Kling–Gupta efficiency
Kling–Gupta efficiency (KGE) is a metric used in hydrology to compare model results with observed data. It was created to improve on common measures like the Nash–Sutcliffe efficiency by combining three parts of the time series: shape similarity, variability similarity, and bias.
- r is the Pearson correlation between observed and simulated values (how well the shapes match).
- α is the ratio of the standard deviation of the simulated data to that of the observed data (how the spread compares).
- β is the ratio of the mean of the simulated data to the mean of the observed data (how biased the average is).
The KGE is calculated as:
KGE = 1 - sqrt((r - 1)^2 + (α - 1)^2 + (β - 1)^2)
A KGE of 1 means a perfect match; lower values indicate a worse fit. A modified version, KGE', was later proposed to adjust certain bias aspects.
This page was last edited on 2 February 2026, at 15:13 (CET).