DocumentCode :
1997346
Title :
RUSLE model based quantitative evaluation on the soil erosion of Wen County of Gansu Province, China
Author :
Xie, Yaowen ; Lin, Jingli
Author_Institution :
Key Lab. of West China´´s Environ. Syst. (Minist. of Educ.), Lanzhou Univ., Lanzhou, China
fYear :
2010
fDate :
18-20 June 2010
Firstpage :
1
Lastpage :
6
Abstract :
With steep slopes, high mountains, concentrated rainfalls and frequent rainstorms, the agricultural production and economic development of the Wen County, the southernmost county, also heavily damaged by 5.12 Earthquake, of Gansu Province in northwest China, are gravely constrained by serious soil erosion. To make effective soil and water conservation measures, quantitative evaluation of soil erosion situation is urgently needed. Traditional qualitative evaluation methods and techniques of soil erosion are unable to meet the rapid and quantitative need. Using GIS (Geographic Information System), RS (Remote Sensing) and combining with RUSLE (the Revised Universal Soil Loss Equation) model, which being widely used in many regions, this study aims to quantitatively and objectively survey the soil erosion situation of Wen County in 2008. The results of the study will provide reference for soil and water conservation and ecological construction in this area. The TM images acquired in June 25, 2008 were selected as the remote sensed data, and thus 30m×30m resolution was defined as the basic evaluating cell correspondingly. After a series of processing and calculation, the land use and NDVI (Normalized Difference Vegetation Index) data are obtained. Based on the daily rainfall, vector soil data, DEM, along with the land use and NDVI data, the RUSLE factors are calculated including rain erosivity (R), soil erodibility (K), cover and management factor(C), slope length (LS) and supporting practice factor (P). Then, using RUSLE model, the soil erosion modulus is calculated and the grades of soil erosion, namely slight, light, moderate, intensive, extreme intensive, and severe, are determined. The conclusions are as follows: 1. The total soil erosion of Wen County is serious and the area of slight, light, moderate, intensive, extreme intensive and severe are respectively 512.86km2, 1100.15km2, 881.52km2, 605.05km2, 661.74km2 and 1016.13km2, taking up 10.74%, 23.03%, 18.45%, 12.67%, 13.85% and 21.27% of the total area correspondingly. The soil erosion area is 4264.59km2, taking up 89% of total statistical area and all kinds of erosion types show a relative balanced distribution in amounts, although light erosion, moderate erosion and severe erosion have a greater-than 15% proportion respectively. 2. The distribution of erosion land has great regularity: Slight erosion and light erosion mainly distribute in the top area of mountain ridges with good vegetation cover, or plain land besides rivers with low slopes. Moderate and strong erosion distribute in the middle of hillsides. The very strong and severe erosion are concentrated in the hillsides near river ways, or very steep part of mountains. 3. The erosion grades are closely correlated with the land use and population. The area covered by forest or high densities grass has light erosion grades, while the high populated farmland and low vegetation coverage land win the very high erosion grades.
Keywords :
digital elevation models; erosion; soil; vegetation; vegetation mapping; AD 2008 06 25; China; Gansu Province; RUSLE model; TM images; Wen County; digital elevation model; erosion grades; erosion land; geographic information system; normalized difference vegetation index; quantitative evaluation; rain erosivity; remote sensing; revised universal soil loss equation; slope length; soil erodibility; soil erosion; water conservation; Biological system modeling; Gallium nitride; Humans; Mathematical model; Rivers; Soil; Vegetation mapping; GIS; RS; RUSLE; Wen County; soil erosion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoinformatics, 2010 18th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-7301-4
Type :
conf
DOI :
10.1109/GEOINFORMATICS.2010.5567775
Filename :
5567775
Link To Document :
بازگشت