CSR5d project

This repository includes scripts for generating results in our 2024 GRL paper, Deciphering the Role of Total Water Storage Anomalies in Mediating Regional Flooding.

Explanation of scripts

Data handling

• downloadERA5SWE.py: Download ERA5 Snow Water Equivalent data from CDS portal
• downloadGloFAS.py: Download GloFAS data from CDS portal
• parseYangtze.py: Parse Yangtze station data into GRDC format

Analyses

• grdc.py: Main code for CSR.5d analysis. This generates Figures 1, 2,3 and Figure S1, S3 in the paper
• grdc_monthly5d.py: Main code for upsampled CSR.monthly analysis (linearly interpolated to the same 5-day intervals as CSR.5d). This generates Figure S2 in the paper

Utility functions

• myutils.py: Various utility functions
• dataloader_global.py, csr5dloader.py: data loading and pre-processing functions
• glofas_all_new.py: code for extracting GloFAS flow series from GRDC gage locations

Dependencies

The following is a list of major dependencies. A full list is provided in conda_env.yaml

• rioxarray, geopandas, tigramite, cartopy, xarray, shapely

We used data from GloFAS, ERA5, and GRDC, and Köppen–Geiger. The references are given in the paper.

The CSR.5d dataset is maintained by Dr. Himanshu Save (himanshu.save@csr.utexas.edu).

If you use materials in this repo, please consider citing our GRL paper

@article{sun2024deciphering,
  title={Deciphering the Role of Total Water Storage Anomalies in Mediating Regional Flooding},
  author={Sun, Alexander Y and Save, Himanshu and Rateb, Ashraf and Jiang, Peishi and Scanlon, Bridget R},
  journal={Geophysical Research Letters},
  volume={51},
  number={16},
  pages={e2023GL108126},
  year={2024},
  publisher={Wiley Online Library},
  doi={10.1029/2023GL108126}
}