Slope spectrum variation in a simulated loess watershed

A simulated loess watershed, where the loess material and relief properly represent the true loess surface, is adopted to investigate the variation in slope spectrum with loess watershed evolution. The evolution of the simulated loess watershed was driven by the exogenetic force of artificial rainfall. For a period of three months, twenty artificial rainfall events with different intensities and durations were carried out. In the process, nine DEM data sets, each with 10 mm grid resolution, were established by the method of close-range photogrammetry. The slope spectra were then extracted from these DEMs. Subsequent series of carefully designed quantitative analyses indicated a strong relationship between the slope spectrum and the evolution of the simulated loess watershed.Quantitative indices of the slope spectrum varied regularly following the evolution of the simulated loess watershed. Mean slope, slope spectrum information entropy (H), terrain driving force (Td), Mean patch area (AREA_MN), Contagion Index (CONTAG), and Patch Cohesion Index (COHESION) kept increasing following the evolution of the simulated watershed, while skewness (S), Perimeter-Area Fractal Dimension (PAFRAC), and Interspersion and Juxtaposition Index (IJI) represented an opposite trend. All the indices changed actively in the early and active development periods, but slowly in the stable development periods. These experimental results indicate that the time series of slope spectra was able to effectively depict the slope distribution of the simulated loess watershed, thus presenting a potential method for modeling loess landforms.

[1]  E. F. Hollyday.  Drainage basin characteristics from ERTS data , 1975 .

[2]  J. D. Ploey.  Rainfall simulation runoff and soil erosion , 1983 .

[3]  R. Keren,et al.  Polymer effects on water infiltration and soil aggregation , 1997 .

[4]  Richard J. Pike,et al.  Geomorphometry -diversity in quantitative surface analysis , 2000 .

[5]  John P. Wilson,et al.  Terrain analysis : principles and applications , 2000 .

[6]  J. Poesen,et al.  Effects of water quality on infiltration, runoff and interrill erosion processes during simulated rainfall , 2001 .

[7]  Thomas H Meyer,et al.  Terrain Analysis: Principles and Applications , 2001 .

[8]  Igor V. Florinsky,et al.  Errors of signal processing in digital terrain modelling , 2002, Int. J. Geogr. Inf. Sci..

[9]  Qing Zhu,et al.  Digital terrain modeling - principles and methodology , 2004 .

[10]  Guoan Tang,et al.  DEM-based research on the terrain driving force of soil erosion in the Loess Plateau , 2006, Geoinformatics.

[11]  Long Yi,et al.  Research on the slope spectrum of the Loess Plateau , 2008 .

[12]  Yi Long,et al.  Research on the slope spectrum of the Loess Plateau , 2008 .

[13]  T. Hengl,et al.  Geomorphometry: Concepts, software, applications , 2009 .

[14]  Longitudinal and transverse profiles of hilly and mountainous watersheds in Japan , 2009 .

[15]  B. Fu,et al.  Modeling soil erosion and its response to land-use change in hilly catchments of the Chinese Loess Plateau. , 2010 .

[16]  Igor V. Florinsky,et al.  Digital Terrain Analysis in Soil Science and Geology , 2011 .

[17]  Clemens Eisank,et al.  Local variance for multi-scale analysis in geomorphometry , 2011, Geomorphology.

[18]  S. Walsh,et al.  Geospatial technologies and digital geomorphological mapping: Concepts, issues and research , 2012 .

[19]  I. Evans.  Geomorphometry and landform mapping: What is a landform? , 2012 .

[20]  I. Florinsky.  Digital Terrain Modeling , 2012 .

[21]  John P. Wilson,et al.  Digital terrain modeling , 2012 .

[22]  C. Cai,et al.  Slope development of tableland in the Holocene on the Chinese Loess Plateau , 2012 .

[23]  G. Krieger,et al.  The TanDEM-X Mission: Earth Observation in 3D , 2013 .