Abstract

Core Ideas WTC analysis was used to elucidate the non‐stationary C/N relationship at different time scales. Water transit times (≈groundwater contribution) were key drivers for the C/N relationship. Phase shifts between the C/N time series increased with rising groundwater influence. WTC analysis can help to identify spatiotemporally dependent relationships in cachtments. Understanding natural controls on N and C biogeochemical cycles is important to estimate human impacts on these cycles. This study examined the spatiotemporal relationships between time series of weekly monitored stream and groundwater N and C (assessed by NO3− and dissolved organic C [DOC]) in the forested Wüstebach catchment (Germany). In addition to traditional correlation analysis, we applied wavelet transform coherence (WTC) analysis to study variations in the correlation and lag time between the N and C time series for different time scales. Median transit times were used to connect hydrologic and water chemistry data. We defined three stream‐water groups: (i) subsurface runoff dominated locations with strong seasonal fluctuations in concentrations, short transit times, and strong negative C/N correlations with short time lags, (ii) groundwater dominated locations, with weaker seasonal fluctuations, longer transit times, and weaker C/N correlations with lags of several months, and (iii) intermediate locations, with moderate seasonal fluctuations, moderate transit times, and strong C/N correlations with short time lags. Water transit times could be identified as key drivers for the C/N relationship and we conclude that C and N transport in stream water can be explained by mixing of groundwater and subsurface runoff. Complemented by transit times and the hydrochemical time series, WTC analysis allowed us to discriminate between different water sources (groundwater vs. subsurface runoff). In conclusion, we found that in time series studies of hydrochemical data, e.g., DOC and NO3−, WTC analysis can be a viable tool to identify spatiotemporally dependent relationships in catchments.

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