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| Titel |
Gained insights from combined high-frequency and long-term water quality monitoring in agricultural catchments |
| VerfasserIn |
Seifeddine Jomaa, Rémi Dupas, Andreas Musolff, Joachim Rozemeijer, Dietrich Borchardt, Michael Rode |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250149493
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| Publikation (Nr.) |
 EGU/EGU2017-13848.pdf |
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| Zusammenfassung |
| Despite extensive efforts to reduce nitrate (NO3) transfer in agricultural areas, the NO3 concentration in rivers often changes little. To investigate the reasons for this limited response, NO3 dynamics in a 100 km² agricultural catchment in eastern Germany was analysed from decadal to infra-hourly time scales.
First, Dynamic Harmonic Regression (DHR) analysis of a 32-year (1982-2014) record of NO3 and discharge revealed that i) the long-term trend in NO3 concentration was closely related to that in discharge, suggesting that large-scale weather and climate patterns were masking the effect of improved nitrogen management on NO3 trends; ii) maximum winter and minimum summer concentrations had a persistent seasonal pattern, which was interpreted as a dynamic NO3 concentration from the soil and subsoil columns; and iii) the catchment progressively changed from chemodynamic to more chemostatic behaviour over the three decades of study, which is a sign of long-term homogenisation of NO3 concentrations in the profile.
Second, infra-hourly (15 min time interval) analysis of storm-event dynamics during a typical hydrological year (2005-2006) was performed to identify periods of the year with high leaching risk and to link the latter to agricultural management practices in the catchment. Also, intra-hourly data was used to improve NO3 load estimation during storm events. An Event Response Reconstruction (ERR) model was built using NO3 concentration response descriptor variables and predictor variables deduced from discharge and precipitation records. The ERR approach significantly improved NO3 load estimates compared to linear interpolation of grab-sampling data (error was reduced from 10 to 1%).
Finally, this study shows that detailed physical understanding of NO3 dynamics across time scales can be obtained only through combined analysis of long-term records and high-resolution sensor data. Hence, a joint effort is advocated between environmental authorities, who usually perform long-term monitoring, and scientific programmes, which usually perform high-resolution monitoring. |
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