A dynamic compartment model to predict sedimentation and suspended particulate matter in coastal areas

This paper presents a new dynamic mass-balance model for suspended particulate matter (SPM) and sedimentation in coastal areas handling all important fluxes of SPM to, from and within coastal areas, as such areas can be defined according to the topographical bottleneck method. The model is based on ordinary differential equations and the calculation time (dt) is one month to reflect seasonal variations. An important demand, related to the practical utility of the model, is that it should be driven by variables readily accessed from standard monitoring programs or maps. Added to the dynamic core model are several (static) empirical regressions for standard operational effect variables used in coastal management, such as the Secchi depth, the oxygen saturation in the deep water, and chlorophyll-a concentrations. The obligatory driving variables include four morphometric parameters (coastal area, section area, mean and maximum depth), latitude (to predict surface water and deep water temperatures, stratification and mixing) and Secchi depth or SPM-concentrations in the sea outside the given coastal area. The model is based on four compartments: two water compartments (surface water and deep water; the separation between these two compartments is done not in the traditional manner from temperatures but from sedimentological criteria, as the water depth separating transportation areas from accumulation areas) and two sediment compartments (ET-areas, i.e., erosion and transportation areas where fine sediments are discontinuously being deposited, and A-areas, i.e., accumulation areas where fine sediments are continuously being deposited). The processes accounted for include inflow and outflow via surface and deep water, input from point sources, from primary production, from land uplift, sedimentation, burial (the transport of matter from surficial A-sediments to underlying sediments), resuspension, mixing and mineralization. The model has been validated with good results (the predictions of sedimentation are within the 95% confidence limits of the empirical data used to validate the model) against data collected by sediment traps placed in 17 Baltic coastal areas of different character. The paper also presents sensitivity and uncertainty tests of the model. The weakest part of the model concerns the sub-model to predict the ET-areas. Many of the structures in the model are general and have also been used with similar success for other types of aquatic systems (mainly lakes) and for other substances (mainly phosphorus, radionuclides and metals). We also present approaches to indicate how the model could be modified for coastal areas other than those included in this study, e.g., for open coasts, estuaries or areas influenced by tidal variations.