Identifying Non-Perennial River Reaches: A Hybrid Model Combining WEP-L and Random Forest

The proportion of non-perennial rivers within the global river network is increasing, and research on these rivers has significantly grown in recent years due to their important role in water resource management and ecosystems. However, existing identification methods primarily rely on river networks with monitoring data and often overlook the temporal variation in flow, limiting further research and analysis. We propose a novel identification approach that couples the WEP-L model with random forest prediction, based on a comprehensive analysis of the limitations of current methods. Specifically, this method involves simulating river flow and incorporating time-series forecasting to facilitate the identification of non-perennial rivers. This approach also divides non-perennial rivers into significantly seasonal and non-significantly seasonal rivers by incorporating seasonal analysis, providing a theoretical foundation for studying their causes and formulating conservation strategies. Using the Yellow River basin in Gansu province as a case study, the results indicate that the total length of non-perennial rivers is 13,085.67 km, accounting for 42.09% of the region’s river length. The cessation periods of significant seasonal non-perennial rivers are primarily in fall and winter, while flow periods are concentrated in summer. The findings provide valuable guidance for the ecological conservation and sustainable management of non-perennial rivers, both in the Yellow River basin and other regions. The introduction and application of this method are expected to improve the identification and management of non-perennial rivers, contributing to the long-term sustainability of water resources.