Improving Model Performance by Adapting the KGE Metric to Account for System Non-Stationarity
Geoscientific systems tend to be characterized by pronounced temporal non-stationarity, arising from seasonal and climatic variability in hydrometeorological drivers, and from natural and anthropogenic changes to land use and cover. As has been pointed out, such variability renders "the assumption of statistical stationarity obsolete in water management", and requires us to "account for, rather than ignore, non-stationary trends" in the data. However, metrics used for model development are typically based on the implicit and unjustifiable assumption that the data generating process is time-stationary. Here, we introduce the JKGE_ss metric (adapted from KGE_ss) that detects and accounts fo...
| Authors | M Jawad, HV Gupta, YH Wang et al. |
|---|---|
| Primary category | cs.LG |
| Published | 5 April 2026 |
| Last updated at source | 9 April 2026 |
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