Water level fluctuations drive bank instability in a hypertidal estuary

Abstract

Abstract. Hypertidal estuaries are very dynamic environments characterized by high tidal ranges (> 6 m) that can experience rapid rates of bank retreat. Whilst a large body of work on the processes, rates, patterns, and factors driving bank erosion has been undertaken in fluvial environments, the process mechanics affecting the stability of the banks with respect to mass failure in hypertidal settings are not well-documented. In this study, the processes and trends leading to bank failure and consequent retreat in hypertidal estuaries are treated within the context of the Severn Estuary (UK) by employing a combination of numerical models and field-based observations. Our results highlight that the periodic fluctuations in water level associated with the hypertidal environment drive regular fluctuations in the hydrostatic pressure exerted on the incipient failure surfaces that range from a confinement pressure of 0 kPa (at low tide) to ∼ 100 kPa (at high tide). However, the relatively low transmissivity of the fine-grained banks (that are typical of estuarine environments) results in low seepage inflow/outflow velocities (∼ 3 × 10−10 m s−1), such that variations in positive pore water pressures within the saturated bank are smaller, ranging between about 10 kPa (at low tide) and ∼ 43 kPa (at high tides). This imbalance in the resisting (hydrostatic confinement) versus driving (positive pore water pressures) forces thereby drives a frequent oscillation of bank stability between stable (at high tide) and unstable states (at low tide). This transition between stability and instability is found not only on a semidiurnal basis but also within a longer time frame. In the spring-to-neap transitional period, banks experience the coexistence of high degrees of saturation due to the high spring tides and decreasing confinement pressures favoured by the still moderately high channel water levels. This transitional period creates conditions when failures are more likely to occur.