A Framework for Assessing Concentration?Discharge Catchment Behavior From Low?Frequency Water Quality Data

Effective nutrient pollution mitigation measures require in-depth understanding of spatio-temporal controls on water quality which can be obtained by analyzing export regime and hysteresis patterns in concentration-discharge () relationships. Such analyses high-frequency data (hourly or higher resolution), hampering the assessment widely available low-frequency (monthly, biweekly) regulatory data. We propose a reproducible classification relationships considering (dilution, constancy, enrichment) long-term average pattern (clockwise, no hysteresis, anticlockwise) applicable to The is based power-law models with separate parametrization for low high discharge rising falling hydrograph limb, enabling better representation dynamics. has been applied 30-years record daily streamflow monthly spot samples solute concentrations 45 Scottish catchments contrasting characteristics terms topography, climate, soil land cover. found that solute- catchment-specific linked upland versus lowland variability. However as relationship between behavior catchment variable, we future typologies should integrate both response, is, classification, characteristics. data-driven allows us increase information content thus inform measures, monitoring strategies, modeling approaches. approaches open up an ability characterize processes best management wider number catchments, subject surveillance outside research catchments.