Dataset for Cryo-FSC: A Dynamic Functional Connectivity Index Reveals Spatio-Temporal Shifts in Sediment Transport in the Permafrost-Dominated River Systems

# Source Code and Sample Datasets for Cryo-FSC

## Overview
This repository contains the core computational scripts and sample data slices for the manuscript: 
**"Cryo-FSC: A Dynamic Functional Connectivity Index Reveals Spatio-Temporal Shifts in Sediment Transport in the Permafrost-Dominated River Systems"** (currently under review at *Water Resources Research*).

The Cryo-FSC index is a novel tool designed to dynamically quantify functional sediment connectivity in permafrost-dominated river systems, explicitly integrating key cold-region dynamics such as meltwater contributions, vegetation shifts, and active layer freeze-thaw status.

## ⚠️ Important Notice for Reviewers Regarding Data
Due to Zenodo's file size limitations and the massive storage requirements of the long-term, high-resolution spatial datasets spanning from 2000 to 2022 across the entire Source Region of the Yangtze River (SRYR), **the data provided in this repository are compressed sample slices.** These sample datasets are provided **strictly for peer-review purposes** to demonstrate the functionality of the source code, verify the computational logic of the Cryo-FSC framework, and ensure the reproducibility of our methodology. 

**Full Dataset Access:** The complete continuous datasets and spatial products are securely archived by the research team. If you require access to the full, uncompressed dataset for further validation or subsequent research, please do not hesitate to contact the corresponding authors.

## Repository Contents
Scripts: Contains the core source code used to generate the Cryo-FSC index.
Sample_data: Contains compressed spatial data slices for demonstration. Example: Cryo-FSC_200101.tif]

## Note on Cryospheric Forcing Data
Please note that the calculations for the core cryospheric variables, runoff coefficients (integrating both meltwater and precipitation), and land surface thermal states were simulated offline. For detailed physical parameterizations and the computational framework of these processes, please refer to the Distributed Hydro-Thermal Coupled (DHTC) model developed by our team:
* Guo, L., et al. (2024). Development of a modular distributed hydro-thermal coupled hydrological model for cold regions. Journal of Hydrology.
Guo, L., et al. (2025). Hydrological Changes Caused by Integrated Warming, Wetting, and Greening in Permafrost Regions of the Qinghai‐Tibetan Plateau. Water Resources Research.

##Contact Information
For full data requests or technical questions, please contact the corresponding authors

##Citation
If you use the code or conceptual framework provided in this repository, please cite the associated manuscript once published in Water Resources Research.