On attempting to close the water balance when all fluxes are questionable: what can we learn from the spatial coherence of the water balance anomaly signal ?

The struggle to reliably close the water balance at the catchment scale has been a major issue for conceptual hydrological models. Inter-catchment groundwater flows (IGF), human influences, forcing biases and streamflow uncertainties all unite to provide high-end puzzles even to the most enduring hydrologist. In the absence of a better assessment of each of these non-closure sources, many mesoscale conceptual models either choose to accept the mismatch between observed and simulated streamflow, or to force the water balance closure through calibration. Here, we argue that, when working at the mesoscale, ridding ourselves of the actual non-closure complexity through calibration can (or should) be avoided: rather, we propose to grapple with water balance anomalies by explicitly addressing all of their potential causes, ahead of any subsequent parameter estimation.Specifically, we take advantage of the recent proliferation of natural streamflow datasets, enriched with a number or regional and national contributions to evaluate water-balance anomalies as computed with the CERRA-Land climate reanalyses over the period 1984-2024. Thereon, we develop a methodology based on the spatial analysis of the distribution of catchments’ distances to a Budyko-type curve. Our belief is that the spatial coherence of this water balance anomaly signal can be used to disentangle the different causes of the water balance non-closure and, in particular, to discriminate between those which have local determinants (such as groundwater flows) and those involving regional factors (such as forcing biases). Finally, we further break down the contribution of the forcing biases based on a priori knowledge about precipitation (P) and potential evaporation (E0) biases. We present our results under the form of a pan-European map displaying all catchment-specific non-closure sources, with a three-way scale (e.g. ternary plot) measuring the respective weights of P, E0 and IGF.