Evaluating the impact of percolated reclaimed water from river-channel reservoir on groundwater using tracers in Beijing, Northern China

Abstract

As an increasingly important aspect of water management, historical dry river-channels, ponds or lakes are operated for the storage of reclaimed water as a landscape with the need for reuse of water. However, the percolated reclaimed water may have an adverse effect on groundwater quality. The aims of this work are to evaluate the potential for using various groundwater constituents or characteristics as tracers of percolated reclaimed water, to clarify the groundwater hydrochemical process with the effect of the reclaimed water recharge, and to estimate the degree to which the infiltrated reclaimed water has mixed with the native groundwater. Results obtained by comparing analysis between the dry season and wet season are presented based on multivariate statistics analysis, correlation of hydrochemical elements, and stable isotopes. The groundwater with the impact of reclaimed water was clustered together with higher Cl, K and NH4–N concentrations, lower Ca concentrations and more enriched heavy isotopes using unprecedentedly 3D-biplot; The water types of the groundwater change from Ca–Mg–HCO3–Cl, via Ca–Na–Mg–HCO3–Cl to Na–Ca–Mg–Cl–HCO3 with increasing reclaimed water percolated into the groundwater; the most useful tracers for evaluation of the fate and mixing of reclaimed water are chloride ion and oxygen-18 and chloride ion is more accurate than oxygen-18 to quantify the recharge source of the groundwater from the reclaimed water; using a two-end-member mixing model to calculate the reclaimed water discharged into the groundwater, the proportion of reclaimed water in groundwater is up to 94% near the unlined riverbed and up to 43% far from it. These results demonstrate the potential of the combined application of multivariate statistics analysis, traditional hydrochemical analysis and isotopes to assess the percolated reclaimed water in the groundwater, especially using 3D-biplot to determine the spatial water quality changes defined by the different factors.