scholarly journals Response of runoff and soil loss to reforestation and rainfall type in red soil region of southern China

2010 ◽  
Vol 22 (11) ◽  
pp. 1765-1773 ◽  
Author(s):  
Zhigang Huang ◽  
Zhiyun Ouyang ◽  
Fengrui Li ◽  
Hua Zheng ◽  
Xiaoke Wang
Keyword(s):  
Soil Loss ◽  
Southern China ◽  
Red Soil ◽  
Rainfall Type ◽  
Runoff And Soil Loss

scholarly journals A Remote Sensing Based Method to Detect Soil Erosion in Forests

2019 ◽  
Vol 11 (5) ◽  
pp. 513 ◽  
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.

scholarly journals Adapting the WEPP hillslope model to predict unpaved road soil erosion in southern China

2021 ◽  
Author(s):  
Longxi Cao ◽  
Ting Zhang ◽  
Yi Wang
Keyword(s):  
South China ◽  
Soil Loss ◽  
Laser Scanning ◽  
Southern China ◽  
Critical Shear Stress ◽  
Red Soil ◽  
Unpaved Roads ◽  
Erosion Risk ◽  
Low Efficiency ◽  
Road Segments

Process-based erosion models are efficient tools that can be used to predict where and when erosion occurs. On unpaved roads that have been recognized as important sediment sources, soil loss along road segments should be precisely predicted. This study was performed using the hillslope version of the Water Erosion Prediction Project (WEPP) to estimate soil loss from 20 typical road segments in the red soil region of South China. Terrestrial laser scanning (TLS)-measured soil losses were used to validate the model simulations. The results showed that the WEPP model could reasonably predict the total soil loss in relatively short (less than 100 m) and gentle (slope gradient lower than 10%) road segments. In contrast, the WEPP-simulated soil loss was underestimated for long or steep road segments. Detailed outputs along roads revealed that most of the peak soil loss rates could not be adequately calculated. The linear critical shear stress and the sediment equilibrium theory in the WEPP model for soil detachment simulation might be responsible for the underestimation. Additionally, the lack of upslope flow and the curved road tortuosity were found to be connected to the relatively low efficiency of the model outputs. Nevertheless, the WEPP simulation could accurately fit the trend of soil loss variation along road segments despite underestimation. Furthermore, the simulated results could provide a reliable prediction of the maximum soil loss positions. Therefore, the WEPP model could be adopted to evaluate the erosion risk of unpaved roads in the red soil region of South China.

Runoff and soil loss from Pinus massoniana forest in southern China after simulated rainfall

CATENA ◽  
2015 ◽  
Vol 129 ◽  
pp. 1-8 ◽  
Author(s):  
Longxi Cao ◽  
Yin Liang ◽  
Yi Wang ◽  
Huizhong Lu
Keyword(s):  
Soil Loss ◽  
Southern China ◽  
Pinus Massoniana ◽  
Simulated Rainfall ◽  
Runoff And Soil Loss

ASSESSMENT OF SOIL EROSION IN VINH LINH, QUANG TRI USING RMMF MODEL (REVISED MORGAN - MORGAN - FINNEY)

2013 ◽  
Vol 83 (5) ◽  
Author(s):  
Nguyễn Quang Việt ◽  
Trương Đình Trọng ◽  
Hồ Thị Nga
Keyword(s):  
Soil Erosion ◽  
Land Cover ◽  
Soil Loss ◽  
Soil Particle ◽  
Transport Capacity ◽  
Gis Technology ◽  
Particle Detachment ◽  
Sediment Transport Capacity ◽  
Northern District ◽  
Runoff And Soil Loss

Vinh Linh, the northern district of Quang Tri province is characterized by a diversified topography with a large variety of elevations, high rainfall, and decreasing land cover due to forest exploiting for cultivation land. Thus, there is a high risk of erosion, soil fertility washout. With the support of GIS technology, the authors used the rMMF model to measure soil erosion. The input data of model including 15 coefficients related to topography, soil properties, climate and land cover. The simulations of rMMF include estimates of rainfall energy, runoff, soil particle detachment by raindrop, soil particle detachment by runoff, sediment transport capacity of runoff and soil loss. The result showed that amount of soil loss in year is estimated to vary between 0 kg/m2 minimum and 149 kg/m2 maximum and is divided into 4-classes of erosion. Light class almost covers the region researched (75.9% of total area), while moderate class occupies 8.1% of total area, strong classes only hold small area (16% of total area). Therefore, protection of the forest floor in sloping areas is one of the most effective methods to reduce soil erosion.

Runoff and Soil Loss of a Typical Subtropical Forest Stricken by Wenchuan Earthquake

2013 ◽  
Vol 19 (5) ◽  
pp. 766-773
Author(s):  
Jinniu WANG ◽  
Geng SUN ◽  
Fusun SHI ◽  
Jiceng XU ◽  
Yan WU ◽  
...  
Keyword(s):  
Wenchuan Earthquake ◽  
Soil Loss ◽  
Subtropical Forest ◽  
Runoff And Soil Loss

scholarly journals Evaluating of the spatial heterogeneity of soil loss tolerance and its effects on erosion risk in the carbonate areas of southern China

Solid Earth ◽  
2017 ◽  
Vol 8 (3) ◽  
pp. 661-669 ◽  
Author(s):  
Yue Li ◽  
Xiao Yong Bai ◽  
Shi Jie Wang ◽  
Luo Yi Qin ◽  
Yi Chao Tian ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Spatial Heterogeneity ◽  
Soil Loss ◽  
Carbonate Rock ◽  
Southern China ◽  
Clastic Rock ◽  
Erosion Risk ◽  
Soil Loss Tolerance ◽  
Loss Tolerance ◽  
The Relationship

Abstract. Soil loss tolerance (T value) is one of the criteria in determining the necessity of erosion control measures and ecological restoration strategy. However, the validity of this criterion in subtropical karst regions is strongly disputed. In this study, T value is calculated based on soil formation rate by using a digital distribution map of carbonate rock assemblage types. Results indicated a spatial heterogeneity and diversity in soil loss tolerance. Instead of only one criterion, a minimum of three criteria should be considered when investigating the carbonate areas of southern China because the one region, one T value concept may not be applicable to this region. T value is proportionate to the amount of argillaceous material, which determines the surface soil thickness of the formations in homogenous carbonate rock areas. Homogenous carbonate rock, carbonate rock intercalated with clastic rock areas and carbonate/clastic rock alternation areas have T values of 20, 50 and 100 t/(km2 a), and they are extremely, severely and moderately sensitive to soil erosion. Karst rocky desertification (KRD) is defined as extreme soil erosion and reflects the risks of erosion. Thus, the relationship between T value and erosion risk is determined using KRD as a parameter. The existence of KRD land is unrelated to the T value, although this parameter indicates erosion sensitivity. Erosion risk is strongly dependent on the relationship between real soil loss (RL) and T value rather than on either erosion intensity or the T value itself. If RL > > T, then the erosion risk is high despite of a low RL. Conversely, if T > > RL, then the soil is safe although RL is high. Overall, these findings may clarify the heterogeneity of T value and its effect on erosion risk in a karst environment.

scholarly journals Identifying Human-Induced Spatial Differences of Soil Erosion Change in a Hilly Red Soil Region of Southern China

2019 ◽  
Vol 11 (11) ◽  
pp. 3103
Author(s):  
Dong Huang ◽  
Xiaohuan Yang ◽  
Hongyan Cai ◽  
Zuolin Xiao ◽  
Dongrui Han
Keyword(s):  
Soil Erosion ◽  
Human Impact ◽  
Human Impacts ◽  
Southern China ◽  
Red Soil ◽  
Jiangxi Province ◽  
Negative Effects ◽  
Gravity Center ◽  
Local Conditions ◽  
Spatial Differences

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.

Sign in / Sign up

Export Citation Format

Share Document