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

Yongfen Zhang,Yuejun Song,Kaitao Liao,Xiaofei Nie,Nong Wang,Chongjun Tang,Shiqiang Zhang

doi:10.3390/land10090990

Yongfen Zhang, Yuejun Song + Show 5 more

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https://doi.org/10.3390/land10090990

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Abstract

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.

Highlights

As a comprehensive reflection of the ecological-environmental system in a region, the landscape pattern is a spatial arrangement of different landscape mosaics that results from the interaction of multiple natural and human factors [1,2]
Based on the monthly runoff and sediment discharge data measured at four hydrological stations in the periods 1980–1985 (P1980s), 1993–1998 (P1995s), and 2005–2010 (P2010s), the sequential uncertainty fitting 2 (SUFI-2) algorithm in the soil and water assessment tool (SWAT) calibration uncertainty program was used to analyze the uncertainty of the output of the SWAT model at each relevant sub-river basin, as well as to calibrate and validate the SWAT model
Five combinations of landscape metrics were chosen for analysis

Summary

Introduction

As a comprehensive reflection of the ecological-environmental system in a region, the landscape pattern is a spatial arrangement of different landscape mosaics that results from the interaction of multiple natural and human factors [1,2]. Studying the response of the water and sediment processes to landscape pattern changes in a river basin from a landscape ecology perspective can to some extent reveal the effects of changes in natural conditions and human activity on the water and sediment in the river basin [5,6,7]. Land use—an important component of a landscape—primarily acts on the vegetation landscape pattern and processes such as hydrological flow. The spatial land-use pattern has notable impacts on runoff, soil erosion, and sediment yield at different scales [8]. PLSR is an important tool for quantitatively studying the relationships between landscape metrics and soil erosion and sediment yield in river basins [9,17,18]

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