AMBER salmon: A digital river network containing reach-specific habitat variables related to the North-East Atlantic distribution of Atlantic salmon (Salmo salar)

Summary

This dataset was collated through an offshoot of the AMBER project. One of the aims of AMBER was to evaluate the merits of different restoration actions proposed to reconnect Europe’s fragmented and impounded rivers. To this end, an assessment of barrier impacts at pan-European level was desired. We collated this composite digital river network, and associated catchment, lake, and subcatchments geospatial data, to support assessment of impacts of barriers on Atlantic salmon (Salmo salar) at a regional scale. The river network may facilitate studies of other aquatic species, particularly diadromous fishes, owing to its hydrologically consistent anabranching topology.

Accurately mapped channel planforms are a requirement for quantifying regional and locally-relevant impacts of barriers on the longitudinal connectivity of rivers. To this end, and in contrast to regional-extent digital river networks that have been derived using the D8 flow accumulation method, EU-Hydro was derived from aerial imagery and digital elevation data, and therefore was the chosen foundation for the composite river network. However, the amount of detail and spatial extent of EU-Hydro was insufficient to capture some North-East Atlantic salmon populations, so hydrography90, CCM2 and OpenStreetMap data were included where necessary.

Topological adjustments of the composite river network were necessary to facilitate hydrologic routing from source to sea. Adjustments included dissolving pseudo-nodes, splitting polylines at lake polygon perimeters, disconnection of incorrectly joined reaches between neighbouring catchments (i.e., inaccurate topological bifurcations/diffluences), and reversal of flow directions in cases of topological loops. Following this preparation using graph-based methods, we were able to generate lookup fields for network tracing and aggregation of upstream/downstream information.

To facilitate estimation of barrier-attributable losses of Atlantic salmon habitat in terms of wetted area, we added data fields containing reach specific hydraulic geometries. To do so, we used downscaling and hydrologic routing of gridded runoff data (using hydrostreamer) followed by a catchment character-aware statistical model relating aerial imagery-derived channel width to discharge, and further approximated depth using Burek et al.’s (2014) Manning’s equation derived method, adjusting for channel gradient (using elevatr and exactextractr) and a estimated hydraulic roughness.

To estimate general suitability of habitat to Atlantic salmon based on water temperature, and potential losses of habitat due to poor water quality (e.g., quantified by WFD ecological quality scores), we spatially interpolated DynWat and DynQual gridded model outputs onto river segments using a topological adjustment to approximate monthly average temperatures at the reach scale.

All geospatial data in this repository follow a naming convention that links river segments to lake flowlines and associated catchment and segment-specific subcatchment polygons, enabling various table join operations and efficient data extraction. To facilitate efficient extraction/ queries, data are provided here in parquet format, including pre-calculated concatenated lists of all upstream and downstream segment ids and shortest downstream paths per segment each stored as a list column.

Note – An ongoing project within the ICES working group WGTRUTTA (Working Group to Develop and Test Assessment Methods for Sea Trout (Salmo Trutta) Populations) is currently using the river network and national-level river obstacle data to map the available habitat for sea trout (anadromous Salmo trutta). It is intended to publish the results of that project following an interactive web based GIS validation coordinated through WGTRUTTA and the ICES Data Centre, which will identify the first barrier encountered by anadromous trout migrating upstream from the tidal limit.

Limitations

We acknowledge that the digital representations of the river systems included in this repository are likely inaccurate in comparison to many national level higher-resolution products. These inaccuracies include, but are not limited to, geometric planform oversimplification, incorrectly mapped anabranches and diffluences, and modelled hydraulic geometries. Moreover, river geometries vary in detail among countries, even within a single product (e.g., EU-Hydro for Scotland is more detailed (or "segment-dense") than for Ireland). With many known and potential limitations in mind, users should carefully inspect their chosen areas of interest for errors and compare the data in this repository to other products to assess suitability for their study before using these data.

Note - These data are released under the version 0.9.0, as it is expected that errors will require correction before submission of a manuscript describing the full methods including code and validation (e.g., hydraulic geometry/channel width model, downscaled water temperatures vs. observations etc.) for publication in a data/geospatial data journal and ascension to version 1.0.0.

Licences and redistribution of modified open-licensed geospatial data

Licences

The digital river network and associated geospatial data in this repository are composed of raw, modified, and derived geospatial data from publicly available (open data) sources. Among the licences for these datasets, there were conflicting redistribution terms that dictated how we have packaged the data in this repository. The original authors presented their terms for redistribution as described below:

EU-Hydro Copernicus Land Monitoring Service Dataset: "The Copernicus land monitoring products and services are made available on a principle of full, open and free access, as established by the Commission Delegated Regulation (EU) No 1159/2013 of 12 July 2013." (https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32013R1159)

CCM2: "Data are provided free of charge for non-commercial use." We interpreted this statement as compatible with CC BY NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).

Hydrography90: "the dataset is protected by the Creative Commons Attribution-Non-Commercial 4.0 International License CC-BY-NC 4.0" (https://creativecommons.org/licenses/by-nc/4.0/)

OpenStreetMap: "You are free to copy, distribute, transmit and adapt our data, as long as you credit OpenStreetMap and its contributors. If you alter or build upon our data, you may distribute the result only under the same license"; ODbL v1 (https://opendatacommons.org/licenses/odbl/)

Modifications and file contents

The geometries of the EU-Hydro and OSM river networks were edited to fix broken connections and adjust topology for hydrologic routing. The geometries of the CCM2 river network were edited to ensure hydrologically consistent connectivity with EU-Hydro at EEA boundaries. All river network geometries were edited to split river lines at lake polygon perimeters where splits were not already present. Owing to the incompatibility between CC BY 4.0, CC-BY-NC 4.0, and ODbL v1, geospatial river networks, lakes, and derivative catchments and subcatchments were necessarily written to separate parquet files, thus this repository constitutes a Collective Database (https://wiki.openstreetmap.org/wiki/Collective_Database_Guideline). NOTE - Users should be aware that querying the collection from multiple DRN river line or subcatchment parquet files simultaneously should be seamless (e.g., using the arrow package in R to query a single river system "river_group"), and therefore not require any further geometry operations to restore topological connectivity.

Derivative catchment polygons are stored in separate parquet files; however, as the EU-Hydro licence is permissive, catchment polygons that cross EU-Hydro and CCM2 boundaries are retained unbroken within a single parquet file. This aggregation of data was considered appropriate because it avoids users having to dissolve catchment polygons in cases where river systems crossed the borders between CCM2 and EU-Hydro spatial extents. As a result, catchment polygons are stored in three files, reflecting three licenses: (i) CC-BY-NC v4.0, for hydrography90 catchments and those that cross CCM2 and EU-Hydro boundaries; (ii) CC-BY 4.0, consistent with EU-Hydro for catchments that fall entirely within EU-Hydro's spatial extent, and (iii) ODbL, consistent with OSM for all catchments within Isle of Man, Orkney, Shetland and Faroe Islands.

Lakes were collated from four sources, (i) CCM2, for which we deemed license redistribution terms to be are consistent with CC-BY NC 4.0, (ii) EU-Hydro and HydroLAKES, which we deemed consistent with CC-BY 4.0, and (iii) OpenStreetMap, which is licensed under ODbL v1. Following the same approach to that used above for the enveloping catchments, we split the data into three files.

The files are licensed as follows:

Digital river network (linestrings) and subcatchments (polygons; where subcatchment polygons are associated with individual river segments)

1. amber_drn_eu_hydro_rivers & amber_subcatchments_eu_hydro_rivers (CC BY 4.0)
2. amber_drn_ccm2 & amber_subcatchments_ccm2 (CC BY NC 4.0)
3. amber_drn_hydrography90 & amber_subcatchments_hydrography90 (CC BY NC 4.0)
4. amber_drn_osm_waterways & amber_subcatchments_osm_waterways (ODbL)

Catchments (polygons enveloping complete river systems)

1. amber_h1_catchments_eu_hydro_ccm2_hydrography90 (CC BY NC 4.0)
2. amber_h1_catchments_eu_hydro (CC BY 4.0)
3. amber_h1_catchments_osm (ODbL)

Lakes (polygons)

1. amber_lakes_eu_hydro_ccm2_hydrography90 (CC BY NC 4.0)
2. amber_lakes_eu_hydro (CC BY 4.0)
3. amber_lakes_osm (ODbL)

River obstacles (points)

1. amber_post_glacial_analysis (ODbL)

OSM countries (polygons)

1. countries_osm_admin_levels_2_and_4 (ODbL)

Computation regions (polygons)

1. amber_salmon_regions_eu_hydro (CC BY 4.0)
2. amber_salmon_regions_eu_hydro_ccm2_hydrography90 (CC BY NC 4.0)
3. amber_salmon_regions_osm (ODbL)

Example R code to read geospatial data from multiple parquet files

# ------------------------------------------------------ #
# READ DRN FOR BARENTS SEA 
# ------------------------------------------------------ #
arrow_ds <- arrow::open_dataset(paste0(
  "C:\\PATHTO\\zenodo_drn_files\\"
        )) |>
  dplyr::filter(.data$sea_region == "Barents Sea") |>
  dplyr::select(c("riverID","geom"))

con <- DBI::dbConnect(duckdb::duckdb(), shutdown = TRUE)
duckdb::duckdb_register_arrow(con, "riv_table", arrow_ds)
DBI::dbExecute(con, "INSTALL spatial;")
DBI::dbExecute(con, "LOAD spatial;")
rivdb <- dplyr::tbl(con, "riv_table") |>
  dplyr::mutate("geom" = ST_GeomFromWKB(.data$geom))

drn <- rivdb |>
  dplyr::collect() |>
  dplyr::mutate("geom" = sf::st_as_sfc(.data$geom)) |>
  sf::st_as_sf() |>
  sf::st_set_crs("EPSG:3035")

drn |>
  ggplot2::ggplot()+
  ggplot2::geom_sf(ggplot2::aes(geometry = geom))
# ------------------------------------------------------ #

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