高能中层宏观潮汐海滩的卫星平衡海岸线建模

IF 4.2 2区 工程技术 Q1 ENGINEERING, CIVIL
Georgios Azorakos , Bruno Castelle , Vincent Marieu , Déborah Idier
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引用次数: 0

摘要

模拟和预测沙质海岸线的未来是沿岸研究的一个主要挑战,对可持续的沿岸管理至关 重要。然而,目前最娴熟的海岸线模型主要依靠数据来校准自由参数,因此仅限于世界上少数监测良好的地点。在此,我们探讨了光学卫星图像所带来的挑战和机遇,以便为以跨岸传输为主的地点的平衡海岸线模型校准提供有用的信息。我们将重点放在法国西南部的 Truc Vert 海滩,之前的研究表明,该海滩的平衡模型具有良好的技能,可以再现从数小时(风暴)到数十年时间尺度的海岸线变化。为了测试模型的性能,提取了 11 年(2009-2020 年)的卫星推导水线,并通过不同的水位修正(如潮汐和/或涨潮)和不同的沿岸平均长度,以及不同的不确定性,进一步转化为卫星推导海岸线(SDS)。此外,还对模型校准所需的时间序列持续时间和采样频率进行了研究。使用 SDS 数据校核的模型与使用原位沿岸平均海岸线位置校核的模型显示出相似的技能,即使是未经校正的 SDS 数据集,其均方根误差(RMSE)也约为 30 米。最后,为了进一步研究数据集中采样频率和噪声的影响,我们使用合成海岸线进行了分析。结果表明,只要采样频率较高(dt ≤ 30 天),噪声的影响就可以忽略不计。在进一步验证之前,结果表明,在以跨岸传输为主的沙质海岸,使用未经校正的 SDS 数据集进行海岸线模型校准具有很大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Satellite-derived equilibrium shoreline modelling at a high-energy meso-macrotidal beach

Modelling and predicting the future of sandy shorelines is a key challenge in coastal research and is critical for sustainable coastal management. However, currently the most skillful shoreline models strongly rely on data to calibrate the free parameters, and are thus restricted to a few well monitored sites in the world. Here we address the challenges and opportunities offered by optical satellite imagery to provide useful information for equilibrium shoreline model calibration on cross-shore transport dominated sites. We focus on Truc Vert beach, southwest France, where previous work showed good equilibrium model skill to reproduce shoreline change from the time scales of hours (storms) to decades. Satellite derived waterlines are extracted over 11 years (2009–2020) and further transformed into satellite derived shorelines (SDS) with different water level corrections (e.g. tide and/or run up) and varying alongshore averaging lengths, and thus different uncertainties, in order to test model performance. Successively the timeseries duration and sampling frequency required for model calibration were also investigated. The model calibrated using the SDS data showed similar skill as the model calibrated using in-situ alongshore averaged shoreline positions, even for the uncorrected SDS dataset which Root Mean Square Error (RMSE) are approximately 30 m. Alongshore averaging was found to be the only necessary processing of the SDS data while any other site-specific corrections did not significantly improve model skill. Finally to further investigate the effect of sampling frequency and noise in the dataset we performed an analysis using a synthetic shoreline. Our results suggest that the effect of noise is negligible as long as the sampling frequency remains high (dt 30 days). Pending further validation, results show the strong potential of using uncorrected SDS dataset for shoreline model calibration at cross-shore transport dominated sandy coasts.

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来源期刊
Coastal Engineering
Coastal Engineering 工程技术-工程:大洋
CiteScore
9.20
自引率
13.60%
发文量
0
审稿时长
3.5 months
期刊介绍: Coastal Engineering is an international medium for coastal engineers and scientists. Combining practical applications with modern technological and scientific approaches, such as mathematical and numerical modelling, laboratory and field observations and experiments, it publishes fundamental studies as well as case studies on the following aspects of coastal, harbour and offshore engineering: waves, currents and sediment transport; coastal, estuarine and offshore morphology; technical and functional design of coastal and harbour structures; morphological and environmental impact of coastal, harbour and offshore structures.
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