具有时滞效应的air2stream河流水温模型及应用研究

Research and Application of the air2stream River Water Temperature Model with Time Lag

高精度河流水温模型对于深入了解水温的时空变化特征和河流生态修复具有重要意义。基于数据驱动的air2stream模型在保证预测精度的同时,避免了计算的复杂性,已成为河流水温模拟常用的模型。由于水的热惯性及水文条件等的影响,河流水温变化往往显著滞后于气温变化,而air2stream原模型并未考虑滞后效应,导致该模型在流量未知情况下实际精度偏低。为解决该问题,采用气温-水温皮尔逊相关系数计算时滞天数,构建具有时滞的air2stream新模型,进一步根据长江中下游地区两个监测站的多年实测数据验证新模型的有效性和稳定性。结果表明:新模型在不引进额外观测数据的条件下具有更高精度且性能更稳定。相比原模型,在两个监测站新模型的均方根误差分别降低约4.29%和5.85%。新模型具有精度高、水文要素需求少的特点,可为长江中下游的水环境影响评价和生态保护提供依据。

High-precision river temperature models are of great significance for the comprehensive understanding of spatiotemporal characteristics of river temperature and ecosystem restoration.The data-driven air2stream model,known for ensuring prediction ac-curacy while avoiding computational complexity,has become a commonly used model in river temperature simulation.However,the original air2stream model does not consider the lag effect of river temperature,primarily caused by factors such as water's thermal inertia and hydrological conditions.This leads to the decreased practical accuracy of the model when flow data is unavailable.To address this issue,this study employed Pearson correlation coefficient between air temperature and water temperature to determine time lag parameters,and constructed a new air2stream model with time lag.Furthermore,the new model's effectiveness and stabil-ity were validated by multi-year observed data from two monitoring stations in the middle and lower reaches of the Yangtze River.The results indicate that the new model offers higher accuracy and stability without additional observation data.Compared with the original model,the Root Mean Square Errors of the new model at the two monitoring stations are reduced by approxi-mately 4.29%and 5.85%respectively.The new model is characterized by high precision and low hydrological data requirements,which can provide a basis for water environmental impact assessment and ecological protection in the middle and lower reaches of the Yangtze River.