DOI: 10.6084/m9.figshare.25829464
title: <b>Antibiotics in the Global River System Arising from Human Consumption</b>

description: <b>Antibiotics in the Global River System Arising from Human Consumption</b><b>Data repository</b>Last updated: April 2025<br>prepared byHeloisa Ehalt Macedo (heloisa.ehaltmacedo@mail.mcgill.ca) and Bernhard Lehner (bernhard.lehner@mcgill.ca)<br><b>1. Overview and background</b>This repository contains the Python code, input, and output data for the research article: Ehalt Macedo, H., Lehner, B., Nicell, J., Khan, U., Klein, E. (2025). Antibiotics in the global river system arising from human consumption. PNAS Nexus. Further information and description of the model can be found in the same publication.The data repository includes 3 datasets:1. Python code: python project repository including the structure necessary for the model to run.2. Input data:a. A table containing information on all river segments associated with geometric attributes from RiverATLAS (Linke et al., 2019) and HydroROUT (Lehner and Grill, 2013), and attributes used in the HydroFATE model (Ehalt Macedo et al., 2024) based on underlying data such as HydroLAKES (Messager et al., 2016), and HydroWASTE (Ehalt Macedo et al., 2022).b. A table of parameters for the model run. The literature sources of the parameters for all substances and the scenarios are described in the research paper.c. A table of country-level consumption per capita of all contaminants being analyzed, as provided by Klein et al. (2018).3. Output data:a. A table including the unique river reach identifier associated with the river network, the resulting concentration and risk quotient for each contaminant, and totals using HydroFATE as described in the research paper.<br><b>2. Repository content</b>The data repository has the following structure:<b>HydroFATE_v1_1.zip/: </b>repository containing:<b>|---------Main_script/:</b><b>|---------------------Input/</b>: empty folder to add input data from “Input_data.gdb.zip”<b>|---------------------</b><b>Output/</b>: empty folder where results will be saved after model run<b>|---------------------</b><b>HydroFATE_v1_1.py</b> : python code with HydroFATE model version 1.1<b>|---------------------</b><b>config.py:</b> config file with model parameters<b>|---------</b><b>LICENSE</b>: license file for python code<b>|---------</b><b>README.md</b>: readme file for code description and compilation instructions<b>|---------</b><b>Technical_documentation_Antibiotics</b>: technical documentation for the code and datasets<b>Input_data.gdb.zip/:</b> file geodatabase in ESRI® geodatabase format containing 3 feature classes (zipped):<b>|---------</b><b>streams:</b> table including global river network attributes.<b>|---------</b><b>parameters</b>: table including parameters and configuration settings.<b>|---------</b><b>consumption:</b><b> </b>table including country-level consumption per capita of all substances.<b>Output.gdb.zip/:</b> file geodatabase in ESRI® geodatabase format containing 1 feature class (zipped):<b>|---------</b><b>Total_results</b>: table with model predictions for every river reach of the global river network.<br><br><b>3. Data format and projection</b>A license for the software ArcGIS Pro is required to run the provided scripts. 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). Full descriptions of dataset attributes can be found in the Technical documentation in this repository.<b>4. License and citations</b><b>4.1 License Agreement</b>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/.<br><b>4.2 Citations and Acknowledgements.</b>Citations and acknowledgements of this dataset should be made as follows:Ehalt Macedo, H., Lehner, B., Nicell, J., Khan, U., Klein, E. (2025). Antibiotics in the global river system arising from human consumption. PNAS Nexus.We kindly ask users to cite this study in any published material produced using it. Online<b>class</b> links to this repository (https://doi.org/10.6084/m9.figshare.25829464) should also be provided.<br><b>5. References</b>Ehalt Macedo, H., Lehner, B., Nicell, J. & Grill, G. HydroFATE (v1): a high-resolution contaminant fate model for the global river system. <i>Geosci. Model Dev.</i> <b>17</b>, 2877-2899, doi:10.5194/gmd-17-2877-2024 (2024).Ehalt Macedo, H., Lehner, B., Nicell, J., Grill, G., Li, J., Limtong, A., and Shakya, R.: Distribution and characteristics of wastewater treatment plants within the global river network, Earth Syst. Sci. Data, 14, 559-577, doi: 10.5194/essd-14-559-2022, 2022.Klein, E. Y., Boeckel, T. P. V., Martinez, E. M., Pant, S., Gandra, S., Levin, S. A., Goossens, H., and Laxminarayan, R.: Global increase and geographic convergence in antibiotic consumption between 2000 and 2015, Proceedings of the National Academy of Sciences, 115, E3463-E3470, doi: 10.1073/pnas.1717295115, 2018.Lehner, B. and Grill, G.: Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems, Hydrol Process, 27, 2171-2186, doi: 10.1002/hyp.9740, 2013.Linke, S., Lehner, B., Ouellet Dallaire, C., Ariwi, J., Grill, G., Anand, M., Beames, P., Burchard-Levine, V., Maxwell, S., Moidu, H., Tan, F., and Thieme, M.: Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution, Scientific Data, 6, 283, doi: 10.1038/s41597-019-0300-6, 2019.Messager, M. L., Lehner, B., Grill, G., Nedeva, I., and Schmitt, O.: Estimating the volume and age of water stored in global lakes using a geo-statistical approach, Nature Communications, 7, 13603, doi: 10.1038/ncomms13603, 2016.