This repository contains the implementation of AWARE 2.0 characterization factors on basin-month-resolution, as documented in https://doi.org/10.1111/jiec.70023. CFs for use in LCA are provided at https://doi.org/10.5281/zenodo.8215863.
For general information on AWARE, see https://wulca-waterlca.org/what-is-aware/
Note: This code allows to recalculate AWARE2.0. However, due to time constraints at the moment of publishing, it is not optimized for efficiency and could very well be implemented much easier without the AWARE_data and AWARE_CF_equation classes. The reason for the rather overcomplicated logic is that the code was extracted from a larger project that required this logic.
AWARE 2.0 provides spatially explicit characterization factors (CFs) that estimate water deprivation potential at the basin level. The methodology combines:
- Actual water availability estimations [from Global Hydrological Model (GHM) WaterGAP2.2e]
- Environmental water requirements (EWR)
- Human water consumption
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AWARE_data.py- Main data class (AWARE_data) that stores and manages all hydrological data obtained from netCDF files, including water consumption, discharge, and environmental water requirements. -
AWARE_CF_equation.py- Core calculation engine (AWARE_CF_equation) that computes AWARE characterization factors from hydrological inputs. Includes basin-subdivision algorithms for subdivided river basins. -
AWARE_data_import.py- Data import and processing functions for converting raw hydrological data (from WaterGAP2.2e) into basin-scale aggregated values. Also works with some other GHMs providing output on ISIMIP.
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WaterGAP 2.2e model outputs for various hydrological variables:
atotuse_*: Total anthropogenic water usedis_*: Water dischargepXXXuse_*: Sectoral water use (domestic, industrial, irrigation, livestock, manufacturing, electricity)qtot_*: Total runoff
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Mapping and basin information:
mapping/BasinGrid.csv- Grid-to-basin mappingmapping/Area.csv- Basin areasmapping/Deltas.csv- Delta basin informationmapping/InlandSinkBasins.csv- Inland sink basinsmapping/InlandSinkInflowCells.csv- Inland sink inflow cells
- Calculated characterization factors and intermediate results
- Separate components for consumption and discharge
- Prescribed differences between original and postprocessed WaterGAP2.2e data for 2009-2019
AWARE2.0_reproduced.ipynb- Main notebook demonstrating the complete AWARE 2.0 calculation workflow
- Python 3.11
- pandas
- xarray
- numpy
- openpyxl (for Excel file handling)
- certifi
- netcdf4
- Clone or download the repository
- Create a Python environment with required Python packages (see requirements.txt for the package versions this code was tested with)
- Download the Input data (see Jupyter Notebook for more information)
- Run Jupyter Notebook
- Data Import: Use functions in
AWARE_data_import.pyto process raw GHM/GCM output data - Create Data Object: Initialize an
AWARE_dataobject with your model combination metadata - Calculate Characterization Factors: Use
AWARECF_equationto compute CFs from hydrological inputs
See the Jupyter notebooks for complete, working examples.
If you use this code in your research, please cite the documentation additional to the repository:
- Seitfudem, G., Berger, M., Schmied, H. M., & Boulay, A.-M. (2025). The updated and improved method for water scarcity impact assessment in LCA, AWARE2.0. Journal of Industrial Ecology, 29(3), 891–907. https://doi.org/10.1111/jiec.70023
Further relevant citations:
- Boulay, A.-M., Bare, J., Benini, L., Berger, M., Lathuillière, M. J., Manzardo, A., Margni, M., Motoshita, M., Núñez, M., Pastor, A. V., Ridoutt, B., Oki, T., Worbe, S., & Pfister, S. (2018). The WULCA consensus characterization model for water scarcity footprints: Assessing impacts of water consumption based on available water remaining (AWARE). International Journal of Life Cycle Assessment, 23(2), 368–378. https://doi.org/10.1007/s11367-017-1333-8
Georg Seitfudem, georg.seitfudem@polymtl.ca
CC BY 4.0