To estimate groundwater flow and transport, lumped conceptual models are widely used due to their simplicity and parsimony - but these models are calibration reliant as their parameters are unquantifiable through measurements. To eliminate this inconvenience, we tried to express these conceptual parameters in terms of hydrodynamic aquifer properties to give lumped models a forward modelling potential. The most generic form of a lumped model representing groundwater is a unit consisting of a linear reservoir connected to a dead storage aiding extra dilution, or a combination of several such units mixing in calibrated fractions. We used one such standard two-store model as our test model, which was previously nicely calibrated on the groundwater flow and transport behaviour of a French agricultural catchment. Then using a standard finite element code, we generated synthetic Dupuit-Forchheimer box aquifers and calibrated their hydrodynamic parameters to exactly match the test model’s behaviour (concentration, age etc). The optimized aquifer parameters were then compared with conceptual parameters to find clear physical equivalence and mathematical correlation - we observed that the recession behaviour depends on the conductivity, fillable porosity, and length of the catchment whereas the mixing behaviour depends on the total porosity and mean aquifer thickness. We also noticed that for a two-store lumped model, faster and slower store represents differences only in porosities making it rather a dual porosity system. We ended with outlining a clear technique on using lumped models to run forward simulations in ungauged catchments where valid measurements of hydrodynamic parameters are available.

Rivers can act as mirrors to in-catchment processes, but integrated concentration-discharge dynamics might not be sufficient for constructing a well-posed solute travel time determination problem. One remedy is to look inside the catchment and see if the extra information provided by long-term time series of groundwater solutes constrains the problem or provides us with some additional insight on retrieving the processes which the stream is aggregating. To test this notion, we used data for Kerrien, a well-studied agriculture dominated small headwater catchment of the French Critical Zone Observatory in Brittany. It contains long-term nitrate concentration time-series from a network of piezometers as well as a stream outlet. In this study, a parsimonious, conceptual dual-permeability mixing model already developed for streams was adapted for piezometers along with detailed uncertainty and sensitivity analysis. We found out the nitrate flushing times of mid to upslope piezometers were consistently higher than the stream outlet. We further observed an asynchronicity in seasonal concentration-discharge dynamics between the piezometers and the stream. We hypothesize the reason behind this counterintuitive finding to be extensive riparian denitrification, vertical stratification of groundwater and disconnect between the stream and the deeper flowpaths that carry legacy contamination, evidenced by the non-closure of water budget at the stream outlet. As a consequence, we argue that in headwater catchments the stream signature might not fully reflect internal processes which can be revealed only by using piezometer data. This adapted conceptual framework could be of great interest for semi-arid catchments where groundwater monitoring could be used in combination or as an alternate to ephemeral streams in travel time determination.