Message Board

Respected readers, authors and reviewers, you can add comments to this page on any questions about the contribution, review, editing and publication of this journal. We will give you an answer as soon as possible. Thank you for your support!

Full name
E-mail
Phone number
Title
Message
Verification Code
Volume 46 Issue 6
Jun.  2024
Turn off MathJax
Article Contents
Liang Dong,Gao Na,Ying Xiaoming, et al. Research and application of constructing a coastal erosion risk prediction model based on LSTM[J]. Haiyang Xuebao,2024, 46(6):130–140 doi: 10.12284/hyxb2024059
Citation: Liang Dong,Gao Na,Ying Xiaoming, et al. Research and application of constructing a coastal erosion risk prediction model based on LSTM[J]. Haiyang Xuebao,2024, 46(6):130–140 doi: 10.12284/hyxb2024059

Research and application of constructing a coastal erosion risk prediction model based on LSTM

doi: 10.12284/hyxb2024059
  • Received Date: 2024-01-24
  • Rev Recd Date: 2024-05-13
  • Available Online: 2024-07-15
  • Publish Date: 2024-06-01
  • Shoreline erosion prediction is one of the hot issues in coastal dynamic geomorphology research. Based on the long short term memory (LSTM), the data of shoreline, water depth, intertidal zone width , and wave and tidal current for ERA5 inversion clollected from 1985 to 2023 near Sheyang County of Jiangsu Province were used to construct a coastal erosion risk prediction model in this study. The prediction model could accurately predict the nonlinear/linear change trend of accelerated erosion, stable erosion or coastline sedimentation. The results showed that the increasing of wave and tidal currents was the main factor of coastal erosion in Sheyang area in recent 20 years under the condition of sand source reduction. Besides, an ideal experiment of coastal protection activities was conducted by using the prediction model, and the protection effects of coastal reinforcement, wave dissipation and weak current engineering were discussed. The results showed that the protection effect of coastal reinforcement is the best, and wave dissipation is better than weak current. The prediction model is reasonable, and has great application value and development potential.
  • loading
  • [1]
    凡姚申, 窦身堂, 裴洪杨, 等. 大河三角洲侵蚀灾害与应对策略研究进展[J]. 自然灾害学报, 2022, 31(2): 12−25.

    Fan Yaoshen, Dou Shentang, Pei Hongyang, et al. Research progress of erosion hazards and coping strategies in mega deltas[J]. Journal of Natural Disasters, 2022, 31(2): 12−25.
    [2]
    李平, 丰爱平, 孙惠凤, 等. 海岸侵蚀灾害调查和评价研究进展与展望[J]. 自然灾害学报, 2021, 30(4): 55−63.

    Li Ping, Feng Aiping, Sun Huifeng, et al. Research progress and prospect of coastal erosion investigation and evaluation[J]. Journal of Natural Disasters, 2021, 30(4): 55−63.
    [3]
    文世勇, 王紫竹, 王涛, 等. 基于遥感技术的海南省海岸侵蚀现状与趋势评估[J]. 灾害学, 2020, 35(1): 138−143. doi: 10.3969/j.issn.1000-811X.2020.01.025

    Wen Shiyong, Wang Zizhu, Wang Tao, et al. Status and trend assessment of coastal erosion at Hainan Province based on remote sensing technology[J]. Journal of Catastrophology, 2020, 35(1): 138−143. doi: 10.3969/j.issn.1000-811X.2020.01.025
    [4]
    HsuJRC, SilvesterR, Xia Yimin. Static equilibrium bays: new relationships[J]. Journal of Waterway, Port, Coastal, and Ocean Engineering, 1989, 115(3): 285−298. doi: 10.1061/(ASCE)0733-950X(1989)115:3(285)
    [5]
    Hsu T W, Jan C D, Wen C C. Modified McCormicks model for equilibrium shorelines behind a detached breakwater[J]. Ocean Engineering, 2003, 30(15): 1887−1897. doi: 10.1016/S0029-8018(03)00042-8
    [6]
    González M, Medina R. On the applicationof static equilibrium bay formulations to natural and man-made beaches[J]. Coastal Engineering, 2001, 43(3/4): 209−225.
    [7]
    Kakisina T J, Anggoro S, Hartoko A, et al. NEMOS (Nearshore Modelling of Shoreline Change) model for abrasion mitigation at the northern coast of Ambon Bay[J]. Aquatic Procedia, 2016, 7: 242−246. doi: 10.1016/j.aqpro.2016.07.034
    [8]
    Young R S, Pilkey O H, Bush D M, et al. A discussion of the generalized model for simulating shoreline change (GENESIS)[J]. Journal of Coastal Research, 1995, 11(3): 875−886.
    [9]
    Castelle B, Reniers A, MacMahan J. Bathymetric control of surf zone retention on a rip-channelled beach[J]. Ocean Dynamics, 2014, 64(8): 1221−1231.
    [10]
    Roelvink D, Reniers A, van Dongeren A, et al. Modelling storm impacts on beaches, dunes and barrier islands[J]. Coastal Engineering, 2009, 56(11/12): 1133−1152.
    [11]
    朱萝云, 刘婷婷, 凡仁福, 等. 1986-2019年粤东企望湾砂质海岸线演变过程与驱动机制研究[J]. 海洋学报, 2022, 44(7): 82−94. doi: 10.12284/j.issn.0253-4193.2022.7.hyxb202207008

    Zhu Luoyun, Liu Tingting, Fan Renfu, et al. Study on the evolution process and driving mechanism of the sandy shoreline of the Qiwang Bay ineastern Guangdong from 1986 to 2019[J]. HaiyangXuebao, 2022, 44(7): 82−94. doi: 10.12284/j.issn.0253-4193.2022.7.hyxb202207008
    [12]
    朱磊, 孙家文, 王宏, 等. 基于XBeach模型的离岸堤群防护效果评价指标[J]. 海洋环境科学, 2020, 39(5): 684−693. doi: 10.12111/j.mes.20190157

    Zhu Lei, Sun Jiawen, Wang Hong, et al. Evaluation index of protection effect of breakwaters based on XBeach model[J]. Marine Environmental Science, 2020, 39(5): 684−693. doi: 10.12111/j.mes.20190157
    [13]
    于航, 张建鹏, 陈根发, 等. 基于改进XBeach的波浪作用下岸滩冲淤演变特性的数值研究[J]. 水动力学研究与进展, 2023, 38(3): 495−503.

    Yu Hang, Zhang Jianpeng, Chen Genfa, et al. Numerical study of beach profile evolution under waves based on Improved XBeach[J]. Chinese Journal of Hydrodynamics, 2023, 38(3): 495−503.
    [14]
    Zheng Gang, Li Xiaofeng, Zhang Ronghua, et al. Purely satellite data-driven deep learning forecast of complicated tropical instabilitywaves[J]. Science Advances, 2020, 6(29): eaba1482. doi: 10.1126/sciadv.aba1482
    [15]
    Nieves V, Radin C, Camps-Valls G. Predicting regional coastal sea level changes with machine learning[J]. Scientific Reports, 2021, 11(1): 7650. doi: 10.1038/s41598-021-87460-z
    [16]
    Gers F A, Schmidhuber J, Cummins F. Learning to forget: continual prediction with LSTM[J]. Neural Computation, 2000, 12(10): 2451−2471.
    [17]
    Hochreiter S, Schmidhuber J. Long short-term memory[J]. Neural Computation, 1997, 9(8): 1735−1780. doi: 10.1162/neco.1997.9.8.1735
    [18]
    刘建伟, 宋志妍. 循环神经网络研究综述[J]. 控制与决策, 2022, 37(11): 2753−2768.

    Liu Jianwei, Song Zhiyan. Overview of recurrent neural networks[J]. Control and Decision, 2022, 37(11): 2753−2768.
    [19]
    张忍顺, 陆丽云, 王艳红. 江苏海岸侵蚀过程及其趋势[J]. 地理研究, 2002, 21(4): 469−478. doi: 10.3321/j.issn:1000-0585.2002.04.009

    Zhang Renshun, Lu Liyun, Wang Yanhong. The mechanism and trend of coastal erosion of Jiangsu Province in China[J]. Geographical Research, 2002, 21(4): 469−478. doi: 10.3321/j.issn:1000-0585.2002.04.009
    [20]
    Zhang Changkuan, YangYaozhong, Tao Jianfeng, et al. Suspended sediment fluxes in the radial sand ridge field of SouthYellow Sea[J]. Journal of Coastal Research, 2013, 65(sp1): 624−629.
    [21]
    张林. 苏北废黄河三角洲海岸冲淤演变及其控制因素[D]. 上海: 华东师范大学, 2015.

    Zhang Lin. The coastal erosion-deposition evolution and controlling factors of the abandoned Yellow River delta in northern Jiangsu province[D]. Shanghai: East China Normal University, 2015.
    [22]
    刘小喜, 陈沈良, 蒋超, 等. 苏北废黄河三角洲海岸侵蚀脆弱性评估[J]. 地理学报, 2014, 69(5): 607−618. doi: 10.11821/dlxb201405004

    Liu Xiaoxi, Chen Shenliang, Jiang Chao, et al. Vulnerability assessment of coastal erosion along the Abandoned Yellow River Delta of northern Jiangsu, China[J]. ActaGeographicaSinica, 2014, 69(5): 607−618. doi: 10.11821/dlxb201405004
    [23]
    Shi Hongyuan, Cao Xuefeng, Li Qingjie, et al. Evaluating the accuracy of ERA5 wave reanalysis in the water around China[J]. Journal of Ocean University of China, 2021, 20(1): 1−9. doi: 10.1007/s11802-021-4496-7
    [24]
    张达恒, 时连强, 龚照辉, 等. 冬季波浪与人工岛联合作用下日月湾海滩冲淤演变特征[J]. 热带海洋学报, 2022, 41(4): 71−81. doi: 10.11978/2021150

    Zhang Daheng, Shi Lianqiang, Gong Zhaohui, et al. Evolution characteristics of beach erosion and accretion at the Riyue Bay under the combined impacts of winter waves and artificial island[J]. Journal of Tropical Oceanography, 2022, 41(4): 71−81. doi: 10.11978/2021150
    [25]
    Bheeroo R A, Chandrasekar N, Kaliraj S, et al. Shoreline change rate and erosion risk assessment along the Trou Aux Biches–Mont Choisy beach on the northwest coast of Mauritius using GIS-DSAS technique[J]. Environmental Earth Sciences, 2016, 75(5): 444.
    [26]
    张长宽, 黄婷婷, 陶建峰, 等. 江苏海岸潮滩剖面形态与动力泥沙响应关系[J]. 河海大学学报(自然科学版), 2020, 48(3): 245−251.

    Zhang Changkuan, Huang Tingting, Tao Jianfeng, et al. Response relationship of tidal flat profile and dynamic sediment along Jiangsu Coast[J]. Journal of Hohai University (Natural Sciences), 2020, 48(3): 245−251.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(12)  / Tables(3)

    Article views (204) PDF downloads(28) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return