1,721,004 research outputs found
Sand Engine: First monitoring and modelling results of a mega-nourishment; building with nature
No full textLuijendijk Arjen. Sand Engine: First monitoring and modelling results of a mega-nourishment; building with nature. In: 33èmes Journées de l’Hydraulique Grands Aménagements Hydrauliques Enjeux Sociétaux, Bénéfices Economiques et Innovations Techniques 14 - 16 novembre 2012. 2012
Regional-scale analysis of dune-beach systems using Google Earth Engine
Full text linkCoastal sand dunes provide a large variety of ecosystem services, among which the inland protection from marine floods. Nowadays, this protection is fundamental, and its importance will further increase in the future due to the rise of the sea level and storm violence induced by climate change. Despite the crucial role of coastal dunes and their potential application in mitigation strategies, the phenomenon of the coastal squeeze, which is mainly caused by the urban sprawl, is progressively reducing the extents of the areas where dune can freely undergo their dynamics, thus dramatically impairing their capability of providing ecosystem services.
Aiming to embed the use of satellite images in the study of coastal foredune and beach dynamics, we developed a classification algorithm that uses the satellite images and server-side functions of Google Earth Engine (GEE). The algorithm runs on the GEE Python API and allows the user to retrieve all the available images for the study site and the chosen time period from the selected sensor collection. The algorithm also filters the cloudy and saturated pixels and creates a percentile-composite image over which it applies a random forest classification algorithm. The classification is finally refined by defining a mask for land pixels only.
According to the provided training data and sensor selection, the algorithm can give different outcomes, ranging from sand and vegetation maps, beach width measurements, and shoreline time evolution visualization. This very versatile tool that can be used in a great variety of applications within the monitoring and understanding of the dune-beach systems and associated coastal ecosystem services. For instance, we show how this algorithm, combined with machine learning techniques and the assimilation of real data, can support the calibration of a coastal model that gives the natural extent of the beach width and that can be, therefore, used to plan restoration activities
Towards multifunctional coastal management
Full text linkClimate change is the most formidable challenge that our ever-increasing world population faces, and it poses special problems for those living near coasts. People have always been attracted to the coast, as a place to live and work, and to relax. By 2050, around half of the world’s population is expected to live near the coast, the vast majority in developing countries. How will we cope with rapidly rising sea levels and more intense and frequent storm surges
Multi-decadal shoreline change in coastal natural world heritage sites – a global assessment
Full text linkNatural World Heritage Sites (NWHS), which are of Outstanding Universal Value, are increasingly threatened by natural and anthropogenic pressures. This is especially true for coastal NWHS, which are additionally subject to erosion and flooding. This paper assesses shoreline change from 1984 to 2016 within the boundaries of 67 designated sites, providing a first global consistent assessment of its drivers. It develops a transferable methodology utilising new satellite-derived global shoreline datasets, which are classified based on linearity of change against time and compared with global datasets of geomorphology (topography, land cover, coastal type, and lithology), climate variability and sea-level change. Significant shoreline change is observed on 14% of 52 coastal NWHS shorelines that show the largest recessional and accretive trends (means of -3.4 m yr
-1 and 3.5 m yr
-1, respectively). These rapid shoreline changes are found in low-lying shorelines (<1 m elevation) composed of unconsolidated sediments in vegetated tidal coastal systems (means of -7.7 m yr
-1 and 12.5 m yr
-1), and vegetated tidal deltas at the mouth of large river systems (means of -6.9 m yr
-1 and 11 m yr
-1). Extreme shoreline changes occur as a result of redistribution of sediment driven by a combination of geomorphological conditions with (1) specific natural coastal morphodynamics such as opening of inlets (e.g. Río Plátano Biosphere Reserve) or gradients of alongshore sediment transport (e.g. Namib Sea) and (2) direct or indirect human interferences with natural coastal processes such as sand nourishment (e.g. Wadden Sea) and damming of river sediments upstream of a delta (e.g. Danube Delta). The most stable soft coasts are associated with the protection of coral reef ecosystems (e.g. Great Barrier Reef) which may be degraded/destroyed by climate change or human stress in the future. A positive correlation between shoreline retreat and local relative sea-level change was apparent in the Wadden Sea. However, globally, the effects of contemporary sea-level rise are not apparent for coastal NWHS, but it is a major concern for the future reinforcing the shoreline dynamics already being observed due to other drivers. Hence, future assessments of shoreline change need to account for other drivers of coastal change in addition to sea-level rise projections. In conclusion, extreme multi-decadal linear shoreline trends occur in coastal NWHS and are driven primarily by sediment redistribution. Future exacerbation of these trends may affect heritage values and coastal communities. Thus shoreline change should be considered in future management plans where necessary. This approach provides a consistent method to assess NWHS which can be repeated and help steer future management of these important sites.
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Satellite image processing for the coarse-scale investigation of sandy coastal areas
Full text linkIn recent years, satellite imagery has shown its potential to support the sustainable management of land, water, and natural resources. In particular, it can provide key information about the properties and behavior of sandy beaches and the surrounding vegetation, improving the ecomor-phological understanding and modeling of coastal dynamics. Although satellite image processing usually demands high memory and computational resources, free online platforms such as Google Earth Engine (GEE) have recently enabled their users to leverage cloud-based tools and handle big satellite data. In this technical note, we describe an algorithm to classify the coastal land cover and retrieve relevant information from Sentinel-2 and Landsat image collections at specific times or in a multitemporal way: the extent of the beach and vegetation strips, the statistics of the grass cover, and the position of the shoreline and the vegetation–sand interface. Furthermore, we validate the algorithm through both quantitative and qualitative methods, demonstrating the goodness of the derived classification (accuracy of approximately 90%) and showing some examples about the use of the algorithm’s output to study coastal physical and ecological dynamics. Finally, we discuss the algorithm’s limitations and potentialities in light of its scaling for global analyses.Coastal Engineerin
Crossing borders in coastal morphodynamic modelling
No full textSand is the second-most used natural resource behind water and will be under increasingly high demand in coming decades. One of the reasons for this is that, worldwide, sand is more and more applied to counteract beach erosion.This thesis presents new techniques in remote sensing and numerical modelling to better understand beach erosion and predict the dynamics of our sandy coastlines. To this end, it explores the crossing of three types of borders. First, international borders are crossed in a global assessment of historic beach dynamics using satellite imagery. Second, the boundaries between model time scales - from storms to decadal times - are dissolved by means of a new morphodynamic acceleration technique. Finally, the developed seamless modelling approach enables to cross the ever-changing boundary between water and land, where sand moves from the wet to the dry domain and vice versa. This work results in a landscaping model that can better forecast the future behavior of sandy beaches in a changing climate.Coastal Engineerin
The Sand Motor: A Nature-Based Response to Climate Change: Findings and Reflections of the Interdisciplinary Research Program NatureCoast
No full textNatureCoast is the largest research program that focused on the Sand Motor, a large sandy peninsula, constructed in 2011 on the Dutch North Sea coast near The Hague. This unprecedented pilot project involved placing 21.5 million m3 of sand on and in front of the beach with the aim that it would spread along the coast. The Sand Motoris a unique beach nourishment due to its size, the design philosophy behind it, and its multifunctionality. It combines the primary function of coastal protection with the creation of a new natural landscape that also provides new leisure opportunities. From the outset, “learning by doing” has been a crucial part of the project and NatureCoast was an integral part of this. Because of its innovations, the Sand Motor has triggered considerable political and scientific interest from all over the world. Broad research consortia were formed to conduct interdisciplinary research on the Sand Motor.The NatureCoast program was carried out by a consortium of knowledge institutes and universities, and the research was conducted in cooperation with end-users from private companies, research institutes and governmental organizations. The Dutch Technology Foundation (NWO-TTW) provided the largest shareof the project funds. The research in NatureCoast focused on six themes: coastal safety, dune formation, marine ecology, terrestrial ecology, hydrology and geochemistry, and governance. This book presents countless facets of the Sand Motor, but we also hope it demonstrates the scientific merits of interdisciplinary research and how, ultimately, societies can benefit from it.Coastal Engineerin
A novel coastal landscape model for sandy systems: Community base for interdisciplinary research on coastal evolution
Full text linkA common measure to mitigate erosion along sandy beaches is the implementation of sand nourishments. The design and societal acceptance of such a soft mitigation measure demands information on the expected evolution at various time scales ranging from a storm event to multiple decades. Process-based morphodynamic models are increasingly applied to obtain detailed information on temporal behaviour. This paper discusses the process-based morphodynamic model applied to the Sand Motor and how the morphodynamic forecasts have benefitted from the findings of an interdisciplinary research program called NatureCoast. The starting point is the morphodynamic prediction of the Sand Motor made for an Environmental Impact Assessment in 2008 before construction began. After the construction, the model computations were optimized using the first-year field measurements and insights by applying advanced model features. Next, an integrated model was developed that seamlessly predicts the morphodynamics in both the subaqueous and subaerial domains of the Sand Motor. Decadal predictions illustrate the need to be able to resolve the marine and aeolian processes simultaneously in one modelling framework in the case of dynamic coastal landscapes. Finally, a novel morphodynamic acceleration technique was developed that allows for predicting the morphodynamics for multiple decades while incorporating storm events in one simulation. Combining the above-mentioned developments has led to a unique, open-source, process-based landscape tool for (complex) coastal sandy systems, which can stimulate further collaboration between research communities. Moreover, this work demonstrates the evolution from mono- to interdisciplinary forecasts of coastal evolution
A Global View on Beach Erosion
No full textCoastal zones have long attracted humans and human activities, due to the economic opportunities they offer, their aesthetic value, and the diverse ecosystem services they provide. As a result, coastal zones throughout the world have become heavily populated and developed, with 15 of the world’s 20 megacities (population >10 million) being in the coastal zone. The global coastline is spatially varied and comprises different coastal landforms, such as barrier islands, sea cliffs, sandy coasts, tidal flats, and river deltas. Of these different coastline types, the sandy coasts are highly dynamic in time and space and constitute a substantial part of the world’s coastline. Sandy coasts are highly developed and densely populated due to the amenitiesCoastal Engineerin
Sandy strategies in social context:Introduction
Full text linkAll over the world, climate change and sea-level rise are forcing societies to take action. They need to develop new and innovative approaches to adapt. But such technological innovations do not develop in a social vacuum; they are often closely linked to finding solutions to social challenges. The successful introduction of technological innovations, such as the Sand Motor, depends on whether a range of political and societal parties are willing and able to commit themselves to this solution. Considering the unprecedented scale, and thus potential social impact, of a project like the Sand Motor, it should come as no surprise that its introduction was not without challenges. In this chapter, we discuss why many political and societal parties came to support the Sand Motor pilot project
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