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Selection of stations

GloFAS v5 verification activities are based on the river gauging stations used in the GloFAS v5 calibration, which was carried out by the Joint Research Centre (JRC) of the European Commission (see GloFAS v5 calibration hydrological model performance). The verification is based on 5,378 calibration stations, located in 119 countries. Each station is located on the GloFAS v5 river network and has daily river discharge observations available to the GloFAS team. The same set of stations is used for the GloFAS v5 hydrological model performance assessment and for the hydrological model performance layer in the map viewer:

Length of observation record: No minimum record length is applied in the verification. The observation records for all stations start between January 1979 and January 2020 and end between January 1983 and January 2026. 1,044 stations have observations in 2025. From the first to the last observation, the records cover 3.1 to 47 years (median 35.6 years). Taking gaps into account, the amount of data available per station ranges from 1.7 to 47 equivalent years (median 30.9 years). An equivalent year is 365.25 days with data, so a 20-year record with 50 % gaps counts as about 10 equivalent years.
Short records: 21 stations have fewer than 4 equivalent years of observations. Even though the scores will not be robust for such short records, which users should be aware of, they are kept so that users can still get a first impression of the model performance at these stations.
Lake, reservoir and human influence: Unlike the GloFAS v4 general hydrological model performance assessment, which used station networks without large lake or reservoir influence, no stations are excluded on this basis in GloFAS v5. All stations are verified, including those with lakes or reservoirs upstream. Scores at stations with a strong lake, reservoir or human influence should be interpreted with care, as these catchments are more difficult to model. A specific group of 228 stations with reservoirs built during the observation record is described in the last section of this page.

Verification period

The GloFAS v5 hydrological model performance assessment and the evaluation layer in the map viewer are based on the GloFAS v5 historical river discharge reanalysis, available from January 1979 to December 2025. The data can be accessed via EWDS https://ewds.climate.copernicus.eu/datasets/cems-glofas-historical?tab=download.

The verification uses the whole reanalysis period with all available river discharge observations, from 1 January 1979 at the earliest to 31 December 2025 at the latest. Both the general performance analysis (GloFAS v4 general hydrological model performance) and the GloFAS hydrological model performance layer in the map viewer (placeholder - GloFAS hydrological model performance web product) used this period. The observations are the most recent ones available in the GloFAS hydrological observation database at the time of the verification (autumn 2026). For each station, the scores are computed over all days on which both the reanalysis and the observations are available. Gaps in the observations are not filled. There is no separate verification period. The model spin-up years covered an earlier period, from 1975 until the end of 1978, and are not part of the verification.

The reanalysis is the simulation from which the GloFAS flood thresholds (return periods) are derived. The verification therefore shows how well the simulation that underpins the forecast flood thresholds reproduces the observed river discharge.

Performance scores

GloFAS hydrological performance verification is done against river discharge observations available to the GloFAS team. The hydrological model performance analysis was conducted based on the modified Kling–Gupta efficiency metric (KGE; ideal value is 1):

KGE' = 1 - \sqrt{
(r - 1)^2 +
\left(\frac{\mu_s}{\mu_o} - 1\right)^2 +
\left(\frac{\sigma_s / \mu_s}{\sigma_o / \mu_o} - 1\right)^2
}

, ,

The three component scores of the KGE were also used:

Pearson correlation (r) in KGE highlights temporal errors through the strength of the linear relationship between simulation and observation time series. It ranges from -1 to 1, with 1 as ideal value.
Bias ratio represents the bias errors, ranging from 0 to +Inf, with 1 as ideal value. Also, the 0-centred version bias (ideal value = 0) defined as β-1, and its absolute value version absbias were used
Variability ratio shows the variability related errors in the simulation. It ranges from 0 to +Inf, with 1 as optimal value. Also, 0-centred var (ideal value = 0) defined as γ-1 and its absolute value version absvar were used

In all the GloFAS v4 calibration hydrological model performance, the GloFAS v4 general hydrological model performance and the GloFAS hydrological model performance web product, the KGE' and the three KGE' components (bias, variability ratios and correlation) were used. For the calibration model performance (GloFAS v4 calibration hydrological model performance), the original β and γ ratio errors were considered. However, in the general GloFAS v4.0 model evaluation (GloFAS v4 general hydrological model performance) and the evaluation web product (GloFAS hydrological model performance web product), besides the correlation (pcorr), the β-1 (bias) and γ-1 (var) were considered to represent the bias and variability errors. These were chosen instead of β and γ as they have 0 as optimal values instead of 1 (with a range from -1 to infinity), and thus the sign intuitively shows whether the bias/variability is negatively or positively erroneous. In addition, the absolute values of bias (absbias) and var (absvar) were also used, which are useful in model comparison and can show the magnitude difference of these errors.

Finally, a specific index was also used for measuring timing errors (timing in days; ideal value is 0), which shows the time delay between the simulated and observed river discharge time series (and also the absolute value abstiming). Timing is time lag (or shift) L that maximises R_xy(L), cross correlation function R_xy(m) with the simulated (x) and observed (y) time series shifted by L days. Positive/negative timing error indicates delayed/advanced simulated river discharge. So, for example a timing error of +5 means the simulation needs to be shifted by 5 days backwards (brought earlier) to get to the highest correlation, i.e. the simulation is generally 5-day late predicting the ups and downs in the flow time series. Although this is not directly equivalent to measuring the timing error of the flood peaks, it is in very good relation with that and can be used as a simple estimate.