The relation between soil erosion dynamics and landscape pattern variation in the Minjiang River headwaters in Sichuan, China

Author(s):  
C Li ◽  
H Jiang ◽  
O Luukkanen ◽  
Y Liu
2014 ◽  
Vol 24 (1) ◽  
pp. 50-59
Author(s):  
Qingchun Wen ◽  
Xiuzhen Li ◽  
Hongshi He ◽  
Yuanman Hu ◽  
Xin Chen ◽  
...  

Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 990
Author(s):  
Yongfen Zhang ◽  
Nong Wang ◽  
Chongjun Tang ◽  
Shiqiang Zhang ◽  
Yuejun Song ◽  
...  

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.


2020 ◽  
Vol 38 (5) ◽  
pp. 5697-5705
Author(s):  
Jinxin Zhang ◽  
Hui Li ◽  
Xiufang Zhang ◽  
Hua Yu ◽  
Fengna Liang ◽  
...  

2020 ◽  
Author(s):  
Liding Chen

<p>Linking landscape patterns to specific ecological processes has been and will continue to be a key topic in landscape ecology. However, the traditional landscape pattern analysis by landscape metrics inspired by patch-matrix model (PMM) may be difficult to reach such a requirement, and thus landscape pattern analysis to denote the significance of ecological process is strongly hindered. To find conceptual and methodological innovations integrating ecological processes with landscape patterns is important. In this paper, we proposed a conceptual model, i.e., the source-pathway-sink model (SPSM) by defining the role of each landscape unit to a specific process before conducting landscape pattern analysis. The traditional landscape matrices derived from the patch-matrix model is visual- or geometrical-oriented but lack of linkage to ecological significance. The source-pathway-sink model is process-oriented, dynamic, and scale dependent. This model as a complementary to the patch-corridor-matrix model can provide a simple and dynamic perspective on landscape pattern analysis. Based on the SPSM model, a landscape index was developed in term of the process of soil erosion, and further testified by using on-site measurements. It was found the new landscape index based on SPSM is useful in evaluating the risk of soil erosion from landscape pattern at watershed. Finally, a case study was conducted in the loess hilly areas to define the risk area of soil erosion that will be useful for sustainable land use management and optimization in future.</p>


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