Effects of grass contour hedgerow systems on controlling soil erosion in red soil hilly areas, Southeast China

Soil erosion (SE) processes are closely related to natural conditions and human activities, posing a threat to environment and society. Identifying the human impact on regional SE changes is increasingly essential for pertinent SE management. Jiangxi province is studied here as a representative area of hilly-red-soil regions within southern China. The main objectives of this study were to investigate the changing trend of SE within Jiangxi and identify human impacts on regional SE change from the perspective of spatial differences, through a new approach based on a gravity-center model. Our results showed that SE status presented an overall amelioration from 1990 to 2015, while the average soil erosion modulus (SEM) declined from 864 to 281 Mg/(km2·a). Compared to the situation under human and natural impacts, human-induced spatial differences of SE change demonstrated that the western and northwest regions showed stronger negative effects; the southern region shifted towards negative effects; the northeast region presented a much weaker negative effect. Our results indicated that 4 cities with strong negative effects need more attention in further SE management suited to their local conditions and development, and also suggested that the approach based on a gravity-center has potential for identifying the human impact on regional SE change from the perspective of spatial patterns.

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Benefit Analyses of Soil and Water Conservation: A Case Study in a Hilly Red Soil Area in Southeast China

2011 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring ◽

10.1109/cdciem.2011.156 ◽

2011 ◽

Author(s):

Huang Hong ◽

Cao Wenzhi ◽

Li Ying ◽

Su Caixia ◽

Zhong Binglin ◽

...

Keyword(s):

Water Conservation ◽

Red Soil ◽

Soil And Water Conservation ◽

Southeast China ◽

Soil And Water ◽

Soil Area

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Soil Erosion and Nutrient Cycling on Sloping Upland Ecosystems of Red Soil in Southern China

Soil Erosion and Dryland Farming ◽

10.1201/9781482274523-30 ◽

2000 ◽

pp. 219-232

Keyword(s):

Soil Erosion ◽

Nutrient Cycling ◽

Southern China ◽

Red Soil

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Distribution of soil nutrients and erodibility factor under different soil types in an erosion region of Southeast China

PeerJ ◽

10.7717/peerj.11630 ◽

2021 ◽

Vol 9 ◽

pp. e11630

Author(s):

Man Liu ◽

Guilin Han

Keyword(s):

Soil Erosion ◽

Soil Nutrients ◽

Soil Ph ◽

Major Elements ◽

Soil Types ◽

Soil Erodibility ◽

Soil Evolution ◽

Southeast China ◽

Red Soils ◽

K Factor

Background Soil erosion can affect the distribution of soil nutrients, which restricts soil productivity. However, it is still a challenge to understand the response of soil nutrients to erosion under different soil types. Methods The distribution of soil nutrients, including soil organic carbon (SOC), soil organic nitrogen (SON), and soil major elements (expressed as Al2O3, CaO, Fe2O3, K2O, Na2O, MgO, TiO2, and SiO2), were analyzed in the profiles from yellow soils, red soils, and lateritic red soils in an erosion region of Southeast China. Soil erodibility K factor calculated on the Erosion Productivity Impact Calculator (EPIC) model was used to indicate erosion risk of surface soils (0∼30 cm depth). The relationships between these soil properties were explored by Spearman’s rank correlation analysis, further to determine the factors that affected the distribution of SOC, SON, and soil major elements under different soil types. Results The K factors in the red soils were significantly lower than those in the yellow soils and significantly higher than those in the lateritic red soils. The SON concentrations in the deep layer of the yellow soils were twice larger than those in the red soils and lateritic red soils, while the SOC concentrations between them were not significantly different. The concentrations of most major elements, except Al2O3 and SiO2, in the yellow soils, were significantly larger than those in the red soils and lateritic red soils. Moreover, the concentrations of major metal elements positively correlated with silt proportions and SiO2 concentrations positively correlated with sand proportions at the 0∼80 cm depth in the yellow soils. Soil major elements depended on both soil evolution and soil erosion in the surface layer of yellow soils. In the yellow soils below the 80 cm depth, soil pH positively correlated with K2O, Na2O, and CaO concentrations, while negatively correlated with Fe2O3 concentrations, which was controlled by the processes of soil evolution. The concentrations of soil major elements did not significantly correlate with soil pH or particle distribution in the red soils and lateritic red soils, likely associated with intricate factors. Conclusions These results suggest that soil nutrients and soil erodibility K factor in the yellow soils were higher than those in the lateritic red soils and red soils. The distribution of soil nutrients is controlled by soil erosion and soil evolution in the erosion region of Southeast China.

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Effects of Land Use and Slope Gradient on Soil Erosion in a Red Soil Hilly Watershed of Southern China

Sustainability ◽

10.3390/su71014309 ◽

2015 ◽

Vol 7 (10) ◽

pp. 14309-14325 ◽

Cited By ~ 28

Author(s):

Zhanyu Zhang ◽

Liting Sheng ◽

Jie Yang ◽

Xiao-An Chen ◽

Lili Kong ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

Southern China ◽

Red Soil ◽

Slope Gradient ◽

Hilly Watershed ◽

Effects Of Land Use

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Mechanized and Optimized Configuration Pattern of Crop-Mulberry Systems for Controlling Agricultural Non-Point Source Pollution on Sloping Farmland in the Three Gorges Reservoir Area, China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17103599 ◽

2020 ◽

Vol 17 (10) ◽

pp. 3599

Author(s):

Shouqin Zhong ◽

Zhen Han ◽

Jiangwen Li ◽

Deti Xie ◽

Qingyuan Yang ◽

...

Keyword(s):

Soil Erosion ◽

Three Gorges Reservoir ◽

Three Gorges Reservoir Area ◽

Three Gorges ◽

Point Source Pollution ◽

The Three Gorges ◽

Contour Hedgerow ◽

Sloping Farmland ◽

Contour Hedgerows ◽

Non Point Source Pollution

High-intensity utilization of sloping farmland causes serious soil erosion and agricultural non-point source pollution (AGNSP) in the Three Gorges Reservoir Area (TGRA). Crop-mulberry systems are important agroforestry systems for controlling soil, water, and nutrient losses. However, there are many different mulberry hedgerow planting patterns in the TGRA. In this study, soil structure, nutrient buildup, and runoff nutrient loss were observed in field runoff plots with five configurations: P1 (two longitudinal mulberry hedgerows), P2 (two mulberry contour hedgerows), P3 (three mulberry contour hedgerows), P4 (mulberry hedgerow border), and P5 (mulberry hedgerow border and one mulberry contour hedgerow), as well as a control (CT; no mulberry hedgerows). P1 had the smallest percentage of aggregate destruction (18.8%) and largest mean weight diameter (4.48 mm). P5 led to the greatest accumulation of ammonium nitrogen (NH4+–N) and total phosphorus (TP) (13.4 kg ha−1 and 1444.5 kg ha−1 on average, respectively), while P4 led to the greatest accumulation of available phosphorus (AP), nitrate nitrogen (NO3−–N), and total nitrogen (TN) (114.0, 14.9, and 1694.1 kg ha−1, respectively). P5 was best at preventing soil erosion, with the smallest average annual runoff and sediment loss of 112.2 m3 ha−1 and 0.06 t ha−1, respectively, which were over 72.4% and 87.4% lower than those in CT, respectively. P5 and P4 intercepted the most N in runoff, with average NH4+–N, NO3−–N, particulate N, and TN losses of approximately 0.09, 0.07, 0.41, and 0.58 kg ha−1, respectively, which were 49.7%, 76.2%, 71.3%, and 69.9% lower than those in CT, respectively. P5 intercepted the most P in runoff, with average TP and total dissolved phosphorus (TDP) losses of 0.09 and 0.04 kg ha−1, respectively, which were 77.5% and 70.4% lower than those in CT, respectively. Therefore, the pattern with one mulberry hedgerow border and one mulberry contour hedgerow (P5) best controlled AGNSP, followed by that with only a mulberry hedgerow border (P4).

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Impacts of collapsing gullies on the dynamics of soil organic carbon in the red soil hilly region of southeast China

CATENA ◽

10.1016/j.catena.2020.104547 ◽

2020 ◽

Vol 190 ◽

pp. 104547

Author(s):

Yue Zhang ◽

Dongfeng Zhao ◽

Jinshi Lin ◽

Lin Jiang ◽

Bifei Huang ◽

...

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Red Soil ◽

Southeast China ◽

Hilly Region ◽

Red Soil Hilly Region

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A Remote Sensing Based Method to Detect Soil Erosion in Forests

Remote Sensing ◽

10.3390/rs11050513 ◽

2019 ◽

Vol 11 (5) ◽

pp. 513 ◽

Cited By ~ 4

Author(s):

Hanqiu Xu ◽

Xiujuan Hu ◽

Huade Guan ◽

Bobo Zhang ◽

Meiya Wang ◽

...

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Soil Loss ◽

Southern China ◽

Red Soil ◽

Forest Area ◽

Landsat 8 ◽

Large Spatial Scale ◽

Five Factors

Rainwater-induced soil erosion occurring in the forest is a special phenomenon of soil erosion in many red soil areas. Detection of such soil erosion is essential for developing land management to reduce soil loss in areas including southern China and other red soil regions of the world. Remotely sensed canopy cover is often used to determine the potential of soil erosion over a large spatial scale, which, however, becomes less useful in forest areas. This study proposes a new remote sensing method to detect soil erosion under forest canopy and presents a case study in a forest area in southern China. Five factors that are closely related to soil erosion in forest were used as discriminators to develop the model. These factors include fractional vegetation coverage, nitrogen reflectance index, yellow leaf index, bare soil index and slope. They quantitatively represent vegetation density, vegetation health status, soil exposure intensity and terrain steepness that are considered relevant to forest soil erosion. These five factors can all be derived from remote sensing imagery based on related thematic indices or algorithms. The five factors were integrated to create the soil erosion under forest model (SEUFM) through Principal Components Analysis (PCA) or a multiplication method. The case study in the forest area in Changting County of southern China with a Landsat 8 image shows that the first principal component-based SEUFM achieves an overall accuracy close to 90%, while the multiplication-based model reaches 81%. The detected locations of soil erosion in forest provide the target areas to be managed from further soil loss. The proposed method provides a tool to understand more about soil erosion in forested areas where soil erosion is usually not considered an issue. Therefore, the method is useful for soil conservation in forest.

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