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Global prevalence of non-perennial rivers and streams

dataset
posted on 03.06.2021, 11:58 authored by Mathis MessagerMathis Messager, Bernhard LehnerBernhard Lehner
Global prevalence of non-perennial rivers and streams
June 2021

prepared by
Mathis L. Messager (mathis.messager@mail.mcgill.ca)
Bernhard Lehner (bernhard.lehner@mcgill.ca)

1. Overview and background
2. Repository content
3. Data format and projection
4. License and citations
4.1 License agreement
4.2 Citations and acknowledgements


1. Overview and background
This documentation describes the data produced for the research article: Messager, M. L., Lehner, B., Cockburn, C., Lamouroux, N., Pella, H., Snelder, T., Tockner, K., Trautmann, T., Watt, C. & Datry, T. (2021). Global prevalence of non-perennial rivers and streams. Nature. https://doi.org/10.1038/s41586-021-03565-5

In this study, we developed a statistical Random Forest model to produce the first reach-scale estimate of the global distribution of non-perennial rivers and streams. For this purpose, we linked quality-checked observed streamflow data from 5,615 gauging stations (on 4,428 perennial and 1,187 non-perennial reaches) with 113 candidate environmental predictors available globally. Predictors included variables describing climate, physiography, land cover, soil, geology, and groundwater as well as estimates of long-term naturalised (i.e., without anthropogenic water use in the form of abstractions or impoundments) mean monthly and mean annual flow (MAF), derived from a global hydrological model (WaterGAP 2.2; Müller Schmied et al. 2014). Following model training and validation, we predicted the probability of flow intermittence for all river reaches in the RiverATLAS database (Linke et al. 2019), a digital representation of the global river network at high spatial resolution.

The data repository includes two datasets resulting from this study:
1. a geometric network of the global river system where each river segment is associated with:
i. 113 hydro-environmental predictors used in model development and predictions, and
ii. the probability and class of flow intermittence predicted by the model.
2. point locations of the 5,516 gauging stations used in model training/testing, where each station is associated with a line segment representing a reach in the river network, and a set of metadata.

These datasets have been generated with source code located at messamat.github.io/globalirmap/.

Note that, although several attributes initially included in RiverATLAS version 1.0 have been updated for this study, the dataset provided here is not an established new version of RiverATLAS.


2. Repository content
The data repository has the following structure (for usage, see section 3. Data Format and Projection; GIRES stands for Global Intermittent Rivers and Ephemeral Streams):

GIRES_v10_gdb.zip/ : file geodatabase in ESRI® geodatabase format containing two feature classes (zipped)
|——— GIRES_v10_rivers : river network lines
|——— GIRES_v10_stations : points with streamflow summary statistics and metadata

GIRES_v10_shp.zip/ : directory containing ten shapefiles (zipped)
Same content as GIRES_v10_gdb.zip for users that cannot read ESRI geodatabases (tiled by region due to size limitations).
|——— GIRES_v10_rivers_af.shp : Africa
|——— GIRES_v10_rivers_ar.shp : North American Arctic
|——— GIRES_v10_rivers_as.shp : Asia
|——— GIRES_v10_rivers_au.shp : Australasia
|——— GIRES_v10_rivers_eu.shp : Europe
|——— GIRES_v10_rivers_gr.shp : Greenland
|——— GIRES_v10_rivers_na.shp : North America
|——— GIRES_v10_rivers_sa.shp : South America
|——— GIRES_v10_rivers_si.shp : Siberia
|——— GIRES_v10_stations.shp : points with streamflow summary statistics and metadata

Other_technical_documentations.zip/ : directory containing three documentation files (zipped)
|——— HydroATLAS_TechDoc_v10.pdf : documentation for river network framework
|——— RiverATLAS_Catalog_v10.pdf : documentation for river network hydro-environmental attributes
|——— Readme_GSIM_part1.txt : documentation for gauging stations from the Global Streamflow Indices and Metadata (GSIM) archive

README_Technical_documentation_GIRES_v10.pdf : full documentation for this repository


3. Data format and projection
The geometric network (lines) and gauging stations (points) datasets are distributed both in ESRI® file geodatabase and shapefile formats. The file geodatabase contains all data and is the prime, recommended format. Shapefiles are provided as a copy for users that cannot read the geodatabase. Each shapefile consists of five main files (.dbf, .sbn, .sbx, .shp, .shx), and projection information is provided in an ASCII text file (.prj). The attribute table can be accessed as a stand-alone file in dBASE format (.dbf) which is included in the Shapefile format.

These datasets are available electronically in compressed zip file format. To use the data files, the zip files must first be decompressed.

All data layers are provided in geographic (latitude/longitude) projection, referenced to datum WGS84. In ESRI® software this projection is defined by the geographic coordinate system GCS_WGS_1984 and datum D_WGS_1984 (EPSG: 4326).


4. License and citations
4.1 License agreement
This documentation and datasets are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (CC-BY-4.0 License). For all regulations regarding license grants, copyright, redistribution restrictions, required attributions, disclaimer of warranty, indemnification, liability, waiver of damages, and a precise definition of licensed materials, please refer to the License Agreement (https://creativecommons.org/licenses/by/4.0/legalcode). For a human-readable summary of the license, please see https://creativecommons.org/licenses/by/4.0/.

4.2 Citations and acknowledgements.
Citations and acknowledgements of this dataset should be made as follows:
Messager, M. L., Lehner, B., Cockburn, C., Lamouroux, N., Pella, H., Snelder, T., Tockner, K., Trautmann, T., Watt, C. & Datry, T. (2021). Global prevalence of non-perennial rivers and streams. Nature. https://doi.org/10.1038/s41586-021-03565-5

We kindly ask users to cite this study in any published material produced using it. If possible, online links to this repository (https://doi.org/10.6084/m9.figshare.14633022) should also be provided.

Funding

Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery grants RGPIN/341992-2013 and RGPIN/04541-2019

H2O’Lyon Doctoral School, Doctoral Fellowship, ANR-17-EURE-0018

European Union’s Horizon 2020, DRYvER project, #869226

McGill University, Tomlinson Doctoral Fellowship

History