Abstract. International collaboration between research institutes and universities is a promising way to reach consensus on hydrological model development. Although model comparison studies are very valuable for international cooperation, they do often not lead to very clear new insights regarding the relevance of the modelled processes. We hypothesise that this is partly caused by model complexity and the comparison methods used, which focus too much on a good overall performance instead of focusing on a variety of specific events. In this study, we use an approach that focuses on the evaluation of specific events and characteristics. Eight international research groups calibrated their hourly model on the Ourthe catchment in Belgium and carried out a validation in time for the Ourthe catchment and a validation in space for nested and neighbouring catchments. The same protocol was followed for each model and an ensemble of best-performing parameter sets was selected. Although the models showed similar performances based on general metrics (i.e. the Nash–Sutcliffe efficiency), clear differences could be observed for specific events. We analysed the hydrographs of these specific events and conducted three types of statistical analyses on the entire time series: cumulative discharges, empirical extreme value distribution of the peak flows and flow duration curves for low flows. The results illustrate the relevance of including a very quick flow reservoir preceding the root zone storage to model peaks during low flows and including a slow reservoir in parallel with the fast reservoir to model the recession for the studied catchments. This intercomparison enhanced the understanding of the hydrological functioning of the catchment, in particular for low flows, and enabled to identify present knowledge gaps for other parts of the hydrograph. Above all, it helped to evaluate each model against a set of alternative models.

Abstract. Streamflow is often the only variable used to evaluate hydrological models. In a previous international comparison study, eight research groups followed an identical protocol to calibrate 12 hydrological models using observed streamflow of catchments within the Meuse basin. In the current study, we quantify the differences in five states and fluxes of these 12 process-based models with similar streamflow performance, in a systematic and comprehensive way. Next, we assess model behavior plausibility by ranking the models for a set of criteria using streamflow and remote-sensing data of evaporation, snow cover, soil moisture and total storage anomalies. We found substantial dissimilarities between models for annual interception and seasonal evaporation rates, the annual number of days with water stored as snow, the mean annual maximum snow storage and the size of the root-zone storage capacity. These differences in internal process representation imply that these models cannot all simultaneously be close to reality. Modeled annual evaporation rates are consistent with Global Land Evaporation Amsterdam Model (GLEAM) estimates. However, there is a large uncertainty in modeled and remote-sensing annual interception. Substantial differences are also found between Moderate Resolution Imaging Spectroradiometer (MODIS) and modeled number of days with snow storage. Models with relatively small root-zone storage capacities and without root water uptake reduction under dry conditions tend to have an empty root-zone storage for several days each summer, while this is not suggested by remote-sensing data of evaporation, soil moisture and vegetation indices. On the other hand, models with relatively large root-zone storage capacities tend to overestimate very dry total storage anomalies of the Gravity Recovery and Climate Experiment (GRACE). None of the models is systematically consistent with the information available from all different (remote-sensing) data sources. Yet we did not reject models given the uncertainties in these data sources and their changing relevance for the system under investigation.

The knowledge of rainfall patterns is a key issue for regionalization in hydroclimatic studies. In mountainous areas, the sparsity of the measurement network and the complexity of relationships between rainfall and topography make an accurate and reliable spatialization of rainfall amounts at the regional scale difficult. The purpose of this paper is to present an objective, analytical and automatic model of quantification and mapping of orographic rainfall applied to the north-eastern part of France but also applicable in other complex terrain. PLUVIA distributes point measurements of monthly, annual and climatological rainfall to regularly spaced grid cells through a multiple regression analysis of rainfall versus morpho-topographic parameters derived from a digital elevation model. The use of an omnidirectional parameterization of the topography induced by a windowing technique allows better account to be taken of the synopticscale weather systems generating the different rainfall quantities of interest and the spatial scale of orographic effects. It also provides a more physical interpretation of geographical and topographical parameters selected for spatial estimation. The application relies on a network of more than 150 rain gauges spread over 30 000 km 2 and concerns monthly to several yearly amounts of a sequence of 20 years. Advantages and limitations of the PLUVIA system are compared with those of two commonly used methods of multi-variate geostatistics: kriging with external drift and extended collocated co-kriging.

High spatio-temporal resolution monitoring has only been progressively developed in the Rhine-Meuse basins over the last few decades. As a consequence, basic hydrological information can be very scarce in some areas. In regions which are homogeneous from a hydroclimatological and physiogeographical point of view, hydrographs can be reproduced via regionalized hydrological models, provided that climatological observation series are available.The Alzette river basin, monitored since the mid-1990s by a very dense hydroclimatological observation network, had been chosen in the framework of the IRMA-SPONGE project FRHYMAP for transposing the conceptual hydrological models HRM and SOCONT and regionalizing their parameters. The regionalized models were to be used both for extending the currently available runoff series and evaluating runoff in neighbouring non-monitored basins.The 16 monitored sub-basins of the Alzette, reflecting the physiogeographical diversity of the study area, were divided into two subsets, serving for both the calibration and the validation procedures. Once the transposition of the models to the Alzette basin had been successfully assessed, their parameters were linked to the physiogeographical characteristics of the sub-basins. The performance of the thus regionalized models was assessed via a validation on a subset of basins that had not been retained for the elaboration of the regional parameter sets.The transposition of the HRM and SOCONT model to the Alzette river basin was completed successfully. Results overall proved to be satisfying, with the HRM model performing equally well for low flows and high flows, while the SOCONT model showed best results for high flows and a systematic overestimation of the mean discharge. Both models proved to be adequate for evaluating daily runoff in non-monitored basins of the Grand-Duchy of Luxembourg, helping thus to counterbalance the considerable lack of hydrological observation series in this part of the Rhine basin.

Abstract. Streamflow is often the only variable used to constrain hydrological models. In a previous international comparison study, eight research groups followed an identical protocol to calibrate a total of twelve hydrological models using observed streamflow of catchments within the Meuse basin. In the current study, we hypothesize that these twelve process-based models with similar streamflow performance have similar representations of internal states and fluxes. We test our hypothesis by comparing internal states and fluxes between models and we assess their plausibility using remotely-sensed products of evaporation, snow cover, soil moisture and total storage anomalies. Our results indicate that models with similar streamflow performance represent internal states and fluxes differently. Substantial dissimilarities between models are found for annual and seasonal evaporation and interception rates, the number of days per year with water stored as snow, the mean annual maximum snow storage and the size of the root-zone storage capacity. Relatively small root-zone storage capacities for several models lead to drying-out of the root-zone storage and significant reduction of evaporative fluxes each summer, which is not suggested by remotely-sensed estimates of evaporation and root-zone soil moisture. These differences in internal process representation imply that these models cannot all simultaneously be close to reality. Using remotely-sensed products, we could evaluate the plausibility of model representations only to some extent, as many of these internal variables remain unknown, highlighting the need for experimental research. We also encourage modelers to rely on multi-model and multi-parameter studies to reveal to decision-makers the uncertainties inherent to the heterogeneity of catchments and the lack of evaluation data.