TY - JOUR
T1 - Spatial and Temporal Variability in Concentration-Discharge Relationships at the Event Scale
AU - Musolff, Andreas
AU - Zhan, Qing
AU - Dupas, Remí
AU - Minaudo, Camille
AU - Fleckenstein, Jan H.
AU - Rode, Michael
AU - Dehaspe, Joni
AU - Rinke, Karsten
N1 - 7289, AqE; Data archiing: no NIOO data
PY - 2021
Y1 - 2021
N2 - The analysis of concentration-discharge (C-Q) relationships from low-frequency observations is commonly used to assess solute sources, mobilization, and reactive transport processes at the catchment scale. High-frequency concentration measurements are increasingly available and offer additional insights into event-scale export dynamics. However, only few studies have integrated inter-annual and event-scale C-Q relationships. Here, we analyze high-frequency measurements of specific conductance (EC), nitrate (NO3-N) concentrations and spectral absorbance at 254 nm (SAC254, as a proxy for dissolved organic carbon) over a two year period for four neighboring catchments in Germany ranging from more pristine forested to agriculturally managed settings. We apply an integrated method that adds a hysteresis term to the established power law C-Q model so that concentration intercept, C-Q slope and hysteresis can be characterized simultaneously. We found that inter-event variability in C-Q hysteresis and slope were most pronounced for SAC254 in all catchments and for NO3-N in forested catchments. SAC254 and NO3-N event responses in the smallest forested catchment were closely coupled and explainable by antecedent conditions that hint to a common near-stream source. In contrast, the event-scale C-Q patterns of EC in all catchments and of NO3-N in the agricultural catchment without buffer zones around streams were less variable and similar to the inter-annual C-Q relationship indicating a homogeneity of mobilization processes over time. Event-scale C-Q analysis thus added key insights into catchment functioning whenever the inter-annual C-Q relationship contrasted with event-scale responses. Analyzing long-term and event-scale behavior in one coherent framework helps to disentangle these scattered C-Q patterns.
AB - The analysis of concentration-discharge (C-Q) relationships from low-frequency observations is commonly used to assess solute sources, mobilization, and reactive transport processes at the catchment scale. High-frequency concentration measurements are increasingly available and offer additional insights into event-scale export dynamics. However, only few studies have integrated inter-annual and event-scale C-Q relationships. Here, we analyze high-frequency measurements of specific conductance (EC), nitrate (NO3-N) concentrations and spectral absorbance at 254 nm (SAC254, as a proxy for dissolved organic carbon) over a two year period for four neighboring catchments in Germany ranging from more pristine forested to agriculturally managed settings. We apply an integrated method that adds a hysteresis term to the established power law C-Q model so that concentration intercept, C-Q slope and hysteresis can be characterized simultaneously. We found that inter-event variability in C-Q hysteresis and slope were most pronounced for SAC254 in all catchments and for NO3-N in forested catchments. SAC254 and NO3-N event responses in the smallest forested catchment were closely coupled and explainable by antecedent conditions that hint to a common near-stream source. In contrast, the event-scale C-Q patterns of EC in all catchments and of NO3-N in the agricultural catchment without buffer zones around streams were less variable and similar to the inter-annual C-Q relationship indicating a homogeneity of mobilization processes over time. Event-scale C-Q analysis thus added key insights into catchment functioning whenever the inter-annual C-Q relationship contrasted with event-scale responses. Analyzing long-term and event-scale behavior in one coherent framework helps to disentangle these scattered C-Q patterns.
KW - international
KW - Plan_S-Compliant_OA
U2 - 10.1029/2020WR029442
DO - 10.1029/2020WR029442
M3 - Article
VL - 57
JO - Water Resources Research
JF - Water Resources Research
IS - 10
M1 - e2020WR029442
ER -