潟湖

Multi tool use潟湖是一種因為海灣被沙洲所封閉而演變成的湖泊,所以一般都在海邊。這些湖本來都是海灣,後來在海灣的出海口處由於泥沙沉積,使出海口形成了沙洲,繼而將海灣與海洋分隔,因而成為湖泊。潟湖也指珊瑚环礁所围成的水域,有的高潮时可与海相通,此类珊瑚礁潟湖若严格按地理学的湖泊定义其实不是湖,而是海湾。[1]
潟[2]在汉语中是鹵鹹地之意,如《史記·貨殖列傳130》中载有“地潟”;《汉书》中载有“海濒广潟”,现較常見於日语,如新潟。“潟湖”曾一度被写为“泻湖”(如1983年版《现代汉语词典》1276页),但在1996年版《现代汉语词典》中已重新规范为“潟湖”,在该版本《现代汉语词典》1395页的“泻湖”词条中写道:“泻湖,潟湖的旧称[3]。”但仍有很多人把“潟湖”寫成「泻(瀉)湖」。
功能
- 具有防洪的功能:潟湖可宣洩區域排水,因而很少發生水災。
- 保護海岸的功能:由於外有沙洲的阻擋可防止颱風暴潮侵蝕沖刷海岸。
- 是天然的養殖場:潟湖是鱼、虾、貝和螃蟹的孕育場,也是鄰近漁民的天然養殖場。
- 由於潟湖外側往往有沙洲作為防波堤,其內風平浪靜,因此有時可以改建為人工港(如右圖的臺灣高雄港)。
著名潟湖
七股潟湖、台江內海
- 太湖
- 杭州西湖
- 大鵬灣
- 威尼斯潟湖
- 戈佐內海
- 科勒潟湖
- 雅个冬错
- 亚历山德里娜湖
注释
^ 中国社会科学院语言研究所词典编辑室.现代汉语词典,第6版,商务印书馆,2012年,北京,1401页
^ 「潟」,拼音:xì,注音:ㄒㄧˋ,中古擬音:.mw-parser-output .IPAfont-family:"Charis SIL","Doulos SIL","Linux Libertine","Segoe UI","Lucida Sans Unicode","Code2000","Gentium","Gentium Alternative","TITUS Cyberbit Basic","Arial Unicode MS","IPAPANNEW","Chrysanthi Unicode","GentiumAlt","Bitstream Vera","Bitstream Cyberbit","Hiragino Kaku Gothic Pro","Lucida Grande",sans-serif;text-decoration:none!important.mw-parser-output .IPA a:link,.mw-parser-output .IPA a:visitedtext-decoration:none!important
siek,思積切,音同「细」
^ 1996年版《现代汉语词典》,1354页
參看
外部連結
 | 维基共享资源中相关的多媒体资源:潟湖
|
规范控制 | - AAT: 300008679
- NDL: 01214183
|
---|
|
uAOf3EZ,R3,TlNo02Mm6ixOx6jZRzL PTvs,xNmbakK77y Gr,2EJ vF1PgMlq,5SGN
Popular posts from this blog
Ramiro Burr's New Blog - to go back: www.ramiroburr.com From Latin rock to reggaeton, boleros to blues,Tex-Mex to Tejano, conjunto to corridos and beyond, Ramiro Burr has it covered. If you have a new CD release, a trivia question or are looking for tour info, post a message here or e-mail Ramiro directly at: musicreporter@gmail.com Top Tejano songwriter Luis Silva dead of heart attack at 64 By Ramiro Burr on October 23, 2008 8:40 AM | Permalink | Comments (12) | TrackBacks (0) UPDATE: Luis Silva Funeral Service details released Visitation 4-9 p.m. Saturday, Rosary service 6 p.m. Saturday at Porter Loring, 1101 McCullough Ave Funeral Service 10:30 a.m. Monday St. Anthony De Padua Catholic Church, Burial Service at Chapel Hills, 7735 Gibbs Sprawl Road. Porter Loring (210) 227-8221 Related New Flash: Irma Laura Lopez: long time record promoter killed in accident NewsFlash: 9:02 a.m. (New comments below) Luis Silva , one of the most well-known ...
1 I having trouble getting my ResourceDictionary.MergedDictionaries to load from app.xaml. My WPF app has a static class with a Main defined and startup object set to it. Within Main I created an instance of App and run it. The override OnStartup fires and the mainwindow.cs InitializeComponent gives the error "Message "Cannot find resource named 'MaterialDesignFloatingActionMiniAccentButton'. If I put the resources in the mainwindow.xaml everything is fine, but I wanted them to load at the app level so I they are not in each page. Any help appreciated. public partial class App protected override void OnStartup(StartupEventArgs e) base.OnStartup(e); var app = new MainWindow(); var context = new MainWindowViewModel(); app.DataContext = context; app.Show(); from the Main.. var app = new App(); app.Run(); app.xaml.. <Application x:Class="GS.Server.App" xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:...
up vote 2 down vote favorite There is a clear pattern that show for two separate subsets (set of columns); If one value is missing in a column, values of other columns in the same subset are missing for any row. Here is a visualization of missing data My tries up until now, I used ycimpute library to learn from other values, and applied Iterforest. I noted, score of Logistic regression is so weak (0.6) and thought Iterforest might not learn enough or anyway, except from outer subset which might not be enough? for example the subset with 11 columns might learn from the other columns but not from within it's members, and the same goes for the subset with four columns. This bar plot show better quantity of missings So of course, dealing with missings is better than dropping rows because It would affect my prediction which does contain the same missings quantity relatively. Any better way to deal with these ? [EDIT] The nullity pattern is confirmed: machine-learning cor...