five

Streamflow Correlation Map Grids in and near West Virginia 1930-2011

收藏
DataONE2016-10-29 更新2024-06-26 收录
下载链接:
https://search.dataone.org/view/b9405294-f189-41e1-a32a-3ce1bcc018de
下载链接
链接失效反馈
官方服务:
资源简介:
Correlation of flows at pairs of streamgages were evaluated using a Spearman’s rho correlation coefficient to better identify gages that can be used as index gages to estimate daily flow at ungaged stream sites in West Virginia. Correlation maps were developed for each candidate index streamgage using ordinary kriging, and have been compiled as grids. Sets of grids were developed for correlation of daily flows of streamgages on unregulated streams in and near (within 50 miles of) West Virginia that were operated during the 1930-2011 water years for: (1) complete water years for the entire period of record (1930-2011), (2) October-December for the entire period of record, (3) January-March for the entire period of record, (4) April-June for the entire period of record, (5) July-September for the entire period of record, (6) complete water years for 1963-1969, (7) complete water years for 1970-1979, and (8) complete water years for 1992-2011. Details of analytical approach, results, discussion, and limitations are contained in U.S. Geological Survey Scientific Investigations Report 2014-5061.at https://pubs.usgs.gov/sir/2014/5061/

本研究采用斯皮尔曼ρ相关系数(Spearman's rho correlation coefficient),对成对河道水文站(streamgage)的流量相关性开展评估,以精准筛选可作为基准水文站(index gages)的站点,用于估算西弗吉尼亚州内无监测河道站点(ungaged stream sites)的日流量。针对每一处候选基准水文站,本研究采用普通克里金法(ordinary kriging)生成相关性分布图,并将其整合为网格数据集。 针对1930-2011水文年期间投入运行的、位于西弗吉尼亚州境内及周边(50英里范围内)未受调控河道上的河道水文站,基于其日流量相关性,构建了多组网格数据集,涵盖以下8类场景: (1) 全记录周期(1930-2011年)内的完整水文年 (2) 全记录周期内的10月-12月 (3) 全记录周期内的1月-3月 (4) 全记录周期内的4月-6月 (5) 全记录周期内的7月-9月 (6) 1963-1969年的完整水文年 (7) 1970-1979年的完整水文年 (8) 1992-2011年的完整水文年 本研究的分析方法、结果、讨论及局限性等详细内容,收录于美国地质调查局(U.S. Geological Survey)2014-5061号科学调查报告(Scientific Investigations Report),可通过链接https://pubs.usgs.gov/sir/2014/5061/查阅。
创建时间:
2016-10-29
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作