Coastal risk adaptation: the potential role of accessible geospatial Big Data

Increasing numbers of people are living in and using coastal areas. Combined with the presence of pervasive coastal threats, such as flooding and erosion, this is having widespread impacts on coastal populations, infrastructure and ecosystems. For the right adaptive strategies to be adopted, and planning decisions to be made, rigorous evaluation of the available options is required. This evaluation hinges on the availability and use of suitable datasets. For knowledge to be derived from coastal datasets, such data needs to be combined and analysed in an effective manner. This paper reviews a wide range of literature relating to data-driven approaches to coastal risk evaluation, revealing how limitations have been imposed on many of these methods, due to restrictions in computing power and access to data. The rapidly emerging field of ‘Big Data’ can help overcome many of these hurdles. ‘Big Data’ involves powerful computer infrastructures, enabling storage, processing and real-time analysis of large volumes and varieties of data, in a fast and reliable manner. Through consideration of examples of how ‘Big Data’ technologies are being applied to fields related to coastal risk, it becomes apparent that geospatial Big Data solutions hold clear potential to improve the process of risk based decision making on the coast. ‘Big Data’ does not provide a stand-alone solution to the issues and gaps outlined in this paper, yet these technological methods hold the potential to optimise data-driven approaches, enabling robust risk profiles to be generated for coastal regions.     

Simplified two-dimensional numerical modelling of coastal flooding and example applications

In this paper we outline the development and application of a simple two-dimensional hydraulic model for use in assessments of coastal flood risk. Such probabilistic assessments typically need evaluation of many thousands of model simulations and hence computationally efficient codes of the type described here are required. The code, LISFLOOD-FP, uses a storage cell approach discretized as a regular grid and calculates the flux between cells explicitly using analytical relationships derived from uniform flow theory. The resulting saving in computational cost allows fine spatial resolution simulations of regional scale flooding problems within minutes or a few hours on a standard desktop PC. The development of the code for coastal applications is described, followed by an evaluation of its performance against four test cases representing a variety of flooding problems at different scales. For three of these cases an observed flood extent is available to compare to model predictions. In each case the model is able to match the observed shoreline to within the error of the of the observed flow, topography and validation data and outperforms a non-model flood extent prediction made using a simple Geographical Information System (GIS) technique.     

Learning from data for wind-wave forecasting

Along with existing numerical process models describing the wind-wave interaction, the relatively recent development in the area of machine learning make the so-called data-driven models more and more popular. This paper presents a number of data-driven models for wind-wave process at the Caspian Sea. The problem associated with these models is to forecast significant wave heights for several hours ahead using buoy measurements. Models are based on artificial neural network (ANN) and instance-based learning (IBL) .To capture the wind-wave relationship at measurement sites, these models use the existing past time data describing the phenomenon in question. Three feed-forward ANN models have been built for time horizon of 1, 3 and 6 h with different inputs. The relevant inputs are selected by analyzing the average mutual information (AMI). The inputs consist of priori knowledge of wind and significant wave height. The other six models are based on IBL method for the same forecast horizons. Weighted k-nearest neighbors (k-NN) and locally weighted regression (LWR) with Gaussian kernel were used. In IBL-based models, forecast is made directly by combining instances from the training data that are close (in the input space) to the new incoming input vector. These methods are applied to two sets of data at the Caspian Sea. Experiments show that the ANNs yield slightly better agreement with the measured data than IBL. ANNs can also predict extreme wave conditions better than the other existing methods.     

基于物理关联深度学习的海浪浪高预测方法

精确的海浪有效波高（简称浪高）预测对于海上生产生活具有重要意义。针对现有海浪浪高预测模型对不同海洋要素间关联信息考虑不足,以及长时序浪高数据本身存在非平稳性的问题,本文设计了一种考虑物理约束与差值约束的海浪浪高时间序列预测方法。该方法基于风速与浪高之间的物理关联,设计物理约束,并通过提取差分信息设计差值约束,结合现有基于深度学习的时间序列预测模型,实现浪高预测。采用黄海和东海的6个不同站点浮标数据进行了大量实验。实验结果表明,本文提出的方法可以利用海洋要素间的物理关联,有效提高浪高预测精度,并避免因不同要素间融合造成的信息间干扰;同时,利用差值约束,限制时间序列预测结果的变动范围。本文方法可以与不同类型的时间序列预测模型相结合,显著提升原有模型的性能,并在长时间序列的预测中体现出很好的鲁棒性,为海洋要素预测中物理与数据驱动模型的有效结合提供了思路和验证。     

"3S"支持下的海洋功能区划工作底图制图技术

本文以江苏省海洋功能区划工作底图的制作过程为例,阐述了“3S”技术在海洋功能区划工作底图的制作过程中的应用,对遥感技术在淤泥质海岸带信息提取方面的方法进行了重点研究和探索,并进一步展望了“3S”技术在制图中的应用前景。     

地理信息系统在海岸海洋地貌研究中的应用

随着现代海洋观测技术的发展,通过海岸海洋地貌调查获得的数据急剧增长。运用地理信息系统(GIS)将不同学科、不同来源、不同格式的数据进行集成管理、分析和表达已成为当前海岸海洋地貌研究的重点。系统介绍了GIS技术在海岸海洋地貌研究中新的方法体系,包括数据获取、数据处理、数据分析和数据表达四个部分,重点研究了GIS空间技术、海底地形建模和用三维可视化技术解译海洋地学,探索陆海交互作用中隐含信息的方法,并将其应用到沿海城市规划、海港选址、大陆架岛礁地貌环境研究的具体实例中,研究范围从陆到海涵盖整个海陆交互作用带,为海岸海洋社会发展、经济建设及外交权益提供科学基础和决策支持。通过上述方法体系与应用研究说明,以GIS为核心建立的多源地理空间信息平台使传统海岸海洋地貌研究的范围、内容及方法都发生了重大变化,但多源数据信息的精确解译和成功应用必须同时具有空间信息学和地貌学专家知识。     

Dissolved organic nitrogen dynamics in the North Sea: A time series analysis (1995–2005)

Dissolved organic nitrogen (DON) dynamics in the North Sea was explored by means of long-term time series of nitrogen parameters from the Dutch national monitoring program. Generally, the data quality was good with little missing data points. Different imputation methods were used to verify the robustness of the patterns against these missing data. No long-term trends in DON concentrations were found over the sampling period (1995–2005). Inter-annual variability in the different time series showed both common and station-specific behavior. The stations could be divided into two regions, based on absolute concentrations and the dominant times scales of variability. Average DON concentrations were 11 μmol l⁻¹ in the coastal region and 5 μmol l⁻¹ in the open sea. Organic fractions of total dissolved nitrogen (TDN) averaged 38 and 71% in the coastal zone and open sea, respectively, but increased over time due to decreasing dissolved inorganic nitrogen (DIN) concentrations. In both regions intra-annual variability dominated over inter-annual variability, but DON variation in the open sea was markedly shifted towards shorter time scales relative to coastal stations. In the coastal zone a consistent seasonal DON cycle existed with high values in spring–summer and low values in autumn–winter. In the open sea seasonality was weak. A marked shift in the seasonality was found at the Dogger Bank, with DON accumulation towards summer and low values in winter prior to 1999, and accumulation in spring and decline throughout summer after 1999. This study clearly shows that DON is a dynamic actor in the North Sea and should be monitored systematically to enable us to understand fully the functioning of this ecosystem.     

Quantitative evaluation of the time-line reduction performance in high definition marine magnetic surveys

The effectiveness of the time reduction procedure is the critical problem for the informative contents evaluation in the high definition (HD) geomagnetic marine surveys. The use of magnetogradiometers is a good solution for the time-reduction in the regional offshore studies but often, for technical reasons, this is not a practicable method in the very detailed coastal, canal or harbour surveys where the use of coastal base stations may be preferable. On the other hand the uncertainty of the full transferability of the coastal magnetograms to large areas of marine surveys can disrupt the time-reduced data sets by a geomagnetic residual time component. The phenomenon is related to the distance from the coastal observatory and to the homogeneity of the local magnetic characteristics of the crust. The maximum applicability distance of the time-line correction (TL) is qualitatively evaluated and is shown to be inconsistent with geomagnetic marine surveys in high definition. In this work we show a quantitative method to evaluate the stability of the coastal observatory magnetograms over the nearby marine area, together with the numerical degree of precision of the correction. The method is based on a double survey of the same profile (timer track: TT) at two different times. The surveys produce two different row data sets where the difference is related only to the geomagnetic time variations. Using the coastal observatory magnetograms we time-reduce the two data sets: if the coastal observatory magnetograms are fully coherent in the whole survey area the difference between the two reduced data sets will be zero. However, if the time variations measured in the observatory are inadequate in amplitude or phase to model the corresponding time variations in the surveyed profile (TT), the discrepancy between the time reduced data sets will not be zero. Similar TTs starting with various course from the base station permit the surveyed area to be split into sectors with variable degree of time coherence and to assign a degree of precision to the time-reduced survey.     

Managing coastal evolution in a more sustainable manner. The Conscience approach

This paper summarises the main findings of the Conscience research project, whose primary objective was to define and validate, through pilot applications, a methodology to support the implementation, for European coasts, of concepts such as coastal resilience, favorable sediment status, strategic sediment reservoirs and coastal sediment cells. The Conscience conceptual framework to managing coastal erosion has proved to be an efficient tool, because it provides a consistent approach where objective (data) and subjective (desired status) information are analyzed and compared from the standpoint of a consensus target (objective). Moreover, this is done using the best available knowledge and observations, considering always their level of uncertainty, to conduct a sustainable management policy for coastal erosion. The methodology has been tested in field cases from The Netherlands, Poland, Romania, Spain, United Kingdom and Ireland, to cover different time and space scales, together with a wide range of processes and different management objectives.     

A small-scale spatial analysis system for maritime Australia

Within the field of resource and environmental management, the paramount value of a spatial analysis system is as a tool for regionalising a case-area in diverse directed ways, each being useful for (i) increasing scientific understanding of that area (intellectualisation) or (ii) for allocating operational categories (for example, funding categories, regulatory categories) differentially between parts of the case-area (called operations support or policy support). Success in serving these scientific and administrative values depends in turn upon two primary attributes of the spatial analysis system and a larger number of secondary attributes. These primary attributes are (i) the range and quality of geocoded data sets held in store or able to be accessed and (ii) the range of spatial analysis techniques which can be called upon for operating on stored data sets. Secondary attributes influencing a spatial analysis system's value include its accessibility to potential users, its ease of use, the judgment and experience of its users and the quality of its cartographic and other outputs. The present paper is a status report on the Australian Coastal And Marine Resources Information System, CAMRIS, a spatial analysis system developed as a demonstration for Australia. CAMRIS contains or can access raw and value-added data sets which comprehensively cover both terrestrial and marine components of the Australian maritime estate. Onshore, for the immediate coastal strip, data held or accessible include geocoded data on vegetation, geology, landform, wetland and coastline type, land use, climate and population. For coastal drainage basins, data sets include river networks, river flows, wetland attributes, soils, geology, elevation, vegetation, mineral deposits, beach attributes, population and bird distributions. Nearshore data include geocoded data on estuary attributes, island attributes, seagrass beds and marine protected areas. Offshore (oceanic) geocoded data held or accessible include bathymetry, sea surface temperature and salinity/dissolved oxygen profiles, together with a variety of geophysical records including gravity, magnetics, seismic track lines, substrates, waves, winds, storms, tides and cyclones. While raw data are stored as such whenever available, many of these data sets are in value-added form, held perhaps as a surface or choropleth or as a function of primary data items. A range of spatial analysis techniques is routinely available for application to CAMRIS data sets including those within the SPANS, Arc Info, and Idrisi geographic information systems, the S Plus exploratory data analysis package, and specialist in-house packages such as PATN for multivariate positive classification and LUPIS for resource allocation and normative classification. CAMRIS demonstration studies in various stages of completion address: (1) selection of coastal and marine protected areas; (2) identification of priority areas for the management of land-based marine pollution; (3) planning for coastal population growth; and (4) synoptic impacts of climatic change in the coastal zone. Further candidate studies being considered include mariculture prospects and proactive management of oil spills and leaks. An important indicator of success for the CAMRIS project would be for it to be seen as a prototype for a properly-funded multi-agency national maritime (coastal and marine) spatial analysis system. Australia, with one of the worlds largest and most diverse maritime estates and with a small population imposing increasing pressures on that estate, needs powerful policy and operations support tools.     

Practical use of video imagery in nearshore oceanographic fieldstudies

An approach was developed for using video imagery to quantify, in terms of both spatial and temporal dimensions, a number of naturally occurring (nearshore) physical processes. The complete method is presented, including the derivation of the geometrical relationships relating image and ground coordinates, principles to be considered when working with video imagery and the two-step strategy for calibration of the camera model. The techniques are founded on the principles of photogrammetry, account for difficulties inherent in the use of video signals, and have been adapted to allow for flexibility of use in field studies. Examples from field experiments indicate that this approach is both accurate and applicable under the conditions typically experienced when sampling in coastal regions. Several applications of the camera model are discussed, including the measurement of nearshore fluid processes, sand bar length scales, foreshore topography, and drifter motions. Although we have applied this method to the measurement of nearshore processes and morphologic features, these same techniques are transferable to studies in other geophysical settings     

Application of remote sensing video systems to coastline management problems

This contribution evaluates the application of coastal video systems to monitoring and management of coastal stability problems on sandy coastlines. Specifically, video-derived parameters (coastal state indicators or CSIs) are developed which facilitate the measurement of the shoreline evolution (erosion/accretion) and response to storms, seasonal cycles and anthropogenic interventions like beach/shoreface nourishment and dredging. The primary variable which forms the basis for all the CSIs discussed in this contribution is the shoreline position derived from time-averaged video images. These waterlines are used to generate secondary products including shoreline contours at a constant pre-defined level, (intertidal) beach volumes, and momentary shoreline positions which reflect the sand volume in a meter wide section of the intertidal coast. Video-derived coastal state indicators were verified via comparisons with traditional topographical/bathymetric surveying techniques and a good agreement was found in all cases. CSIs were computed for three contrasting sandy coastal environments including an unprotected natural beach, a protected beach and a spit. Firstly, results are presented which demonstrate the advantages of coastal video systems over and above infrequent traditional topographic/bathymetric surveying methods. Namely, the ability of video-derived CSIs to quantify the magnitude, accurate location, precise timing and rates of change associated with individual extreme events and seasonal variability in the wave climate. Secondly, video-derived coastal state indicators were used to monitor two different types of human intervention, including beach nourishments and a dredged pit in a navigation channel. The video-derived datasets of coastal state indicators offered significant improvement to current CZM practices, facilitating better timing of management interventions as well as more effective monitoring of the spatial impact and longevity of these actions.     

Remote sensing of coastal interactions in the Mediterranean region

The coastal regions of the Mediterranean are the site of countless economic and recreational activities, but are threatened by dramatic dangers of misuse and pollution. Adequate tools are needed to study the environmental pressure imposed on these regions by the conflicting needs of protecting their ecological balance and exploiting their natural resources. Coastal ecosystems are very sensitive to the environmental impact of land use in watersheds, along the coast and further inland, of fluvial discharges, and of marine processes. Weathering, erosion, or waste disposal on land, as well as other activities at sea, such as shipping, dumping or oil extraction, are but a few of the factors which would require that the coastal areas be suitably monitored. Modern techniques of environmental assessment call for the use of integrated observation systems. The collection of data with traditional coastal installations remains an important component of such research. However, the large space scales and short time scales of many near-coastal and/or marine processes require the use of (orbital) remote sensors. In particular, optical sensors, operating in the visible/infrared spectral region, have shown their usefulness for providing novel information on physical, geo-chemical and biological processes of the coastal area. Optical remote sensing of the coastal zone finds applications in studies of land use, surface cover, hydrology and coastal ecology at large; of water quality and sediment transport, coastal runoff and circulation, or dynamical processes (looking, e.g., at the evolution of pigment and/or temperature patterns, and their distribution as related to plankton dynamics, currents or river plumes); as well as in those of energy transfer, carbon cycling and climatology in general. Selected applications of optical observation techniques in the Mediterranean region, conducted in the framework of international demonstration programmes (i.e. the Ocean Colour European Archive Network, OCEAN, Project), provide examples of the remote sensing potential in the field of integrated coastal/marine environmental management.     

基于深度学习的视频观测潮位技术研究——以厦门高崎码头为例

近岸潮位观测是海洋工程应用、海岸防灾减灾、海岸带管理以及海洋有关科研工作中最基础的工作之一。文章基于视频图像深度学习的方法,使用YOLOv5目标检测算法从安装在近岸的固定摄像机拍摄的视频帧中提取潮汐水位特征进行潮位分析。研究采用厦门高崎码头的分辨率为1920×1080的高清摄像头2023年2月的影像数据作为训练集和验证集,2023年3月的影像数据作为测试集,利用岸边验潮井逐时潮位数据进行标注,采用YOLOv5目标检测算法来训练。计算结果显示,通过视频观测潮位在训练集和测试集上的误差分别为3.9 cm和5.3 cm。视频中1个像素点代表3.8 cm,因此潮位观测的平均误差为像素级。研究表明在近岸通过高清摄像头基于图像深度学习进行潮位观测的方法是可行的,观测精度取决于图像目标物的分辨率。     

静态平衡岬湾海岸理论及其在黄、渤海海岸的应用

岬湾海岸是一种稳定的海岸存在形式,在天然海岸中岬湾地貌占51%。岬湾海岸研究是研究砂质海岸稳定性及演变的重要内容。岬湾海岸理论在海岸稳定性、海岸工程预测以及海岸综合治理方面有其重要的工程价值。文中详细讨论了岬湾理论中最具工程意义的抛物线型岬湾海岸线及基于静态平衡岬湾海岸理论开发的可视化应用软件MEPBay在海岸工程中的应用,并验证了该理论对黄、渤海海岸的适用性。MEPBay软件不仅有助于理解海岸形态过程,也是海岸工程师在岸线保护及海岸管理实践中的有力辅助工具。     

Concepts and science for coastal erosion management - An introduction to the Conscience framework

The main objective of the Conscience project was to develop and test concepts, guidelines and tools for the sustainable management of erosion along the European coastline, based on the best available scientific knowledge and on existing practical experience. Four concepts are potentially capable of providing the nexus between scientific knowledge and management: coastal resilience, coastal sediment cell, favourable sediment status and strategic sediment reservoir. The project has tested the use of these concepts and found that they are useful, provided that they are positioned and linked within a logical structure that we shall call the Conscience “Frame of Reference”, defined in time and space and supported through data and monitoring. Practical experience in six coastal sites in Europe has shown that the use of this Frame of Reference together with these concepts can make management objectives explicit and transparent. It can therefore support the design of an appropriate, resilience based coastal erosion management practice.     

环渤海沿岸海表温度资料的均一性检验与订正

本文对环渤海沿岸具有代表性且资料完整的6个海洋观测站的月均海表温度(SST)序列作均一性检验和订正。我国海洋观测站密集度低,难以选择参考序列,本文首先采用不依赖参考序列的惩罚最大F检验(PMFT)方法对SST序列检验,利用详尽的元数据对检验结果进行确认,再对不连续点订正,该方法适用于元数据详尽的海洋观测站。对于元数据不详尽的观测站,使用惩罚最大T检验(PMT)方法,选取与海洋台站距离近且相关显著的气象观测站的均一化地面气温序列来制作参考序列,对SST序列进行检验和订正。结果表明,环渤海地区SST序列都存在一定非均一性,观测站较大距离迁移和观测系统变更(从人工观测到自动化观测)是造成非均一性的重要原因。订正后的环渤海地区年平均SST增温趋势更加明显。本文使用不同方法来检验SST序列的均一性,该思路对沿海其他海区观测站SST均一性检验和订正有一定参考价值和应用前景,可为沿海气候变化研究提供科学准确的第一手资料。     

Estimating extreme water level probabilities: A comparison of the direct methods and recommendations for best practise

Over the past five decades, several approaches for estimating probabilities of extreme still water levels have been developed. Currently, different methods are applied not only on transnational, but also on national scales, resulting in a heterogeneous level of protection. Applying different statistical methods can yield significantly different estimates of return water levels, but even the use of the same technique can produce large discrepancies, because there is subjective parameter choice at several steps in the model setup. In this paper, we compare probabilities of extreme still water levels estimated using the main direct methods (i.e. the block maxima method and the peaks over threshold method) considering a wide range of strategies to create extreme value dataset and a range of different model setups. We primarily use tide gauge records from the German Bight but also consider data from sites around the UK and Australia for comparison. The focus is on testing the influence of the following three main factors, which can affect the estimates of extreme value statistics: (1) detrending the original data sets; (2) building samples of extreme values from the original data sets; and (3) the record lengths of the original data sets. We find that using different detrending techniques biases the results from extreme value statistics. Hence, we recommend using a 1-year moving average of high waters (or hourly records if these are available) to correct the original data sets for seasonal and long-term sea level changes. Our results highlight that the peaks over threshold method yields more reliable and more stable (i.e. using short records leads to the same results as when using long records) estimates of probabilities of extreme still water levels than the block maxima method. In analysing a variety of threshold selection methods we find that using the 99.7th percentile water level leads to the most stable return water level estimates along the German Bight. This is also valid for the international stations considered. Finally, to provide guidance for coastal engineers and operators, we recommend the peaks over threshold method and define an objective approach for setting up the model. If this is applied routinely around a country, it will help overcome the problem of heterogeneous levels of protection resulting from different methods and varying model setups.     

Stability of rubble-mound breakwater using H50 wave height parameter

The prediction of rubble mound breakwaters' stability is one of the most important issues in coastal and maritime engineering. The stability of breakwaters strongly depends on the wave height. Therefore, selection of an appropriate wave height parameter is very vital in the prediction of stability number. In this study, H₅₀, the average of the 50 highest waves that reach the breakwater in its useful life, was used to predict the stability of the armor layer. First, H₅₀ was used instead of the significant wave height in the most recent stability formulas. It was found that this modification yields more accurate results. Then, for further improvement of the results, two formulas were developed using model tree.To develop the new formulas, two experimental data sets of irregular waves were used. Results indicated that the proposed formulas are more accurate than the previous ones for the prediction of the stability parameter. Finally, the proposed formulas were applied to regular waves and a wide range of damage levels and it was seen that the developed formulas are applicable in these cases as well.