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rnrfa: An R package to Retrieve, Filter and Visualize Data from the UK National River Flow Archive
File(s)
RJ-2016-036.pdf (3.22 MB)
Published version
Author(s)
Vitolo, C
Fry, M
Buytaert, W
Type
Journal Article
Abstract
The UK National River Flow Archive (NRFA) stores several types of hydrological data and metadata: daily river flow and catchment rainfall time series, gauging station and catchment informa tion. Data are served through the NRFA web services via experimental RESTful APIs. Obtaining NRFA data can be unwieldy due to complexities in handling HTTP GET requests and parsing responses in JSON and XML formats. The rnrfa package provides a set of functions to programmatically access, filter, and visualize NRFA data using simple R syntax. This paper describes the structure of the rnrfa package, including examples using the main functions gdf() and cmr() for flow and rainfall data, respectively. Visualization examples are also provided with a shiny web application and functions provided in the package. Although this package is regional specific, the general framework and structure could be applied to similar databases.
Date Issued
2017-03-01
Date Acceptance
2017-03-01
Citation
The R Journal, 2017, 8 (2), pp.102-116
URI
ISSN
2073-4859
Publisher
The R Foundation
Start Page
102
End Page
116
Journal / Book Title
The R Journal
Volume
8
Issue
2
Copyright Statement
© 2017 The Author(s). This article is licensed under a Creative Commons Attribution 3.0 Unported license (https://creativecommons.org/licenses/by/3.0/) .
Sponsor
Natural Environment Research Council (NERC)
Natural Environment Research Council (NERC)
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000395669800008&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
NEC04229
NE/J016578/1
Subjects
Science & Technology
Technology
Physical Sciences
Computer Science, Interdisciplinary Applications
Statistics & Probability
Computer Science
Mathematics
0104 Statistics
Publication Status
Published