Abstract. Characterizing and understanding spatial variability in
water quality for a variety of chemical elements is an issue for present and
future water resource management. However, most studies of spatial
variability in water quality focus on a single element and rarely consider
headwater catchments. Moreover, they assess few catchments and focus on
annual means without considering seasonal variations. To overcome these
limitations, we studied spatial variability and seasonal variation in
dissolved C, N, and P concentrations at the scale of an intensively farmed
region of France (Brittany). We analysed 185 headwater catchments (from
5–179 km2) for which 10-year time series of monthly
concentrations and daily stream flow were available from public databases.
We calculated interannual loads, concentration percentiles, and seasonal
metrics for each element to assess their spatial patterns and correlations.
We then performed rank correlation analyses between water quality, human
pressures, and soil and climate features. Results show that nitrate
(NO3) concentrations increased with increasing agricultural pressures
and base flow contribution; dissolved organic carbon (DOC) concentrations
decreased with increasing rainfall, base flow contribution, and topography;
and soluble reactive phosphorus (SRP) concentrations showed weaker positive
correlations with diffuse and point sources, rainfall and topography. An
opposite pattern was found between DOC and NO3: spatially, between
their median concentrations, and temporally, according to their seasonal
cycles. In addition, the quality of annual maximum NO3 concentration
was in phase with maximum flow when the base flow index was low, but this
synchrony disappeared when flow flashiness was lower. These DOC–NO3
seasonal cycle types were related to the mixing of flow paths combined with
the spatial variability of their respective sources and to local
biogeochemical processes. The annual maximum SRP concentration occurred
during the low-flow period in nearly all catchments. This likely resulted
from the dominance of P point sources. The approach shows that despite the
relatively low frequency of public water quality data, such databases can
provide consistent pictures of the spatio-temporal variability of water
quality and of its drivers as soon as they contain a large number of
catchments to compare and a sufficient length of concentration time series.
Stochastic Assessment of Nonpoint Source Contamination: Joint Impact of Aquifer Heterogeneity and Well Characteristics on Management Metrics