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Evaporation is gaining increasing attention as a calibration and evaluation variable in hydrologic studies that seek to improve the physical realism of hydrologic models and go beyond the long‐established streamflow‐only calibration. However, this trend is not yet reflected in sensitivity analyses aimed at determining the relevant parameters to calibrate, where streamflow has traditionally played a leading role. On the basis of a Pareto optimization approach, we propose a framework to integrate the temporal dynamics of streamflow and evaporation into the sensitivity analysis and calibration stages of the hydrologic modeling exercise, here referred to as "Pareto‐based sensitivity analysis" and "multiobjective calibration." The framework is successfully applied to a case study using the Variable Infiltration Capacity (VIC) model in three catchments located in Spain as representative of the different hydroclimatic conditions within the Iberian Peninsula. Several VIC vegetation parameters were identified as important to the performance estimates for evaporation during sensitivity analysis, and therefore were suitable candidates to improve the model representation of evaporative fluxes. Sensitivities for the streamflow performance, in turn, were mostly driven by the soil and routing parameters, with little contribution from the vegetation parameters. The multiobjective calibration experiments were carried out for the most parsimonious parameterization after a comparative analysis of the performance gains and losses for streamflow and evaporation, and yielded optimal adjustments for both hydrologic variables simultaneously. Results from this study will help to develop a better understanding of the trade‐offs resulting from the joint integration of streamflow and evaporation data into modeling frameworks. Key Points: Vegetation parameters are rarely considered in sensitivity analysis and their potential as calibration targets remains unexploredVIC vegetation parameters reflect high sensitivities toward evaporation and lead to an improvement in model performance during calibrationCombining Pareto‐based sensitivity analysis and multiobjective calibration improves the representation of both streamflow and evaporation [ABSTRACT FROM AUTHOR]

Cellular automata models are popular tools for exploring future land change pathways. But simulation modelling approaches often focus too narrowly on calibration against historic reference maps, limiting the diversity of possible outcomes. We argue that, contrary to what is commonly believed, there is no 'best model', and that model specification and calibration accuracy depend on the objective of the research. We propose a multi-model ensemble approach, in which a wide range of models and calibration rules sets are systematically tested against multiple metrics. We apply our approach to a case study in Spain. No single model performed well for all statistics, illustrating the danger of cherry-picking statistics for best performance. In our case study, accounting for historic land changes in model design was useful for simulating compact urban development, but limited the variability of simulation outcomes. The accessibility model driver improved urban pattern replication, while suitability without accessibility was useful for simulating low-density development encroaching on natural areas. Rather than abandoning calibrations that show low agreement with reference maps based on a small number of metrics we should seek to understand what each metric is telling us and use this information to enrich the diversity of simulated outcomes. [ABSTRACT FROM AUTHOR]

The oscillation between the promise and the disappointment of biobanks as techno‐scientific infrastructures for contemporary biomedical research is frequent in the literature. In this article, we analysed how the precariousness of biobanks is leading to shifts in the focus of biobanking in Spain, where there are calls for some practices to be rearticulated. Drawing upon fieldwork and interviews with biobankers, we looked at which practices are highlighted for change to make biobanks worth maintaining and keep them afloat. We analysed these practices to unpack the values biobankers deploy to make sense of biobanking and turn it into two worthiness criteria: social return and dynamism. These criteria are intertwined and revolve around ethically calibrating the accumulation and sharing practices, 'sharing but not too much'. The porosity of biobanking practices and legislation, not to mention over a decade of austerity measures make biobanks fragile scientific infrastructures in Spain. We examine how biobanking practices are shifting in Spain to stay in the precarious techno‐scientific present while challenging assumptions on cryopreservation and preparedness. Our local account highlights the relevance of further inquiries on shifts in biobanking to attend to which kinds of biomedical research and knowledge might be coproduced by such infrastructural reconfigurations. [ABSTRACT FROM AUTHOR]

Featured Application: The methodology proposed in this manuscript makes it possible to improve the estimation of flood zones and their flow depth values in situations where there are no available bathymetric data of the channel (or they are scarce and do not allow for its shape reconstruction). It could improve flood risk assessment too. The accurate estimation of flood risk depends on, among other factors, a correct delineation of the floodable area and its associated hydrodynamic parameters. This characterization becomes fundamental in the flood hazard analyses that are carried out in urban areas. To achieve this objective, it is necessary to have a correct characterization of the topography, both inside the riverbed (bathymetry) and outside it. Outside the riverbed, the LiDAR data led to an important improvement, but not so inside the riverbed. To overcome these deficiencies, different models with simplified bathymetry or modified inflow hydrographs were used. Here, we present a model that is based upon the calibration of the Manning's n value inside the riverbed. The use of abnormally low Manning's n values made it possible to reproduce both the extent of the flooded area and the flow depth value within it (outside the riverbed) in an acceptable manner. The reduction in the average error in the flow depth value from 50–75 cm (models without bathymetry and "natural" Manning's n values) to only about 10 cm (models without bathymetry and "calibrated" Manning's n values), was propagated towards a reduction in the estimation of direct flood damage, which fell from 25–30% to about 5%. [ABSTRACT FROM AUTHOR]