Data-based analysis about the influence on erosion rates of the Tibetan Plateau. (1st August 2022)

• Record Type: Journal Article
• Authors: He, Junqing; Yang, Rong; Su, Cheng
• Is Part Of: Journal of Asian earth sciences. Volume 233(2022)
• Publication Date: 2022-08-01
• Subjects: 10Be catchment-wide erosion rate -- Tibetan Plateau -- Polynomial fitting -- K-medoids clustering -- Data-based analysis; Earth sciences -- Asia -- Periodicals; Sciences de la terre -- Asie -- Périodiques; Earth sciences; Asia; Periodicals; 555.05
• DOI: 10.1016/j.jseaes.2022.105246
• Languages: English
• ISSNs: 1367-9120

Abstract

Graphical abstract: Highlights: Data-based analysis confirms former empirical studies about the complicated mechanisms towards erosion. Clustering of the dataset is consistent with the separation of Inner and Peripheral of Tibetan Plateau. Fitting of quadratic polynomials suggests non-linear and multi-factor coupling relation with erosion. Abstract: Understanding the mechanisms and influential parameters of erosion rates is of great significance to comprehend landscape evolution and surface process. For years, many scientists have dedicated themselves into investigating the controlling factors of erosion rates over different spatial–temporal scales and various erosion mechanisms have been proposed, such as tectonics, climate, lithology, vegetation and etc., solely or coupled. Here, we exert data-based analysis of the catchment-wide 10 Be erosion rates around the Tibetan Plateau (TP) (n = 289) to establish the correlation between erosion rates and other geological and topographic indices with bivariate analysis (Pearson and Spearman correlation), polynomial fitting (linear and quadratic) and data-based clustering (K-medoids). The results show that it is better to cluster the whole TP into two parts (the Inner Group (n = 176) and the Peripheral Group (n = 113)) where the quadratic fitting polynomials can reach an acceptable fitting (R 2 > 0.6 and RMSE < 0.23) for erosion rates. This relationship is non-linear and multi-factor-coupling, indicating complex mechanisms towards erosion.