Catchment-scale assessment of groundwater discharge using ecological, thermal, and hydrochemical surveillance data in the Halton Region, Ontario

• Aggregation of >21,000 interpolated groundwater and stream monitoring data • Ecological parameters reflective of larger-scale groundwater discharge patterns • Temperature but not hydrochemical gradients reflect groundwater discharge dynamics • Surface water surveillance data can guide groundwater discharge monitoring efforts Groundwater-surface water exchange is spatiotemporally variable and costly to assess at high-resolution across large areas. This study explores the application of readily available surface water monitoring data to identify potential groundwater discharge locations in 15 catchments within Conservation Halton's jurisdiction within the Halton Region, Ontario, Canada. We first compared two interpolated groundwater discharge models and subsequently contrasted these against stream ecology data (macrophyte and fish taxa) and surface- and groundwater quality measurements that were aggregated to derive temperature and hydrochemical (alkalinity, chloride) gradients across the hyporheic zone. Both groundwater models agreed in their prediction of discharge locations for only 52% of monitoring sites, corroborating the need for further reconnaissance of potential discharge areas. Fish temperature preferences and ecological temperature classifications aligned reasonably with the groundwater discharge models (<55% of sites) and air-to-stream temperature differences agreed better with groundwater discharge predicted by modeling (p<0.04, R 2 >0.40) than stream-to-groundwater gradients (p<0.1, R 2 <0.25). Instead, hydrochemical signatures of both chloride and alkalinity in the streams were more ambiguous and displayed poor correlation with groundwater discharge maps and other monitoring parameters. Finally, we amalgamated the various investigated parameters into a classification scheme to determine the likelihood of groundwater discharge at the monitoring locations . This work exemplifies how combining commonly available monitoring information may be used to provide additional insight into groundwater discharge dynamics and stream health across larger and diverse catchment types where lack of in-situ monitoring or unverified numerical models complicate a clear understanding of groundwater discharge patterns.