Quantitative evaluation of soil erosion of land subsided by coal mining using RUSLE

2012 ◽  
Vol 22 (1) ◽  
pp. 7-11 ◽  
Author(s):  
Lei Meng ◽  
Qiyan Feng ◽  
Kan Wu ◽  
Qingjun Meng
2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Liu Ning ◽  
Zhao Xiao-Guang ◽  
Song Shi-Jie ◽  
Zhou Wen-Fu

Underground coal mining will cause large-scale surrounding rock movement, resulting in surface subsidence and irreversible deformation of surface morphology, which would lead to geological disasters and ecological environment problems. In this paper, FLAC3D numerical model is built based on the natural slope gradient, slope type, and included angle between the slope and working face, and their influences on the change of surface morphology and soil erosion caused by underground coal mining is studied. Research results show that the change of slope gradient caused by underground mining decreases with the increase of natural slope gradient, while slope length has opposite laws; different slope types have different changes of slope morphology. The order of slope types corresponding to gradient changes is mixed slope < uniform slope < concave slope < convex slope; the length of the concave and uniform slope decreases, and the convex and mixed slope length increases. When the included angle between the slope and working face is 0° ≤ α < 90°, the underground mining will cause the natural slope gradient increase, the change of the slope gradient will increase with the rise of the angle, the slope length will decrease, and the rate of decrease will be reduced with the increase of the angle. Coal mining will cause the increasing of the runoff and erosion modulus of slope, mainly runoff modulus.


2011 ◽  
Vol 225-226 ◽  
pp. 1246-1249
Author(s):  
Jie Tang ◽  
Yao Ji

This paper partitioned five major coal mining areas respectively in central, southern and eastern Jilin Province for case study based on current situation of exploitation and distribution of coal resources through artificial neural network(ANN) and the 3S technology to gain soil erosion loss mass. On the basis of RUSLE equation, BP neural network is fused to gain the rainfall erosion index of higher precision than those of traditional method. By extracting of indices and raster calculation on the platform of ERDAS and ArcGIS software, we made predication of soil erosion loss of the coal mining areas. After verification, the precision of rainfall erosion index is high, and thus improved the predicting accuracy of soil erosion. Comparative analysis shows that the soil erosion in central section of Jilin Province has much lower intensity, and high degree erosion occurred in the east and south mostly.


2021 ◽  
Vol 41 (10) ◽  
Author(s):  
韩旭,田培,黄建武,王珂珂,王瑾钰,刘目兴,潘成忠 HAN Xu

2021 ◽  
Author(s):  
William Rapuc ◽  
Julien Bouchez ◽  
Pierre Sabatier ◽  
Kim Genuite ◽  
Jérôme Poulenard ◽  
...  

&lt;p&gt;Soil erosion is one of the main environmental threats affecting the Critical Zone (CZ) and thus ecosystem services and human societies. This represents an emerging concern considered as one of the geosciences/society central issues. Through time, the physical erosion is linked to both, precipitation amounts induced by climate fluctuations, and the evolution of vegetation cover and land-use. Understanding these forcing factors is key to improve our management of this resource, especially in mountainous areas where CZ erosion is highest. Only studies combining large spatial and temporal approaches allow to assess the effect of these forcing factors on soil erosion rates. Here, we apply a retrospective approach based on lake sediments to reconstruct the long-term evolution of erosion in Alpine landscapes. Lake Iseo located in northern Italy at the downstream end of the Val Camonica acts as a natural sink for all the erosion products from a large watershed (1777 km&amp;#178;). This watershed is representative of the southern Italian Alps, where Holocene human activity and climate fluctuations are well known. The approach combines a source-to-sink method, using isotopic geochemistry (&amp;#949;Nd, &lt;sup&gt;87&lt;/sup&gt;Sr/&lt;sup&gt;86&lt;/sup&gt;Sr), with a multiproxy study of a lacustrine sediment section covering the last 2000 years. The applied methodology allows us to disentangle the role of climate and land use as erosion forcing factors through their differential impact on the various rock types present in the watershed. Indeed, the high-altitudinal part of the Val Camonica, the erosion of which is dominated by glacier advances and retreats, presents isotopic signature different from those of the sedimentary rocks located in the lower part of the watershed, where both human activities and precipitations impacted erosion through time. A chronicle of glacial erosion over the last 2000 years was produced. Once the climatic trend was highlighted, the signal of erosion of sedimentary rocks was investigated to understand the influence of humans. From the Roman Period to the Industrial Age several period of deforestation and increased human pressure were documented. The past sediment yield inferred for sedimentary rocks exhibits the highest values (&gt; 80 t.km&lt;sup&gt;-2&lt;/sup&gt;.yr&lt;sup&gt;-1&lt;/sup&gt;) at periods of intense human practices. Hence, since the late Roman Period, human activities seem to be the dominant forcing factor of the physical erosion in mountainous environment of northern Italy. This study presents the first reconstruction through time of sediment yield derived from lake sediment associated with sediment sources identification and quantitative evaluation of the erosion forcing factors.&lt;/p&gt;


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