Assessing the effects of land use and topography on soil erosion on the Loess Plateau in China

Sun, Wenyi; Shao, Quanqin; Liu, Jiyuan; Zhai, Jun

doi:10.1016/j.catena.2014.05.009

Cited by 366 publications

(263 citation statements)

References 51 publications

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“…The high values may be due to the highly dissected terrain and abrupt slope changes near the drainage channels. Similar LS values have already been reported by various researchers in various regions and landscapes including mountainous sub watershed in western Ghats of Kerala (Prasannakumar et al, 2012), Densu river basin of Ghana (Ashiagbor et al, 2013), Kufranja watershed of Jordan (Farhan et al, 2013), Loess Plateau in north China (Sun et al, 2014) and Pathri Rao sub watershed in Shivalik region of Uttarakhand, India (Suresh Kumar and Kushwaha, 2013). All these studies unanimously agreed that higher LS factor values are observed in hilly and gully regions as well as mountainous areas with very steep topography and these areas are prone to sever erosion, due to topography.…”

Section: Ls Factorsupporting

confidence: 88%

Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS

Kalambukattu

Kumar

2017

Eurasian Journal of Soil Science (Ejss)

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Article Info Received : 28.06.2016 Accepted : 01.09.2016 Soil erosion is one of the major cause of land degradation and is a serious threat to food security and agricultural sustainability. Revised Universal Soil Loss equation (RUSLE) model using remote sensing (RS) and Geographical Information Systems (GIS) inputs was employed to estimate soil erosion risk in a watershed of mid-Himalaya in Uttarakhand state, India. Spatial distribution of soil erosion risk area in the watershed was estimated by integrating various RUSLE factors (R, K, LS, C, P) in raster based GIS environment. RUSLE model factor maps were generated using remote sensing satellite data (IRS LISS III and LANDSAT-8) and Digital elevation model. Agriculture (59%) was found to be the dominant land use system followed by scrub land (20%) in the watershed. Rainfall erosivity (R) factor was estimated using past 23 years rainfall data. SRTM DEM was used to generate slope length -steepness (LS) factor in this highly rugged terrain. Nearly 70% of the watershed is having steep to moderately steep slope (>40%). Satellite data was interpreted to prepare physiographic map at 1:50,000 scale. Surface soil samples collected in each physiographic unit was analyzed to generate soil erodibility (K) map. Soil erodibility factor ranged from 0.033 to 0.077 in the watershed. Soil erosion risk analysis showed that 36.25%, 9.31%, 15.80%, 15.27%, 11.46% and 11.89% area of watershed falls under very low, low, moderate, moderate high, high and very high erosion risk classes respectively. The average annual erosion rate was predicted to be 65.84 t/ha/yr. The soil erosion rates were predicted to vary from 3.24 t/ha/yr in dense mixed forest cover to 87.98 t/ha/yr in open scrub land. The soil erosion map thus generated employing remote sensing and GIS techniques, can serve as a tool for deriving strategies for effective planning and implementation of various management and conservation practices for soil and water conservation in the watershed.

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Section: Ls Factorsupporting

confidence: 88%

Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS

Kalambukattu

Kumar

2017

Eurasian Journal of Soil Science (Ejss)

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“…In most regions of the Loess Plateau, a majority (60%) of annual precipitation (about 400 mm) falls between July and September. Annual evapotranspiration is typically 1400-2000 mm [27,28]. A vegetation gradient exists in the plateau, which transitions from forests in the southeast to woody steppe, steppe, and desert steppe in the northwest.…”

Section: Study Areamentioning

confidence: 99%

Accuracy Assessment and Inter-Comparison of Eight Medium Resolution Forest Products on the Loess Plateau, China

Yang

Dong

Liu

et al. 2017

IJGI

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Abstract:Forests play an important role in maintaining ecosystem services, especially in ecologically fragile areas such as the Loess Plateau (LP) in China. However, there is still great uncertainty in the spatial extent and distribution of forests in such a fragmented region. In order to examine the advantages and disadvantages of existing forest mapping products, we conducted a thorough accuracy assessment on the eight recent, medium resolution (30-50 m) products by using the LP in 2010 as the region of interest. These mapping products include Landsat and/or PALSAR images, including the forest products from GlobeLand30, FROM-GLC, Hansen, ChinaCover, NLCD-China, GLCF VCF, OU-FDL, and JAXA. The same validation data were used to assess and rank the accuracy of each product. Additionally, the spatial consistency of the different forest products and their dependence on the terrain were analyzed. The results showed that the overall accuracies of the eight forest products on the LP in 2010 were between 0.93 ± 0.003 and 0.97 ± 0.002 with a 95% confidence interval, and GlobeLand30 presented the highest overall accuracy (0.97 ± 0.002). Among them, the PALSAR-based products (OU-FDL and JAXA) indicated relatively high accuracies, while the six Landsat-based products showed a large diversity in the accuracy. According to the eight products, the total estimated forest area of the LP varied from 7.627 ± 0.077 to 10.196 ± 0.1 million ha with a 95% confidence interval. We also found that the consistency in the spatial distribution of forests between these maps: (1) increased substantially with increasing elevation until 2000m, but then decreased at higher elevations, and (2) showed mild variation along increasing slope, but had a slight rate of increase. Our findings implied that future forest mapping studies should consider topographical attributes such as elevation and slope in their final products. Our results are fundamental in guiding future applications of these existing forest maps.

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“…Therefore less soil erosion and sediment concentration in the river. A research conducted in Loess Plateau in China has concluded that the best soil protection from erosion has been found under forest, shrub, and dense grass covers (Sun et al, 2014).…”

Section: Sediment Of the Studied Catchmentsmentioning

confidence: 99%

Water and sediment yields from two catchments with different land cover areas

Basuki

2017

J.Degrade.Min.Land Manage.

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:Land cover and human activities affect water yield and soil erosion-sedimentation in a catchment. Therefore, a study to obtain information of water and sediment yields from two catchments covered by different land cover areas has been conducted in Tanjung and Bakar catchments. The catchments are located in Tanah Laut Regency, South Kalimantan Province. The area of secondary forest inTanjung and Bakar catchments are 31 and 10%. The water yield was obtained by measuring Stream Water Level (SWL) and converted the data into stream water discharge using a stream water discharge rating curve. Sediment samples were taken for every increament of SWL. The sediment concentration in water samples were converted to sediment discharge (kg/second) using a sediment discharge rating curve. The results showed that water and sediment yields in 2016 of Tanjung cacthment were higher than Bakar catchment. The water and sediment yields of Tanjung were 2994 mm and 15.7 t/ha. Bakar catchment produces water yield 2750 mm and sediment yield 7.4 t/ha. Based on the study, it shows that the suspended sediment in stream water is not only affected by the percentage of forest cover, but it is also influenced by the activities within the catchment such as traditional mining. Keywords: forest area, sediment yield, water yieldTo cite this article: Basuki, T.M. 2017. Water and sediment yields from two catchments with different land cover areas.

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Assessing the effects of land use and topography on soil erosion on the Loess Plateau in China

Cited by 366 publications

References 51 publications

Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS

Modelling soil erosion risk in a mountainous watershed of Mid-Himalaya by integrating RUSLE model with GIS

Accuracy Assessment and Inter-Comparison of Eight Medium Resolution Forest Products on the Loess Plateau, China

Water and sediment yields from two catchments with different land cover areas

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