Soil erosion spatial distribution simulation of the Jinghe river basin in the Loess Plateau of China

2015 ◽  
pp. 63-70
Author(s):  
G Wu ◽  
D Wang ◽  
Y Wu ◽  
X Chen ◽  
W Wei
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
River Basin ◽  
Loess Plateau ◽  
The Loess Plateau ◽  
Jinghe River Basin ◽  
Jinghe River

scholarly journals Spatial Variabilities of Runoff Erosion and Different Underlying Surfaces in the Xihe River Basin

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 352 ◽  
Author(s):  
Ning Wang ◽  
Zhihong Yao ◽  
Wanqing Liu ◽  
Xizhi Lv ◽  
Mengdie Ma
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
River Basin ◽  
Loess Plateau ◽  
Arable Land ◽  
Alluvial Soil ◽  
Underlying Surface ◽  
Spatial Gradient ◽  
Hydrological Process ◽  
The Loess Plateau

Runoff erosion capacity has significant effects on the spatial distribution of soil erosion and soil losses. But few studies have been conducted to evaluate these effects in the Loess Plateau. In this study, an adjusted SWAT model was used to simulate the hydrological process of the Xihe River basin from 1993 to 2012. The spatial variabilities between runoff erosion capacity and underlying surface factors were analyzed by combining spatial gradient analysis and GWR (Geographically Weighted Regression) analysis. The results show that the spatial distribution of runoff erosion capacity in the studying area has the following characteristics: strong in the north, weak in the south, strong in the west, and weak in the east. Topographic factors are the dominant factors of runoff erosion in the upper reaches of the basin. Runoff erosion capacity becomes stronger with the increase of altitude and gradient. In the middle reaches area, the land with low vegetation coverage, as well as arable land, show strong runoff erosion ability. In the downstream areas, the runoff erosion capacity is weak because of better underlying surface conditions. Compared with topographic and vegetation factors, soil factors have less impact on runoff erosion. The red clay and mountain soil in this region have stronger runoff erosion capacities compared with other types of soils, with average runoff modulus of 1.79 × 10−3 m3/s·km2 and 1.68 × 10−3 m3/s·km2, respectively, and runoff erosion power of 0.48 × 10−4 m4/s·km2 and 0.34 × 10−4 m4/s·km2, respectively. The runoff erosion capacity of the alluvial soil is weak, with an average runoff modulus of 0.96 × 10−3 m3/s·km2 and average erosion power of 0.198 × 10−4 m4/s·km2. This study illustrates the spatial distribution characteristics and influencing factors of hydraulic erosion in the Xihe River Basin from the perspective of energy. It contributes to the purposeful utilization of water and soil resources in the Xihe River Basin and provides a theoretical support for controlling the soil erosion in the Hilly-gully region of the Loess Plateau.

scholarly journals Spatial Distribution Characteristics and Optimum Layout of Urban and Rural Areas in Different Geomorphological Types

2020 ◽  
Vol 24 (3) ◽  
pp. 267-275
Author(s):  
Jing Li ◽  
Zhongyuan Cai ◽  
Lianru Duan
Keyword(s):  
Spatial Distribution ◽  
River Basin ◽  
Rural Areas ◽  
Distribution Characteristics ◽  
Rural Settlements ◽  
Spatial Distribution Characteristics ◽  
Jinghe River Basin ◽  
Urban And Rural Areas ◽  
Jinghe River ◽  
Channel Type

Taking Jinghe River Basin in the Loess geomorphological area and Guangnan County in the karst geomorphological area as the study area, the spatial distribution characteristics of urban and rural areas of different geomorphological types are analyzed. By using GIS and related statistical analysis software, this paper summarizes three basic urban and rural types: river channel type, plateau surface type, and loess terrace horizon prototype in the Loess Landscape Jinghe River Basin. It is known that most towns in the loess plateau gully area are in the Jinghe River Basin. According to the spatial distribution characteristics of urban and rural areas, the optimal layout based on the main structure of five districts, nine River corridors, and four plates is proposed. Using the DEM module of ArcGIS to divide the elevation and gradient of Guangnan County, we know that the density of urban and rural settlements in Guangnan County is low and the spatial distribution is dispersed, and the distribution of urban and rural settlements shows a strong elevation orientation. The distribution of urban and rural settlements has a normal distribution relationship with the elevation. The largest number of urban and rural settlements is between 2.1° and 25°. According to the present situation of settlement distribution, this paper puts forward some optimization strategies, such as appropriate settlement scale, settlement space development monitoring, and so on.

scholarly journals Vegetation Restoration Alleviated the Soil Surface Organic Carbon Redistribution in the Hillslope Scale on the Loess Plateau, China

2021 ◽  
Vol 8 ◽  
Author(s):  
Yipeng Liang ◽  
Xiang Li ◽  
Tonggang Zha ◽  
Xiaoxia Zhang
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Organic Carbon ◽  
Loess Plateau ◽  
Effective Means ◽  
Soil Surface ◽  
Vegetation Restoration ◽  
The Loess Plateau ◽  
Loess Slope ◽  
Carbon Redistribution

The redistribution of soil organic carbon (SOC) in response to soil erosion along the loess slope, China, plays an important role in understanding the mechanisms that underlie SOC’s spatial distribution and turnover. Consequently, SOC redistribution is key to understanding the global carbon cycle. Vegetation restoration has been identified as an effective method to alleviate soil erosion on the Loess Plateau; however, little research has addressed vegetation restoration’s effect on the SOC redistribution processes, particularly SOC’s spatial distribution and stability. This study quantified the SOC stock and pool distribution on slopes along geomorphic gradients in naturally regenerating forests (NF) and an artificial black locust plantation (BP) and used a corn field as a control (CK). The following results were obtained: 1) vegetation restoration, particularly NF, slowed the migration of SOC and reduced the heterogeneity of its distribution effectively. The topsoil SOC ratios of the sedimentary area to the stable area were 109%, 143%, and 210% for NF, BP, and CK, respectively; 2) during migration, vegetation restoration decreased the loss of labile organic carbon by alleviating the loss of dissolved organic carbon (DOC) and easily oxidized organic carbon (EOC). The DOC/SOC in the BP and NF increased significantly and was 13.14 and 17.57 times higher, respectively, than that in the CK (p < 0.05), while the EOC/SOC in the BP and NF was slightly higher than that in the CK. A relevant schematic diagram of SOC cycle patterns and redistribution along the loess slope was drawn under vegetation restoration. The results suggest that vegetation restoration in the loess slope, NF in particular, is an effective means to alleviate the redistribution and spatial heterogeneity of SOC and reduce soil erosion.

scholarly journals How to Optimize Ecosystem Services Based on a Bayesian Model: A Case Study of Jinghe River Basin

2019 ◽  
Vol 11 (15) ◽  
pp. 4149
Author(s):  
Chengyan Tang ◽  
Jing Li ◽  
Zixiang Zhou ◽  
Li Zeng ◽  
Cheng Zhang ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Soil Erosion ◽  
River Basin ◽  
Swat Model ◽  
Agricultural Productivity ◽  
Spatial Optimization ◽  
Water Yield ◽  
Mountain Areas ◽  
Jinghe River Basin ◽  
Jinghe River

Based on a Bayesian Network Model (BBN), we established an ecological service network system of the Jinghe River Basin in 2015. Our method consisted of using the distributed eco-hydrological model (Soil and Water Assessment Tool (SWAT) model) to simulate water yield, the Carnegie-Ames-Stanford Approach (CASA) model to estimate Net Primary Productivity (NPP), the Universal Soil Loss Equation (USLE) model to calculate soil erosion and the Crop Productivity (CP) model to simulate agricultural productivity to quantify the four ecosystem services. Based on the network established, the key variable subset and the visual optimal state subset, which we visualized, were analyzed and used to provide spatial optimization suggestions for the four kinds of ecosystem services studied. Our results indicate that water yield, concentrated in the middle and lower reaches of the mountain and river areas, is increasing in the Jinghe River Basin. NPP is continuously increasing and is distributed in the middle and lower reaches of the mountain areas on both sides of the river. Agricultural productivity also shows an upward trend, with areas of high productivity concentrated in the southern downstream mountain areas. On the contrary, the amount of soil erosion is declining, and the high erosion value is also declining, mainly in the upper reaches of the basin (in the Loess Hilly Area). Additionally, we found that a synergistic relationship exists between water yield, NPP and agricultural productivity, which can increase vegetation cover, leading to enhanced agricultural productivity. However, water yield can be reduced as required in order to balance the tradeoff between water yield and soil erosion. Clear regional differences exist in ecosystem services in the river basin. In the future, the two wings of the middle and lower reaches of the river basin will be the main areas of optimization, and it is likely that an optimal ecosystem services pattern can be reached.

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