Assess Water Quality Trends with Generalized Additive Models

Assess Water Quality Trends for Long-Term Monitoring Data in Estuaries using Generalized Additive Models following Wood (2017) and Error Propagation with Mixed-Effects Meta-Analysis following Sera et al. (2019) . Methods are available for model fitting, assessment of fit, annual and seasonal trend tests, and visualization of results.

wqtrends

R package to assess water quality trends for long-term monitoring data in estuaries using Generalized Additive Models with error propagation from mixed-effect meta-analysis. Uses concepts in the mgcv and mixmeta packages. Detailed information on the methods used in this package are described in the following open access article:

Beck, M.W., de Valpine, P., Murphy, R., Wren, I., Chelsky, A., Foley, M., Senn, D.B. 2022. Multi-scale trend analysis of water quality using error propagation of Generalized Additive Models. Science of the Total Environment. 802:149927. https://doi.org/10.1016/j.scitotenv.2021.149927

Installation

Install the package from CRAN as follows. The development version of the package can be installed from r-universe. The source code is available on GitHub.

# Install wqtrends in R:
install.packages('wqtrends')

# load wqtrends
library(wqtrends)

Issues and suggestions

Please report any issues and suggestions on the issues link for the repository.