Hydro-Sedimentological Modelling of a Small, Trained Tidal Inlet System: “A case study of the Currumbin Creek tidal inlet, Queensland, Australia”

Abstract

Tidal inlets are one of the most important elements of coastal areas. Many tidal inlets all around the world have been identified with a great variety of characteristics such as shape, size and sedimentary structure. In earlier studies, only the very large inlets, as well as those highly socio-economically valuable, were at the centre of interest for researchers at the request of managing authorities. At the present time, a great amount of resources is still being diverted to these larger inlets. In contrast, while smaller inlets are considered important to the daily lives and activities of local communities, for many of them, there is a challenging need to balance the maintenance costs with achievable benefits. Currumbin Creek is a small tidal inlet located in South-East Queensland, Australia. This creek has a long history of maintenance due to the partial closure of its entrance, as well as unsafe navigation through the entrance channel. Since 1981, when the two jetties at the entrance became operational, annual dredging has been required to keep the entrance open for all its different stakeholders. However, the current investment in dredging does not provide a desirable outcomes, and soon after each dredging campaign, the entrance exhibits shallowness and navigation difficulty. Hence, following some discrete and limited research, which was conducted during the last decade, this project has been introduced to investigate the issue of entrance viability by performing field measurements and a computer simulations. Data from various resources were collected and analysed, leading to a comprehensive project-specific field measurement campaign. The justification for this campaign was the need to collect as much concurrent data as possible, which could be used for the calibration and validation of the outputs of the computer modelling. Following that, a state-of-the-art process-based simulation method was chosen to conduct the necessary hindcasting and forecasting simulation.