How Much Information Is Needed for Reliable Groundwater Level Imputation? Evidence from Drought Conditions in Sweden

Abstract

Reconstructing groundwater levels during drought is important for assessing water availability. This study investigated the information required for groundwater-level imputation under drought conditions in Sweden. Daily records from 297 monitoring wells were analysed, with drought periods identified using the Standardized Groundwater Index (SGI) and removed to create artificial gaps. Predictors included nearby groundwater-level records, rolling sums of net precipitation (NP), and time variables representing day of year, month and continuous time. Two methods, missForest and ARCHI, were evaluated using RMSE, MAE and Pearson correlation. Configuration comparisons used 147 eligible wells for missForest and 210 for ARCHI, with a separate comparison on 140 common wells. Nearby groundwater-level records were the most important source of information for missForest. NP and time variables provided complementary benefits when reference-well information was limited. Within the eligible sample, approximately 3 to 5 reference wells were sufficient to achieve near-optimal performance, depending on the metric and tolerance, with limited further improvements beyond about 8. Near-optimal performance was defined using 5% and 10% tolerances relative to the best tested configuration. Pearson correlation metric satisfied these criteria with fewer reference wells. On the 140 common wells, missForest W5 (Top10 + NP1–3 + Time) achieved 35.9% lower median RMSE and 39.6% lower median MAE than ARCHI n8, together with higher median correlation. Overall, combining reference-well observations with climatic and time information improved reconstruction performance. Minimum information requirements remained dependent on the evaluation sample, metric and tolerance definition. The descriptive SGI analysis characterised drought variability, while preservation of drought-event characteristics after imputation remains to be evaluated.