Spatiotemporal development of the 2018–2019 groundwater drought in the Netherlands: a data-based approach

Abstract

Abstract. The 2018–2019 drought in northwestern Europe caused severe damage to a wide range of sectors, and has made clear that even in temperate-climate countries adaptations are needed to cope with increasing future drought frequencies. A crucial component of drought management strategies is to monitor the status of groundwater resources. However, providing up-to-date assessments of regional groundwater drought development remains challenging due to the limited quality of available data. This limits many studies to small selections of groundwater monitoring sites, giving an incomplete image of drought dynamics. In this study, a time series modelling-based method for data preparation was developed and applied to map the spatiotemporal development of the 2018–2019 groundwater drought in the southeastern Netherlands, based on a large set of monitoring data. The data preparation method was evaluated for its usefulness and reliability for groundwater drought quantification and prediction. The analysis showed that the 2018–2019 meteorological drought caused extreme groundwater drought throughout the southeastern Netherlands, breaking 30-year records almost everywhere. Drought onset and duration were strongly variable in space, with especially higher elevated areas remaining in severe drought well into 2020. Groundwater drought development appeared to be governed dominantly by the spatial distribution of rainfall and the geological-topographic setting. The time series modelling-based data preparation method was found a useful tool to enable a detailed, consistent record of regional groundwater drought development. Applying a validation step before analysis turned out to be important for good results. The time series simulations were generally found to be reliable; however, the use of time series simulations rather than direct measurement series can bias drought estimations especially at a local scale, and underestimate spatial variability. Finally, time series modelling showed to be a promising tool for regional-scale drought nowcasting and prediction. Further development of time-series based validation and simulation methods, combined with accessible and consistent monitoring data, will be valuable to enable better groundwater drought monitoring in the future.