A statistical–dynamical method for predicting estuary morphology

Abstract

A statistical–dynamical model for estuary morphodynamics is presented and demonstrated with a case study on the Humber Estuary, UK. The model presented here is hybrid in nature where simplified process dynamics are combined with a data-driven approach. The modelling methodology uses an inverse technique to construct an unknown source function in the model-governing equation, using historic measurements of estuary bathymetry. Spatial and temporal variability of the source function was established using empirical orthogonal eigenfunction analysis. Predictions of estuary morphology are obtained by extrapolating the temporal coefficients of the EOFs, in order to construct a predicted source function which is then used in the hybrid morphodynamic equation to obtain the predicted estuary morphology. The model was applied to predict the morphological evolution of the Humber Estuary over a period of a decade. Predicted results were compared with measured bathymetry data. The results reveal that the model captured the decadal scale morphodynamic response of the estuary with a good qualitative accuracy, despite the simplified approach used in the model. The accuracy of model predictions can be greatly improved if high-frequency bathymetry data are available.