基于数据同化的深水湖库水温中短期预报  

Medium and short term prediction of water temperature in deep water lake-reservoir based on data assimilation

作　　者：孙博闻[1] 杨晰淯 暴柱[2] 刘晓波[3] 刘畅[3] 高学平[1] SUN Bowen;YANG Xiyu;BAO Zhu;LIU Xiaobo;LIU Chang;GAO Xueping(State Key Laboratory of Hydraulic Engineering Simulation and Safety,Tianjin University,Tianjin 300350,China;Luanhe River Water Quality Monitoring Center of Haihe River Basin,Luanhe River Diversion Project Management Bureau of Haihe River Water Conservancy Commission,Tangshan 064309,China;Institute of Water Ecology and Environment,China Institute of Water Resources and Hydropower Research,Beijing 100038,China)

机构地区：[1]天津大学水利工程仿真与安全国家重点实验室,天津300350 [2]水利部海河水利委员会引滦工程管理局海河流域滦河水质监测中心,河北唐山064309 [3]中国水利水电科学研究院水生态环境研究所,北京100038

出　　处：《水利学报》2022年第12期1445-1455,共11页Journal of Hydraulic Engineering

基　　金：国家自然科学基金项目(51609166);国家重点研发计划项目(2016YFC0401701)。

摘　　要：深水湖库的水温分布与演化影响着水体运动、生化反应和水生生物的新陈代谢过程,在中短期时间尺度上预报水温变化对湖库水质管理与生态环境安全十分必要。本文基于集合卡尔曼滤波算法与CE-QUAL-W2模型,构建可综合考虑模型参数、边界条件以及观测数据不确定性的湖库水温数据同化系统,利用水库调度数据与气象数据作为预报条件,将该系统应用于大黑汀水库进行1~10 d的中短期水温预报。结果表明:当集合数为100、模拟误差和观测误差分别为10%和1%时,同化系统能够兼顾较高的计算效率与模拟精度。同时校正模型参数和状态变量,能够使数据同化系统在不同水深处的水温模拟精度较无数据同化模拟结果提升41.2%~68.8%。随着预报期由1 d延长至10 d,各水深的预报误差由0.22~0.35℃增大至0.77~1.09℃。无论水库处于分层期或混合期,数据同化系统均能够在预报期内的气象条件及水库调度等内外部因素驱动下维持较高的准确性,高精度的水温中短期预报方法可以为湖库供水与生态安全提供理论与技术支撑。The distribution and evolution of water temperature in deep-water lakes and reservoirs affect water movement,biochemical reactions,and the metabolic processes of aquatic organisms.Forecasting water temperature changes is necessary for lake and reservoir water quality management and ecological environment safety.In this study a lake and reservoir water temperature data assimilation system is constructed on the basis of the ensemble Kalman filter algorithm and the CE-QUAL-W2 model,which is able to comprehensively consider model parameters,boundary conditions,and the uncertainty of observation data.The system is applied to Daheiting Reservoir for 1-10 days of medium and short term water temperature forecasting using reservoir operation data and meteorological data as forecast conditions.The results show that when the number of sets is 100,the simulation error and the observation error are 10%and 1%,the assimilation system can consider higher calculation efficiency and simulation accuracy.Simultaneously correcting the model parameters and state variables can increase the water temperature simulation accuracy of the data assimilation system at different water depths by 41.2%-68.8%compared to the results without data assimilation.As the forecast period was extended from 1 to 10 days,the forecast error of each water depth increased from 0.22-0.35℃to 0.77-1.09℃.Regardless of whether the reservoir is in the stratified or mixed period,the data assimilation system can maintain high accuracy under the internal and external factors such as meteorological conditions and reservoir scheduling during the forecast period.The high-precision medium and short term water temperature forecast method can provide theoretical and technical support for lake and reservoir water supply and ecological security.

关 键 词：湖库水温 中短期预报 数据同化 CE-QUAL-W2 集合卡尔曼滤波 

分 类 号：TV131[水利工程—水力学及河流动力学]