Prediction of Shoreline Change for the Calculation of the Integrated Littoral Sediment Budget

The severe coastal erosions are being accelerated along the east coast of South Korea owing to the intermittent erosions and depositions caused by the imbalance between the effective sediment volume supplied from coasts and rivers and the sediment transport rate. Consequently, many studies are being conducted to develop coastal-erosion reduction measures. To accurately determine the cause of coastal erosion, the causes of the erosion and deposition should be accurately diagnosed, and a comprehensive evaluation system for the sediment transport mechanism in the watershed and sea while considering regional characteristics is required. In particular, realizing the evaluation of the effective sediment volume that flows from the river to the sea through observations is a highly challenging task, and various research and developments are required to realize it, as it is still in the basic research stage. The purpose of this study was to systematically analyze the comprehensive sediment budget for coastal areas. First, an analytical system was developed. Then, a shoreline model was constructed by considering the size of the mixed particles. The parameters required for developing the model were determined using the observation data to improve the shoreline model. A sediment runoff model was applied to evaluate the effective sediment volume supplied from the river to the sea, and the applicability of this model was evaluated by comparing it with the sediment supply volume according to the soil and water assessment tool model. The representative wave and the input parameters of the model were set using the observation data of several years. It was found that the prediction performance of the shoreline change model improved when the effective sediment volume was considered, and the particles of the sediment on the shore were assumed to comprise multiple sizes. In particular, the prediction performance improved when the balance of the sediment budget was adjusted by applying a groin having a structurally similar performance to take into consideration the geographic features of the Deokbongsan (island) in front of the river mouth bar. The model demonstrated a good performance in reproducing long-term shoreline changes when the characteristics of the sea waves and the effective sediment volume were considered.

Coastal Erosion Vulnerability in Mainland China Based on Fuzzy Evaluation of Cloud Models

Global climate change-induced sea-level rise and storm wave intensification, along with the large population densities and high-intensity human development activities in coastal areas, have caused serious burden and damage to China’s coasts, led to the rapid growth of artificial shorelines development, and formed a “new Great Wall” of reinforced concrete against the laws of nature. After the last ice age, transgression formed the different features of China’s coast. Depending on the types of geological and landform features, coasts are divided into 36 evaluation units, and 10 indicators are selected from natural aspects (including tectonics, geomorphology, sediment, and storms) and aspects of social economy (population, GDP, Gross Domestic Product), and cloud model theory is used to build a coastal erosion vulnerability evaluation index system in China. The results show that high grade (V), high-middle grade (IV), middle grade (III), low-middle grade (II), and low grade (I) coastal erosion vulnerability degrees account for 5.56, 13.89, 41.67, 33.33, and 5.56% of the Chinese coastlines, respectively. The coastal erosion vulnerability of the subsidence zone is significantly higher than that of the uplift zone. Reverse cloud model and analytic hierarchy process calculation show that the main factors that control coastal erosion vulnerability since the transgression after the last ice age are geological structure, topography and lithological features, and in recent years, the decrease in sea sediment loads and increase in reclamation engineering. Mainland China must live with the basic situation of coastal erosion, and this study shows that the index system and method of cloud modeling are suitable for the evaluation of the coastal erosion vulnerability of the Chinese mainland. This study provides a scientific basis for the adaptive management of coastal erosion, coastal disaster assessment and the overall planning of land and sea.

Deconvolving The Effects of Coastal Erosion and Sea-Level Rise in Assessing Shoreline Retreat Along Semi-Arid Urban Coasts

The alarming vulnerability of low-lying sandy beaches to the acceleration of global sea level rise has been confirmed in the recent IPCC AR6 report. The situation is worsened by increasing coastal erosion, resulting in additional shoreline retreat of sandy beaches along several semi-arid urban coastal areas around the globe. The additional shoreline retreats from erosion are indicative of the rising imbalance in coastal sedimentary processes, which are a direct consequence of changes in precipitation patterns, urban growth, and change in land use. To quantify the magnitude and timescale of both coastal erosion and sea-level rise (SLR) in generating shoreline retreat of sandy beaches in semi-arid urban areas, we combine photogrammetric and statistical methods to measure and forecast the decadal evolution of these coastlines using two well-characterized sites that are hypothesized herein to be globally representative of these types of coasts undergoing rapid urban growth. We use multi-decadal shoreline positioning and land use classification surveys of the Southern California (SC, USA) and the Hammamet-North (HAM, Tunisia) beaches from aerial and orbital photogrammetric images, combined with the Digital Shoreline Analysis System, for the period from 1985 to 2018. Our results suggest that the current average shoreline retreat rates of sandy beaches range from -0.75 to -1.24 m/yr in SC and from -0.21 to -4.49 m/yr in HAM under similar aridity, land coverage and precipitation patterns. The observed decadal changes in shoreline positions along these semi-arid urban coastal areas are found to be accentuated by anthropogenic drivers associated with extensive urbanization, causing sediment imbalance at the coastline, adding up to the effect of the accelerating SLR. We assess that ~81% and 57% of the observed shoreline retreat was due to SLR, and 19% to 43% due to coastal erosion from urban growth along SC and HAM beaches, respectively. Using these measured rates, we establish a semi-empirical numerical model that combines urban growth and the observed shoreline retreat rate to forecast retreat rates through 2100 for both of our study areas, inferred herein to be representative of other global semi-arid urban coasts. Our model suggests that future average total shoreline retreat rates, accounting for both urban growth and SLR, range from -2 to -4 m/yr for SC and HAM sandy beaches, respectively, through 2100. The above suggests that if no mitigation is made, by 2100 the cumulative shoreline retreat in these urban areas could significantly exceed the Global Scale Assessment Model’s [46] cumulative projected average retreat of -30 m, confirming the alarming vulnerability of the semi-arid coastal urban areas that would need intensive and costly beach nourishment to control increasing shoreline erosion.