4.7 Article

Ship wakes and their potential shoreline impact in Tampa Bay

期刊

OCEAN & COASTAL MANAGEMENT
卷 211, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ocecoaman.2021.105749

关键词

Ship wakes; Coastal erosion; Maritime; Estuary; Automatic identification system

资金

  1. Southeast Coastal Ocean Observing Regional Association [IOOS.16(028)USF.ML.OBS.1]
  2. Gulf of Mexico Coastal Ocean Observing System [02-S160275]
  3. Greater Tampa Bay Marine Advisory Council-PORTS, Inc. [2500-1066-00]
  4. Tampa Bay Estuary Program [6911]
  5. US Fish and Wildlife [F17AC00815]

向作者/读者索取更多资源

The study calculated ship wakes in Tampa Bay, Florida using AIS data and found that passenger class vessels produced the highest wakes, while cargo class vessels had the largest number of ships estimated to produce high wakes. The research also revealed that differences in vessel representation in the two sets of AIS data affected the distribution of wake energy by vessel class.
Ship wakes generated by vessels moving through ecologically sensitive areas, or near poorly-protected infrastructure, can negatively impact these systems. This is especially true in regions hosting large seaports. Ship wakes in Tampa Bay, Florida, were calculated during two time periods using vessel movement data reported through the Automatic Identification System (AIS). The first period was for the years 2015-2017 using data from a government database. The second was during part of 2018 obtained by local monitoring. Only vessels operating at low Froude numbers were examined. Wake heights were estimated from each AIS record using an empirical equation and partitioned by functional vessel class. The largest estimated wakes were produced by the Passenger class. Cargo class vessels had the largest number of ships estimated to produce high wakes. Egmont Key, a longeroding barrier island at the mouth of the Bay, was potentially subjected to the highest number of ship wakes and the highest cumulative wake energy. Differences in vessel representation in the two sets of AIS data yielded different distributions of wake energy by vessel class. Some strategies for managing wake energy are discussed.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据