An R package for correcting continuous water quality monitoring data for drift

被引:4
|
作者
Shaughnessy, Andrew R. [1 ,4 ]
Prener, Christopher G. [2 ]
Hasenmueller, Elizabeth A. [3 ]
机构
[1] St Louis Univ, St Louis, MO 63103 USA
[2] St Louis Univ, Dept Sociol & Anthropol, St Louis, MO 63103 USA
[3] St Louis Univ, Dept Earth & Atmospher Sci, St Louis, MO 63103 USA
[4] Penn State Univ, Dept Geosci, 503 Deike Bldg, State Coll, PA 16802 USA
关键词
Water quality; R; Continuous monitoring data; Drift corrections; VARIABILITY;
D O I
10.1007/s10661-019-7586-x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Continuous water quality monitoring ins- truments are used to understand the chemical and physical behaviors of aquatic environments over time. However, the data generated from these instruments are susceptible to inaccuracies due to drift that can occur between site visits. While there are several software packages available to correct drift in water quality data, these packages are often proprietary, expensive, and/or do not offer the user control over the data corrections. This paper describes driftR, an R package that corrects drift in water quality data. driftR implements either one- or two-point variable data corrections based on the number of standards used to calibrate the sensor of interest, then linearly interpolates the correction over the period of interest. This program gives control to users to correct each parameter in a way that is ideal for their unique stu- dies and offers a free, reproducible method for drift correction.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] CONSIDERATIONS OF SCALE IN WATER-QUALITY MONITORING AND DATA-ANALYSIS
    LOFTIS, JC
    MCBRIDE, GB
    ELLIS, JC
    WATER RESOURCES BULLETIN, 1991, 27 (02): : 255 - 264
  • [22] stab: An R package for drug stability data analysis
    Lee, Hsin-ya
    Wu, Pao- chu
    Lee, Yung-jin
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2010, 100 (02) : 140 - 148
  • [23] Simulation of Synthetic Complex Data: The R Package simPop
    Templ, Matthias
    Meindl, Bernhard
    Kowarik, Alexander
    Dupriez, Olivier
    JOURNAL OF STATISTICAL SOFTWARE, 2017, 79 (10): : 1 - 38
  • [24] ggroups: an R package for pedigree and genetic groups data
    Nilforooshan, Mohammad Ali
    Saavedra-Jimenez, Luis Antonio
    HEREDITAS, 2020, 157 (01)
  • [25] Analyzing Intraday Financial Data in R: The highfrequency Package
    Boudt, Kris
    Kleen, Onno
    Sjorup, Emil
    JOURNAL OF STATISTICAL SOFTWARE, 2022, 104 (08): : 1 - 36
  • [26] ggroups: an R package for pedigree and genetic groups data
    Mohammad Ali Nilforooshan
    Luis Antonio Saavedra-Jiménez
    Hereditas, 157
  • [27] Multiple-Table Data in R with the multitable Package
    Walker, Steven C.
    Guenard, Guillaume
    Solymos, Peter
    Legendre, Pierre
    JOURNAL OF STATISTICAL SOFTWARE, 2012, 51 (08): : 1 - 38
  • [28] Analyzing Remote Sensing Data in R: The landsat Package
    Goslee, Sarah C.
    JOURNAL OF STATISTICAL SOFTWARE, 2011, 43 (04):
  • [29] Simulating Survival Data Using the simsurv R Package
    Brilleman, Samuel L.
    Wolfe, Rory
    Moreno-Betancur, Margarita
    Crowther, Michael J.
    JOURNAL OF STATISTICAL SOFTWARE, 2021, 97 (03): : 1 - 27
  • [30] An R package for the integrated analysis of metabolomics and spectral data
    Costa, Christopher
    Maraschin, Marcelo
    Rocha, Miguel
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2016, 129 : 117 - 124