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Background and aims: The focus of this paper is on the improvement of substance use disorder (SUD) screening and measurement. Using a multi‐dimensional item response theory model, the bifactor model, we provide a psychometric harmonization between SUD, depression, anxiety, trauma, social isolation, functional impairment and risk‐taking behavior symptom domains, providing a more balanced view of SUD. The aims are to (1) develop the item‐bank, (2) calibrate the item‐bank using a bifactor model that includes a primary dimension and symptom‐specific subdomains, (3) administer using computerized adaptive testing (CAT) and (4) validate the CAT‐SUD in Spanish and English in the United States and Spain. Design Item bank construction, item calibration phase, CAT‐SUD validation phase. Setting: Primary care, community clinics, emergency departments and patient‐to‐patient referrals in Spain (Barcelona and Madrid) and the United States (Boston and Los Angeles). Participants/cases: Calibration phase: the CAT‐SUD was developed via simulation from complete item responses in 513 participants. Validation phase: 297 participants received the Composite International Diagnostic Interview (CIDI) and the CAT‐SUD. Measurements A total of 252 items from five subdomains: (1) SUD, (2) psychological disorders, (3) risky behavior, (4) functional impairment and (5) social support. CAT‐SUD scale scores and CIDI SUD diagnosis. Findings Calibration: the bifactor model provided excellent fit to the multi‐dimensional item bank; 168 items had high loadings (> 0.4 with the majority > 0.6) on the primary SUD dimension. Using an average of 11 items (four to 26), which represents a 94% reduction in respondent burden (average administration time of approximately 2 minutes), we found a correlation of 0.91 with the 168‐item scale (precision of 5 points on a 100‐point scale). Validation: strong agreement was found between the primary CAT‐SUD dimension estimate and the results of a structured clinical interview. There was a 20‐fold increase in the likelihood of a CIDI SUD diagnosis across the range of the CAT‐SUD (AUC = 0.85). Conclusions: We have developed a new approach for the screening and measurement of SUD and related severity based on multi‐dimensional item response theory. The bifactor model harmonized information from mental health, trauma, social support and traditional SUD items to provide a more complete characterization of SUD. The CAT‐SUD is highly predictive of a current SUD diagnosis based on a structured clinical interview, and may be predictive of the development of SUD in the future. [ABSTRACT FROM AUTHOR]

Hospitals present a widely recognized margin for energy conservation due to their elevated final energy use intensity. Specifically, operating rooms are among the functional areas with greatest energy demand in hospitals, given the stringent indoor conditions for patients and surgical staff. However, energy efficiency in surgical facilities has traditionally been overlooked by the scientific literature in favor of guaranteeing adequate air quality conditions. This paper assesses the potential energy savings that could be achieved in a surgical suite in a Spanish hospital by lowering the current ventilation rates to the lowest energy-demanding values recommended by the proper Spanish standard and other international codes. Likewise, the paper assesses the actual hygrothermal and ventilation conditions in the suite based on the results of a continuous monitoring campaign performed for a period of 12 days. Simulations undertaken with a dynamic energy model specifically developed and calibrated for this work revealed that the average energy intensity of the suite is 1021 kWh/m 2 /year (1685 kWh/m 2 /year for operating rooms), with 80% of the total annual thermal demand corresponding to periods of inactivity. In addition, energy savings between 40% and 80% are possible while complying with both national and international standards. [ABSTRACT FROM AUTHOR]

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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]

In this paper, the HBV-TEC hydrological model is presented. The development of this model version, aims to provide researchers and scholars with a stable and robust implementation of the HBV hydrological model based on the R programming language. To evaluate its performance, the HBV-TEC model was applied to three subcatchments of the Aguacaliente river catchment, an experimental catchment located in the province of Cartago, Costa Rica. Results suggest a satisfactory performance of the model for two subcatchments and an unsatisfactory performance of the remaining subcatchment; most of which could be attributed to unsufficient meteorological data along with a highly heterogeneous spatial rainfall-distribution. [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]

In this paper, an experimental and numerical approach to the characterization of thermal bridges is presented. The need for this characterization was found within an experimental study in a 2 floor high façade. This façade was constructed with 3 concrete elements which were placed in it to produce a similar thermal bridge effect to the one created by floor slabs traditional building construction in Spain. Commonly applied thermal assessments perform one-dimensional heat transfer analysis over planar elements such as the façades studied in this experiment. However, it is well known that thermal bridges are locations in buildings where one-dimensional heat transfer analysis cannot be applied. This problem was approached by creating a numerical 2D thermal model which was calibrated against experimental data from several temperature and heat flux sensors which were located at specific points in the thermal bridge elements. [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]

Hydrological models are widely used tools in water resources management. Their successful application requires an efficient calibration of the model parameters. Nowadays, there are very powerful global search methods applied to this end, but they have the disadvantage of presenting a high computational cost, because the numerical model to be calibrated needs to be evaluated a large number of times with different parameter sets. In this context, surrogate models can reduce significantly the run time of hydrological models, easing the total computational burden of global search methods. In the present work, we propose and explore the combination of a swarm intelligence-based optimization method, the artificial bee colony algorithm, with a surrogate model based on artificial neural networks in order to calibrate hydrological models. The proposed approach (ABC-ANN) is applied to the calibration and validation of a nine-parameter continuous hydrological model in two basins located in the northwest of Spain. Several aspects of the algorithm are evaluated, including its capability to calibrate the model parameters and its efficiency in terms of CPU time compared to a standard implementation of the ABC algorithm. Results show that the ABC-ANN algorithm is able to identify the location of suitable parameter sets with an accuracy rate within 89 and 99 %, and a reduction in CPU time of more than three orders of magnitude when compared to a sequential implementation. In addition, the frequency distribution of the parameter sets identified gives valuable information about the sensitivity of model output to the input parameters. [ABSTRACT FROM AUTHOR]

After 5 years in orbit, the Global Precipitation Measurement (GPM) mission has produced enough quality-controlled data to allow the first validation of their precipitation estimates over Spain. High-quality gauge data from the meteorological network of the Spanish Meteorological Agency (AEMET) are used here to validate Integrated Multisatellite Retrievals for GPM (IMERG) level 3 estimates of surface precipitation. While aggregated values compare notably well, some differences are found in specific locations. The research investigates the sources of these discrepancies, which are found to be primarily related to the underestimation of orographic precipitation in the IMERG satellite products, as well as to the number of available gauges in the GPCC gauges used for calibrating IMERG. It is shown that IMERG provides suboptimal performance in poorly instrumented areas but that the estimate improves greatly when at least one rain gauge is available for the calibration process. A main, generally applicable conclusion from this research is that the IMERG satellite-derived estimates of precipitation are more useful (r2 > 0.80) for hydrology than interpolated fields of rain gauge measurements when at least one gauge is available for calibrating the satellite product. If no rain gauges were used, the results are still useful but with decreased mean performance (r2 ≈ 0.65). Such figures, however, are greatly improved if no coastal areas are included in the comparison. Removing them is a minor issue in terms of hydrologic impacts, as most rivers in Spain have their sources far from the coast. [ABSTRACT FROM AUTHOR]

The aim of this work was to apply a one-dimensional hydrodynamic and water quality DYRESM--CAEDYM model to the Boadella reservoir, Catalonia, Spain. Thus, simulation length was two years (2000 and 2001) with the aim to predict temperature, dissolved inorganic phosphorus and chlorophyll. The DYRESM--CAEDYM input data were meteorological data, river inflow and outflow data, morphometry parameters, an initial profile and file configuration data. The CAEDYM model also requires a configuration file and initial profiles for all the water quality data, but these data are not complete. Therefore, simulation may not be reliable or well analysed because of a lack of field nutrient data; so we will focus on the simulation of temperature, dissolved oxygen and chlorophyll. After simulation and calibration, coupling of those models might be a good tool to have an idea about Boadella reservoir water quality behaviour. [ABSTRACT FROM AUTHOR]

Aims and objectives: To evaluate both concordance among those measurements obtained by three different pulse oximeters currently used by nursing professionals in hospital units and the factors which can influence this concordance. Background: Many models of wireless pulse oximeters in the present market do not offer possibility of calibration and, therefore, they do not ensure patients' safety in daily clinical practice. Design: This is a descriptive and cross-sectional study. The sample of patients (140) was selected from such hospital units, and all of them had to fulfil inclusion and exclusion criteria for participation. Methods: The instruments used to carry out this research were a monitor (calibrated), two models of portable wireless pulse oximeters (used for 3 years by the nursing staff, without being calibrated), a tympanic thermometer and a weather meter. The concordance correlation coefficient (CCC) was used to establish the concordance, whereas the Landis-Koch criteria were used to interpret the results. Results: The concordance among the three devices was considered as “good” (CCC: 0.925 and 0.974 (95%)). The CCC (0.925) for saturation measures was regarded as “very good”/”almost perfect,” and the pulse measure was considered as “very good” CCC 0.974, providing in both cases a high level of concordance (CCC > 0.91). Conclusions: The overall concordance as regards pulse and oxygen saturation among the three pulse oximeters analysed is considered as “very good” according to the Landis-Koch criteria. Relevance to clinical practice: There exists a “very good” concordance among two wireless oximeters which have been used by the health staff for 3 years and which did not offer any possibility of calibration and one monitor which belongs to the healthcare institution. This aspect is of crucial importance in daily clinical practice, and it is also relevant to ensure patient’s safety. [ABSTRACT FROM AUTHOR]

The Tramuntana range, in the northwestern sector of the island of Mallorca (Balearic Islands, Spain), is frequently affected by rockfalls which have caused significant damage, mainly along the road network. In this work, we present the procedure we have applied to calibrate and validate rockfall modelling in this region, using 103 cases of the available detailed rockfall inventory (630 rockfall events collected since the eighteenth century). We have exploited STONE (Guzzetti et al. 2002), a GIS-based rockfall simulation software which computes 2D and 3D rockfall trajectories starting from a DTM and maps of the dynamic rolling friction coefficient and of the normal and tangential energy restitution coefficients. The appropriate identification of these parameters determines the accuracy of the simulation. To calibrate them, we have selected 40 rockfalls along the range which include a wide variety of outcropping lithologies. Coefficients values have been changed in numerous attempts in order to select those where the extent and shape of the simulation matched the field mapping. Best results were summarized with the average statistical values for each parameter and for each geotechnical unit, determining that mode values represent more precisely the data. Initially, for the validation stage, 10 well-known rockfalls exploited in the calibration phase have been selected. Confidence tests have been applied to their modelling results taking into account not only the success but also the mistakes. The best accuracy is obtained when the rockfall has a preferential trajectory and worse results when the rockfall follows two or more trajectories. Additionally, the greater the rockfall runout length, the less precise the simulation is. We have further validated the calibrated parameters along the Ma-road (111 km), the main transportation corridor in the range, using 63 rockfall events that occurred during the past 18 years along the road. Of the rockfalls where source areas were properly identified, 81.5 % are well represented by STONE modelling, as the travel paths and the depositional areas are successfully ascertained. Results of the analysis have been used by the Road Maintenance Service of Mallorca to assess hazard and risk posed by rockfall at regional scale to design the road management plan. [ABSTRACT FROM AUTHOR]

Good air quality is essential for both human beings and the environment in general. The three most harmful air pollutants are nitrogen dioxide (NO2), ozone (O3) and particulate matter. Due to the high cost of monitoring stations, few examples of this type of infrastructure exist, and the use of low-cost sensors could help in air quality monitoring. The cost of metal-oxide sensors (MOS) is usually below EUR 10 and they maintain small dimensions, but their use in air quality monitoring is only valid through an exhaustive calibration process and subsequent precision analysis. We present an on-field calibration technique, based on the least squares method, to fit regression models for low-cost MOS sensors, one that has two main advantages: it can be easily applied by non-expert operators, and it can be used even with only a small amount of calibration data. In addition, the proposed method is adaptive, and the calibration can be refined as more data becomes available. We apply and evaluate the technique with a real dataset from a particular area in the south of Spain (Granada city). The evaluation results show that, despite the simplicity of the technique and the low quantity of data, the accuracy obtained with the low-cost MOS sensors is high enough to be used for air quality monitoring. [ABSTRACT FROM AUTHOR]

Hydrological models are increasingly used for studying watershed behavior and its response to past and future events. The main objective of this study was to conduct a sensitivity analysis of the MOHID-Land model and identify the most relevant parameters/processes influencing river flow generation. MOHID-Land is a complex, physically based, three-dimensional model used for catchment-scale applications. A reference simulation was implemented in the Ulla River watershed, northwestern Spain. The sensitivity analysis focused on sixteen parameters/processes influencing water dynamics at that scale. River flow generation was influenced by the resolution of the simulation grid, soil water infiltration, and crop evapotranspiration. Baseflow was affected by soil hydraulic properties, the depth of the soil profile, and the dimensions of the river cross-sections. Peak flows were mostly constrained by Manning's coefficient in the river network, as well as the dimensions of the river cross-sections. The MOHID-Land model was then used to simulate daily streamflow during a 10-year period (2008−2017). Model simulations were compared against measured data at four hydrometric stations characterizing the natural flow regime of the Ulla River, resulting in coefficients of determination (R2) from 0.56 to 0.85; ratios of the standard deviation of the root mean square error to observation (RSR) between 0.4 and 0.67, and Nash and Sutcliffe model efficiency (NSE) values ranging from 0.55 to 0.84. The MOHID-Land model thus has the capacity to reproduce watershed behavior at a daily scale with reliable accuracy, constituting a powerful tool to improve water governance at the watershed scale. [ABSTRACT FROM AUTHOR]

Process-based crop models such as AquaCrop are useful for a variety of applications but must be accurately calibrated and validated. Sugar beet is an important crop that is grown in regions under water scarcity. The discrepancies and uncertainty in past published calibrations, together with important modifications in the program, deemed it necessary to conduct a study aimed at the calibration of AquaCrop (version 6.1) using the results of a single deficit irrigation experiment. The model was validated with additional data from eight farms differing in location, years, varieties, sowing dates, and irrigation. The overall performance of AquaCrop for simulating canopy cover, biomass, and final yield was accurate (RMSE = 11.39%, 2.10 t ha−1, and 0.85 t ha−1, respectively). Once the model was properly calibrated and validated, a scenario analysis was carried out to assess the crop response in terms of yield and water productivity to different irrigation water allocations in the two main production areas of sugar beet in Spain (spring and autumn sowing). The results highlighted the potential of the model by showing the important impact of irrigation water allocation and sowing time on sugar beet production and its irrigation water productivity. [ABSTRACT FROM AUTHOR]

Calibration of conceptual rainfall–runoff models (CRRM) for water-resource assessment (WRA) is a complicated task that contributes to the reliability of results obtained from catchments. In recent decades, the application of automatic calibration techniques has been frequently used because of the increasing complexity of models and the considerable time savings gained at this phase. In this work, the traditional Rosenbrock (RNB) algorithm is combined with a random sampling method and the Latin hypercube (LH) to optimize a multi-start strategy and test the efficiency in the calibration of CRRMs. Three models (the French rural-engineering-with-four-daily-parameters (GR4J) model, the Swedish Hydrological Office Water-balance Department (HBV) model and the Sacramento Soil Moisture Accounting (SAC-SMA) model) are selected for WRA at nine headwaters in Spain in zones prone to long and severe droughts. To assess the results, the University of Arizona's shuffled complex evolution (SCE-UA) algorithm was selected as a benchmark, because, until now, it has been one of the most robust techniques used to solve calibration problems with rainfall–runoff models. This comparison shows that the traditional algorithm can find optimal solutions at least as good as the SCE-UA algorithm. In fact, with the calibration of the SAC-SMA model, the results are significantly different: The RNB algorithm found better solutions than the SCE-UA for all basins. Finally, the combination created between the LH and RNB methods is detailed thoroughly, and a sensitivity analysis of its parameters is used to define the set of optimal values for its efficient performance. [ABSTRACT FROM AUTHOR]

Different types of measuring errors can increase the uncertainty of solar radiation measurements, but most common quality control (QC) methods do not detect frequent defects such as shading or calibration errors due to their low magnitude. We recently presented a new procedure, the Bias-based Quality Control (BQC), that detects low-magnitude defects by analyzing the stability of the deviations between several independent radiation databases and measurements. In this study, we extend the validation of the BQC by analyzing the quality of all publicly available Spanish radiometric networks measuring global horizontal irradiance (9 networks, 732 stations). Similarly to our previous validation, the BQC found many defects such as shading, soiling, or calibration issues not detected by classical QC methods. The results questioned the quality of SIAR, Euskalmet, MeteoGalica, and SOS Rioja, as all of them presented defects in more than 40% of their stations. Those studies based on these networks should be interpreted cautiously. In contrast, the number of defects was below a 5% in BSRN, AEMET, MeteoNavarra, Meteocat, and SIAR Rioja, though the presence of defects in networks such as AEMET highlights the importance of QC even when using a priori reliable stations. [ABSTRACT FROM AUTHOR]