Process inference from topographic fractal characteristics in the tectonically active Northwest Himalaya, India

Abstract

Topography evolves under the coupled effect of exogenic and endogenic governing factors, and their scale-(in)variant dynamics. This results in a self-affine topography across a finite range, with a characteristic fractal dimension. Fractal analysis has been used to classify geological terrains having distinct litho-tectonic settings. However, process-based understanding of the fractal behaviour of a natural landscape is still limited. The current study aims to substantiate and expand upon the present knowledge of topographic response to the complex actions of the governing factors using fractal characteristics. We examined the association between the litho-tectonic, climatic settings and the fractal characteristics of the topography in the tectonically active Northwest Himalaya. Our analysis was carried out in three separate sectors having diverse litho-tectonic settings. We used the roughnesslength method to calculate the fractal parameters (fractal dimension, D; ordinate intercept, q). The Higher and the Lesser Himalaya were found to be characterized by low D and high q, while the tectonically active Sub Himalaya was found to have moderate D and low q. The southernmost foreland alluvial plains were characterized by high D and low q. Clusters of the fractal parameters were found to be consistent in spatial pattern across the three sectors. Our results showed that the geological-geomorphological settings and the associated processes (e.g. uplift, erosion and diffusion) can be well inferred using the fractal characteristics of the topography. Further, our results implied first-order control of lithology in sustaining and shaping the topographic geometry (both its amplitude and texture) in the tectonically active Northwest Himalaya. The spatial distribution of the fractal parameters also suggested the secondary control of tectonic uplift and, to a much lesser extent, mean annual rainfall on the topographic geometry. These results collectively point to the role of complex actions of the governing factors in the landscape evolution process.

Geomorphic diversity of the Indian sub‐continent: Progress and updates

“…The use of scale‐independent fractal parameters provides an opportunity to understand the texture of the landscape along with relief (Sung & Chen, 2004) and hence can complement morphometric studies of Himalayan terrain. Sahoo et al (2020) have utilized fractal characteristics of topography in the northwest Himalaya to infer geological‐geomorphological settings and the associated processes. This paper covers three sectors of the northwest Himalaya namely, the Kangra re‐entrant, the Nahan salient, and Dehradun re‐entrant to understand the combined effect of tectonics, lithology and surface processes on topography using fractal characteristics.…”

A novel approach to the classification of terrestrial drainage networks based on deep learning and preliminary results on solar system bodies

“…Recently, the twodimensional fractal analysis of some patterns featured by self-similarity [19], together with other metrics, such as the hierarchical order, the sinuosity, and the density of drainage, was proved as a valid tool to discriminate primary (tectonic) processes from secondary ones (erosion), through the interpretation of the fractal dimension. As the latter increases, the effect linked to erosion processes compared to tectonic ones, increases, hence the irregularity of pattern too [20,21,22,23,24,25].…”