The Influence of Model Structure Uncertainty on Water Quality Assessment

Physically-based mathematical water quality models are known as potentially effective tools to simulate the temporal and spatial variations of water quality variables along rivers. Each model relies on specific sets of assumptions and equations to simulate the physico-biochemical processes, which influence on its simulation results. This paper aims to improve the insight in the uncertainties related to state–of–the–art river physico-biochemical water quality modelling. Sensitivity analysis is applied to the processes implemented in three most popular commercial software packages: MIKE11, InfoWorks RS and InfoWorks ICM. This is done for the Molse Neet river case study. Firstly, the physico-biochemical processes are screened to obtain a preliminary assessment on the critical processes and to determine the processes that require more detailed comparison. Then, local sensitivity analysis is carried out to specify the sensitive parameters and processes. Results show that the hydrodynamic results, heat transfer rate and reaeration simulations cause large differences in model simulation outputs for water temperature and dissolved oxygen concentrations. The ignorance of processes related to sediment transport, phytoplankton and bacteria has a significant influence on the higher values of organic matter and lower values of dissolved oxygen concentrations. The three models show consensus on the main pollutant sources explaining organic matter and nitrate concentrations, but disagree on the main factors explaining the DO concentrations.