Classification of soft cliff dynamics using remote sensing and data mining techniques.

Coastal soft cliffs are subject to changes related to both marine and subaerial processes. It is imperative to comprehend the processes governing cliff erosion and develop predictive models for effective coastal protection. The primary objective of this study was to bridge the existing knowledge gap by elucidating the intricate relationship between changes in cliff system morphology and the driving forces behind these changes, all within the context of ongoing climate change. Therefore in this study, we employed various quantitative numerical methods to investigate the factors influencing coastal cliffs and the adjacent beaches. Our analysis involved the extraction of several morphological indicators, derived from terrestrial laser scanning data, which were then used to assess how cliffs respond to extreme weather events. The data span two winter storm seasons (2016-2018) and encompass three soft-cliff systems situated along the southern Baltic Sea, each characterized by distinct beach and cliff morphology. We conducted a detailed analysis of short-term cliff responses using various data mining techniques, revealing intricate mechanisms that govern beach and cliff changes. This comprehensive analysis has enabled the development of a classification system for soft cliff dynamics. Our statistical analysis highlights that each study area exhibits a unique conditional dependency between erosion processes and hydrometeorological conditions, both during and between storm events. Furthermore, our findings underscore the vulnerability of cliff coastlines to extreme water levels and episodes of intense precipitation.

Future losses of ecosystem services due to coastal erosion in Europe.

Coastal erosion is a major issue facing Europe that will only worsen under future climate change and the resulting sea level rise. One effect of erosion is the loss of ecosystem services, which are provided by coastal areas, such as provisioning, regulating, habitat, and cultural services. These services can be quantified in monetary terms. Here, we present comprehensive estimates of future decline in coastal ecosystem services due to the erosion of sandy coastlines. We used datasets derived from remote sensing products: a pan-European land cover/use dataset (Corine Land Cover) and new global probabilistic coastal erosion projections constrained by artificial and topographical barriers to erosion. The results include historical changes (2000-2018) and projections under two emission scenarios (RCP4.5 and RCP8.5) for 2050 and 2100 together with uncertainty bounds. We estimate that in 2018, the coastal zone (excluding open sea) included 579,700 km2 of habitats generating 494 billion euros of services annually. The future sea-level rise could erode 1.0% [90% confidence interval 0.7-1.5%] of the 2018 area under RCP4.5, and 1.2% [0.7-2.2%] under RCP8.5. The decline in services would be even greater: 4.2% [3.0-6.1%] under RCP4.5, and 5.1% [3.3-8.5%] under RCP8.5. The highest absolute losses would be sustained by salt marshes, while relative losses would be highest in beaches, sands, and dunes. The most affected countries in relative economic terms would be Denmark, Albania, Greece, Estonia, and Finland, but countries such as Germany, the Netherlands, and France would be among those losing the largest share of their coastal ecosystem services. Regional analysis using NUTS 3 regions shows high diversity of the impacts, with many regions along the North Sea and eastern Mediterranean Sea that are heavily affected by coastal erosion-induced loss of ecosystem services. The study highlights the urgency of undertaking mitigation actions.

Cliff erosion monitoring dataset on selected sites of Polish coast.

Coastal storms are highly unpredictable phenomena, frequently changing their characteristics and directly linked to global climate changes. They result in an intensive erosion processes and, are now a serious concern for the communities inhabiting the littoral zones. However, owing to the technical difficulties in registering morphological changes on cliff coasts, most short-term monitoring systems, analyses, and models have been implemented primarily along the dune coasts. Notwithstanding these difficulties, the changes on cliff coasts have been investigated quantitatively in order to properly identify the mechanisms controlling those phenomena. Here, we report on three soft-cliff systems in the southern Baltic Sea that were monitored with the use of terrestrial laser scanner (TLS) technology. A time series of thirteen topographic surveys were generated over a period of two years (12.2016-04.2018) and presented as coastal profiles with 50 meter spacing.

Application of empirical wave run-up formulas to the Polish Baltic Sea coast.

Advanced, multidimensional models are typically applied when researching processes occurring in the nearshore. Relatively simple, empirical equations are commonly used in coastal engineering practice in order to estimate extreme wave run-up on beaches and coastal structures. However, they were mostly calibrated to the characteristics of oceanic coasts, which have different wave regime than a semi-enclosed basin like the Baltic Sea. In this paper we apply the formulas to the Polish Baltic Sea coast. The equations were adjusted to match local conditions in two test sites in Miedzyzdroje and Dziwnówek, where beaches are under continuous video surveillance. Data from WAM wave model and coastal gauge stations were used, as well as precise measurements of the beaches' cross-sections. More than 600 run-up events spanning from June to December 2013 were analysed, including surges causing dune erosion. Extreme wave run-up R2% was calculated and presented as a percentage value indicating what part of the beach was inundated. The method had a root-mean-square error of 6.1 and 6.5 percentage points depending on the test site. We consider it is a fast and computationally undemanding alternative to morphodynamic models. It will constitute a part of the SatBaltyk Operating System-Shores, delivering forecasts of wave run-up on the beaches for the entire Polish coastline.