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Integrated data-modelling approach for suspended sediment transport on a regional scale
Vos, R.J.; ten Brummelhuis, P.G.J.; Gerritsen, H. (2000). Integrated data-modelling approach for suspended sediment transport on a regional scale. : 177-200

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  • Vos, R.J.
  • ten Brummelhuis, P.G.J.
  • Gerritsen, H., more

    This paper discusses an integrated data-modelling concept to monitor the seasonal variability of suspended particulate matter (SPM) patterns in the North Sea. It covers two aspects. First, the use of SPM transport model data to retrieve SPM concentrations from NOAA/AVHRR reflectance imagery by improving the algorithm to convert the reflectance data to SPM concentrations and to generate synoptic SPM images which are consistent in time. Second, the use of these observed SPM concentrations as model output targets to assess the sensitivity of the model performance for various model input parameters in some initial model set-ups, for example, the loads and dumping, the critical shear stress for erosion and sedimentation and settling velocity. The sensitivity analysis is based on the definition of a so-called Goodness-of-Fit (GoF) criterion (also denoted as cost-function) being a measure to quantify the difference between the model output and the model output targets, which is derived from both synoptic NOAA/AVHRR imagery and in situ concentration data. Key element in this approach is the requirement that a GoF criterion is defined that mimics the main features of the end-user requirements (i.e. the modelling objective) and the associated characteristic length and time scales. The sensitivity analysis is carried out by means of the adjoint model which is shown to provide a detailed, that is fully spatially and temporally distributed, insight into the model sensitivities. The objective of this chapter is to describe the components in the integrated use of observations and models as outlined above. This approach is demonstrated in a number of case studies of SPM transport in the Dutch Coastal Zone and in the North Sea. From the case studies, it can be concluded that loads and dumping are a major source of error. Due to the absence of observations over the vertical, the errors in the erosion/sedimentation processes that govern the vertical exchange and the bed sediment load are difficult to assess. As such, concentration profile observations and synoptic remote sensing imagery are considered to provide an ideal and necessary combination to monitor the SPM transport on a regional scale.

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