Abstract
Abstract. In this paper, changes of sediment yield and sediment transport were assessed using the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information Systems (GIS). This model was based on the integrated use of precipitation data, Landsat images in 2000, 2005 and 2010, terrain parameters (slope gradient and slope length) and soil composition in Zhifanggou watershed, Gansu Province, Northwestern China. The obtained results were basically consistent with the measured values. The results showed that the mean modulus of soil erosion is 1224, 1118 and 875 t km−2 yr−1 and annual soil loss is 23 130, 21 130 and 16 536 in 2000, 2005 and 2010 respectively. The measured mean erosion modulus were 1581 and 1377 t km−2 yr−1, and the measured annual soil loss were 29 872 and 26 022 t in 2000 and 2005. From 2000 to 2010, the amount of soil erosion was reduced yearly. Very low erosion and low erosion dominated the soil loss status in the three periods, and moderate erosion followed. The zones classified as very low erosion were increasing, whereas the zones with low or moderate erosion were decreasing. In 2010, no zones were classified as high or very high soil erosion.
Highlights
Soil erosion is a process which refers to the destruction, separation, removal and sedimentation of the earth’s surface soil and its parent material caused by hydraulic, wind, freezing and thawing, gravity and other external forces (Meyer, 1984)
This paper focused on analysing the land use pattern, vegetation distribution and soil erosion status based on the Revised Universal Soil Loss Equation (RUSLE) model and the impact of slope changes and land use types on erosion by using remote sensing (RS) and Geographical Information Systems (GIS) in the Zhifanggou watershed, Loess Plateau
The areas classified as very low erosion are increasing, whilst the areas with low or moderate erosion are decreasing
Summary
Soil erosion is a process which refers to the destruction, separation, removal and sedimentation of the earth’s surface soil and its parent material caused by hydraulic, wind, freezing and thawing, gravity and other external forces (Meyer, 1984). Soil erosion has caused a set of ecological and environmental problems such as land degradation, soil fertility loss, river siltation, making it a global research focus. Since the 1950s, to quantify soil loss and determine its risk, a number of soil erosion models were established based on measured data or the results of previous studies, and numerous research results were obtained using Geographical Information Systems (GIS) and remote sensing (RS). One of the most applied models to estimate soil erosion is the Universal Soil Loss Equation (USLE) and its modified version the Revised Universal Soil Loss Equation (RUSLE). Lu et al (2001) used GIS and the RUSLE model to map and quantitatively predict patch and gully erosion in Australia. Liu (2002) established China’s Soil Erosion Prediction Equation (CSLE) by the study of a slope erosion prediction model. One of the most applied models to estimate soil erosion is the Universal Soil Loss Equation (USLE) and its modified version the Revised Universal Soil Loss Equation (RUSLE). Lu et al (2001) used GIS and the RUSLE model to map and quantitatively predict patch and gully erosion in Australia. Liu (2002) established China’s Soil Erosion Prediction Equation (CSLE) by the study of a slope erosion prediction model. Gao et al (2015) calculated the soil erosion modulus in the Loess Plateau of
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