This study assesses the worth of routinely collected hydraulic data (groundwater head, stream stage and streamflow) and lesser collected water chemistry data (Radon-222, Carbon-14, electrical conductivity (EC)) in the context of making regional-scale surface water-groundwater (SW-GW) exchange flux predictions. Using integrated SW-GW flow and transport numerical models, first-order, second-moment (FOSM) analyses were employed to assess the extent of the uncertainty reduction or lack thereof in SW-GW exchange flux predictions following acquisition of hydraulic and water chemistry observation data. With a case study of the Campaspe River in the Murray-Darling Basin (Australia), we explored the apparent information content of these data during low, regular and high streamflow conditions. Also, a range of spatial and temporal prediction scales were considered: catchment-wide and reach-based spatial scales and annual and monthly temporal scales. Generally, the data worth evaluations showed significant variability across predictions that were dependent on the spatiotemporal scale of the SW-GW exchange, the magnitude and direction of the SW-GW exchange flux and the prevailing streamflow conditions. These dependencies serve to emphasise the importance of prediction specificity with respect to SW-GW exchange. Among existing data, the most worth was found in Radon-222, groundwater hydraulic head, EC, and streamflow data showing average reductions in uncertainty of 41%, 38%, 32%, and 23% respectively. Assessment of type and spatiotemporal locations of potential data showed Radon-222 to be the next most important observation type across many predictions in locations with data paucity of all data types. Hydraulic observation data types were found to inform SW-GW exchange flux best under high- and regular- streamflow conditions when the magnitude of exchange fluxes were largest, whereas the water chemistry data was of highest value for low- and regular-streamflow conditions where groundwater is discharging to the stream.
- Data worth
- surface water-groundwater interaction
- surface–subsurface modelling