tidyhydro

The tidyhydro package provides a set of commonly used metrics in hydrology (such as NSE, KGE, pBIAS) for use within a tidymodels infrastructure. Originally inspired by the yardstickand hydroGOF packages, this library is mainly written in C++ and provides a very quick estimation of desired goodness-of-fit criteria.

Installation

You can install the development version of tidyhydro from GitHub with:

# install.packages("devtools")
devtools::install_github("atsyplenkov/tidyhydro")

# OR

# install.packages("pak")
pak::pak("atsyplenkov/tidyhydro")

Example

The tidyhydro package follows the philosophy of yardstick and provides S3 class methods for vectors and data frames. For example, one can estimate NSE and pBIAS for a data frame like this:

library(yardstick)
library(tidyhydro)
data(solubility_test)

nse(solubility_test, solubility, prediction)
#> # A tibble: 1 × 3
#>   .metric .estimator .estimate
#>   <chr>   <chr>          <dbl>
#> 1 nse     standard       0.879

pbias(solubility_test, solubility, prediction)
#> # A tibble: 1 × 3
#>   .metric .estimator .estimate
#>   <chr>   <chr>          <dbl>
#> 1 pbias   standard      -0.512

or create a metric_set and estimate several parameters at once like this:

hydro_metrics <- yardstick::metric_set(nse, pbias)

hydro_metrics(solubility_test, solubility, prediction)
#> # A tibble: 2 × 3
#>   .metric .estimator .estimate
#>   <chr>   <chr>          <dbl>
#> 1 nse     standard       0.879
#> 2 pbias   standard      -0.512

We do understand that sometimes one needs a qualitative interpretation of the model; therefore, we populated every function with a performance argument. When performance = TRUE, the metric interpretation will be returned according to Moriasi et al. (2015).

hydro_metrics(solubility_test, solubility, prediction, performance = TRUE)
#> # A tibble: 2 × 3
#>   .metric .estimator .estimate
#>   <chr>   <chr>      <chr>    
#> 1 nse     standard   Excellent
#> 2 pbias   standard   Excellent

Benchmarking

Since the package uses Rcpp in the background, it performs slightly faster than its ancestors:

bench::mark(
  tidyhydro = tidyhydro::nse_vec(
    solubility_test$solubility,
    solubility_test$prediction
  ),
  hydroGOF = hydroGOF::NSE(
    sim = solubility_test$prediction,
    obs = solubility_test$solubility
  ),
  check = TRUE,
  relative = TRUE
)
#> # A tibble: 2 × 6
#>   expression   min median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>
#> 1 tidyhydro   1      1         1.71       1       1   
#> 2 hydroGOF    2.05   1.94      1         16.0     3.51

Alternatives

• R
  • hydroGOF - Goodness-of-fit functions for comparison of simulated and observed hydrological time series