Climate Driven Hydrologic Nonstationarity Patterns across the Continental United States

This repository contains the code and data for the research project "Climate Driven Hydrologic Nonstationarity Patterns across the Continental United States". The project investigates the impact of climate change and land use-land cover change on hydrologic nonstationarity in various catchments across the Continental United States (CONUS).

Contents

Google Earth Engine scripts

• ECMWF climate reanalysis data gee_export_ecmwf.js
• forest cover gee_export_forest.js
• impervious surface data gee_export_impervious.js
• generating maps gee_maps.js

Python scripts

• Mann-Kendall statistical analysis mannkendal.py
• Run the Mann-Kendall run_mk.py
• Regression analysis code regression_qp.ipynb
• Add the land use land cover results to Mann Kendal analysis add_lulc_to_mk_results.py
• Summarize the nonstationarity stationaritySummary_MannKendal_.py

Other

• attributes_with_NWM_LSTM_PP.csv
• calc_error.txt
• calc_output.txt
• job
• results-mk-lc.txt
• results-mk-runoff-ratio.txt
• results-mk.txt
• usgs_site_info.csv

License

This project is under a proprietary license. Please see LICENSE.md for more details. Citation

• Proprietary license for the code and data. LICENSE.md

Directories

Directories containing various data and results used in the study.

• ecmwf
• lulc
• maps
• nldas_precipitation
• pq
• usgs_streamflow

Usage

To use the scripts in this repository, follow these steps:

• Clone the repository to your local machine.
• Ensure you have the necessary Python environment to run the scripts. Dependencies include pandas, numpy, matplotlib, and other standard scientific Python packages.
• For Google Earth Engine scripts, you need access to Google Earth Engine and the necessary setup to run JavaScript-based scripts.
• The preprint.pdf file contains the research paper associated with this project.

Citation

If you use the code or data from this project, please cite the associated writeup with the DOI at the top of this page.