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浅水湖泊水质参数的伴随方程协同反演方法

陈燕 刘昭伟

水力发电学报2026,Vol.45Issue(8):50-59,10.
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水力发电学报2026,Vol.45Issue(8):50-59,10.DOI:10.11660/slfdxb.20260805

浅水湖泊水质参数的伴随方程协同反演方法

An adjoint method for multi-parameter inversion in shallow lake water quality modeling

陈燕 1刘昭伟2

作者信息

  • 1. 上海市城市建设设计研究总院(集团)有限公司,上海 200125
  • 2. 清华大学 水圈科学与水利工程全国重点实验室,北京 100084||清华四川能源互联网研究院,成都 610213
  • 折叠

摘要

Abstract

In large shallow lakes,where hydrodynamic conditions are relatively weak,biochemical processes play a dominant role in water quality evolution.This makes key parameters-such as the degradation coefficient and internal source strength-significantly impact water quality simulation.However,these parameters are often difficult to estimate directly due to the high complexity of biochemical processes in a natural water body,thereby posing a key challenge to the improvement of simulation accuracy.This paper formulates a gradient analytical expression of objective function with respect to parameters,focusing on degradation coefficient and internal source strength,through deriving an adjoint system of the depth-averaged convection-diffusion equation based on the adjoint equation method.Then,by applying the Broyden-Fletcher-Goldfarb-Shanno(BFGS)optimization algorithm,we construct a collaborative inversion framework for water quality parameters,and implement it on the OpenFOAM numerical platform.This joint inversion method is applied in a case study of CODMn analysis for the Naisi Lake of the East Route of the South-to-North Water Diversion Project.It shows conceptually reasonable ranges of the optimized degradation coefficient k=0.0185 d-1 and internal source strength S=0.179 g·m-2·d-1,and achieves the model simulations with relative RMSE values less than 16.6%,a significant reduction compared to the initial parameter scheme.The application also demonstrates its stable high-efficiency convergence in optimization calculations.Thus,this method can effectively improve the identification accuracy of parameters in the shallow lake water quality models,a useful approach to parameter inversion under complicated water environmental conditions.

关键词

水环境模拟/降解系数/内源源强/伴随方程法/南四湖

Key words

water environment simulation/degradation coefficient/internal source intensity/adjoint equation method/Nansi Lake

分类

资源环境

引用本文复制引用

陈燕,刘昭伟..浅水湖泊水质参数的伴随方程协同反演方法[J].水力发电学报,2026,45(8):50-59,10.

基金项目

京津冀环境综合治理国家科技重大专项(2025ZD1202102) (2025ZD1202102)

水圈科学与水利工程全国重点实验室重点项目(sklhse-TD-2026-B01) (sklhse-TD-2026-B01)

清华四川能源互联网研究院重点创新项目(35130240067) (35130240067)

水力发电学报

1003-1243

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