLE

Ye¹,

Hua²,

Huang³

et al. 2020

Pol. J. Environ. Stud.

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Soil erosion is an important part of land ecological change and global environmental change. In southern China, the red soil hilly area is a region with serious soil erosion and water and soil loss. In this study, the spatial distribution of soil erosion and its change induced by land use types were obtained with the spatial operation analysis technology of a geographic information system and the revised universal soil loss equation model (RUSLE). The results show that soil erosion is most very lightly eroded in the study area as a whole, and has a wide yet relatively concentrated distribution, namely spatial aggregation distribution. The average soil erosion rate is the highest in Zhenghe County, followed by Wuyishan City, Shunchang County and Changting County, and relatively low in other counties. Further analysis on soil erosion under different land use types shows that erosion is more serious in unused land, orchard, dry land and rural settlements, and less severe in grassland, urban land, woodland and paddy field. This can be explained by the differences in vegetation cover, soil and water conservation measures, and the degree of human disturbance under different land use patterns.

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“…The differences in correlation between ELEV and total runoff depth, TN and TP can be mainly attributed to land use and soil vertical zone differentiation in the TGRA. Slope gradient and length proved to be the main topographic factors affecting soil erosion [23,54,55]. As for SLO, some studies have demonstrated that infiltration and, consequently, runoff, is independent of SLO [56], or may even decrease with rising SLO levels, because the larger erosion on steeper slopes can reduce surface sealing [57].…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, land cover will change the soil structure to some extent, and then soil texture and structure will affect surface runoff generation, as well as its infiltration, lateral flow and nutrient losses [18]. Meanwhile, topographic terrain (including elevation, slope gradient, and slope length) are also important influential factors [20,23]. However, factors in different studies showed different correlations with runoff and nutrient loss processes.…”

Section: Introductionmentioning

confidence: 99%

Spatial Variation Pattern Analysis of Hydrologic Processes and Water Quality in Three Gorges Reservoir Area

Chen

Zhang

et al. 2019

Water

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The Three Gorges Project (TGP) has greatly enhanced the heterogeneity of the underlying surface in the Three Gorges Reservoir Area (TGRA), thereby affecting the hydrologic processes and water quality. However, the influence of the differences of underlying surfaces on the hydrologic processes and water quality in the TGRA has not been studied thoroughly. In this research, the influence of the heterogeneity of landscape pattern and geographical characteristics on the spatial distribution difference of hydrologic processes and water quality in the different tributary basins of the TGRA was identified. The TGRA was divided into 23 tributary basins with 1840 sub-basins. The spatial differentiation of the hydrologic processes and water quality of the 23 tributary basins was examined by the Soil and Water Assessment Tool (SWAT). The observed data between 1 January 2010 and 31 December 2013 were used to calibrate and validate the model, after which the SWAT model was applied to further predict the runoff and water quality in the TGRA. There are 25 main model parameters, including CN2, CH_K2 and SOL_AWC, which were calibrated and validated with SWAT-Calibration and Uncertainty Procedures (SWAT-CUP). The landscape patterns and geomorphologic characteristics in 23 tributary basins were investigated and spatially visualized to correlate with surface runoff and nutrient losses. Due to geographical difference, the average total runoff depth (2010-2013) in the left bank area (538.6 mm) was 1.4 times higher than that in the right bank area (384.5 mm), total nitrogen (TN) loads in the left bank area (6.23 kg/ha) were 1.9 times higher than in the right bank area (3.27 kg/ha), and total phosphorus (TP) loads in the left bank area (1.27 kg/ha) were 2.2 times higher than in the right bank area (0.58 kg/ha). The total runoff depth decreased from the head region (553.3 mm) to the tail region (383.2 mm), while the loads of TN and TP were the highest in the middle region (5.51 kg/ha for TN, 1.15 kg/ha for TP), followed by the tail region (5.15 kg/ha for TN, 1.12 kg/ha for TP) and head region (3.92 kg/ha for TN, 0.56 kg/ha for TP). Owing to the different spatial distributions of land use, soil and geographical features in the TGRA, correlations between elevation, slope gradient, slope length and total runoff depth, TN and TP, were not clear and no consistency was observed in each tributary basin. Therefore, the management and control schemes of the water security of the TGRA should be adapted to local conditions.

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An improved method for calculating slope length (λ) and the LS parameters of the Revised Universal Soil Loss Equation for large watersheds

Cited by 93 publications

References 30 publications

Soil Erosion Modeling and Comparison Using Slope Units and Grid Cells in Shihmen Reservoir Watershed in Northern Taiwan

Soil Erosion Modeling and Comparison Using Slope Units and Grid Cells in Shihmen Reservoir Watershed in Northern Taiwan

Quantitative Evaluation of Soil Erosion in the Upper Minjiang River Basin of China Based on Integration of Geospatial Technologies Using RUSLE

Spatial Variation Pattern Analysis of Hydrologic Processes and Water Quality in Three Gorges Reservoir Area

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