水科学进展2023，Vol.34Issue(6)：901-912,12.DOI:10.14042/j.cnki.32.1309.2023.06.008
输水渠系水动力数字孪生模型糙率估计方法
Roughness estimation methods of hydrodynamic digital twin models for canal systems
摘要
Abstract
A segmented estimation method of roughness based on the variation of hydraulic radius and estimation accuracy is proposed in order to realize the real-time and high-fidelity roughness estimation of hydrodynamic digital twin(DT)models.This method considers the spatial variability of the roughness value in the longitudinal direction of canals.Based on canal segmentation,two different estimation frameworks,the independent estimation method and joint estimation method,are proposed.The ensemble Kalman filter algorithm is applied to estimate the roughness of each canal segment online based on the limited observed water levels.The results show that the two estimation methods can improve the accuracy of the model by 20%—50%.In addition,the independent estimation method is suitable for a complex canal system with a small error accumulation,while the joint estimation method is suitable for simple canals with unavailable observations.The proposed method can be used for parameter estimation and variable updating of hydrodynamic DT models,and provide a reference for the construction of DT water networks.关键词
糙率/输水渠系/数字孪生/南水北调/集合卡尔曼滤波/分段估计Key words
roughness/water transfer systems/digital twin/South-to-North Water Diversion Project/ensemble Kalman filter/segmented estimation分类
建筑与水利引用本文复制引用
管光华,刘王嘉仪,陈晓楠,史良胜..输水渠系水动力数字孪生模型糙率估计方法[J].水科学进展,2023,34(6):901-912,12.基金项目
国家自然科学基金资助项目(51979202 （）
51879199)The study is financially supported by the National Natural Science Foundation of China(No.51979202 （）
No.51879199). （）
