Python code to identify sources of chemical pollutants in waterways

The code was developed as part of a six-month project funded via a NERC Exploring the Frontiers grant. K. Chrapkiewicz was the principal code developer with A. Lipp. We made use of existing models developed by co-investigators A. Lipp and R. Barnes. This work built upon the optimisation techniques developed by A. Lipp, G. Roberts and colleagues. The data inverted in this study were generated L Barron and colleagues (Egli et al., 2023).

To run the code please see the readme files that accompany this repository. Briefly, once the code is downloaded and installed a minimum working example can be run using > python examples/mwe.py. Examples of data and their associated formats are included with this repository. The raw chemical data are also included. Examples of outputs in the form of figures (.png format) are also included. With regards to quality assurance, a synthetic data inversion was conducted and an Analysis of Variance and an assessment of the uncertainties were also carried out. Further details are provided in the supporting documentation and cited papers.