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Free keywords:
TURBULENCE-INDUCED FLOCCULATION; SUSPENDED PARTICULATE MATTER; VARIABLE
FRACTAL DIMENSION; COHESIVE SEDIMENT; COAGULATION EFFICIENCY; FLOC
CHARACTERISTICS; SETTLING VELOCITY; SCHELDT ESTUARY; SEINE ESTUARY;
PARTICLESSuspended particulate matter (SPM); Flocculation/aggregation; Size
class-based model; Distribution-based model; Tidal dynamics; Model
comparison;
Abstract:
Modeling suspended particulate matter (SPM) dynamics is essential to calculate sediment transport budgets and to provide relevant knowledge for the understanding of biogeochemical cycles in coastal waters. Natural flocs are characterized by their size, shape, structure and density that determine their settling velocity and therefore their vertical as well as horizontal transport. During transport, several processes, in particular aggregation and fragmentation, alter these particle properties. In the present study, we compare two different OD modeling approaches for flocculation processes, a size class-based (SCB) model and a distribution-based (DB) model that follows the first moment of the particle distribution function. The study leads to an improved understanding of both models, which aim to better resolve SPM dynamics in spatial and ecosystem models in the near future. Both models are validated using data from laboratory experiments. The time evolution of the particle dynamics subjected to tidal forcing is represented equally well by both models, in particular in terms of (i) the mean diameter, (ii) the computed mean settling velocity and (iii) the particle size distribution. A sensitivity study revealed low sensitivity to changes in the collision efficiency and initial conditions, but a high sensitivity with respect to the particles' fractal dimension. The latter is an incitation to enhance the knowledge on processes related to changes of fractal dimension in order to further improve SPM transport models. The limitations of both models are discussed. The model intercomparison revealed that the SCB model is useful for studies focussing on the time evolution of floc distributions, especially under highly variable conditions. By contrast, the DB model is more suitable for studies dealing with larger spatial scales and, moreover, with coupled marine physical-biogeochemical systems, as it is computationally very effective. (C) 2010 Elsevier Ltd. All rights reserved.
