Reconstructing missing data by comparing imputation and interpolation techniques: applications for long-term groundwater monitoring

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dc.contributor.authorBronowicka-Mielniczuk, Urszula
dc.contributor.authorMielniczuk, Jacek
dc.contributor.authorSkowron, Piotr
dc.date.accessioned2026-09-04T07:33:38Z
dc.date.available2026-09-04T07:33:38Z
dc.date.issued2026
dc.description.abstractMissing data is a pervasive challenge in environmental monitoring, severely hindering reliable analysis and effective water resource management. This study addresses this issue in the context of the EU Nitrates Directive (91/676/EEC), focusing on the proportion of groundwater monitoring sites expected to exceed the regulatory limit of 50 mg NO₃⁻/L. Overall, 57% of observations were missing, with 99% of monitoring stations experiencing data gaps over the 2000–2024 study period. Six reconstruction techniques were evaluated: k-nearest neighbours, multiple imputation by chained equations, missForest, natural neighbour, inverse distance weighting, and indicator kriging. This work presents a novel approach to comparing various imputation techniques for reconstructing threshold overruns and modelling trends in exceedance rates. Moving beyond conventional error metrics, the evaluation is grounded in distributional similarity and monotonic dependence using Hellinger and Kullback-Leibler distances and generalised Lorenz curves. Based on the comparative analysis, indicator kriging was identified as the most robust approach and was subsequently adopted to parameterise the log-linear trend in the proportion of monitoring stations expected to exceed the concentration threshold. This study provides a methodological framework for addressing extreme missingness in environmental monitoring networks, offering actionable insights for EU Member States reporting under the Nitrates Directive.
dc.description.sponsorshipThe presented results were obtained as part of work carried out jointly with the Institute of Soil Science and Plant Cultivation (IUNG PIB) under task 1.1 “Fertilization of agricultural land” financed from a budget subsidy allocated to the implementation of tasks of the Polish Ministry of Agriculture and Rural Development in 2023.
dc.identifier.citationSci Rep (2026)
dc.identifier.doi10.1038/s41598-026-69512-4
dc.identifier.issnonline ISSN: 2045-2322
dc.identifier.urihttps://bc.iung.pl/handle/123456789/4809
dc.identifier.urihttps://www.nature.com/articles/s41598-026-69512-4
dc.language.isoen
dc.publisherNature Portfolio
dc.subjectgroundwater quality, nitrate pollution, missing data, imputation methods, indicator kriging
dc.titleReconstructing missing data by comparing imputation and interpolation techniques: applications for long-term groundwater monitoring
dc.typeArticle
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