Uncertainty of Slope Length Derived from Digital Elevation Models of the Loess Plateau, China

• Published in: Journal of mountain science Vol. 11; no. 5; pp. 1169 - 1181
• Main Authors: Zhu, Shi-jie, Tang, Guo-an, Xiong, Li-yang, Zhang, Gang
• Format: Journal Article
• Language: English
• Published: Heidelberg Science Press 01.09.2014; Springer Nature B.V
• Subjects: DEM; Earth and Environmental Science; Earth Sciences; Ecology; Elevation; Environment; Geography; Gullies; Hydrologic modeling; Landforms; Mathematical models; Mountains; Soil erosion; 不确定性; 中国; 分辨率; 地形复杂性; 坡长; 数字高程模型; 黄土高原; China, People's Rep., Loess Plateau; China, People's Rep; Digital Elevation Models (DEM); Uncertainty; Slope length; Loess terrain
• ISSN: 1672-6316; 1993-0321; 1008-2786
• DOI: 10.1007/s11629-013-2788-0

Although many studies have investigated slope gradient uncertainty derived from Digital Elevation Models（DEMs）, the research concerning slope length uncertainty is far from mature. This discrepancy affects the availability and accuracy of soil erosion as well as hydrological modeling. This study investigates the formation and distribution of existing errors and uncertainties in slope length derivation based on 5-m resolution DEMs of the Loess Plateau in the middle of China. The slope length accuracy in three different landform areas is examined to analyse algorithm effects. The experiments indicate that the accuracy of the flat test area is lower than that of the rougher areas. The value from the specific contributing area（SCA） method is greater than the cumulative slope length（CSL）, and the differences between these two methods arise from the shape of the upslope area. The variation of mean slope length derived from various DEM resolutions and landforms. The slope length accuracy decreases with increasing grid size and terrain complexity at the six test sites. A regression model is built to express the relationship of mean slope length with DEM resolution less than 85 m and terrain complexity represented by gully density. The results support the understanding of the slope length accuracy, thereby aiding in the effective evaluation of the modeling effect of surface process.