基于随机森林模型的湫水河流域洪水过程模拟

Random Forests Model Based Flood Process Simulation in the Qiushui River Basin

摘要: 黄河中游干旱半干旱地区洪水预报精度水平普遍不高，其主要原因在于降雨时空高度变异性以及大范围水土保持措施对产汇流的强烈干扰。随着现代统计理论发展，智能机器学习算法为该地区洪水预报提供了新的途径。以黄河中游左岸湫水河流域为例，采用随机森林算法建立暴雨洪水预报模型，对汛期场次洪水过程进行模拟，结果表明：当计算时间步长为1小时，随机森林模型的确定性系数(NSE)平均值为0.47，以NSE ≥ 0.60衡量，合格率为42%；当计算时间步长为0.5小时，NSE平均值为0.76，场次洪水预报合格率为88%；由此可知，输入资料精度是决定模型精度的主要因素。此外，不同时间步长条件下，随机森林模型的应用效果均明显优于传统的多元回归统计模型，表明随机森林模型适用于湫水河流域的洪水过程预报，对黄河中游黄土高原地区防洪预警具有一定参考价值。

Abstract: The accuracy level of flood forecasting in arid and semi-arid areas of the middle Yellow River region is generally not high, which is mainly due to the spatial and temporal variability of rainfall and the inten-sive disturbances of large-scale soil and water conservation measures on the runoff production and routing processes. With the development of modern statistical theory, intelligent machine learning algorithms provide a new way for flood forecasting in this region. Taking the Qiushui River Basin on the left bank of the middle reaches of the Yellow River as an example, the random forest algorithm was used to establish the storm-flood forecasting model and simulate the rainfall-runoff during the flood season. The results showed that when the calculation time step was 1 hour, the average value of the Nash-Sutcliffe efficiency (NSE) of the Random Forest model was 0.47, and the qualified rate was 42% when NSE ≥ 0.60 was measured. When the calculation time step was 0.5 hours, the average NSE value was 0.76, and the corresponding qualified rate increased to 88%. Therefore, the accuracy of the input data was a main factor affecting the model accuracy in this region. In addition, under different time steps conditions, the performance of the Random Forest model is obviously better than that of the traditional multivariate regression statistical model, indicating that the random forest model is suitable for flood process prediction in the Qiushui River basin, and has a certain reference value for the flood warning in the Loess Plateau in the middle reaches of the Yellow River.