Calibration and identifiability analysis of a water quality model to evaluate the contribution of different processes to the short-term dynamics of suspended sediment and dissolved nutrients in the surface water of a rural catchment

1998 ◽  
Vol 12 (5) ◽  
pp. 683-699 ◽  
Author(s):  
M. van Der Perk
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Suspended Sediment ◽  
Water Quality Model ◽  
Quality Model ◽  
Dissolved Nutrients ◽  
Short Term ◽  
Identifiability Analysis ◽  
Rural Catchment

Identifiability analysis of the CSTR river water quality model

2006 ◽  
Vol 53 (1) ◽  
pp. 93-99 ◽  
Author(s):  
J. Chen ◽  
Y. Deng
Keyword(s):  
Water Quality ◽  
River Water ◽  
Sampling Frequency ◽  
Water Quality Model ◽  
River Water Quality ◽  
Quality Model ◽  
Identifiability Analysis ◽  
Quality Models ◽  
Observational Errors ◽  
Water Quality Models

Conceptual river water quality models are widely known to lack identifiability. The causes for that can be due to model structure errors, observational errors and less frequent samplings. Although significant efforts have been directed towards better identification of river water quality models, it is not clear whether a given model is structurally identifiable. Information is also limited regarding the contribution of different unidentifiability sources. Taking the widely applied CSTR river water quality model as an example, this paper presents a theoretical proof that the CSTR model is indeed structurally identifiable. Its uncertainty is thus dominantly from observational errors and less frequent samplings. Given the current monitoring accuracy and sampling frequency, the unidentifiability from sampling frequency is found to be more significant than that from observational errors. It is also noted that there is a crucial sampling frequency between 0.1 and 1 day, over which the simulated river system could be represented by different illusions and the model application could be far less reliable.

Sign in / Sign up

Export Citation Format

Share Document