摘要：Human activity has polluted freshwater ecosystems across the planet, harming biodiversity, human
health, and the economy. Improving water quality depends on identifying pollutant sources in river
networks, but pollutant concentrations fluctuate in time. Continuous monitoring of many points in
river networks is expensive, impeding progress in developing countries where water quality is
degrading fastest. In this study, we analyzed 4523 water chemistry time series of ten parameters ( - NO , 3
- PO , 4
3 TP, DOC, - SO , 4
2 Cl−, Na+, Ca2+, Mg2+, K+) across four temperate ecoregions in France (ca.
560 000 km2
). We quantified the spatial stability of water chemistry across the monitoring stations
using rank correlations between instantaneous concentrations and water quality metrics derived from
6-year time series(2010–2015). The strength of this rank correlation represents how well a water
quality evaluation metric can be characterized with a single sampling for a given water quality
parameter. Results show that a single sampling captured a mean of 88% of the spatial variability of
these parameters, across ecoregions with different climate and land-use conditions. The spatial
stability resulted both from high spatial variability among sites and high temporal synchrony among
time series. These findings demonstrate that infrequent but spatially dense water sampling can achieve
two of the major goals of water quality monitoring: identify pollutant sources and inform ideal
locations for conservation and restoration interventions.
关键词：water quality; stability; catchment; monitoring; river network
