DOI: 10.5285/f7aada06-7352-44c0-988e-2f4b31690189
title: River planform dynamics in the Beas and Sutlej catchments, India, 1847 and 1989-2018

description: The data was produced as part of a study to determine human impacts on river planform change within the context of short- and long-term river channel dynamics. To this end, the Himalayan Sutlej-Beas River system was used as a case study to (i) systematically assess changes in river planform characteristics over centennial, annual, seasonal, and episodic timescales; (ii) connect the observed patterns of planform change to human-environment drivers and interactions; and (iii) conceptualise these geomorphic changes in terms of timescale-dependant evolutionary trajectories. The dataset was derived from historic maps (1847-1850) and remote sensing data (Landsat over a 30-year period). It comprises post monsoon season wet river area annually 1989-2018, post monsoon season active gravel bars annually 1989-2018, active channel area (maximum extent between 1989-2018), active channel width annually 1989-2018, active channel width assessed from historic map (1847–1850), and the Anabranching index, annually 1989-2018. The work was supported by the Natural Environment Research Council (Grant NE/S01232X/1).
description: Wet river area: The annual wet river area was extracted automatically from satellite imagery of Landsat 5 to 8 (1989 to 2018) using average post-monsoon season (October-December) values of the modiﬁed Normalized Difference Water Index (mDNWI) to differentiate water and land areas (Huang et al., 2018). The wet river area was extracted from the mNDWI raster images by the threshold mNDWI > 0.15. After manual editing to remove individual water pixels away from the river, the raster images were converted to polygon shapeﬁles). There is a feature for each year of measurement. The wet river area was calculated for Reaches 1 and 2 and for each of the sections within Reach 2; these values are tabulated in the .csv files as an annual series.

Active gravel bars: Visible red reﬂectance from Landsat 5 to 8 (1989 to 2018) was used to identify bare gravel bars showing high reﬂectance (> 0.16) using average post-monsoon season (October-December) values. Only pixels within a buffer deﬁned by the maximum extent of the wet river area over the observed period were considered. After applying the reflectance threshold to raster images, shapeﬁles were created to define the active gravel bars as features. There is a feature for each year of measurement.

Active Channel Area: The wet river area shapefiles from individual years 1989-2018 were aggregated together to produce a single feature that delineates areas that were wetted in the post-monsoon season in one or more years between 1989-2018, to estimate the extent of the active channel.

Active channel width: The channel width was considered as the width of the wet area, including any gravel bars where that were surrounded by water. This width was automatically calculated every 2 km and was repeated for wet areas estimates derived from an historic map (“The Trans-Sutluj Division, comprising the districts of Jalundhur, Hoshyarpoor and Kangra”) (Revenue Survey of India, 1852) which was produced between 1847 and 1852.  Width was measured perpendicular to the riverbank. The mean active channel width was calculated for Reaches 1 and 2 and for each of the sections within Reach 2; these values are tabulated in the .csv files as an annual series.

Anabranching Index (AI): The anabranching index reﬂects the number of active channels separated by bars or islands, measured in at least 10 cross sections (spaced the width of one braid plain apart). The AI was calculated for Reaches 1 and 2 and for each of the sections within Reach 2; these values are tabulated in the .csv files as an annual series.

Quality control: Landsat satellite data was used to collect information on spectral surface reflectance.  These data are accompanied by quality assessment bands which were used to select data before processing, particularly with respect to obtaining cloud-free images.  Processing was conducted by the project team, with using and spot validation against aerial satellite photography. Data were checked for errors at all stages by members of the project team at Cranfield University.