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  • [This dataset is embargoed until May 1, 2023]. 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). Full details about this dataset can be found at https://doi.org/10.5285/f7aada06-7352-44c0-988e-2f4b31690189

  • Terrestrial laser scanner (TLS) and CT scan data collected during flume experiments on a gravel bed. TLS data show the bed surface topography before and after waterworking of the bed. CT scan data show the 3D structure of sections of the river bed after waterworking. Some CT data has been processed to segment the images into the individual gravel grains, and for some of these data a database of grain properties is also available. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/6749d033-cdf4-479b-ba85-015c3dbb476a

  • Dataset contains Terrestrial laser scanner (TLS) and CT scan data collected during fieldwork on a small gravel-bed river. TLS data show the river bed surface topography collected at five intervals between September 2014 and October 2018. CT scan data show the 3D structure of sections of the river bed. CT data has been processed to segment the images into gravel grains and fine-grained matrix. Full details about this dataset can be found at https://doi.org/10.5285/b30b4d56-f0a9-43e8-aacc-09d9b5b1f9fc

  • [This dataset is embargoed until May 1, 2023]. The data comprises river section, zone and test site delineation, winter Season average NDVI by section and zone 1989-2020, land cover maps seasonally 1989-2020, and derived land cover fractions by section and zone 1989-2020. The data was produced as part of a study to determine how changes in geomorphic form and dynamics due to human alteration to river flows and riparian land management relate to changes in vegetation communities in the Sutlej and Beas Rivers, India. Vegetated and other land cover, including water area, were quantified by winter season NDVI trends (in the plains of Punjab) and seasonal supervised classification of Landsat data for over a 30-year period. The work was supported by the Natural Environment Research Council (Grant NE/S01232X/1). Full details about this dataset can be found at https://doi.org/10.5285/9a96e199-34d0-46f9-9a64-140d300a2531

  • The data set contains the Philippines bridge inventory, river migration geodatabase and source code to assess active river channel change (i.e. planform adjustments) using Landsat 5, 7 and 8 products in Google Earth Engine. The data set contains hydro-morphological and bridge characteristics for 74 bridges (> 200 m deck length) in the Philippines from 1988 to 2019 and is available in .csv and .shp format. For a given region of interest (ROI), the code will extract active river channel masks, calculate similarity coefficients between active river channel masks at decadal intervals and calculate active widths and centreline statistics. The code was used by Boothroyd et al. (in press) to investigate decadal river migration at critical bridge infrastructure in the Philippines. Full details about this dataset can be found at https://doi.org/10.5285/2efd24f9-e745-4f54-8bbd-6439b0ad93e5

  • Data comprise resistance of aquatic bioconstructions (Trichoptera cases), and the loose sediment they were built from, to hydraulic forces measured in a hydraulic flume. S1_Velocimetry_data contains the output after post-processing the acoustic Doppler velocimetry data for each flow stage. This includes the mean and SD of velocity (m/s) for each direction (U – downstream, V – vertical and W- cross stream), the quality of the data recorded by the ADV (Signal to noise ratio and correlation) and calculated values of turbulent kinetic energy and bed shear stress. An explanation of each variable and units are included in the file. S2_Case-grain-size-distribution_data contains the grain size distributions for each caddisfly case obtained by sieving the case sediment. Includes the mass of sediment in half phi size intervals from 0.063 mm to 8 mm diameter. An explanation of each variable and units are included in the file. S3_Entrainment_data contains the percentage of sediment entrained during each flow stage (1-11). Percentage of sediment measured using photography of sediment remaining on the measurement platform. An explanation of each variable and units are included in the file. S4_Case-and-entrainment-threshold_data contains the caddisfly case characteristics (mass and a,b&c axes), critical entrainment thresholds and general movement data for each case and loose sediment. An explanation of each variable and units are included in the file. Full details about this dataset can be found at https://doi.org/10.5285/cce26277-0b17-4c25-aa08-dd1486f89d9b