Improved assessment of automated gap imputation in large groundwater level data sets

Uneven measurement frequencies and continuous gaps in hydrographs are among the major challenges when dealing with regional-scale groundwater level data sets, especially if compiled from different countries. A variety of automated gap imputation methods can be applied to infill a large number of missing values, yet the assessment of modeling performance remains a difficult task often performed by randomly introduced missing values. However, large groundwater level data sets rarely have random gaps and more complex gap patterns can be observed. Here we present a new artificial gap introduction technique (TGP - typical gap patterns) mimicking realistic gap patterns characteristic to regional scale groundwater level data sets thus improving the assessment of gap imputation methods. Imputation performance of machine learning algorithm missForest and imputePCA were compared with routinely used linear interpolation to create gapless groundwater hydrographs for the Baltic states (Estonia, Latvia, Lithuania). Our results showed that infilling performance varies among different gap patterns (TGP). Overall, the missForest algorithm significantly outperformed imputePCA and linear interpolation even when infilling up to 2.5 years long gaps, while linear interpolation produced similarly good results to missForest when infilling relatively short (random-like) gaps. It was observed that imputation performance substantially decreased when infilling previously unseen extremes (such as severe drought episodes in 2018) or groundwater hydrographs likely affected by water abstraction (located near major agglomerations).

The study has been founded by Iceland, Liechtenstein and Norway through the EEA and Norway Grants Fund for Regional Cooperation project No.2018-1-0137 “EU-WATERRES: EU-integrated management system of cross-border groundwater resources and anthropogenic hazards”. The research further contributes to the grant TRV2019/45670 awarded by the Swedish Transport Administration (Trafikverket).