Hydrochemical modelling of a stream dominated by organic acids and organically bound aluminium

First Dynamic Model of Dissolved Organic Carbon Derived Directly from High-Frequency Observations through Contiguous Storms

“…All interpretations presented within this study were based on variables recorded every 15 min and so avoided any aliasing effect on TC fast . Observational data sets associated with previous DOC modeling studies − do not have this sustained intensity of DOC monitoring. As a result, these studies may not have observations sufficient to prevent temporal aliasing in the DOC LOAD dynamics and resultant model parameters.…”

“…Dynamic models that are built directly from the information contained within time-series observations (i.e., data-based models without predetermined model structures) have the greatest potential to have parsimonious structures. Only a few dynamic models for the simulation of stream DOC CONC (or DOC LOAD ) over time have been developed, notably the dynamic conceptual models of Hornberger et al, Taugbøl et al, Boyer et al, , Futter et al, , and Ågren et al These models differ from steady-state models of DOC (e.g., Grieve, and Liu et al) in that dynamic models are able to simulate the effects of initial conditions or “memory effects” (i.e., effects of past values of DOC or associated mobilization processes or transport variables) as well as lags to response and exhaustion of stores. Although some of these dynamic models may be described as parsimonious, none have utilized regularly sampled, subdaily data from contiguous storm events or have had their structure (and associated parameters) derived directly from the dynamics contained within observed, subdaily time series of DOC LOAD (i.e., data-based models).…”

Separating the natural and anthropogenic components of spring flood pH decline: A method for areas that are not chronically acidified

“…While the mechanistic models could be used to try to distinguish natural from anthropogenic influences, the large amount of information and site history needed for each application of such models limits their use as an operational management tool. A more fundamental concern is the overparameterization of such models which makes it unclear as to whether they have succeeded in accurately describing episode processes [TaugbOl et al, 1994].…”