The data set contains multi-temporal aerial imagery for two river segments in the Philippines. Imagery covers: (i) the downstream segment of the Bislak River and (ii) the confluence of the Abuan, Bintacan and Pinacanauan de Ilagan Rivers (referred to as ‘Ilagan’ in this data resource). Repeat aerial surveys were completed in 2019 and 2020. The data coverage includes the river channels, floodplains and surrounding areas. Raw aerial images were processed to produce spatially corrected orthoimagery (see supporting documentation). The resulting orthoimagery has a 0.2 m spatial resolution, containing information on the red, green and blue (RGB) bands. The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312. Full details about this dataset can be found at https://doi.org/10.5285/e040ff39-2176-4ed4-9e5d-861bdae8a030

These data are input files for CAESAR-Lisflood (CL), a numerical hydrodynamic-landscape evolution model. These files were created to support coupled hydrodynamic-landscape evolution modelling to evaluate the geomorphological response of river channels affected by the 7th February 2021 ice-rock avalanche and debris flow in Chamoli District, Uttarakhand, India. They include 10 m digital elevation models (DEMs) of bed rock and land surface topography in a gridded (raster) format. They also include reanalysis-derived river discharge data generated by the GEOGloWS project at the following locations: Rontigad, Rishiganga, Dhauliganga, and Alaknanda. The configuration settings and parameters for CL modelling are also included. Full details about this dataset can be found at https://doi.org/10.5285/4cdd86b3-bf58-457d-b8cf-b57aed2d56d0

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

This data set contains satellite-derived information on geomorphic river mobility for ten catchments in the Philippines. We applied the locational probability approach to map the proportion of time that a river channel occupies a particular location. We quantified satellite-derived locational probabilities for 600 km2 of riverbed. The information is useful for predicting and developing resilience to river-related hazards in dynamic landscapes. We provide example Google Earth Engine (GEE) and MATLAB codes to replicate satellite-derived locational probability analyses, and provide outputs for each catchment. Data sets include: (1) example GEE codes to run satellite imagery analyses; (2) example MATLAB codes and data to generate locational probabilities; (3) example MATLAB codes and data to produce longitudinal analyses; and, (4) processed locational probability outputs for the ten catchments. The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312. Full details about this dataset can be found at https://doi.org/10.5285/a2bcc66e-4dcc-4ed1-897d-cdf36dde246d

The shapefiles contain the classification and locations of each river style determined by the authors. The data were used to characterise the river styles in Bislak River, Philippines. Shapefiles were clipped to the catchment boundary from different national government agencies to produce different thematic maps. Catchment properties such as land use (from the National Mapping and Resource Information Authority (NAMRIA)), geology (from the Mines and Geosciences Bureau), fault (from Philippine Institute of Volcanology and Seismology, rainfall isohyets, slope map, and the digital elevation model (also from NAMRIA) were used for regional and catchment analysis. The data only covers the whole Bislak catchment, Philippines. The CSV contains data used for the stream power analysis where stream power is a factor of slope and discharge. Full details about this dataset can be found at https://doi.org/10.5285/31ae71aa-74a9-466b-9a3a-25d2b1a9406e

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

These data are GIS shapefiles which contain geospatial information describing the location and condition of bridges, buildings and roads in Chamoli District, Uttarakhand, India, following the 7th February 2021 avalanche and debris flow hazard cascade (the so-called ‘Chamoli event’). The dataset also contains a GIS shapefile which contains polygon outlines supporting geomorphological analysis of change in river valleys between the avalanche source and the town of Joshimath. The latter is designed to be used in conjunction with the other data resources contained in this data collection. Full details about this dataset can be found at https://doi.org/10.5285/a763e254-c249-4934-b0fb-c3b808b37db6

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

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

This dataset contains a national-scale geodatabase of stream network and river catchment characteristics in the Philippines. It presents detailed information on 128 medium- to large-sized catchments (catchment area > 250 km2). The quantitative descriptions provide context for enabling geomorphologically-informed sustainable river management. The geodatabase provides a baseline understanding of fundamental topographic characteristics in support of varied geomorphological, hydrological and geohazard susceptibility applications. Data sets include: 1) GIS shapefiles with river catchment properties; 2) GIS shapefiles with stream network properties; 3) spreadsheets containing morphometric and topographic characteristics (n = 91); 4) example MATLAB code and topographic data to replicate the analysis for a selected catchment. The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312/1. Full details about this dataset can be found at https://doi.org/10.5285/49ae11ec-e4e5-4e4a-b091-976d18c4ee3e