Land use, soil erosion, and sediment yield at Pinto Lake, California: comparison of a simplified USLE model with the lake sediment record

Abstract. Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as a soil erosion agent for four different land use/land cover types in a subalpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide depositions, the fallout radionuclide 137Cs and modelling with the Revised Universal Soil Loss Equation (RUSLE). RUSLE permits the evaluation of soil loss by water erosion, the 137Cs method integrates soil loss due to all erosion agents involved, and the measurement of snow glide deposition sediment yield can be directly related to snow-glide-induced erosion. Further, cumulative snow glide distance was measured for the sites in the winter of 2009/2010 and modelled for the surrounding area and long-term average winter precipitation (1959–2010) with the spatial snow glide model (SSGM). Measured snow glide distance confirmed the presence of snow gliding and ranged from 2 to 189 cm, with lower values on the north-facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is an important information with respect to conservation planning and expected and ongoing land use changes in the Alps. Snow glide erosion estimated from the snow glide depositions was highly variable with values ranging from 0.03 to 22.9 t ha−1 yr−1 in the winter of 2012/2013. For sites affected by snow glide deposition, a mean erosion rate of 8.4 t ha−1 yr−1 was found. The difference in long-term erosion rates determined with RUSLE and 137Cs confirms the constant influence of snow-glide-induced erosion, since a large difference (lower proportion of water erosion compared to total net erosion) was observed for sites with high snow glide rates and vice versa. Moreover, the difference between RUSLE and 137Cs erosion rates was related to the measured snow glide distance (R2 = 0.64; p < 0.005) and to the snow deposition sediment yields (R2 = 0.39; p = 0.13). The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding appears to be a crucial and non-negligible process impacting soil erosion patterns and magnitude in subalpine areas with similar topographic and climatic conditions.

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Using SWAT to Evaluate Streamflow and Lake Sediment Loading in the Xinjiang River Basin with Limited Data

Water ◽

10.3390/w12010039 ◽

2019 ◽

Vol 12 (1) ◽

pp. 39 ◽

Cited By ~ 2

Author(s):

Lifeng Yuan ◽

Kenneth J. Forshay

Keyword(s):

Soil Erosion ◽

River Basin ◽

Lake Sediment ◽

Sediment Yield ◽

Sediment Load ◽

Poyang Lake ◽

Sediment Source ◽

Sediment Loading ◽

Source Areas ◽

Annual Sediment

Soil erosion and lake sediment loading are primary concerns of watershed managers around the world. In the Xinjiang River Basin of China, severe soil erosion occurs primarily during monsoon periods, resulting in sediment flow into Poyang Lake and subsequently causing lake water quality deterioration. Here, we identified high-risk soil erosion areas and conditions that drive sediment yield in a watershed system with limited available data to guide localized soil erosion control measures intended to support reduced sediment load into Poyang Lake. We used the Soil and Water Assessment Tool (SWAT) model to simulate monthly and annual sediment yield based on a calibrated SWAT streamflow model, identified where sediment originated, and determined what geographic factors drove the loading within the watershed. We applied monthly and daily streamflow discharge (1985–2009) and monthly suspended sediment load data (1985–2001) to Meigang station to conduct parameter sensitivity analysis, calibration, validation, and uncertainty analysis of the model. The coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE -observation’s standard deviation ratio (RSR) values of the monthly sediment load were 0.63, 0.62, 3.8%, and 0.61 during calibration, respectively. Spatially, the annual sediment yield rate ranged from 3 ton ha−1year−1 on riparian lowlands of the Xinjiang main channel to 33 ton ha−1year−1 on mountain highlands, with a basin-wide mean of 19 ton ha−1year−1. The study showed that 99.9% of the total land area suffered soil loss (greater than 5 ton ha−1year−1). More sediment originated from the southern mountain highlands than from the northern mountain highlands of the Xinjiang river channel. These results suggest that specific land use types and geographic conditions can be identified as hotspots of sediment source with relatively scarce data; in this case, orchards, barren lands, and mountain highlands with slopes greater than 25° were the primary sediment source areas. This study developed a reliable, physically-based streamflow model and illustrates critical source areas and conditions that influence sediment yield.

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Impact of Land Use Change and Dam Construction on Soil Erosion and Sediment Yield in the Black Soil Region, Northeastern China

Land Degradation and Development ◽

10.1002/ldr.2677 ◽

2017 ◽

Vol 28 (4) ◽

pp. 1482-1492 ◽

Cited By ~ 17

Author(s):

Haiyan Fang

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Use Change ◽

Sediment Yield ◽

Black Soil ◽

Northeastern China ◽

Dam Construction ◽

Black Soil Region

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Predicted trends of soil erosion and sediment yield from future land use and climate change scenarios in the Lancang–Mekong River by using the modified RUSLE model

International Soil and Water Conservation Research ◽

10.1016/j.iswcr.2020.06.006 ◽

2020 ◽

Vol 8 (3) ◽

pp. 213-227 ◽

Cited By ~ 1

Author(s):

Pavisorn Chuenchum ◽

Mengzhen Xu ◽

Wenzhe Tang

Keyword(s):

Climate Change ◽

Land Use ◽

Soil Erosion ◽

Sediment Yield ◽

Mekong River ◽

Climate Change Scenarios ◽

Rusle Model

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Historical sediment record of 137Cs, δ-HCH, and δ 13C reflects the impact of land use on soil erosion

Journal of Mountain Science ◽

10.1007/s11629-013-2945-5 ◽

2014 ◽

Vol 11 (4) ◽

pp. 866-874 ◽

Cited By ~ 4

Author(s):

Xiang-Yu Tang ◽

Xin-Bao Zhang ◽

Zhuo Guan ◽

Yi Long ◽

Qiang Tang ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

Sediment Record ◽

Δ 13C ◽

The Impact

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Sediment Fingerprinting for Calibrating a Soil Erosion and Sediment-Yield Model in Mixed Land-Use Watersheds

Journal of Hydrologic Engineering ◽

10.1061/(asce)he.1943-5584.0001011 ◽

2015 ◽

Vol 20 (6) ◽

Cited By ~ 12

Author(s):

James F. Fox ◽

Darren K. Martin

Keyword(s):

Land Use ◽

Soil Erosion ◽

Sediment Yield ◽

Sediment Fingerprinting ◽

Yield Model ◽

Mixed Land Use

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Soil erosion and sediment delivery in a mountain catchment under scenarios of land use change using a spatially distributed numerical model

Hydrology and Earth System Sciences ◽

10.5194/hess-16-1321-2012 ◽

2012 ◽

Vol 16 (5) ◽

pp. 1321-1334 ◽

Cited By ~ 54

Author(s):

L. C. Alatorre ◽

S. Beguería ◽

N. Lana-Renault ◽

A. Navas ◽

J. M. García-Ruiz

Keyword(s):

Land Use ◽

Soil Erosion ◽

Sediment Yield ◽

Model Calibration ◽

Global Optimum ◽

Model Parameters ◽

Sediment Delivery ◽

Yield Data ◽

Good Convergence ◽

Spatially Distributed

Abstract. Soil erosion and sediment yield are strongly affected by land use/land cover (LULC). Spatially distributed erosion models are of great interest to assess the expected effect of LULC changes on soil erosion and sediment yield. However, they can only be applied if spatially distributed data is available for their calibration. In this study the soil erosion and sediment delivery model WATEM/SEDEM was applied to a small (2.84 km2) experimental catchment in the Central Spanish Pyrenees. Model calibration was performed based on a dataset of soil redistribution rates derived from point 137Cs inventories, allowing capture differences per land use in the main model parameters. Model calibration showed a good convergence to a global optimum in the parameter space, which was not possible to attain if only external (not spatially distributed) sediment yield data were available. Validation of the model results against seven years of recorded sediment yield at the catchment outlet was satisfactory. Two LULC scenarios were then modeled to reproduce land use at the beginning of the twentieth century and a hypothetic future scenario, and to compare the simulation results to the current LULC situation. The results show a reduction of about one order of magnitude in gross erosion (3180 to 350 Mg yr−1) and sediment delivery (11.2 to 1.2 Mg yr−1 ha−1) during the last decades as a result of the abandonment of traditional land uses (mostly agriculture) and subsequent vegetation recolonization. The simulation also allowed assessing differences in the sediment sources and sinks within the catchment.

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Evaluating the effect of land use changes on soil erosion and sediment yield using a grid-based distributed modelling approach

Hydrological Processes ◽

10.1002/hyp.9193 ◽

2012 ◽

Vol 26 (23) ◽

pp. 3579-3592 ◽

Cited By ~ 19

Author(s):

Guoqiang Wang ◽

Hong Jiang ◽

Zongxue Xu ◽

Lijing Wang ◽

Weifeng Yue

Keyword(s):

Land Use ◽

Soil Erosion ◽

Sediment Yield ◽

Land Use Changes ◽

Distributed Modelling ◽

Grid Based ◽

Modelling Approach

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A New Indicator to Better Represent the Impact of Landscape Pattern Change on Basin Soil Erosion and Sediment Yield in the Upper Reach of Ganjiang, China

Land ◽

10.3390/land10090990 ◽

2021 ◽

Vol 10 (9) ◽

pp. 990

Author(s):

Yongfen Zhang ◽

Nong Wang ◽

Chongjun Tang ◽

Shiqiang Zhang ◽

Yuejun Song ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

River Basin ◽

Landscape Metrics ◽

Landscape Pattern ◽

Sediment Yield ◽

River Basins ◽

Landscape Patterns ◽

Soil Erodibility ◽

Land Use Pattern

Landscape patterns are a result of the combined action of natural and social factors. Quantifying the relationships between landscape pattern changes, soil erosion, and sediment yield in river basins can provide regulators with a foundation for decision-making. Many studies have investigated how land-use changes and the resulting landscape patterns affect soil erosion in river basins. However, studies examining the effects of terrain, rainfall, soil erodibility, and vegetation cover factors on soil erosion and sediment yield from a landscape pattern perspective remain limited. In this paper, the upper Ganjiang Basin was used as the study area, and the amount of soil erosion and the amount of sediment yield in this basin were first simulated using a hydrological model. The simulated values were then validated. On this basis, new landscape metrics were established through the addition of factors from the revised universal soil loss equation to the land-use pattern. Five combinations of landscape metrics were chosen, and the interactions between the landscape metrics in each combination and their effects on soil erosion and sediment yield in the river basin were examined. The results showed that there were highly similar correlations between the area metrics, between the fragmentation metrics, between the spatial structure metrics, and between the evenness metrics across all the combinations, while the correlations between the shape metrics in Combination 1 (only land use in each year) differed notably from those in the other combinations. The new landscape indicator established based on Combination 4, which integrated the land-use pattern and the terrain, soil erodibility, and rainfall erosivity factors, were the most significantly correlated with the soil erosion and sediment yield of the river basin. Finally, partial least-squares regression models for the soil erosion and sediment yield of the river basin were established based on the five landscape metrics with the highest variable importance in projection scores selected from Combination 4. The results of this study provide a simple approach for quantitatively assessing soil erosion in other river basins for which detailed observation data are lacking.

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