Exponential distribution of wave-driven near-bed water speeds under short-crested waves: a case study in the eastern Gulf of Riga, the Baltic Sea
Loads exerted to the seabed by short-crested wind-seas with a wide directional spread have extensive spatio-temporal variability. We quantify this variability in terms of near-bed water speed using an array of nine high-resolution hydromast devices for recording pressure and water velocity in the ra...
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Estonian Academy Publishers
2025-01-01
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| Series: | Proceedings of the Estonian Academy of Sciences |
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| author | Maris Eelsalu Laura Piho Juris Aigars Loreta Kelpšaitė-Rimkienė Vitalijus Kondrat Maarja Kruusmaa Kevin E. Parnell Asko Ristolainen Ilona Šakurova Māris Skudra Maija Viška Tarmo Soomere |
| author_facet | Maris Eelsalu Laura Piho Juris Aigars Loreta Kelpšaitė-Rimkienė Vitalijus Kondrat Maarja Kruusmaa Kevin E. Parnell Asko Ristolainen Ilona Šakurova Māris Skudra Maija Viška Tarmo Soomere |
| author_sort | Maris Eelsalu |
| collection | DOAJ |
| description | Loads exerted to the seabed by short-crested wind-seas with a wide directional spread have extensive spatio-temporal variability. We quantify this variability in terms of near-bed water speed using an array of nine high-resolution hydromast devices for recording pressure and water velocity in the range of 0.12â1 m/s mounted at a distance of 10 m from each other on a rigid rectangular frame of 20 Ã 20 m in approximately 4 m deep water and 700 m from the eastern shore of the Gulf of Riga near Skulte (Latvia) in AugustâSeptember 2022. This array is complemented by an acoustic Doppler velocimeter (ADV). The average background current is very weak, approximately 0.003 m/s in the measurement location. The empirical distributions of velocity components are symmetric but greatly deviate from the expected Gaussian distribution. The empirical distributions of water speeds follow an exponential distribution rather than a Rayleigh or Forristall distribution. This shape of the distributions appears in the range of 0.2â0.7 m/s while the maximum speed reaches 1.22 m/s. The rate parameter (inverse scale parameter) varies almost by a factor of two in recordings by different devices. The recordings make it possible to identify wakes of vessels entering to or departing from the Port of Skulte. |
| format | Article |
| id | doaj-art-5de1c22ee06d48b2b4f9cb192e32436e |
| institution | Kabale University |
| issn | 1736-6046 1736-7530 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Estonian Academy Publishers |
| record_format | Article |
| series | Proceedings of the Estonian Academy of Sciences |
| spelling | doaj-art-5de1c22ee06d48b2b4f9cb192e32436e2025-02-10T10:10:04ZengEstonian Academy PublishersProceedings of the Estonian Academy of Sciences1736-60461736-75302025-01-017412342https://doi.org/10.3176/proc.2025.1.03https://doi.org/10.3176/proc.2025.1.03Exponential distribution of wave-driven near-bed water speeds under short-crested waves: a case study in the eastern Gulf of Riga, the Baltic SeaMaris Eelsalu0Laura Piho1Juris Aigars2Loreta Kelpšaitė-Rimkienė3Vitalijus Kondrat4Maarja Kruusmaa5Kevin E. Parnell6Asko Ristolainen7Ilona Šakurova8Māris Skudra9Maija Viška10Tarmo Soomere11Wave Engineering Laboratory, Department of Cybernetics, School of Science, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, EstoniaCenter for Biorobotics, School of Information Technologies, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, EstoniaLatvian Institute of Aquatic Ecology, Voleru iela 4, Kurzemes rajons, LV-1007 Rīga, LatviaMarine Research Institute, Klaipėda University, Herkaus Manto g. 84, 92294 Klaipėda, LithuaniaMarine Research Institute, Klaipėda University, Herkaus Manto g. 84, 92294 Klaipėda, LithuaniaCenter for Biorobotics, School of Information Technologies, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, EstoniaWave Engineering Laboratory, Department of Cybernetics, School of Science, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, EstoniaCenter for Biorobotics, School of Information Technologies, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, EstoniaMarine Research Institute, Klaipėda University, Herkaus Manto g. 84, 92294 Klaipėda, LithuaniaLatvian Institute of Aquatic Ecology, Voleru iela 4, Kurzemes rajons, LV-1007 Rīga, LatviaLatvian Institute of Aquatic Ecology, Voleru iela 4, Kurzemes rajons, LV-1007 Rīga, LatviaWave Engineering Laboratory, Department of Cybernetics, School of Science, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia; Estonian Academy of Sciences, Kohtu 6, 10130 Tallinn, EstoniaLoads exerted to the seabed by short-crested wind-seas with a wide directional spread have extensive spatio-temporal variability. We quantify this variability in terms of near-bed water speed using an array of nine high-resolution hydromast devices for recording pressure and water velocity in the range of 0.12â1 m/s mounted at a distance of 10 m from each other on a rigid rectangular frame of 20 Ã 20 m in approximately 4 m deep water and 700 m from the eastern shore of the Gulf of Riga near Skulte (Latvia) in AugustâSeptember 2022. This array is complemented by an acoustic Doppler velocimeter (ADV). The average background current is very weak, approximately 0.003 m/s in the measurement location. The empirical distributions of velocity components are symmetric but greatly deviate from the expected Gaussian distribution. The empirical distributions of water speeds follow an exponential distribution rather than a Rayleigh or Forristall distribution. This shape of the distributions appears in the range of 0.2â0.7 m/s while the maximum speed reaches 1.22 m/s. The rate parameter (inverse scale parameter) varies almost by a factor of two in recordings by different devices. The recordings make it possible to identify wakes of vessels entering to or departing from the Port of Skulte.https://kirj.ee/wp-content/plugins/kirj/pub/proc-1-2025-23-42_20250120131110.pdfwave loadswave climatenear-bottom velocitywater speedhydromastin-situ measurementsadvweibull distribution |
| spellingShingle | Maris Eelsalu Laura Piho Juris Aigars Loreta Kelpšaitė-Rimkienė Vitalijus Kondrat Maarja Kruusmaa Kevin E. Parnell Asko Ristolainen Ilona Šakurova Māris Skudra Maija Viška Tarmo Soomere Exponential distribution of wave-driven near-bed water speeds under short-crested waves: a case study in the eastern Gulf of Riga, the Baltic Sea Proceedings of the Estonian Academy of Sciences wave loads wave climate near-bottom velocity water speed hydromast in-situ measurements adv weibull distribution |
| title | Exponential distribution of wave-driven near-bed water speeds under short-crested waves: a case study in the eastern Gulf of Riga, the Baltic Sea |
| title_full | Exponential distribution of wave-driven near-bed water speeds under short-crested waves: a case study in the eastern Gulf of Riga, the Baltic Sea |
| title_fullStr | Exponential distribution of wave-driven near-bed water speeds under short-crested waves: a case study in the eastern Gulf of Riga, the Baltic Sea |
| title_full_unstemmed | Exponential distribution of wave-driven near-bed water speeds under short-crested waves: a case study in the eastern Gulf of Riga, the Baltic Sea |
| title_short | Exponential distribution of wave-driven near-bed water speeds under short-crested waves: a case study in the eastern Gulf of Riga, the Baltic Sea |
| title_sort | exponential distribution of wave driven near bed water speeds under short crested waves a case study in the eastern gulf of riga the baltic sea |
| topic | wave loads wave climate near-bottom velocity water speed hydromast in-situ measurements adv weibull distribution |
| url | https://kirj.ee/wp-content/plugins/kirj/pub/proc-1-2025-23-42_20250120131110.pdf |
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