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AbstractGroundwater resources are of utmost importance in sustaining water related ecosystems, including humans. The long-lasting impacts from anthropogenic activities require early actions, owing to the natural time lag in groundwater formation and renewal. The European Union (EU) policy, within the implementation of the Water Framework Directive (WFD), requires Member States to identify and reverse any significant and sustained upward trend in the concentration of pollutants, defining specific protection measures to be included in the River Basin Management Plans (RBMP). In Italy, official guidelines for trend and trend reversal assessment have been published recently. Statistical methods, such as the Mann-Kendall test for trend analysis and the Sen's method for estimating concentration scenarios, should be applied at the fixed terms stated by the WFD implementation cycles to identify upward trends, while the Pettitt test is proposed for the identification of trend reversal. In this paper, we present an application of a slightly modified version of the Italian Guidelines to a groundwater body in Northern Italy featuring nitrate pollution and discuss its advantages and limitations. In addition to Pettitt test, for the trend reversal analysis, we apply the Mann-Kendall test in two sections and compare the results. We conclude that this method seems more reliable than Pettitt test to identify a reversal point in quality time series. The overall procedure can be easily applied to any groundwater body defined at risk across Europe, for the assessment of the upward trends of pollutants and their reversal, even with little chemical monitoring data. Although focused on the EU legislative framework, this procedure may be relevant for a wider context, allowing to individuate upward trend as early warning for contamination processes in an integrated water resources management context.

Groundwater resources are of utmost importance in sustaining water related ecosystems, including humans. The long-lasting impacts from anthropogenic activities require early actions, owing to the natural time lag in groundwater formation and renewal. The European Union (EU) policy, within the implementation of the Water Framework Directive (WFD), requires Member States to identify and reverse any significant and sustained upward trend in the concentration of pollutants, defining specific protection measures to be included in the River Basin Management Plans (RBMP). In Italy, official guidelines for trend and trend reversal assessment have been published recently. Statistical methods, such as the Mann-Kendall test for trend analysis and the Sen's method for estimating concentration scenarios, should be applied at the fixed terms stated by the WFD implementation cycles to identify upward trends, while the Pettitt test is proposed for the identification of trend reversal. In this paper, we present an application of a slightly modified version of the Italian Guidelines to a groundwater body in Northern Italy featuring nitrate pollution and discuss its advantages and limitations. In addition to Pettitt test, for the trend reversal analysis, we apply the Mann-Kendall test in two sections and compare the results. We conclude that this method seems more reliable than Pettitt test to identify a reversal point in quality time series. The overall procedure can be easily applied to any groundwater body defined at risk across Europe, for the assessment of the upward trends of pollutants and their reversal, even with little chemical monitoring data. Although focused on the EU legislative framework, this procedure may be relevant for a wider context, allowing to individuate upward trend as early warning for contamination processes in an integrated water resources management context. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-020-11998-0.

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required. (c) 2017 Published by Elsevier Ltd. ; Australian Research Council (ARC)Australian Research Council [DP130104078, LP130100756] ; GLM development and funding support for LCB, BDB, CB and MRH was provided by the Australian Research Council (ARC) (grants DP130104078 & LP130100756). Additional contributions from individuals and organisations as well as sources of data, provided from a variety of organisations are summarised in Appendix D. This study was made possible through the sharing of ideas, data and models across the AEMON and GLEON networks as well as discussions and working groups held during AEMON workshops and GLEON meetings. ; Public domain authored by a U.S. government employee