Hydrology Graphs This repository contains the code for the manuscript "A Graph Formulation for Tracing Hydrological Pollutant Transport in Surface Waters." There are three main folders containing code and data, and these are outlined below. We call the framework for building a graph of these hydrological systems "Hydrology Graphs". Several of the datafiles for building this framework are large and cannot be stored on Github. To conserve space, the notebook get_and_unpack_data.ipynb or the script get_and_unpack_data.py can be used to download the data from the Watershed Boundary Dataset (WBD), the National Hydrography Dataset (NHDPlusV2), and the agricultural land dataset for the state of Wisconsin. The files WILakes.df and WIRivers.df metnioend in section 1 below are contained within the WI_lakes_rivers.zip folder, and the files 24k Hydro Waterbodies dataset are contained in a zip file under the directory DNR_data/Hydro_Waterbodies. These files can also be unpacked by running the corresponding cells in the notebook get_and_unpack_data.ipynb or get_and_unpack_data.py. 1. graph_construction This folder contains the data and code for building a graph of the watershed-river-waterbody hydrological system. It uses data from the Watershed Boundary Dataset (link here) and the National Hydrography Dataset (link here) as a basis and builds a list of directed edges. We use NetworkX to build and visualize the list as a graph.

1. case_studies This folder contains three .ipynb files for three separate case studies. These three case studies focus on how "Hydrology Graphs" can be used to analyze pollutant impacts in surface waters. Details of these case studies can be found in the manuscript above.

2. DNR_data This folder contains data from the Wisconsin Department of Natural Resources (DNR) on water quality in several Wisconsin lakes. The data was obtained from here using the file Web_scraping_script.py. The original downloaded reports are found in the folder original_lake_reports. These reports were then cleaned and reformatted using the script DNR_data_filter.ipynb. The resulting, cleaned reports are found in the Lakes folder. Each subfolder of the Lakes folder contains data for a single lake. The two .csvs lake_index_WBIC.csv contain an index for what lake each numbered subfolder corresponds. In addition, we added the corresponding COMID in lake_index_WBIC_COMID.csv by matching the NHDPlusV2 data to the Wisconsin DNR's 24k Hydro Waterbodies dataset which we downloaded from here. The DNR's reported data only matches lakes to a waterbody identification code (WBIC), so we use HYDROLakes (indexed by WBIC) to match to the COMID. This is done in the DNR_data_filter.ipynb script as well.

Python Versions The .py files in graph_construction/ were run using Python version 3.9.7. The scripts used the following packages and version numbers: geopandas (0.10.2) shapely (1.8.1.post1) tqdm (4.63.0) networkx (2.7.1) pandas (1.4.1) numpy (1.21.2).

This dataset is associated with the following publication: Cole, D.L., G.J. Ruiz-Mercado, and V.M. Zavala. A graph-based modeling framework for tracing hydrological pollutant transport in surface waters. COMPUTERS AND CHEMICAL ENGINEERING. Elsevier Science Ltd, New York, NY, USA, 179: 108457, (2023).