Characterization methods for small estuarine systems in the mid-Atlantic region of the United States.

J. F. Paul, J. Kiddon, C. Strobel
{"title":"Characterization methods for small estuarine systems in the mid-Atlantic region of the United States.","authors":"J. F. Paul, J. Kiddon, C. Strobel","doi":"10.2174/1874378101004010065","DOIUrl":null,"url":null,"abstract":"Various statistical methods were applied to spatially discrete data from 14 intensively sampled small estuarine systems in the mid-Atlantic U.S. The number of sites per system ranged from 6 to 37. The surface area of the systems ranged from 1.9 to 193.4 km 2 . Parameters examined were depth, bottom temperature, bottom salinity, surface chlorophyll a, bottom dissolved oxygen, lead concentration in sediments, silt-clay content of sediments, and number of infaunal ben- thic species. Statistical methods included means, standard deviations, coefficients of variation, empirical cumulative dis- tribution functions, and contours determined by bivariate interpolation and interpolation by kriging. All of these methods were found to be appropriate depending upon the purpose of the characterization. Contouring was applied only to those systems with at least 23 discrete sample sites (7 systems). Cross-validation and randomization techniques were used to compare the two interpolation methods. Kriging was advantageous over bivariate interpolation when moderate to strong spatial correlation existed in the residuals (that is, after removal of the spatial trend with a nonparametric regression model). When kriging was conducted, the removal of the trend was necessary if the stationarity assumption was to be valid. The Delaware/Maryland coastal bays are shallow, well-mixed (horizontally and vertically) systems that exhibit little or no spatial correlation for the parameters examined. The South and Severn Rivers, subsystems of the Chesapeake Bay, exhibited moderate to strong spatial dependence for some parameters. Randomization techniques were used to evaluate the effect of decreasing the number of sites in kriged parameters. Based upon these randomizations, it was found that 23 discrete sites could be used for kriging in estuaries with characteristics similar to those in the mid-Atlantic and if the sam- ples were collected with a comparable design.","PeriodicalId":247243,"journal":{"name":"The Open Hydrology Journal","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Open Hydrology Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1874378101004010065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Various statistical methods were applied to spatially discrete data from 14 intensively sampled small estuarine systems in the mid-Atlantic U.S. The number of sites per system ranged from 6 to 37. The surface area of the systems ranged from 1.9 to 193.4 km 2 . Parameters examined were depth, bottom temperature, bottom salinity, surface chlorophyll a, bottom dissolved oxygen, lead concentration in sediments, silt-clay content of sediments, and number of infaunal ben- thic species. Statistical methods included means, standard deviations, coefficients of variation, empirical cumulative dis- tribution functions, and contours determined by bivariate interpolation and interpolation by kriging. All of these methods were found to be appropriate depending upon the purpose of the characterization. Contouring was applied only to those systems with at least 23 discrete sample sites (7 systems). Cross-validation and randomization techniques were used to compare the two interpolation methods. Kriging was advantageous over bivariate interpolation when moderate to strong spatial correlation existed in the residuals (that is, after removal of the spatial trend with a nonparametric regression model). When kriging was conducted, the removal of the trend was necessary if the stationarity assumption was to be valid. The Delaware/Maryland coastal bays are shallow, well-mixed (horizontally and vertically) systems that exhibit little or no spatial correlation for the parameters examined. The South and Severn Rivers, subsystems of the Chesapeake Bay, exhibited moderate to strong spatial dependence for some parameters. Randomization techniques were used to evaluate the effect of decreasing the number of sites in kriged parameters. Based upon these randomizations, it was found that 23 discrete sites could be used for kriging in estuaries with characteristics similar to those in the mid-Atlantic and if the sam- ples were collected with a comparable design.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
美国中大西洋地区小型河口系统的表征方法。
采用不同的统计方法对美国大西洋中部14个密集采样的小河口系统的空间离散数据进行了分析,每个系统的站点数量从6到37不等。这些系统的表面积从1.9到193.4 km2不等。检测的参数包括深度、底部温度、底部盐度、表面叶绿素a、底部溶解氧、沉积物中的铅浓度、沉积物的粉质粘土含量和水生底栖生物种类的数量。统计方法包括均值、标准差、变异系数、经验累积分布函数和由二元插值和克里格插值确定的轮廓。根据表征的目的,所有这些方法都是合适的。轮廓只应用于那些至少有23个离散样本点的系统(7个系统)。采用交叉验证和随机化技术对两种插值方法进行比较。当残差中存在中等到强的空间相关性时(即使用非参数回归模型去除空间趋势后),Kriging比二元插值更有利。当进行克里格时,如果平稳性假设是有效的,就必须去除趋势。特拉华州/马里兰州沿海海湾是浅的,混合良好的(水平和垂直)系统,对所检查的参数显示很少或没有空间相关性。作为切萨皮克湾的子系统,南河和塞文河在某些参数上表现出中等到强烈的空间依赖性。随机化技术用于评估减少克里格参数中位点数量的效果。在这些随机化的基础上,发现有23个离散的地点可以用于克里格鱼,这些地点的特征与大西洋中部的河口相似,如果样本是用可比较的设计收集的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Editorial: Hydrology and the Environment Mitigation and Adaptation Responses to Sea Level Rise Mohid Land - Porous Media, a Tool for Modeling Soil Hydrology at PlotScale and Watershed Scale Wealth of the Oceans Innovations Related to Hydrology in Response to Climate Change - A Review
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1