Abstract
Tidal inlets along the central coast of Vietnam are located in a microtidal, wave-dominated coastal environment. In addition, the Vietnam coast is highly influenced by the seasonal monsoon regime, which is characterized by large northeast waves from October to March and calm southeast waves from April to September every year. Consequently, the tidal inlet entrance morphologies often suffer from a dynamic seasonal evolution due to distinct differences in the direction of wave-induced longshore sediment transport (LST) between the two monsoon seasons. The migration or closure of tidal inlets causes a lot of problems for socio-economic development in the region since these are the main reasons leading to an increase in the risk of coastal flooding and the obstruction of navigation. This paper presents a comprehensive study of the morphological evolutions of natural tidal inlets on the central coast of Vietnam using long-term remote sensing data sets and by the Delft3D numerical model. Surprisingly, the estimated LST rates from the former method are in an order of magnitude agreement with the results from the latter one for all of the areas in this study. Based on the conservation equation for sand and comprehensive data collection, a new simple empirical formula for predicting the sand spit elongation rate as a function of the sand spit width is developed. Although the breaching of sand spit might happen during an extreme flood event at some tidal inlets, the growth rate of the spit before and after the breaching is almost unchanged. These findings are very useful information for supporting the local coastal authorities to find better management solutions in terms of sustainable development.
Highlights
Sand spits are one of the most dynamic and complex geographical features in coastal bays, lagoons, and river mouths
The morphological changes in sand spits highly depend on the interactions between wave transformation, tidal exchange, and longshore sediment transport (LST), as well as river discharge
Honegger et al (2020) [15] successfully extended the cBathy depth estimate algorithm to obtain the high-resolution bathymetry of a complex tidal inlet environment based on the time series of X-band radar image, while Rogowski et al (2018) [14] directly used X-band observations to accurately map the morphological changes in shallow ebb tidal deltas at the New River Inlet, North Carolina
Summary
Sand spits are one of the most dynamic and complex geographical features in coastal bays, lagoons, and river mouths. Remote sensing techniques such as video-camera systems [12], Light Detection and Ranging (liDAR) [13], X-band radar [14,15], and satellite imageries [16,17] can provide synoptic coverage over large areas with a wide range of temporal and spatial resolutions Among these studies, Honegger et al (2020) [15] successfully extended the cBathy depth estimate algorithm to obtain the high-resolution bathymetry of a complex tidal inlet environment based on the time series of X-band radar image, while Rogowski et al (2018) [14] directly used X-band observations to accurately map the morphological changes in shallow ebb tidal deltas at the New River Inlet, North Carolina. Exploiting applications of satellite images for areas which have limited field measurement data should be the first option
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