benchmark_KGE_DOY: Calculate benchmark Kling-Gupta efficiency (KGE) values from...

In HyMETT: Hydrologic Model Evaluation and Time-Series Tools

Calculate benchmark Kling–Gupta efficiency (KGE) values from day-of-year (DOY) observations

Description

Calculate benchmark Kling–Gupta efficiency (KGE) values from daily observed time-series data

Usage

benchmark_KGE_DOY(obs_preproc)

Arguments

obs_preproc

'data.frame' of daily observational data, preprocessed as output from preproc_precondition_data or preproc_main "daily".

Details

This function calculates a "benchmark" KGE value (see Knoben and others, 2020) from a daily observed data time-series. First, the interannual mean and median is calculated for each day of the calendar year. Next, the interannual mean and median values are joined to each corresponding day in the observation time series. Finally, a KGE value (GOF_kling_gupta_efficiency) is calculated comparing the mean or median value repeated time series to the daily observational time series. These benchmark KGE values can be used as comparisons for modeled (simulated) calibration results.

Value

A data.frame with columns "KGE_DOY_mean" and "KGE_DOY_median".

References

Knoben, W.J.M, Freer, J.E., Peel, M.C., Fowler, K.J.A, Woods, R.A., 2020. A Brief Analysis of Conceptual Model Structure Uncertainty Using 36 Models and 559 Catchments: Water Resources Research, v. 56.
[Also available at https://doi.org/10.1029/2019WR025975.]

Examples

benchmark_KGE_DOY(obs_preproc = example_preproc)

HyMETT documentation built on Nov. 23, 2023, 1:08 a.m.