This repository contains the source code of the Sublimation-Enhanced Glacier SWAT+ Model (SEGSWAT+), which is an improved modeling approach developed as part of the research published in the paper:
Combining Physical Hydrological Model with Explainable Machine Learning Methods to Enhance Water Balance Assessment in Glacial River Basins
DOI: 10.3390/w16243699
The SEGSWAT+ model improves upon the traditional SWAT+ model by incorporating sublimation dynamics for glacierized basins, addressing critical water balance components in glacial river systems. This enhancement is achieved by combining the physical hydrological modeling capabilities of SWAT+ with insights from explainable machine learning techniques.
- Sublimation Dynamics: Improved simulation of glacier sublimation processes, critical for accurate water balance assessments in high-altitude basins.
- Glacial River Systems: Optimized for assessing water resources in glacier-fed river basins.
本仓库包含**Sublimation-Enhanced Glacier SWAT+ Model (SEGSWAT+)**的源代码，这是在以下研究论文中开发的改进模型方法：
结合物理水文模型和可解释机器学习方法以增强冰川河流流域水量平衡评估
DOI: 10.3390/w16243699
SEGSWAT+ 模型在传统 SWAT+ 模型的基础上进行了改进，通过加入冰川流域的升华动态模拟，解决了高海拔流域水量平衡中的关键问题。该改进方法结合了 SWAT+ 的物理水文建模能力与可解释机器学习技术的洞察。
- 升华动态模拟：改进了冰川升华过程的模拟，对高海拔流域的水量平衡评估至关重要。
- 冰川河流系统优化：专为冰川融水供给的流域水资源评估优化。
If you use SEGSWAT+ in your research, please cite the original paper:
Citation Format / 引用格式:
Yang, R., Wu, J., Gan, G., Guo, R., & Zhang, H. (2024). Combining Physical Hydrological Model with Explainable Machine Learning Methods to Enhance Water Balance Assessment in Glacial River Basins. Water, 16(24), 3699. https://doi.org/10.3390/w16243699